Helmholtz Russian-German Workshop on Systems Biology Moscow ...

<strong>Helmholtz</strong><strong>Russian</strong>-<strong>German</strong> <strong>Workshop</strong> onSystems BiologyFebruary, 27-29, 2008, Moscow

Welcome AddressDear Colleagues,As an exciting new field in biomedical research, systems biology has recently gained a lot of attentionin <strong>German</strong>y. In 2007 the <strong>Helmholtz</strong> Association of <strong>German</strong> Research Centres has launched the<strong>Helmholtz</strong> Alliance on Systems Biology, a large network comprising <strong>Helmholtz</strong> Centres, universitiesand other external partners. The long‐term goal of the initiative is to shed light on the causes ofcomplex disorders and diseases and develop new approaches for treating them.Due to its enormous potential in the field of mathematics and informatics, Russia has been chosen asone of the key partners for the development of international relations with the <strong>Helmholtz</strong> Alliance onSystems Biology.We are happy to welcome you to the workshop on Systems Biology, to be held in Moscow onFebruary 27‐29 2008 in Moscow and are looking forward to an exciting meeting. It should help toopen the field for scientific interactions in the field of systems biology between scientists from Russiaand the <strong>Helmholtz</strong> Association as well as other institutions in <strong>German</strong>y.Prof. Otmar D. WiestlerResearch Field Coordinator Health, <strong>Helmholtz</strong>AssociationChairman and Scientific Director, <strong>German</strong> CancerResearch Center (DKFZ) HeidelbergProf. Roland EilsCoordinator <strong>Helmholtz</strong> Allianceon Systems BiologyDepartment Head, <strong>German</strong> Cancer ResearchCenter (DKFZ) HeidelbergDear Friends and Colleagues,In the name of the president of the <strong>Helmholtz</strong> Association the Moscow Office welcomes you asparticipants of the <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology. I know, some of youhave travelled far in order to join this workshop and others may even visit Russia the first time intheir life. May your efforts not be in vain, but rewarded by meeting new partners for cooperation inthis quickly emerging research field. We are certain that especially in the field of Systems Biologymutual interest and complementing scientific ideas lie immediately ahead of us.In order to pick up on these opportunities the <strong>Helmholtz</strong> Office Moscow supports the workshop withmeans from the Initiative and Networking Fund of the president of the <strong>Helmholtz</strong> Association andoffers those of you who develop a mutual interest for co‐operation our full support for thecompletion of joint proposals within the <strong>Helmholtz</strong>‐Russia Joint Research Group program. With theformation of the Systems Biology Network among six <strong>Helmholtz</strong> Centres and numerous universitiesin <strong>German</strong>y the <strong>Helmholtz</strong> Association provides a unique spectrum of research and infrastructure inthis field. We wish our colleagues and partners from Russia and the <strong>Helmholtz</strong> Centres a successfulconference that will result into new exciting co‐operations in Systems Biology.Dr. Bertram HeinzeHead <strong>Helmholtz</strong> Office Moscow<strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 1

The <strong>German</strong> Cancer Research CenterHeidelbergOur Goals ­ Our TasksIn order to develop new strategies in the battle against cancer, wefirst need to understand the complex biological mechanismsunderlying this disease. What induces cells to grow in anuncontrolled manner? What biochemical processes are occurringwhen this happens? How can we influence these processes?At the <strong>German</strong> Cancer Research Center (Deutsches Krebsforschungszentrum,DKFZ), a globally reknown research institution,our mission is to systematically investigate the mechanisms of cancerdevelopment and to identify cancer risk factors. Based on the resultsof this basic research new approaches are developed for prevention,diagnosis, and treatment of cancer.DKFZ Main BuildingBrief History1964 The <strong>German</strong> Cancer Research Center was set up. The establishment of a national cancerresearch center was initiated by Heidelberg surgeon Professor Karl Heinrich Bauer.1977 The Center joined the Deutsche Forschungsgemeinschaft (DFG).2001 The Center joined the newly structured association "Hermann von <strong>Helmholtz</strong> Association ofNational Research Centers". With its 15 member research centers, an annual budget ofapproximately 2.2 billion Euros and 24,000 staff, the <strong>Helmholtz</strong> Association is <strong>German</strong>y'slargest research organization.2004 The <strong>German</strong> Cancer Research Center, Heidelberg University Hospitals and the <strong>German</strong>Cancer Aid jointly set up the National Center for Tumor Diseases (NCT) Heidelberg.2007 Alliance with Center for Molecular Biology of the University of Heidelberg (ZMBH)Management BoardProf. Dr. Otmar D. WiestlerDr. Josef PuchtaChairman of the Management Board and Scientific DirectorAdministrative‐commercial DirectorStaff (as of Dec. 31, 2007)Total staff 2,128Staff scientists without doctoral students 619 Doctoral students 351Scientific infrastructure 660 Management support 161Technical and central services 104 Apprentices 116Diploma students 117In 2007, there were 154 visiting scientists from over 40 nations working at the DKFZ.Funding 2005Program‐based funding (90%/10% Federal vs. State Funding)Project funding (External funds: DFG, DKH, EU, NIH, etc)Own revenues (License revenues, patient care, donations and bequests)110.8 million EUR29 million EUR18.7 million EUR6 <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology

CommitteesAdvisory CommitteeValery Alexandrovich ChereshnevInstitute of Immunology and Physiology, Ural Branch of the <strong>Russian</strong> Academy of Sciences, Member of<strong>Russian</strong> Parlament (Duma), Ekaterinburg/MoscowNikolay Aleksandrovich KolchanovInstitute of Cytology and Genetics,Siberian Branch of the <strong>Russian</strong> Academy of Sciences, NovosibirskAleksander Aleksandrovich MakarovEngelhardt Institute of Molecular Biology<strong>Russian</strong> Academy of Sciences, MoscowVladimir Petrovich SkulachevBelozersky Institute of Physico‐Chemical Biology,Lomonosov Moscow State University, MoscowVladimir Guevich TumanyanEngelhardt Institute of Molecular Biology<strong>Russian</strong> Academy of Sciences, MoscowSebastian M. SchmidtForschungszentrum Jülich, JülichOtmar D. Wiestler (Chair)<strong>German</strong> Cancer Research Center (DKFZ), HeidelbergScientific CommitteeRoland Eils (Chair)<strong>German</strong> Cancer Research Center (DKFZ), HeidelbergMikhail GelfandInstitute for Information Transmission Problems, MoscowUrsula Klingmüller<strong>German</strong> Cancer Research Center (DKFZ), HeidelbergInna Lavrik<strong>German</strong> Cancer Research Center (DKFZ), HeidelbergOrganizational CommitteeNatalja Dobrowolskaja<strong>Helmholtz</strong> Office MoscowJan Eufinger<strong>German</strong> Cancer Research Center (DKFZ), HeidelbergBertram Heinze<strong>Helmholtz</strong> Office MoscowUrsula Schöttler<strong>German</strong> Cancer Research Center (DKFZ), Heidelberg10 <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology

ParticipantsCV onNameInstitution and CitypageAndrei Alexeevski Belozersky Institite, Moscow State University, Moscow 13Miguel Andrade Max‐Delbrück‐Centrum für Molekulare Medizin (MDC), BerlinAlexander Apt Central Research Institute of Tuberculosis, MoscowIrena Artamonova Vavilov Institute of General Genetics , Moscow 14Verena Becker Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 15Gennady Bocharov Institute of Numerical Mathematics, Moscow 16Sebastian Bohl Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 17Hauke Busch Deutsches Krebsforschungszentrum (DKFZ) , Heidelberg 18Valery Chereshnev Institute of Immunology and Physiology, Moscow/EkaterinburgDmitriy Chudakov Institite of Bioorganic Chemistry , Moscow 19Oleg Demin Moscow State University, Moscow 20Sofia Depner Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 21Markus Diesmann Riken Brain Science Institut (RIKEN BSI), Wako, Japan 22Natalja Dobrowolskaja <strong>Helmholtz</strong> Office Moscow, MoscowVítor dos Santos <strong>Helmholtz</strong>‐Zentrum für Infektionsforschung (HZI), Braunschweig 23Roland Eils Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 24Jan Eufinger Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 25Mikhail Gelfand Institute for Information Transmission Problems, Moscow 26Nail Gizzatkulov (1) Institute for Systems Biology SPb (2) Moscow State University 27Evgeny Gladilin Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 28Giovani Gomez Estrada <strong>Helmholtz</strong> Zentrum München, München 29Ekaterina Goryacheva Institute for Systems Biology SPb, Moscow 30Vadim Govorun Research Institute for Physical–Chemical Medicine, MoscowGeorgy Gulbekyan Moscow State University, Moscow 31Vitaly Gursky St.Petersburg Technical University ‐ Ioffe Physico‐Technical Institute 32Bertram Heinze <strong>Helmholtz</strong> Office Moscow, MoscowThomas Höfer Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 33Ralf Hofestädt Universität Bielefeld ‐ Bioinformatik, Bielefeld 34Anna Ignatovich Institute of Numerical Mathematics, Moscow 35John Ionides St Petersburg State Polytech. Uni, St. Petersburg 36Pavel Ivanov Moscow State University, Moscow 37Lars Kaderali Universität Heidelberg ‐ BIOQUANT , Heidelberg 38Alexey Kazakov Institute for Information Transmission Problems , Moscow 39Ursula Klingmüller Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 40Olga Koborova Moscow State University, Moscow 41Nikolai Kolchanov Novosibirsk Institute of Cytology and Genetics, NovosibirskRainer KönigDeutsches Krebsforschungszentrum (DKFZ) / Universität Heidelberg, 42HeidelbergYuri Kosinsky(1) Institute for Systems Biology SPb (2) Moscow State University, 43MoscowKonstantin Kozlov St.Petersburg Technical University, St. Petersburg 44Ivan Kulakovsky Engelhardt Institute of Molecular Biology , Moscow 45Alexey Lagunin Institute of Biomedical Chemistry RAMS, Moscow 46Inna Lavrik Deutsches Krebsforschungszentrum (DKFZ), Heidelberg 47<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 11

14 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Irena I. ArtamonovaInstitution Vavilov Institute of General Genetics RASContact AdressStreet Address Gubkina 3Zip /Postal Code 119991CityMoscowCountryRussiaPhone +7 916 9155809E‐Mailirenart@gmail.comShort CV1995 MSc, Moscow State University, pure mathematics, magna cum laude1998 MSc, Moscow Institute of Physics and Technology, physical and chemical biology andbiotechnology, magna cum laude2002 PhD, molecular biology1999‐2001 Laboratory of Distant Education, Center of New Information Technologies, MoscowState University, research scientist2002‐2004 Laboratory of Structure and Function of Human Genes, Shemyakin‐OvchinnikovInstitute of Bioorganic Chemistry RAS, junior research scientist2004‐2007 Munich Unformation Center for Protein Science, Institute for Bioinformatics, GSF‐National Research Center for Environment and Heath, Neuherberg, <strong>German</strong>y, postdocfellowSince 2007 Group of Bioinformatics, Vavilov Institute of General Genetics RAS, group leaderAwards1997, 1999 International Soros Science Foundation. Special Ph.D Student award1998 Annual competition of student projects of the Moscow Institute of Physics andTechnology, main prize1997‐1998 Yu. Ovchinnikov student award2006 Best poster prize, Conference ECCB’06, IsraelResearch InterestsComputational biology: evolution of alternative splicing and gene/genome structure of higher eukaryotes;prokaryotic immunity; gene regulation; improvement of gene/protein annotationFive most important publicationsI.I. Artamonova, M.S. Gelfand (2007) Comparative genomics and evolution of alternative splicing: Thepessimists’s science. Review. Chemical Reviews. V. 107, P. 3407‐3430Riley, L., Schmidt, T., Artamonova, I., Wagner, C., Volz, A., Heumann, K., Mewes, H.‐W., Frishman, D.(2007) PEDANT genome database: ten years online. Nucleic Acids Res.V. 35, D354‐7Artamonova II, Frishman G, Gelfand MS, Frishman D. (2005) Mining sequence annotation databanksfor association patterns. Bioinformatics. V. 21 (Suppl_3), P. iii49‐iii57A.D. Neverov, I.I. Artamonova, R.N. Nurtdinov, D. Frishman, M. Gelfand, A. Mironov (2005) Alternativesplicing and protein function. BMC Bioinformatics. V. 6, P. 266R.N. Nurtdinov, I.I. Artamonova, A.A. Mironov, M.S. Gelfand (2003) Low conservation of alternativesplicing patterns in the human and mouse genomes. Human Molecular Genetics, v. 12, P. 1313‐1320.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talkA recently discovered type of the prokaryotic immunity, the CRISPR system, in metagenomesAbstractWe developed a methodology to search for CRISPR cassettes in metagenomes. It is based on acombination of three publicly available programs that, if applied separately, produce heavy falsepositive noise.The application of this schema to the Sargasso Sea metagenome data showed that the frequency ofCRISPR cassettes in this metagenome is almost ten‐fold lower than in completely sequencedprokaryotic genomes on average.The identified CRISPR cassettes were collected in a special database. Families of related cassettes wereformed by analysis of similarity between repeat units. Additional analysis of flanking regions allowsone to distinguish between the lateral transfer and the parallel evolution of the cassettes in relatedstrains. In many cases the similarity between cassettes is confined to single spacers, and some spacersare similar to known phage sequences. These observations support the hypothesis that this systemdefends organisms constituting the metagenome against invasion of foreign DNA.Poster number: 2

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 15Verena Becker, PhDInstitution <strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 280, A150Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐424482Fax +49‐6221‐424488E‐Mailv.becker@dkfz‐heidelberg.deWebsitehttp://www.dkfz.de/en/systembiologie/Short CV1997 High school diploma1997‐2002 Studies in biology at the University of Freiburg2001 Diploma exminations in molecular immunology, developmental biology,biochemistry, and neuropathology2001‐2002 Diploma thesis in the laboratory of PD Dr. U. Klingmüller, Max‐Planck‐Institute ofImmunobiology, Freiburg2003‐2007 Graduate studies at the University of HeidelbergThesis in the laboratory of PD Dr. U. Klingmüller, <strong>German</strong> Cancer Research Center(DKFZ), Heidelbergsince 2007 Postdoctoral research fellow in the laboratory of PD Dr. U. Klingmüller, <strong>German</strong>Cancer Research Center (DKFZ), HeidelbergResearch InterestsUsing the erythropoietin receptor (EpoR) as a model system, we are interested in the early controlmechanisms of cytokine receptor activation. By combining signaling studies and biological assays withmolecular modeling of receptor transmembrane domain dimers, we could show that modulating theEpoR dimer packing density allows for selective amplification of downstream signaling cascades andthus biological decisions. In a systems biology approach, we are analyzing the mechanisms by whichligand‐induced EpoR internalization controls short and long‐term signal activation.Five most important publicationsR. Ketteler, A.C. Heinrich, J.K. Offe, V. Becker, J. Cohen, D. Neumann, and U. Klingmüller. (2002) Afunctional green fluorescent protein‐tagged erythropoietin receptor despite physical separation ofJAK2 binding site and tyrosine residues. J Biol Chem. 277:26547‐26552.W. Ruan, V. Becker, U. Klingmüller, and D. Langosch. (2004) The interface between self‐assemblingerythropoietin receptor transmembrane segments corresponds to a membrane‐spanning leucinezipper. J Biol Chem. 279:3273‐3279.F. Grebien, M.A. Kerenyi, B. Kovacic, T. Kolbe, V. Becker, H. Dolznig, K. Pfeffer, U. Klingmüller, M.Müller, H. Beug, E.W. Müllner, and R. Moriggl. Stat5 activation enables erythropoiesis in the absenceof EpoR and Jak2. Blood, in press.V. Becker, D. Sengupta, S. Heinzer, R. Ketteler, G.M. Ullmann, J.C. Smith, M. Weiss, and U. Klingmüller.Packing density of EpoR transmembrane domain correlates with amplification of biological responses.Submitted.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talkErythropoietin receptor internalization in control of short and long‐term signalingAbstractThe fine‐tuned balance of self‐renewal and rapid adaptation in the hematopoietic system is regulatedby cytokines. To ensure the integrity of blood cells within the body, cytokine receptors display severalmechanisms to efficiently activate as well as terminate signal transduction. The contribution ofreceptor endocytosis and downregulation for signal attenuation of cytokine receptors is still unclearsince in contrast to receptor tyrosine kinases only a minor fraction of receptor proteins is expressed atthe plasma membrane whereas the majority is retained in the endoplasmic reticulum. Applying asystems biology approach, we investigated the dynamics of receptor turnover and internalization ofthe erythropoietin receptor (EpoR), the key factor for definitive erythropoiesis. Receptor endocytosiswas measured with radiolabeled compounds in a time‐resolved manner. Data fitting of ordinarydifferential equation‐based mathematical models describing both constitutive and stimulated EpoRinternalization revealed identifiable parameters. Thus, these models allow for predicting themechanisms by which EpoR internalization determines the kinetics of short as well as long‐termreceptor signaling.Poster number: 3

16 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyProf. Dr. Gennady BocharovInstitution Institute of Numerical MathematicsContact AddressStreet Address Gubkina Street 8Zip /Postal Code 119333CityMoscowCountry<strong>Russian</strong> FederationPhone +7‐495‐9383766Fax +7‐495‐9381821E‐Mailbocharov@inm.ras.ruShort CV1974 ‐ 1980 Moscow Institute for Physics and Technology1980 ‐ present Institute of Numerical Mathematics, <strong>Russian</strong> Academy of Sciences, LeadingResearcher1996 Institute of Experimental Immunology, University of ZurichMay – Nov 2000 The Wellcome Trust Centre for the Epidemiology of Infectious Disease, OxfordUniversityNov 2000 – Aug Department of Infectious Disease Epidemiology, Imperial College London20012003 – 2004 Leverhulme International Professor Chester University2006 ‐ present Department of Computational Technologies and Modelling, Moscow StateUniversityAwards1997‐1999 Fellow of Alexander von Humboldt Foundation, <strong>German</strong>y2007‐2009 Visiting Professor, Mathematics Department, Chester UniversityResearch InterestsGeneral:Application of mathematics to immunology and virology; Mathematical systems theory;System identification; Computational modellingSpecific:Quantitative modeling of virus infections and immune responses in humans (HBV, HCV, HIV, influenza)and experimental animals (LCMV, SIV, MHV);Genetic evolution of HIV within a single host under treatment;Dynamics of labeled (CFSE, BrdU, Ki‐67) T‐lymphocytes in vitro and in vivoFive most important publications1. Tatyana Luzyanina, Sonya Mrusek, John T. Edwards, Dirk Roose, Stephan Ehl and Gennady Bocharov(2007): Computational analysis of CFSE proliferation Journal of Mathematical Biology. 54: 57‐89.2. Burkhard Ludewig and Gennady Bocharov (2006): A systems biologist’s view on dendritic cellcytotoxicT lymphocyte interaction. In: Handbook of Dendritic Cells. Biology, Diseases and Therapie,Eds. M. Lutz, N. Romani and A. Steinkasserer. Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim, Ch. 23:455‐479.3. Gennady Bocharov (2005): Understanding complex regulatory systems: Integrating molecularbiology and systems analysis. Transfusion Medicine and Hemotherapy 32 (6): 304‐3214. Gennady Bocharov, Burkhard Ludewig, Antonio Bertoletti, Paul Klenerman, Tobias Junt, PhilippeKrebs, Tatyana Luzyanina, Cristophe Fraser, and Roy M. Anderson (2004): Underwhelming the ImmuneResponse: Effect of Slow Virus Growth on CD8 + ‐T‐Lymphocyte Responses J. Virology 78: 2247‐22545. Stephan Ehl, Paul Klenerman, Rolf M. Zinkernagel, Gennadii Bocharov(1998): The impact of Variationin the Number of CD8 T‐Cell Precursors on the Outcome of Virus Infection. Cellular Immunology, 189,67‐73Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(+) a talkTitle of poster / talkModelling and identification of distributed parameter systems in immunologyAbstractThe problem of how to develop, in a systematic manner, consistent mathematical models that providea basis for rigorous analysis and quantitative prediction in every day immunology research is explored.We present a quantitative approach towards an integrative modelling of distributed parametersystems in immunology. Two case studies are presented in detail:The type I interferon (IFN) response to coronavirus infection in mice The model of IFN responseconsiders the population dynamics of plasmacytoid dendritic cells and macrophages. It is set up toquantify some fundamental parameters of IFN production and protection and predict the sensitivity ofthe response dynamics.Turnover of labeled (e.g. with fluorescent markers CFSE, BrdU) T lymphocytes in vitro and in vivo. Weidentified a set of mathematical models of differing complexity (formulated with ODEs or hyperbolicPDEs) to quantify the division‐, differentiation and death rate parameters of turning over T cells usingflow cytometry data on the evolution of cell distribution with respect to the fluorescent markers.

18 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Hauke BuschInstitution Theoretical Bioinformatics, <strong>German</strong> Cancer ResearchCenter (DKFZ)Contact AddressStreet Address Bioquant, Im Neuenheimer Feld 267Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐54‐51309Fax +49‐6221‐54‐51488E‐Mailh.busch@dkfz.deWebsitehttp://www.dkfz.de/ibios/Short CV1992‐1998 Study in Physics at the Darmstadt University of Technology1999‐2004 PhD at the Darmstadt University of Technology”Influence of Spatiotemporal Noise on Pattern Formationin Excitable Media“.1999‐2002 Member of the Graduate College 340„Comminication in Biological Systems“2004‐now Postdoc at DKFZ, Group of Prof. R. Eils,Division of Theoretical BioinformaticsHead of Applied Systems Biology Modeling Group2004‐2007 Postdoc Fellow of the Systems Biology BioMS InitiativeResearch InterestsMain research interests:‐ the influence of noise in biological systems‐ development of methods for the efficient simulation of stochastic chemical systems in space andtime.‐ reverse engineering of dynamic gene regulatory networks from high throughput data‐ optimal experiment design strategies for biologcial systems.Five most important publicationsH. Busch, D. Camacho‐Trullio, K. Breuhahn, P. Angel, R.Eils and A. Szabowski, Gene Network Dynamicscontrolling Keratinocyte Migration, submitted.H. Busch, W. Sandmann and V. Wolf, A numerical aggregation algorithm for the enzymecatalyzedsubstrate conversion, in Proceedings of the Int. Conference on Computational Methods in SystemsBiology, Trento, 2006.H. Busch and R. Eils, Systems Biology, in Encyclopedia of Molecular Cell Biology andMolecular Medicine, 14, 123, (2005).H. Busch and M.‐Th. Hütt, Scale‐dependence of spatiotemporal filters inspired by cellularautomata, Int. J. Bifurcation Chaos, 14, 1957, (2004).H. Busch, J. Garcia‐Ojalvo, and F. Kaiser, Influence of spatiotemporal 1/f_‐noise on structure formationin excitable media, Proc. SPIE, 5114, 468, (2003).Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( x) a poster( ) a talkTitle of poster / talkGene Network Dynamics Controlling Keratinocyte MigrationAbstractSo far it is not known how to translate large‐scale omic data into a coherent model of cellularregulation allowing to simulate, predict and control cellular behavior. However, assuming thatinformation on cell wide behavior is reflected in the gene expression kinetics, we infer a dynamic generegulatory network from time series measurements of DNA micro‐array data for well studiedHepatocyte Growth Factor‐induced migration of primary human keratinocytes. Transforming theobtained interactions to the level of signaling pathways, we predict in silico and verify in vitro thenecessary and sufficient time‐ordered events that initiate, maintain and stop migration. We show thatpulse‐like activation of the protooncogene receptor Met triggers a responsive state, while timesequential activation of EGF‐R is required to initiate and maintain migration. Context information forenhancing, delaying or stopping migration is provided via the activity of the PKA‐signaling pathway.Our results shed a new light on a continued kinetic interplay of multiple signaling pathways mediatingthe transition to a migratory system state over a time course of several hours.Poster number: 5

20 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Oleg DeminInstitutionContact AddressStreet Address(1) Institute for Systems Biology SPb (2) MoscowState UniversityLeninskie Gory, 1/73, AN Belozerski IPCB MoscowState UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Maildemin@genebee.msu.suWebsitewww.insysbio.ruShort CV2004‐present CSO Institute for Systems Biology SPb2002–present Principal Research Scientist, Department of Bioenergetics of A.N.BelozerskyInstitute of Physico‐Chemical Biology, Moscow State University1995‐2002 Visiting Research Scientist, Department of Microbial Physiology, Free Universityof Amsterdam, Amsterdam, The Netherlands1995‐2002 Research Scientist, Department of Bioenergetics of A.N.Belozersky Institute ofPhysico‐Chemical Biology, Moscow State University1992‐1995 Post‐graduate of Biophysical Department, Moscow State University1995 Ph.D., Biophysical Department, Faculty of Biology, Moscow State University,Moscow. Title: Structural organization of multi‐enzyme metabolic systems andregulation of their fluxes and concentrations: theoretical approach1992 M.Sc., Faculty of Applied Mathematics and Cybernetics, Moscow State University,Moscow. Title: Optimal control and stability of steady states of metabolicpathways with different feedbacks1986‐1992 Biophysical Department, Faculty of Biology, Moscow State University1989‐1992 Faculty of Applied Mathematics and Cybernetics, Moscow State UniversityAwardsParticipation in EU programmes:2006 ‐ 2008 Systems Biology of RNA metabolism in yeast; Acronym: RiboSys; FP6 SpecificTargeted Project1999 ‐ 2001 European Union INTAS grant1998 ‐ 2000 European Union COPERNICUS grantResearch InterestsResearch Interests of Dr Demin are focused in areas of Systems Biology and Bioinformatics andscientific programming with especial focus on quantitative description of biological processes and theirapplication to biotechnology and biomedicine.Areas of expertise:Modeling of cellular metabolismModeling of cell signalingModeling of gene regulatory networksPathway reconstructionMethods and software for control of industrial biotechnology processesMethods and software for drug safety assessmentMethods and software for kinetic modelingFive most important publicationsMetelkin E., Goryanin I., Demin O. Mathematical modeling of mitochondrial adenine nucleotidetranslocase. Biophys. J (2006) v.90 p.423‐432Goryanin II, Lebedeva GV, Mogilevskaya EA, Metelkin EA, Demin OV. Cellular kinetic modeling of themicrobial metabolism. Methods Biochem Anal (2006) 49, 437‐488Demin O.V., Plyusnina T.Y., Lebedeva G.V., Zobova E.A., Metelkin E.A., Kolupaev A.G., Goryanin I.I.,Tobin F. Kinetic modelling of the E. coli metabolism. IN: Topics in Current Genetics (2005) 31‐67, Eds.Alberghina L., Westerhoff H.V. , SpringerDemin, O.V.,Goryanin, I.I., Kholodenko, B.N., Westerhoff, H.V. Kinetic modeling of energy metabolismand superoxide generation in hepatocyte mitochondria. Molecular Biology (Moscow) (2001) 35(6), 1‐11Kholodenko, B.N., Demin, O.V., Moehren, G., Hoek, J.B. Quantification of short term signaling by theepidermal growth factor receptor. J Biol Chem (1999) 274, 30169‐30181Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will preparea talkTitle of poster / talkModeling in Systems Biology: Applications to Biomedicine and BiotechnologyAbstractTwo approaches of computational systems biology are presented: pathway reconstruction and kineticmodeling. Pathway reconstruction collects all information about players of interest, processesinterconnecting them and their stoichiometry and can be considered as a powerful tool to search fordrug targets, discover possible biomarkers and attribute them to particular cell state or phenomenon.In framework of kinetic modeling approach we mine, collect and integrate quantitative in vitro and invivo experimental data produced by classical biochemistry, genomics, proteomics and metabolomicsand use them to build and verify kinetic models [1,2]. These kinetic models when considered as arepository of all information about the system of interest can be applied to different problems of drugdiscovery and production such as screening optimization [3], investigation/prediction of drug safety [4]and optimization/maximization of yield of drug precursors. Several examples illustrating theseapproaches have been presented.1. E. Metelkin, I. Goryanin, O. Demin (2006) Biophys. J, 90: 423‐432; 2. I. Goryanin, G. Lebedeva, E.Mogilevskaya, E. Metelkin, O. Demin (2006) Methods Biochem Anal, 49: 437‐488 ; 3. M. Noble, Y.Sinha, A. Kolupaev, O. Demin, D. Earnshaw, F. Tobin, J. West, J. Martin, C. Qiu, W. Liu, W. DeWolf Jr., D.Tew, I.Goryanin (2006) Biotechnology and Bioengineering, 95: 560‐571. ;4. E. Mogilevskaya, O. Demin,I. Goryanin (2006) Journal of Biological Physics, 32: 245‐271.

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 21Dr. Sofia DepnerInstitution <strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 280Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone 06221/424534Fax 06621/424551E‐Mails.depner@dkfz.deShort CVborn: 13.09.1968, Moskau1975‐1985 common secondary school Nr. 61, Moskau1985‐1990 Technical institute for forestry, Moskau. Degree: diplom engineer (FH)1994‐2002 Johannes Gutenberg University Mainz, <strong>German</strong>y. Degree: diplom biologist.2002‐2006 PhD Thesis at <strong>German</strong> cancer research center (DKFZ)2006‐dato Postdoc position at DKFZ, group Tumor and MicroenvironmentResearch InterestsRegulation of signal transduction in tumor and stromal cells; The role of cytokines by the interactionsbetween tumor and stromal cells.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( + ) a posterTitle of poster / talkDifferential regulation of IL‐6 signaling pathway in HaCaT A5 benigne tumor keratinocytes andfibroblastsAbstractThe activated progression promoting tumor microenvironment is initially induced by a network oftumor derived growth factors/cytokines that induce cellular responses in tumor and stromal cells. In atumor transplantation model of HaCaT skin squamous cell carcinomas we could demonstrate thefunctional contribution of an IL‐6 regulated growth factor network to tumor progression. The networkinduces tumor cells proliferation and migration as well as persistent angiogenesis, recruitment andactivation of stromal cells. In response to ligand binding the IL‐6R activates the JAK/STAT signallingpathway in stromal fibroblasts and tumor cells but pathway activation results in the induction ofdifferent target genes and triggers different cellular responses in both cell types. This differentialtarget gene response is most likely mediated by a differential kinetics of expression, phosphorylationand nuclear localization of STAT proteins (STAT1 and 3) in both cell types. Additionally tumorkeratinocytes and stromal fibroblasts respond with a different pattern of activation for MAP kinasessuch as Erk1/2.Poster number: 6

22 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Markus DiesmannInstitution RIKEN Brain Science InstituteContact AddressStreet Address 2‐1 HirosawaZip /Postal Code 351‐0198CityWako‐shi, SaitamaCountryJapanPhone +81‐48‐467‐9644Fax +81‐48‐467‐9644E‐Maildiesmann@brain.riken.jpWebsitehttp://www.cnpsn.brain.riken.jpShort CV2006 Unit Leader, RIKEN Brain Science Institute2004 Juniorprofessor, Freiburg2003 Assistant Professor (C1), Freiburg1999 Senior staff , MPI for Dynamics and SelfOrganization, Goettingen1997 PhD studies University of Freiburg1994 PhD studies Weizmann Institute of Science, Rehovot1993 Diploma in Physics (Bochum)Research InterestsThe cortical neuronal network is among the most complex structures found in nature. The functionalrole of its dynamics exhibited on many spatio‐temporal scales is presently not understood.Furthermore, in contrast to other systems, the structure of the cortex is in fact not static butundergoes a continuous activity dependent reorganization. The Diesmann Research Unit studies themechanisms and functional consequences of spike synchronization and plasticity in biologicallyrealistic models of the cortical network. However, this bottom‐up approach alone may not lead to anunderstanding of brain function. For this reason we also incorporate top‐down approaches in ourresearch. At the interface of top‐down and bottom up approaches, our strategy is to implementestablished formal theories of system function like temporal‐difference learning in biologicallyconstrained network models. These investigations depend on large‐scale simulations requiring nonstandardalgorithms and high‐performance parallel computing. Therefore, the unit is also concernedwith the creation of appropriate simulation technology.Five most important publicationsMorrison A, Aertsen A, Diesmann M. (2007) Spike‐time dependent plasticity in balanced recurrentnetworks. Neural Computation 19: 1437–1467.Morrison A, Straube S, Plesser H E, Diesmann M. (2007) Exact subthreshold integration withcontinuous spike times in discrete time neural network simulations. Neural Computation 19: 47—79.Morrison A, Mehring C, Geisel T, Aertsen A, Diesmann M . (2005) Advancing the boundaries of highconnectivity network simulation with distributed computing. Neural Computation 17(8):1776—1801.Mehring C, Hehl U, Kubo M, Diesmann M , Aertsen A. (2003) Activity Dynamics and Propagation ofSynchronous Spiking in Locally Connected Random Networks. Biological Cybernetics 88(5):395—408.Diesmann M , Gewaltig M‐O, Aertsen A. (1999) Conditions for Stable Propagation of SynchronousSpiking in Cortical Neural Networks. Nature 402:529—533.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(X) a talkTitle of poster / talkLarge‐scale simulations of plastic neural systemsAbstractHigher brain functions emerge from large and complex cortical networks and their interactions.However, the large number of neurons combined with the high connectivity of the biological networkand the heterogeneity in neuron and synapse types impose severe constraints on the explorablesystem size which have previously been hard to overcome. Furthermore, the continuousreorganization processes in the brain by different types of plasticity require simulations on thebiological time‐scale of minutes but with a temporal resolution of fractions of a millisecond. In thiscontribution we review three recent advances that enable us to investigate large‐scale networksexploiting modern hybrid multi‐node/multi‐core computer architectures: (1) efficient communicationin distributed simulation, (2) use of continuous spike times in a time‐driven simulation scheme, and (3)a multi‐threaded message‐passing simulation kernel. The technical advances are illustrated by a studyof spike timing dependent plasticity (STDP) in a model of a cubic millimeter of cortical tissue containingsome 1,000,000,000 synapses. www.nest‐initiative.org

24 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyProf. Dr. Roland EilsInstitution <strong>German</strong> Cancer Research Center (DKFZ) andUniversity of Heidelberg (BIOQUANT)Contact AddressStreet Address Im Neuenheimer Feld 580, B080Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐42‐3600Fax +49‐6221‐42‐3610E‐Mailr.eils@dkfz‐heidelberg.deWebsitehttp://www.dkfz.de/tbi/Short CV1992 ‐ 1995 Ph.D. study at University of Heidelberg (Ruprecht‐Karl‐Universität Heidelberg);1995 ‐ 1996 Postdoctoral student at the IWR.1996 – 1996 Guest researcher at the Institut Albert Bonniot, Université Grenoble1996 ‐ 1999 Head of the biocomputing group „Structure and function in cellbiology“, IWR,University of Heidelberg, <strong>German</strong>yJanuary 2000 head of the bioinformatics group „Intelligent bioinformatics systems“ at the<strong>German</strong> Cancer Research Center (dkfz)Since 2002 head of division „Theoretical Bioinformatics“ at the <strong>German</strong> Cancer ResearchCenter (dkfz), Heidelberg, presently with 25 researchersNovember 2002 appointed director of department “Bioinformatics and Functional Genomics” andfull professor (C4) at University of Heidelberg2006 Appointed founding director of BIOQUANT, Heidelberg Universities New Centerfor Systems BiologyAwardsJune 1999 BioFuture prize from the <strong>German</strong> Ministery for Education and Research (approx.1.2 Millionen €)2002/2003 Nominated for full professor positions (C4) at University of Giessen, University ofBonn and University of Heidelberg2005 Microsoft Research award “Computational tools for advancing science”2005 Award for new innovative research by <strong>Helmholtz</strong> Society: “Systems Biology ofComplex Diseases”Five most important publicationsBacher CP, Guggiari M, Brors B, Augui S, Clerc P, Avner P, Eils R*, Heard E* (2006) Transientcolocalization of X‐inactivation centres accompanies the initiation of X inactivation. Nat. Cell Biol. 2006Jan 24; [Epub ahead of print] *corresp. author and equal contribution.Bulashevska S, Eils R (2005) Inferring regulatory logic from gene expression data. Bioinformatics 21:2706‐2713.R. König and R. Eils (2004) Gene expression analysis on biochemical networks using the potts spinmodel. Bioinformatics 20: 1500‐1505.Bentele M, Lavrik I, Ulrich M, Stosser S, Heermann DW, Kalthoff H, Krammer PH, Eils R. (2004)Mathematical modeling reveals threshold mechanism in CD95‐induced apoptosis. J. Cell Biol. 166: 839‐51.Gerlich, D., Kalbfuss, B., Beaudouin, J., Daigle, N., Eils, R.*, Ellenberg, J. (2003) Inheritance ofchromosome topology throughout mitosis. Cell 112: 751‐764. *corresponding authorContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a talkTitle of poster / talkFrom models to experiments and back: challenges and promises of systems biologyResearch InterestsAnalysis and mathematical modelling of complex processes in molecular and cell biology

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 25Dr. Jan EufingerInstitution <strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 580Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐42‐3623Fax +49‐6221‐42‐3620E‐Mailj.eufinger@dkfz‐heidelberg.deWebsitewww.dkfz.de/en/sbcancerwww.helmholtz.de/systemsbiologyShort CV1996 – 2001 Studies in Biology (Diploma), University of Heidelberg2001 4 months internship at BASF, Ludwigshafen2002‐2006 PhD Studies in Molecular Plant Sciences,Heidelberg Institute of Plant Sciences, University of Heidelberg2006/2007 Facility Management at BIOQUANT‐Institute, University of HeidelbergSinceJune 2007Scientific Project Management for the <strong>Helmholtz</strong> Alliance on Systems Biology andSBCancer, <strong>German</strong> Cancer Research Institute (DKFZ) HeidelbergContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkThe research networks of the <strong>Helmholtz</strong> Alliance on Systems BiologyAbstractThe <strong>Helmholtz</strong> Alliance on Systems Biology is a centrally funded, joint initiative of several <strong>Helmholtz</strong>centers and external partners. The aim of the Alliance is to exploit the outstanding expertise of the<strong>Helmholtz</strong> Association in basic, high‐through put and bioinformatics research and to transfer it toinnovative "Systems Biology" type of approaches. Scientific focuses of the Alliance are various complexdiseases with the overall goal to widen the understanding of the causes of these diseases and thedevelopment of new strategies for treating them.The Alliance consists of six interconnected networks, each led by a specific <strong>Helmholtz</strong> centre. TheDKFZ's network "Systems Biology of Signalling in Cancer (SBCancer)", the largest network of theAlliance, concentrates on signalling pathways that play a pivotal role in the cellular decisions betweenproliferation, differentiation and death.For quantitative modeling approaches, the production and integration of standardized information isinevitable. Therefore the <strong>Helmholtz</strong> Alliance will concertedly expand existing experimental, IT andmodeling techniques to provide an integrated efficient structure for all members of the Alliance.In order to promote the emerging discipline of Systems Biology, the <strong>Helmholtz</strong> Alliance will transfer itsknowledge and experience into educational programs (workshops, Summer Schools, PhD programs).Poster number: 7

26 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyProf. Mikhail GelfandInstitution Institute for Information Transmission ProblemsContact AddressStreet Address Bolshoi Karetny per. 19Zip /Postal Code 127994CityMoscowCountryRussiaPhone +7‐495‐6504225Fax +7‐495‐6500579E‐Mailgelfand@iitp.ruWebsitehttp://www.rtcb.iitp.ru/mg_e.htmShort CVcomparative genomicsmetagenomicsfunctional annotation of genes and proteins and metabolic reconstruction fromgenomic dataevolution of metabolic pathways and regulatory systemsalternative splicingstatistics of DNA sequencesAwards2007 A.A.Baev Prize in Genomics and Genoinformatics ‐ <strong>Russian</strong> Academy of Sciences2006 Best publication in a <strong>Russian</strong> scientific journal award ‐ Nauka Publishers2004 Best Scientist of the <strong>Russian</strong> Academy of Sciences (doctors of science, biology) ‐Fund for Support fo the <strong>Russian</strong> Science2001‐2005 and Howard Hughes International Research Scholar2006‐20102000 The President of <strong>Russian</strong> Federation's Award for Young Doctors of ScienceResearch Interestscomparative genomics;metagenomics;functional annotation of genes and proteins and metabolic reconstruction from genomic data;evolution of metabolic pathways and regulatory systems;alternative splicing.Five most important publicationsRodionov DA, Gelfand MS, Todd JD, Curson A.R.J, Johnston A.W.B. Computational reconstruction ofiron‐ and manganese‐responsive transcriptional networks in alfa‐proteobacteria. PLoS Comput Biol.2006, 444: 240.Spirin V, Gelfand MS, Mironov AA, Mirny LA. A metabolic network in the evolutionary context:Multiscale structure and modularity. Proc Natl Acad Sci U S A., 2006, 103: 8774‐8779.Vitreschak AG, Rodionov DA, Mironov AA, Gelfand MS. Riboswitches: the oldest mechanism for theregulation of gene expression? Trends Genet. 2004, 20: 44‐50.Panina EM, Mironov AA, Gelfand MS. Comparative genomics of bacterial zinc regulons: enhanced iontransport, pathogenesis, and rearrangement of ribosomal proteins. Proc Natl Acad Sci U S A. 2003,100: 9912‐9917.Nurtdinov RN, Artamonova II, Mironov AA, Gelfand MS. Low conservation of alternative splicingpatterns in the human and mouse genomes. Hum Mol Genet. 2003, 12:1313‐1320.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(X) a talkTitle of poster / talkRegulatory systems in bacteria: from comparative genomics to reconstruction of evolutionary historyAbstractComparative analysis of bacterial genomes allows not only for identification of new regulatory systemsand functional annotation of hypothetical genes, but also for characterization of changes in regulatorypatterns. Although it is premature to speak about a theory of regulatory evolution, some patterns startto emerge. I will present results of genomic analysis of several systems of varying complexity,providing examples of regulon expansion, contraction, changes in regulatory systems, co‐evolution oftranscription factors and their DNA motifs, etc. In particular, I plan to describe the reconstruction ofthe evolution of iron homeostasis regulation in alpha‐proteobacteria.

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 27Dr Nail GizzatkulovInstitution (1) Institute for Systems Biology SPb (2) Moscow State UniversityContact AddressStreet Address Leninskie Gory, 1/73, AN Belozerski IPCB Moscow State UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailgizzatkulov@gmail.comWebsitewww.insysbio.ruShort CV (keywords)2004‐present Institute for Systems Biology SPb2005‐2006 Research Scientist Keldysh Istitute of Apply Mathematics of <strong>Russian</strong> Academy ofScience, Moscow.2005 Ph.D., Keldysh Istitute of Apply Mathematics of <strong>Russian</strong> Academy of Science,Moscow.2002‐2005 PhD Student of Keldysh Istitute of Apply Mathematics of <strong>Russian</strong> Academy ofScience1996‐2002 Faculty of Applied Mathematics, Ufa Aircraft State Technical UniversityResearch Interests (3‐5 sentences)Research Interests of Dr Gizzatkulov are focused in areas of Systems Biology and Bioinformatics andscientific programming with especial focus on scientific programming of software modeling ofbiological processes and their application to biotechnology and biomedicine. Areas of expertise:Methods and software for control of industrial biotechnology processesMethods and software for drug safety assessmentMethods and software for kinetic modelingContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster(please indicate)() a talkTitle of poster / talkSoftware for modeling complex biological systemsAbstractPoster presents software developed for modeling complex biological systems:Model Creator – create kinetic model from scratch, annotate model, save model to various formatsuch as SBML ( System Biology Markup Language );DBSolve7 – software to create, solve, analyze and visualize kinetic model corresponding to complexbiological systems;One more topic of my poster is software which could be created using engine of DBSolve7 and ModelCreator. This software has been applied to resolve different problems arising in area of biomedicineand biotechnology.Poster number: 8

28 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Evgeny GladilinInstitution <strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 267Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐5451299E‐Maile.gladilin@dkfz‐heidelberg.deShort CVPostdoctoral Scientist, <strong>German</strong> Cancer Research Center, TheoreticalBioinformatics, HeidelbergPhD in Mathematics, Free University BerlinMS in Physics, University HamburgBS in Biophysics, <strong>Russian</strong> State Medical University, MoscowResearch Interestscell mechanics, mechanotransduction, image analysis, numerical modelingFive most important publications1. E. Gladilin, A. Micoulet, B. Hosseini, J. Spatz, K. Rohr, R. Eils. "Finite element analysis ofuniaxial cell stretching: from image to insight". IOP Phys. Biol., Volume 4, Issue 2, p. 104‐113, 20072. E. Gladilin, S. Goetze, J. Mateos‐Langerak, R. van Driel, K. Rohr, R. Eils. "Geometricalprobability approach for analysis of 3D chromatin structure in interphase cell nuclei".Proc. of IEEE CIBCB Symposium, p. 124‐134, 20073. E. Gladilin, S. Goetze, J. Mateos‐Langerak, R. van Driel, R. Eils, K. Rohr."Topological analysis of 3D cell nuclei using finite element template‐based sphericalmapping". Proc. of SPIE MI, vol. 6144, p. 1557‐1566, 20064. E. Gladilin, V. Pekar, K. Rohr, H.S. Stiehl. "A comparison between BEM and FEM for elasticregistration of medical images". Image and Vision Computing, 24(4):375‐379, 20065. E. Gladilin, A. Ivanov, V. Roginsky. "Generic Approach for Biomechanical Simulationof Typical Boundary Value Problems in Cranio‐Maxillofacial Surgery Planning". Proc. ofMICCAI, p. 380‐388, 2004Title of poster / talkComputational analysis of uniaxial cell stretching using time series of microscopic images andpredictive numerical model of cell mechanicsAbstractMechanical forces play an important role in many microbiological phenomena such as embryogenesis,regeneration, cell proliferation and differentiation. Micromanipulation of cells in a controlledenvironment is a widely used approach for understanding cellular responses with respect to externalmechanical forces. While modern micromanipulation and imaging techniques provide useful opticalinformation about the change of overall cell contours under the impact of external loads, the intrinsicmechanisms of energy and signal propagation throughout the cell structure are usually not accessibleby direct observation. This work dealswith the computational modeling and simulation of intracellular strain state of uniaxially stretchedcells captured in a series of images. A nonlinear elastic finite element method was applied fornumerical analysis of inhomogeneous stretching of a rat embryonic fibroblast 52 (REF 52) using asimplified two‐component model of a eukaryotic cell consisting of a stiffer nucleus surrounded by asofter cytoplasm. The difference between simulated and experimentally observed cell contours is usedas a feedback criterion for iterative estimation of canonical material parameters of the twocomponentmodel such as stiffness and compressibility. Analysis of comparative simulations withvarying material parameters shows that (i) the ratio between the stiffness of cell nucleus andcytoplasm determines intracellular strain distribution and (ii) large deformations result in increasedstiffness and decreased compressibility of the cell cytoplasm. The proposed model is able to reproducethe evolution of the cellular shape over a sequence of observed deformations and providescomplementary information for a better understanding of mechanical cell response.Poster number: 9Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talk

Dr. rer. nat. Giovani Gomez Estrada<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 29Institution <strong>Helmholtz</strong> Zentrum MuenchenContact AddressStreet Address Ingolstaedter Landstrasse 1Zip /Postal Code 85794CityNeuherbergCountry<strong>German</strong>yPhone 089 3187‐3683Fax 089 3187‐3585E‐Mailgiovani.estrada@helmholtz‐muenchen.deShort CVBsc in Comp. Eng., 1996, Monterrey Tech, MexicoMsc in Comp. Sci., 1999, Monterrey Tech, MexicoDr. rer. nat., 2007, University of Stuttgart, <strong>German</strong>yResearch positions: Swiss Federal Institute of Technology (ETH, 2000‐2001),Monterrey Tech (2001‐2002), Max Planck Institute (MPI‐MF, 2002‐2006) andRoyal College of Surgeons in Ireland (RCSI, 2006‐2007).Currently a post‐doc in the <strong>Helmholtz</strong> Zentrum Muenchen, Instituteof Bioinformatics and Systems BiologyResearch InterestsBiomedical data analysis and biostatistics (e.g. nanotoxicity, prognosis of breast and gastric cancer),mathematical modelling of multi‐stable dynamic systems with biochemical reaction networks(apoptosis, stability) and discrete structures (cellular tensegrity).Five most important publicationsQuantitative analysis of cell adhesion on aligned micro‐ and nanofibers; Journal of BiomedicalMaterials Research Part A, 84A(2):291‐299, Feb. 2008Cytotoxicity of Single Wall Carbon Nanotubes on Human Fibroblasts; Toxicology in Vitro, 20(7):1202‐1212, Oct. 2006Numerical form‐finding of tensegrity structures; Int. J. of Solids and Structures, 43(22‐23):6855‐6868,Nov. 2006A microarray‐based gastric carcinoma prewarning system; World Journal of Gastroenterology,11(9):1273‐1282, Mar. 2005Characterization of BRCAA1 and its novel antigen epitope identification; Cancer Epidemiology,Biomarker & Prevention, 13(7):1136‐1145, Jul. 2004

30 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr Ekaterina GoryachevaInstitutionContact AddressStreet AddressInstitute for Systems Biology SPbLeninskie Gory, 1/73, AN Belozerski IPCB MoscowState UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailkate@biophys.msu.ruWebsitewww.insysbio.ruShort CV2004‐present CSO Institute for Systems Biology SPb2001–present Institute of Bioorganic Chemistry, <strong>Russian</strong> Academy of Sciences2001 Ph.D., Biophysical Department, Faculty of Biology, Moscow State University,Moscow. Title: The influence of modification of Reaction Centres from purplebacterium Rhodobacter sphaeroides on the electron transfer in the picosecondtime scale.1996‐1999 Post‐graduate of Biophysical Department, Faculty of Biology, Moscow StateUniversity1991‐1996 Biophysical Department, Faculty of Biology, Moscow State UniversityMay 1996: M.Sc., Biophysical Department, Faculty of Biology, Moscow StateUniversity, Moscow. Title: The influence of intramolecular dynamics on kineticsof picosecond stages in Reaction Centres from purple bacterium Rb. sphaeroides.Research InterestsResearch Interests of Dr Goryacheva are focused in areas of Systems Biology and Bioinformatics,databases analysis, kinetic modeling and their application to biotechnology and biomedicine. Areas ofexpertise:Modeling of cellular metabolismModeling of cell signalingModeling of gene regulatory networksPathway reconstructionAnalysis of proteins and peptides structureAnalysis of enzyme‐substrate interactions, search of inhibitorsFive most important publicationsDemin O.V., Lebedeva G.V., Kolupaev A.G., Zobova E.A., Plyusnina T.Yu., Lavrova A.I., Dubinsky A.,Goryacheva E.A., Tobin F., Goryanin I.I. Kinetic Modelling as a Modern Technology to Explore andModify Living Cells. IN: G. Ciobanu, G. Rozenberg (Eds.): Modelling in Molecular Biology (2004),Natural Computing Series, Springer p.59‐103Pletnev VZ, Goryacheva EA, Tsygannik IN, Nesmeianov VA, Pletnev SV, Pangborn W, Daux W. A newcrystal form of the Fab fragment of a monoclonal antibody to human interleukin‐2: the threedimensionalstructure at 2.7 A resolution Bioorg Khim, <strong>Russian</strong> (2004) v30(5) p.466‐469.Krasilnikov PM., Gorokhov VV., Goryacheva EA., Knox PP., Pashchenko VZ., Rubin AB. Investigation ofthe electron transfer reactions and redox characteristics of photoactive bacteriochlorophyll inRhodobacter sphaeroides reaction centers modified by D2O and cryoprotectants. Membr Cell Biol.(2000) v.14(3), p.343‐356.Paschenko VZ., Gorokhov VV., Grishanova NP., Goryacheva EA, Korvatovsky BN., Knox PP., ZakharovaNI., Rubin AB. The influence of structural‐dynamic organization of the RC from purple bacteriumRhodobacter sphaeroides on picosecond stages of photoinduced reactions. // Biochim. Biophys. Acta(1998), v.1364, p.361‐372.Paschenko VZ., Knox PP., Gorokhov VV., Korvatovsky BN., Zakharova NI., Goryacheva EA, Rubin AB.Temperature dependence of first stages of photosynthesis in native and modified RC from bacteriumRhodobacter sphaeroides. Doklady Akademii Nauk (1997) v.357, N6, p.835‐838.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkPathway reconstruction and target identification in breast cancerAbstractBreast cancer is one of the most serious problems of oncology. In the past 20 years, there has been atremendous increase in our knowledge of the molecular mechanisms and pathophysiology of humancancer. However insufficient clinical effectiveness and toxicity to the patient of used antitumortreatments stimulate further investigations of tumor cells features. Effective analysis and fusion ofavailable experimental data is possible using system biology methods, one of them is pathwayreconstruction. Pathway reconstruction of breast cancer cells accumulates all information aboutmetabolic processes, signal transduction, gene regulation playing important role in tumor growth. Thisinformation is necessary for deeper understanding of molecular mechanisms of tumor cellsmetabolism regulation and searching for drug targets and drug combinations for breast cancertreatments.Poster number: 10

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 31Georgy G. GulbekyanInstitution M.V.Lomonosov Moscow State UniversityContact AddressStreet Address Vorobievy GoryZip /Postal Code 119991CityMoscowCountryRussiaPhone +7(495)1372384E‐Mailgulbekyan@gmail.comShort CVEducation B.S., M.S., in Biophysics from School of Physics, M.V.Lomonosov Moscow StateUniversityKeywords Gene expression, microarrays, gene markers, evolutionary algorithms, datamining, acute lymphoblastic leukemiaResearch interestsNew approaches to construction of a compact set of tumor marker genes and its application indifferential diagnosis of various subtypes of acute lymphoblastic leukemia. Tumor marker genes andunderlying biology. Data mining.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkA combined algorithm of tumor marker genes determination and its application to microarray ALL dataGulbekyan, G.G., Valyaev, V.Yu, Ivanov P.S.AbstractWe present a novel algorithm for detecting marker genes in multiclass microarray data that combinestwo well‐proved approaches, namely, supervised classification and evolution simulation. We selectedSupport Vector Machine (SVM) to classify microarray samples. First, we use a LKOCV scheme topartition initial data into training and test datasets and to fit the parameters of classification algorithm.Second, we estimate the classification error for a large number of training/test partitions byrandomizing initial data. Third, we simulate mutations in a randomly chosen set of potential markergenes (predictor) and simultaneous evolution of several such predictors combined in a predictor pool.At each evolutionary epoch, we retain a predictor in or exclude it from the predictor pool based on itsclassification power (quality measure). Fourth, we stop the evolutionary process when changes inclassification quality measure appear to be less than a chosen threshold or after a predefined numberof iterations. Results of applying this algorithm to a model dataset as well as to pediatric acutelymphoblastic leukemia (ALL) microarray data (Ross M. et al. (2003) Blood 102: 2951‐2959) will bepresented.Poster number: 11

32 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyVitaly V. Gursky, PhD studentInstitutionContact AddressStreet AddressZip /Postal Code 194021CityCountryIoffe Physico‐Technical Institute26, Politekhnicheskaya StreetSt. PetersburgRussiaPhone +7 812 2927352Fax +7 812 2971017E‐Mailgursky@math.ioffe.ruShort CV1991‐1999 Magister in Physics, Physics Faculty of the St. Petersburg State University2002‐nowJunior Research Fellow at the Ioffe Physico‐Technical Institute of the <strong>Russian</strong>Academy of SciencesResearch InterestsSystems biology, mathematical modeling in biology, mathematical modeling of gene regulation, genenetworks, mechanisms of development, mechanisms of robustness, development of multi‐cellularorganisms, segmentation of Drosophila, dynamical system applications in modeling segmentation geneexpression in Drosophila, reaction‐diffusion systems in nonlinear scienceFive most important publicationsV. V. Gursky, K. N. Kozlov, A. M. Samsonov, J. Reinitz, Cell divisions as a mechanism for selection instable steady states of multi‐stationary gene circuits, Physica D 218(1): 70‐76, 2006M. G. Samsonova, A. M. Samsonov, V. V. Gursky, C. E. Vanario‐Alonso, A survey of gene circuitapproach applied to modelling of segment determination in fruit fly. In: Multiple aspects of DNA andRNA: from Biophysics to Bioinformatics, Session LXXXII (Eds. D. Chatenay et al.), Elsevier, 2005V. V. Gursky, J. Jaeger, K. N. Kozlov, J. Reinitz, A. M. Samsonov, Pattern formation and nuclear divisionsare uncoupled in Drosophila segmentation: Comparison of spatially discrete and continuous models,Physica D 197: 286‐302, 2004V. V. Gursky, J. Reinitz, A. M. Samsonov, How gap genes make their domains: An analytical study basedon data driven approximations, Chaos 11(1): 132‐141, 2001A. M. Samsonov, V. V. Gursky, Exact solutions to a nonlinear reaction‐diffusion equation andhyperelliptic integrals inversion, J. Phys. A: Math. Gen. 32: 6573‐6588, 1999Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkStable hb expression under variable Bcd morphogen in Drosophila: Asymptotic approach in model ofgap gene expressionAbstractIt is well known that the Bcd morphogen is one of the key regulators of gap gene hb in the earlyDrosophila embryo. In the classical model, the posterior border of the Hb anterior domain gets formedas a threshold dependent response to the Bcd gradient at that position in the A‐P axis of the embryo. Aserious problem in this concept arises from the fact that Bcd concentration exhibits high embryo toembryo variability, which essentially exceeds that of the Hb domain border [1]. A candidate formechanisms stabilizing the expression of gap genes under variable Bcd is the cross regulation betweengap genes. We explore this hypothesis by studying a mathematical model of gap gene expressionformulated in [2]. Under simplifying assumptions of stationarity and sharp sigmoid regulation functionin model equations, the expression patterns in the model can be analytically derived as superpositionsof local interfaces. We obtain analytical formulas for variations of these interfaces as functions of Bcdvariation. By using this approach, we demonstrate that the mechanism of mutual regulation in the gapgene network is able to provide the experimentally observed stability rate of gap gene expression.[1] B. Houchmandzadeh, E. Wieschaus, S. Leibler (2002). Establishment of developmental precision andproportions in the early Drosophila embryo, Nature 415, 798–802.[2] J. Jaeger, S. Surkova, M. Blagov, H. Janssens, D. Kosman, K. N. Kozlov, Manu, E. Myasnikova, C. E.Vanario‐Alonso, M. Samsonova, D. H. Sharp, J. Reinitz (2004). Dynamic control of positionalinformation in the early Drosophila embryo, Nature 430, 368–371.Poster number: 12

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 33Prof. Dr. Thomas HöferInstitution <strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 280Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49 6221 54 51 380Fax +49 6221 54 51 487E‐Mailt.hoefer@dkfz‐heidelberg.deWebsitewww.dkfz.deShort CV2006 – present Group leader, Modeling of Biological Systems, <strong>German</strong> CancerResearch Center, Heidelberg2002 – 2006 Junior professor in theoretical biophysics, Humboldt Univ. Berlin1997 – 2002 Lecturer in biophysics, Humboldt Univ. BerlinExtended research visits to Collège de France (2000/01) and New Jersey MedicalSchool (2001/02)1996 ‐ 1997 Postdoc, Max‐Planck Institute for Physics of Complex Systems, Dresden1996 PhD, mathematical biology, University of Oxford1993 Diplom‐Biophysiker, Humboldt University BerlinAwards1994 ‐ 1996 Jowett Senior Scholar, Balliol College Oxford1993 ‐ 1996 PhD scholarship, Boehringer Ingelheim Fonds1991 ‐ 1993 Fellow, Studienstiftung des deutschen VolkesResearch InterestsMathematical modeling of complex cellular processes:Gene‐regulatory networks, especially in T lymphocyte differentiationSignal transduction pathways (hormone/calcium and cytokine/Stat pathways, T‐cell receptor signaling)Molecular machines of DNA repair, replication, and chromatin regulationFive most important publicationsScheffold, A., Murphy, K.M., and Höfer T.. (2007) Competition for cytokines: Treg cells take all. Nat.Immunol. 8, 1285‐1287Höfer, T., Mühlinghaus, G., Moser, K., Yoshida, T.E., Mei, H., Hebel, K., Hauser, A., Hoyer, B., Luger E.,Dörner, T., Manz, R.A. Hiepe, F., and Radbruch A. (2006) Adaptation of humoral memory. Immunol.Rev. 211, 295‐30Salazar, C. and Höfer, T. (2003) Allosteric regulation of the transcription factor NFAT1 by multiplephosphorylation sites: a mathematical analysis. J. Mol. Biol. 327, 31‐45Höfer, T., Nathanson, H., Löhning, M., Radbruch, A., and Heinrich, R. (2002) GATA‐3 transcriptionalimprinting in Th2 lymphocytes: a mathematical model. Proc. Natl. Acad. Sci. USA 99, 9364‐9368Höfer, T., Venance, L., and Giaume, C. (2002) Control and plasticity of intercellular calcium waves inastrocytes: a modeling approach. J. Neurosci. 22, 4850‐4859Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x ) a talkTitle of poster / talkFrom molecular machines to gene‐regulatory networks in mammalian cellsAbstractThe complexity of regulatory networks in mammalian cells – exemplified by the vast number ofcomponents and their dynamic interactions on a wide range of time and space scales – requiresmathematical models at different levels of organization. I will discuss experimentally‐based models of(i) the protein machinery that recognizes and repairs UV‐damaged DNA, and (ii) a gene‐regulatorynetwork governing T lymphocyte differentiation. Iterative theoretical and experimental analyses ofnetwork dynamics have allowed us to uncover novel regulatory interactions and identify criticalmolecular steps for controlling the biological functions of the respective networks.

34 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyProf. Dr. Ralf HofestädtInstitution Bielefeld UniversityContact AddressStreet Address PF 100131Zip /Postal Code 33501CityBielefeldCountry<strong>German</strong>yPhone 0521 106 5283FaxE‐Mailhofestae@uni‐bielefeld.deWebsitewww.uni‐bielefeld.deShort CV1985‐1990 Assistant researcher, Theoretical Computer Science, University Bonn1990‐1994 Assistant Professor, Institute Applied Computer Science, University Koblenz‐Landau;1995‐1996 Assistant Professor, Institute of Medical Informatics, University Leipzig;1996‐2001 Professor, Institute of Applied Computer Science, University Magdeburg;Science 2001 Professor, Institute of Bioinformatics and Medical Informatics, UniversityBielefeld;2004 University Heidelberg (Rejected 2004), Professor position for Medical Informaticsand Bioinformatics;Since 2004 Member of the Fachkollegium of the <strong>German</strong> Foundation of Science forBioinformatics – since 2004.Scince 2007 Speaker of the “FB Computer Science for Life Science” of the <strong>German</strong> Society ofComputerResearch InterestsDatabases and database integration; Modeling and dimulation of metabolic processes; Drug pointing;Knowledge Representation; Medical Diagnosis Systems, Parallel Computing, GRID Computing,Detection of Metabolic Diseases.Five most important publicationsHofestädt R., Krückeberg F. und Lengauer T. (eds): Informatik in den Biowissenschaften. InformatikAktuell, Springer‐Verlag, Heidelberg 1993.Hofestädt R., Lengauer T., Löffler M. and Schomburg D. (eds): Bioinformatics. LNCS, 1278, Springer‐Verlag 1997.Hofestädt R. and Schnee R.: Studien und Forschungsführer Bioinformatik. Spektrum AkademischerVerlag, Heidelberg, 2002.Collado‐Vides J. and Hofestädt R. (eds): Gene Regulation and Metabolism ‐ Post‐GenomicComputational Approaches. Cambridge, MA: MIT Press, 2002.Kolchanov N. and Hofestädt R. (eds.): Bioinformatics of Genome Regulation and Structure. KluewerAcademic Publishers 2004.Kolchanov N, Milanesi L. and R. Hofestädt (eds): Binformatics of Genome Regulation and Structure II.Kluewer Academic Publishers 2005.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(please indicate)( x) a talkTitle of poster / talkRAMEDIS: monitoring of inborn errors based on clinical and molecular dataAbstractThe RAMEDIS system is a platform independent, web‐based information system for rare diseases onthe basis of individual case reports. It was developed in close cooperation with clinical partners andcollects information on rare metabolic diseases with extensive details, e.g. about occurring symptoms,laboratory findings, therapy and genetic data. This combination of clinical and genetic facts enablesthe analysis of genotype‐phenotype correlations. RAMEDIS supports an extendable number ofdifferent genetic diseases and enables co‐operative studies. Furthermore, use of our system shouldlead to advances in epidemiology, combination of molecular and clinical facts, and generation of rulesfor therapeutic intervention and identification of new diseases.Availability: http://www.ramedis.de

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 35Anna Ignatovich, studentInstitution VMiK MSU, INM RASContact AddressStreet Address Orechovij bulvar, 59 ‐ 20Zip /Postal Code 115 682CityMoscowCountryRussiaPhone 8‐495‐344‐20‐27, 8‐916‐596‐88‐39E‐Mailanja_ignatovich@mail.ruShort CV2003‐2008 Moscow State University, Faculty of Computational Mathematics and CyberneticsResearch Interestsmathematical modeling in immunologymodelling the dynamics of HIV infection (virus quasispieces, recombination and mutation)emergence of drug resistanceepistasisgenetic algorithmsContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(+) a poster( ‐) a talkTitle of poster / talkModelling the dynamics of AZT‐resistant mutants in HIV infectionAbstractTreatment of HIV‐1 infection with drugs (AZT) reduces the HIV‐1 load, but after some time the virusevolves drug resistant mutations. In oder to investigate the evolutionary order in which the mutantsarise and to describe their dynamics, we develop a mathematical model for this situation. The modelconsiders the generation of new mutants, their fitness values and the nucleotide misincorporationrates. The computational results of modelling the AZT‐driven intra‐patient HIV evolution are discussed.Poster number: 13

36 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr John IonidesInstitution St Petersburg State Polytech. UniContact AddressStreet Address Polytehnicheskaya 29Zip /Postal Code 195251CitySt PetersburgCountryRussiaPhone +7 9213152449E‐Mailjohn.ionides@gmail.comShort CV1993‐1998 Ph.D NMR methods (Laboratory of Molecular biology, Cambridge, UK)1998‐2007 work European Bioinformatics Insitiute; structural bioinformatics2007‐ work St Petersburg State Polytech. Uni.; drosophila developmentResearch InterestsMy interestes revolve around the application of computing techniques to the biological sciences. Idivide my time between gene expression models (modelling gene expression in Drosophila embryodevelopment) and developing architectures for handling large biological datasets, in particular theProtein Data Bank (PDB) and the Collaborative Computing Project for NMR (CCPN).Five most important publications• Henrick K, Feng Z, Bluhm WF, Dimitropoulos D, Doreleijers JF, Dutta S, Flippen‐Anderson JL,Ionides J, Kamada C, Krissinel E, Lawson CL, Markley JL, Nakamura H, Newman R, Shimizu Y,Swaminathan J, Velankar S, Ory J, Ulrich EL, Vranken W, Westbrook J, Yamashita R, Yang H,Young J, Yousufuddin M, Berman HM. Remediation of the protein data bank archive.Nucleic Acids Research. 36(Database issue):D426‐33 (2008).• Fogh RH, Boucher W, Vranken WF, Pajon A, Stevens TJ, Bhat TN, Westbrook J, Ionides JM,Laue ED. A framework for scientific data modeling and automated software development.Bioinformatics 21(8): 1678‐84 (2005)• Vranken WF, Boucher W, Stevens TJ, Fogh RH, Pajon A, Llinas M, Ulrich EL, Markley JL,Ionides J, Laue ED. The CCPN data model for NMR spectroscopy: development of a softwarepipeline. Proteins. 2005 Jun 1;59(4):687‐96.• Pajon, A., Ionides, J., Diprose, J., Fillon, J., Fogh, R., Ashton, A.W., Berman, H., Boucher, W.,Cygler, M., Deleury, E., Esnouf, R., Janin, J., Kim, R., Krimm, I., Lawson, K.L., Oeuillet, E.,Poupon, A., Raymond, S., Stevens, T., van Tilbeurgh, H., Westbrook, J., Wood, P., Ulrich, E.,Vranken W., Xueli, L., Laue, E., Stuart, D.I. and Henrick, K. Design of a Data Model forDeveloping Laboratory Information Management and Analysis Systems for ProteinProduction. PROTEINS: Structure, Function, and Bioinformatics 58(2): 278‐84 (2005)• Golovin, T. J. Oldfield, J. G. Tate, S. Velankar, G. J. Barton, H. Boutselakis, D. Dimitropoulos,J. Fillon, A. Hussain, J. M. C. Ionides, M. John, P. A. Keller, E. Krissinel, P. McNeil, A. Naim, R.Newman, A. Pajon, J. Pineda, A. Rachedi, J. Copeland, A. Sitnov, S. Sobhany, A. Suarez‐Uruena, J. Swaminathan, M. Tagari, S. Tromm, W. Vranken and K. Henrick E‐MSD: anintegrated data resource for bioinformatics Nucleic Acids Research, 32 (Database issue),D211‐D216 (2004)Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( x) a poster( ) a talkTitle of poster / talkIncorporating interactions between transcription factors into the quantitative prediction of expressionfrom regulatory sequences in Drosophila segmentationAbstractTaking as our starting point the model for transcription decribed by Janssens et al. (Nature Genetics,38:1159‐65, 2006) we have incorporated terms for cooperativity and coactivation. The result is aconsiderably more general framework that allows us to take into account specific interactionsbetween transcription factors, and consequently to probe for such interactions in silico.Poster number: 14

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 37Dr. Pavel S. IvanovInstitution M.V.Lomonosov Moscow State UniversityContact AddressStreet Address Vorobievy GoryZip /Postal Code 119991CityMoscowCountryRussiaPhone +7(495)939‐3025Fax +7(495)932‐8820E‐Mailpsmart@rambler.ruWebsitewww.psys.msu.ruShort CVEducation B.S., M.S., and Ph.D in Biophjysics from School of Physics, M.V.LomonosovMoscow State UniversityResearchExperience2003‐ Senior Research Scientist. Dept. Biophysics, School of Physics,M.V.Lomonosov Moscow State University, Moscow, Russia2002‐ Visiting Professor. Dept. Molelcular Biology, University of Wyoming,Laramie, WY, USAFundingINTAS 93‐1877, RFBR 95‐05‐14688, DOE OBER DE‐FG02‐01ER63232Keywords Gene expression, microarrays, clustering of expression profiles, regulatorynetworks, operon prediction, gene markers, evolutionary algorithms,Rhodobacter sphaeroides, Mus musculus, acute lymphoblastic leukemiaResearch interestsResampling approaches for validation of microarray data clusteringMechanisms of arginine and polyamines related gene expression and metabolism regulation incardiomyocytes under acute myocardial infarctionNew approaches to construction of a compact set of tumor marker genes and its application indifferential diagnosis of various subtypes of acute lymphoblastic leukemiaInference of operon structure in procaryotes with account of transcriptome variabilityFive most important publicationsSveshnikova A.N., Ivanov P.S. (2007). Gene expression and microarrays: quantitative analysis issues.Rus. Chem. J., 51: 127‐135 (in <strong>Russian</strong>).Harpster M.H., Bandyopadhyay S., Thomas D.P., Ivanov P.S., Keele J.A., Pineguina N., Gao B.,Amarendran V., Gomelsky M., McCormick R.J., Stayton M.M. (2006). Earliest changes in the leftventricular transcriptome postmyocardial infarction. Mamm. Genome, 17: 701‐715.Pappas C.T., Sram J., Moskvin O.V., Ivanov P.S., Mackenzie R.C., Choudhary M., Land M.L., LarimerF.W., Kaplan S., Gomelsky M. (2004). Construction and validation of the Rhodobacter sphaeroides 2.4.1DNA microarray: transcriptome flexibility at diverse growth modes. J. Bacteriol. 186: 4748–4758.Baryshnikov, B.V., Ivanov, P.S. (2000). Problems in estimating dimensions of strange attractors in theanalysis of biophysical data. Biophysics, 45, 520‐524 (in <strong>Russian</strong>).Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkA combined algorithm of tumor marker genes determination and its application to microarray ALL dataGulbekyan, G.G., Valyaev, V.Yu, Ivanov P.S.AbstractWe present a novel algorithm for detecting marker genes in multiclass microarray data that combinestwo well‐proved approaches, namely, supervised classification and evolution simulation. We selectedSupport Vector Machine (SVM) to classify microarray samples. First, we use a LKOCV scheme topartition initial data into training and test datasets and to fit the parameters of classification algorithm.Second, we estimate the classification error for a large number of training/test partitions byrandomizing initial data. Third, we simulate mutations in a randomly chosen set of potential markergenes (predictor) and simultaneous evolution of several such predictors combined in a predictor pool.At each evolutionary epoch, we retain a predictor in or exclude it from the predictor pool based on itsclassification power (quality measure). Fourth, we stop the evolutionary process when changes inclassification quality measure appear to be less than a chosen threshold or after a predefined numberof iterations. Results of applying this algorithm to a model dataset as well as to pediatric acutelymphoblastic leukemia (ALL) microarray data (Ross M. et al. (2003) Blood 102: 2951‐2959) will bepresented.Poster number: 15

38 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Lars KaderaliInstitution University of Heidelberg, Bioquant BQ26Contact AddressStreet Address Im Neuenheimer Feld 267Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐54 51 357Fax +49‐6221‐54 51 486E‐Maillars.kaderali@bioquant.uni‐heidelberg.deWebsitehttp://hades1.bioquant.uni‐heidelberg.deShort CV1995‐2001 Studies Business and Computer Science, University of Cologne2001 Research Sabbatical, Los Alamos National Laboratories, USA2001‐2006 PhD, Computer Science, University of Cologne2006‐2007 Postdoc, <strong>German</strong> Cancer Research Center, HeidelbergSince 2007 Independent Junior Group Leader, University of HeidelbergResearch InterestsMathematical Modeling and analysis of complex processes in molecular and cell biology, with aparticular focus on virus‐host interactionsMethod development for the analysis of experimental high‐throughput data, e.g. RNAi data,Microarray Data, etc.Machine learning tools and statistical learning algorithms in Bioinformatics and Systems BiologyFive most important publications1. Kaderali, Radde (2007). Inferring Gene Regulatory Networks from Gene Expression Data. In: A.Kelemen, A. Abraham, Y. Chen (Editors), Computational Intelligence in Bioinformatics. Springer‐Verlag, in press.2. Radde, Kaderali (2007). Bayesian Inference of Gene Regulatory Networks using Gene ExpressionTime Series Data. LNBI Lecture Notes in Bioinformatics, 4414, 1‐15.3. Schramm, Vandesompele, Schulte, Dreesmann, Kaderali, Brors, Eils, Speleman, Eggert (2007).Translating Expression Profiling into a Clinically Feasible Test to Predict Neuroblastoma Outcome.Clinical Cancer Research 13(5), 1459‐1465.4. Kaderali, Zander, Faigle, Wolf, Schultze, Schrader (2006). CASPAR: A Hierarchical BayesianApproach to predict Survival Times in Cancer from Gene Expression Data. Bioinformatics 22, 1495‐1502.5. Kaderali, Schliep (2001). Selecting signature oligonucleotides to identify organisms using DNAarrays. Bioinformatics 18, 1340‐1349.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkReverse‐Engineering of Gene Regulatory Networks using Bayes’ regularized Differential EquationsAbstractIn this work, we present a novel methodological approach to reverse engineer gene regulatorynetworks from gene expression time series data. We combine differential equations with a dynamicBayesian network approach, enabling us not only to infer a network from given data and makepredictions of future states of the network, but also allowing it to assign confidences to networkpredictions, evaluate different likely network topologies, and make predictions of future states of thenetwork together with confidence intervals on the predictions made. Last but not least, this approachmakes it possible to give feedbak to experimental groups on which additional experiments would yielda maximal reduction in uncertainty about an underlying network topology.We show an evaluation of our approach on simulated data, as well as results on the gene regulatorynetwork underlying the yeast cell cycle, by analyzing publicly available microarray time series data. Inaddition, we point to applications of our approach in the field of medical systems biology.Poster number: 16

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 39Dr. Alexey KazakovInstitution Institute for Information Transmission Problems RASContact AddressStreet Address Bolshoy Karetny per. 19Zip /Postal Code 127994CityMoscowCountryRussiaPhone +7Fax +7 495 650 0579E‐Mailkazakov@iitp.ruWebsitehttp://www.rtcb.iitp.ru/Short CVCurrent degree Ph. D. in genetics (2000)Education 1996 ‐ 1999: PhD Student, National Research Center of Mental Health RAMS1990 ‐ 1996: Student, Department of Biochemistry, <strong>Russian</strong> State MedicalUniversityProfessional 2004 ‐ present: Senior Scientist Researcher, Institute for Informationemployment Transmission Problems RAS2000 ‐ 2003: Scientist Researcher, Branch of corporation “Integrated Genomics,Inc.”1999 ‐ 2000: Junior Scientist Researcher National Research Center for MentalHealth RAMSResearch InterestsI am interested in transcriptional regulation of bacterial genes and organization of antimicrobialpeptides biosynthetic systems. I use comparative genomics and bioinformatics to investigate differentaspects of evolution of coding and regulatory sequences on a genome level. I also participate indevelopment of database of bacterial regulatory motifs.Five most important publications1. Novikova M, Metlitskaya A, Datsenko K, Kazakov T, Kazakov A, Wanner B, Severinov K. TheEscherichia coli Yej Transporter Is Required for the Uptake of Translation Inhibitor Microcin C. JBacteriol, 2007 Nov;189(22):8361‐8365.2. Severinov K, Semenova E, Kazakov A, Kazakov T, Gelfand MS. Low‐molecular‐weight posttranslationallymodified microcins. Mol Microbiol. 2007 Sep;65(6):1380‐94.3. Kazakov AE, Cipriano MJ, Novichkov PS, Minovitsky S, Vinogradov DV, Arkin A, Mironov AA, GelfandMS, Dubchak I. RegTransBase – a database of regulatory sequences and interactions in a wide range ofprokaryotic genomes. Nucleic Acids Res. 2007 Jan;35(Database issue):D407‐12.4. Permina EA, Kazakov AE, Kalinina OV, Gelfand MS. Comparative genomics of regulation of heavymetal resistance in Eubacteria. BMC Microbiol. 2006 Jun 5;6:49.5. Kazakov AE, Shepelev VA, Tumeneva IG, Alexandrov AA, Yurov YB, Alexandrov IA. Interspersedrepeats are found predominantly in the “old” alpha satellite families. Genomics. 2003 Dec;82(6):619‐27Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkIdentification of microcin C‐like antibiotic systemsAbstractMicrocins are a class of small peptide antibiotics secreted by enterobacteria. Genes of microcinsbiosynthesis, maturation and secretion are often organized in operons. Taking into account thearrangement of genes encoding microcin precursor and microcin maturation enzymes, we were ableto identify 17 microcin C‐like antibiotic systems in 13 bacterial species belonging to beta‐, gamma‐ andepsilon‐Proteobacteria, Firmicutes and Cyanobacteria. Heptapeptides structurally similar to microcinC51 precursor were found in all gene clusters identified, except those from Bartonella henselae andtwo Synechococcus strains. In Synechococcus, two (strain CC9605) or three (strain RS9916) directrepeats each encoding 56 or 57 aminoacid polypeptides, respectively, were observed. The ORFs aresufficiently similar between the two Synechococcus strains and the C‐terminal amino acids of all theORFs are asparagines, that is typical for microcin C51‐like precursors. So, the cyanobacterial microcinprecursors may constitute a novel subtype of C51‐related microcins, with potentially differentproperties. Our analysis demonstrates that peptides structurally similar to microcin C51 from E. colimay be produced by a variety of bacterial groups.Poster number: 17

40 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Ursula KlingmüllerInstitution <strong>German</strong> Cancer Research Center (DKFZ), A150Contact AddressStreet Address Im Neuenheimer Feld 280Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone ++49‐6221‐42‐4481Fax ++49‐6221‐42‐4488E‐Mailu.klingmueller@dkfz.deWebsitewww.dkfz.deShort CV1992 PhD University of Heidelberg, <strong>German</strong>y1992‐1993 Postdoctoral Fellow, Harvard Medical School, Boston, USA1993‐1996 Postdoctoral Fellow, Whitehead Institute for Biomedical Research, Cambridge,USA1996‐2003 Independent Group, Leader Max‐Planck‐Institute for Immunology Freiburg,<strong>German</strong>y2003‐2007 Independent Group Leader, <strong>German</strong> Cancer Research Center (DKFZ), Heidelberg,<strong>German</strong>ySince 2007 Division Head, <strong>German</strong> Cancer Research Center (DKFZ), Heidelberg, <strong>German</strong>yAwards1997 FEBS Anniversary Prize2006 R. Eils, U. Klingmüller, O. Wiestler, E. Wanka,. A.‐P. Zeng, R. Balling. “SystemsBiology of Complex Diseases” Ideenwettbewerb <strong>Helmholtz</strong> AssociationResearch InterestsWe are combining generation of spatiotemporal data with mathematical modeling to identify generaldesing principles in signaling pathways determining cellular decisions. After having data‐based modelsfor signaling pathways activated in primary erythroid progenitor cells or hepatocytes our aim is toquantitatively determine alterations promoting tumor progression and predict targets for intervention.Five most important publicationsU. Klingmüller, U. Lorenz, L. C. Cantley, B. G. Neel, and H. F. Lodish. Specific recruitment of SH‐PTP1to the erythropoietin receptor causes inactivation of JAK2 and termination of proliferative signals. Cell(1995) 80:729‐738.H. Wu, U. Klingmüller, and H. F. Lodish. Interaction of the erythropoietin and stem‐cell‐factorreceptors. Nature (1995) 377: 242‐246.I. Swameye, T. G. Müller, J. Timmer, O. Sandra, and U. Klingmüller. Identification of nucleocytoplasmiccycling as a remote sensor in cellular signaling by data‐based dynamic modeling. PNAS (2003)100:1028‐33.A. C. Heinrich, R. Pelanda, and U. Klingmüller. A mouse model for visualization and targeted mutationsin the erythroid lineage. Blood. (2004) 104(3):659‐66.M. Schilling, T. Maiwald, S. Bohl, M. Kollmann, C. Kreutz, J. Timmer, and U. Klingmüller. Computationalprocessing and error reduction strategies for standardized quantitative data in biological networks.FEBS Journal (2005) 272:6400‐6411.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x) a talkTitle of poster / talkLinking the extent of signaling pathway activation with cellular decisionsAbstractCell growth and differentiation processes are tightly controlled by the activation of complexintracellular signaling networks. To identify general design principles and to elucidate molecularmechanisms underlying cellular decisions, it is important to combine time‐resolved quantitative datawith mathematical modeling to test hypothesis, predict the behavior of system and designexperiments most informative for model validation. We established a data‐based mathematical modelto examine control of transforming growth factor beta mediated signaling in hepatocytes and canshow that negative feed‐back mechansims are imortant regulators.

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 41Ms. Olga KoborovaInstitutionFaculty of Bioengineering and BioinformaticsContact AddressStreet Address 2nd Mosfilmovkii sidestr., h.10, fl.16Zip /Postal Code 119285CityMoscowCountry<strong>Russian</strong> FederationPhone +79035802008E‐MailOkoborova@gmail.comShort CV2006‐present2003‐presentAwardsCertificate andmedalLaboratory assistant, Laboratory of Structure‐Function Based Drug Design,Institute of Biomedical Chemistry of Rus.Acad.Med.Sci.Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow StateUniversity, Graduate studentIV Moscow International Congress «Biotechnology: State of the Art andProspects of Development»Research InterestsThe area of interests includes bioinformatics and system biology.Five most important publications1) Koborova O.N., Filimonov D.A., Zakharov A.V., Lagunin A.A., Kel A., Kolpakov F.,Sharipov R., Poroikov V.V. (2007). Anticander drug targets analysis on the basis of bioinformatictechnologies, IV International conference “Postgenomic technologies for development of antitumoragents with novel mechanisms of action”, Moscow, December 3, 2007, p.15.2) Koborova O.N., Zakharov A.V., Lagunin A.A., Filimonov D.А., Kel A., Kolpakov F., Sharipov R.,Poroikov V.V. Computer‐aided prediction of promising anti‐tumor targets taking into accountinformation about probable side effects. (2007). Ibid, p.109.3) Koborova O.N., Zakharov A.V., Kel A., Kolpakov F., Sharipov R., Poroikov V.V. (2007) Computer‐aidedprediction of promisiong pharmacological targets: breast cancer E2F/pRb pathway as a case study. IVMoscow International Congress «Biotechnology: State of the Art and Prospects of Development»,March 12‐16, Moscow. Russia, 2007, p.405.4) Poroikov V.V., Koborova O.N., Zakharov A.V., Lagunin A.A., Filimonov D.A., Gloriozova T.A.,Sharipov R., Kolpakov F., Milanesi L., Kel A. (2006). Targeting cell cycle: old and new stories inanticancer therapy. Abstr. 4 th Eurasian Meeting on Heterocyclic Chemistry. Thessaloniki, Greece,August 27‐31, 2006, p.73‐74.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X ) a poster( ) a talkTitle of poster / talkComputer‐aided prediction of promising drug targets for breast cancerAbstractOne of the most important problems in search for new anticancer therapies is identification ofproteins that are involved in emergence and progression of malignant diseases, and to find the mostprospective targets among them.We propose an algorithm of anticancer drug target identification. The algorithm models cell cycleregulation as logic networks using the beginning states of nodes (proteins and/or genes) in a primarymoment and counting a number of node states in different time moments – trajectories.The method was applied to different types of breast cancer. We used molecular network consisting of8829 nodes and 13613 edges from TRANSPATH database (http://www.biobase.de), and expressiondata, consisting of up and down regulated genes list from Cyclonet database(http://cyclonet.biouml.org). Promising targets were identified and it’s inhibition changes trajectoryinto apoptosis of breast cancer cells. Preliminary results demonstrate the applicability of the methodto find new targets.The work was supported by FP6 grant LSHB‐CT‐2007‐037590 (Net2Drug).Poster number: 18

42 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Rainer KönigInstitution Pharmacy and Molecular Biotechnology –University of HeidelbergContact AddressStreet Address Im Neuenheimer Feld 267Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49 6221 423601Fax +49 6221 423620E‐Mailr.koenig@dkfz.deWebsitewww.dkfz.de/tbi/people/koenigShort CV (keywords)2004 ‐ present Group leader of the Network Modelling group in the Department ofBioinformatics and Functional Genomics (Director: Prof. Dr. Roland Eils), IPMB,Univ. Heidelberg2001 – 2004 Postdoctoral Researcher in the Division of Theoretical Bioinformatics (head:Prof. Dr. Roland Eils), <strong>German</strong> Cancer Research Center, Heidelberg, <strong>German</strong>y.2000 – 2001 Postdoctoral Researcher in the Division of TheoreticalBioinformatics (head: Prof. Dr. Martin Vingron), <strong>German</strong> Cancer ResearchCenter, Heidelberg, <strong>German</strong>y.1996 ‐ 1999 Phd thesis at the EMBL Heidelberg, Phd in 19991989 ‐ 1996 Studies in Physics and Mathematics, Freiburg, Sussex University (England) andHeidelberg, Physics Diploma in 1996, Mathematics and Physics state exam in1997Awards2004 Teaching degree “Baden‐Württemberg‐Zertifikat für Hochschullehre”2003 Supervisor for exchange students of the “Deutscher AkademischerAustauschdienst” (<strong>German</strong> Academic Exchange Service)Referee for the journals Nucleic Acids Research, BioMedCentral (BMCBioinformatics, BMC Genomics) and Journal of Biomedical InformaticsMember of the selection committee for the MSc studies program of MolecularBiotechnology at the Life Science faculty, University of HeidelbergResearch Interests (3‐5 sentences)I'm interested in systematic pattern recognition on networks using machine learning techniques fordefining drug treatments.Five most important publications1. Segun Fatumo, Kitiporn Plaimas, Jan‐Philipp Mallm, Gunnar Schramm, Ezekiel Adebiyi, MarcusOswald, Roland Eils and Rainer König (2008). Estimating novel potential drug targets of Plasmodiumfalciparum by analysing the metabolic network of knock‐out strains in silico, Infection, Genetics andEvolution (in press).2. Gunnar Schramm, Marc Zapatka, Roland Eils and Rainer König (2007). Using gene expression dataand network topology to detect substantial pathways, clusters and switches during oxygen deprivationof Escherichia coli, BMC Bioinformatics, 8:1493. Arunachalam Vinayagam, Coral del Val, Falk Schubert, Roland Eils, Karl‐Heinz Glatting, Sandor Suhaiand Rainer König (2006). GOPET: A tool for automated predictions of Gene Ontology terms, BMCBioinformatics, 7:1614. Rainer König, Gunnar Schramm, Marcus Oswald, Hanna Seitz, Sebastian Sager, Marc Zapatka,Gerhard Reinelt & Roland Eils (2006). Discovering functional gene expression patterns in the metabolicnetwork of Escherichia coli with wavelets transforms, BMC Bioinformatics, 7:1195. Rainer König & Roland Eils (2004). Gene expression analysis on biochemical networks using the Pottsspin model, Bioinformatics, 20, 1500‐1505.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> workshop on systems biologyI will prepare(x ) a poster(please indicate)( ) a talkTitle of poster / talkn.n.Abstractn.n.Poster number: 19

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 43Dr Yuri A KosinskyInstitution(1) Institute for Systems Biology SPb (2) Moscow State UniversityContact AddressStreet Address Leninskie Gory, 1/73, AN Belozerski IPCB Moscow State UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailykos@nmr.ruWebsitewww.insysbio.ruShort CV2004‐present Research Scientist, Institute for Systems Biology SPb2000–present Research Scientist, Department of structural biology of Shemyakin andOvchinnikov Institute of Bioorganic Chemestry, <strong>Russian</strong> Academia of Science2006 Ph.D., Biophysical Department, Faculty of Biology, Moscow State University,Moscow. Title: Molecular modeling of structural and functional aspects of P‐type ATPases interactions with ATP1996‐1999 Post‐graduate of Department of structural biology of Shemyakin andOvchinnikov Institute of Bioorganic Chemestry, <strong>Russian</strong> Academia of Science1996 M.Sc., Medico‐Biological Faculty of <strong>Russian</strong> state medical university, Moscow.Title: Analysis of cofactors microenvironment in proteins1990‐1996 Medico‐Biological Faculty of <strong>Russian</strong> state medical university, MoscowAwardsParticipation in EU programmes:Research InterestsResearch Interests of Dr Kosinsky are focused in areas of Systems Biology, Bioinformatics andmolecular modeling. Areas of expertise:Modeling of cellular metabolismModeling of cell signalingModeling of gene regulatory networksPathway reconstructionMolecular modeling in drug‐designMolecular modeling software developmentFive most important publicationsPyrkov, T.V., Kosinsky, Yu.A, Arseniev, A.S., Priestle, J.P., Jacoby, E., Efremov, R.G. (2007). Docking ofATP to Ca‐ATPase: Considering Protein Domain Motions. J. Chem. Inf. Model. 47, 1171–1181.Pyrkov T.V., Kosinsky Yu.A., Arseniev A.S., Priestle J.P., Jacoby E., Efremov R.G. Complementarity ofhydrophobic properties in ATP‐protein binding: a new criterion to rank docking solutions. (2007)Proteins: Structure, Function, and Bioinformatics 66(2), 388–398.Efremov, R. G., Kosinsky Yu.A., Nolde D.E., Tsivkovskii, R., Arseniev A.S., Lutsenko, S. MolecularModeling of the Nucleotide‐Binding Domain of the Wilson’s Disease Protein: Location of the ATPbindingSite, Domain Dynamics, and Potential Effects of the Major Disease Mutations. (2004) Biochem.J. 382, Part I, 293‐305.Morgan C.T., Tsivkovskii R., Kosinsky Yu.A., Efremov R.G., Lutsenko S. The Distinct FunctionalProperties of the Nucleotide‐binding Domain of ATP7B, the Human Copper‐transporting ATPase.Analysis of the Wilson disease mutations E1064A, H1069Q, R1151H, and C1104F. (2004) J. Biol. Chem.279(35), 36363‐36371.Kosinsky Yu.A., Volynsky P.E., Lagant P., Vergoten G., Suzuki E., Arseniev A.S., Efremov R.G.Development of the Force Field Parameters for Phosphoimidazole and Phosphohistidine. (2004) J.Comput. Chem., 25(11), 1313‐1321.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkDynamics and regulation of signaling and methaboloc networks in mammalian cells: prostanoidsbiosynthesis and signaling system kinetic modeling.AbstractKinetic model of prostaglandines byosynthesis, transport and signaling was build and speciallyadopted for platelets and endothelium cells (ECs). Prothrombotic thromboxane (TXA2) andantithrombotic prostacyclin (PGI2) are main prostanoids are produced by platelets and by EC’s,respectively. So, disbalance in TXA2 and PGI2 synthesis in blood vessels may increase risk of infarcts orstrokes. We have analysed influence of cyclooxygenase‐2 (COX2)‐specific inhibitors (coxibes) onprostanoids synthesis using our kinetic model describing platelets and EC’s interacting by signalingpathways. Our results show that in case of COX2 containing EC’s (inflammatory ECs) applying ofcoxibes may leads to increasing of thrombotic risk, and this effect is more pronounced for inhibitorswith higher COX2‐selectivety.Poster number: 20

44 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyKonstantin KozlovInstitutionSPb SPUContact AddressStreet Address Polytechnicheskaya ul., 29Zip /Postal Code 195251CitySt.PetersburgCountryRussiaPhone +7 812 596 28 31Fax +7 812 596 28 31E‐Mailkozlov@spbcas.ruWebsitehttp://urchin.spbcas.ru/Short CVDate of Birth 02/22/77EducationMaster's Degree in Mathematics, June 2000, Department of appliedMathematics, St.Petersburg State Polytechnical UniversityCurrent Position Research Fellow in Department of Computational Biology, SPb SPUAwardsBest Speaker Award, „Polytechnic Symposium “Young Scientists for Industry of2007Noth‐West region““2007 Award of „Participant of Youth Scientific‐Innovative Competition“Research Interestsimage analysis, mathematical modelling, software development, systems biologyFive most important publicationsKozlov K., Pisarev A., Matveeva A., Kaandorp J. and Samsonova M. (2007): Image Processing PackageProStack for Quantification of Biological Images. In: Proc. of the 4th Intl. Symposium on Networks inBioinformatics (ISNB). Amsterdam, The Netherlands, 204.J. Jaeger, S. Surkova, M. Blagov, H. Janssens, D. Kosman, K.N. Kozlov, Manu, E.M. Myasnikova, C.E.Vanario‐Alonso, M.G. Samsonova, D.H. Sharp, J. Reinitz. (2004): Dynamic control of positionalinformation in the early Drosophila embryo, Nature. Vol. 430. P. 368‐371.J. Jaeger, M. Blagov, D. Kosman, K.N. Kozlov, Manu, E.M. Myasnikova, S. Surkova, C.E. Vanario‐Alonso,M.G. Samsonova, D.H. Sharp, J. Reinitz. (2004): Dynamical analysis of regulatory interactions in the gapgene system of Drosophila melanogaster, Genetics. Vol. 167. P. 1721‐1737.Kozlov K.N., Samsonov A.M. (2003): New Data Processing Technique Based on the Optimal ControlTheory. Techn. Physics, 48, 11: 6‐14.K.N. Kozlov, E.M. Myasnikova, M.G. Samsonova, J. Reinitz, D. Kosman. Method for spatial registrationof the expression patterns of Drosophila segmentation genes using wavelets // Comp. Technol. 2000.Vol. 5. P. 112‐119.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talk 1Comparison of performance of Differential Evolution and Simulated AnnealingDevelopment of robust and reliable algorithms to reduce the complexity of finding the parameters ofmathematical models by fitting to experimental data has become a foreground job as modernmolecular biology accumulates massive amounts of quantitative data. In this work we compare theperformance of two optimization techniques, namely Differential Evolution (DE) and SimulatedAnnealing (SA).Simulated Annealing is a popular method of the functional minimization that was successfully appliedto important biological problems. Differential Evolution is a rather new and promising optimizationtechnique that was invented at the end of the previous century by Storn and Price (Storn, Price, 1995).Both methods are stochastic and are able to find the global extremum of the functional under appropriateconditions.We characterized the dependence of the final functional value and of the iteration number onalgorithmic parameters by extensive series of numerical runs on a test problem The results for bothmethods were then independently fitted to a power law. While the fitting curves appeared to besimilar in shape, the performance of Differential Evolution was superior in all our experiments.Title of poster / talk 2ProStack, the image analysis software to process and quantify patterns of gene expressionInformation on expression in time and space is crucial to infer gene function. Modern sophisticatedmicroscope techniques allow to monitor gene expression in real time, with a single cell resolution, andcan easily produce thousands of images in a single day. However a bottleneck exists at the step ofimage analysis. Due to large number and frequent need for extraction of fine details any visual analysisof images is impractical. Image analysis packages available today are either expensive commercial ordo not support an automatic analysis of images and require strong programming skills to adaptprograms to a new project.We present a new software package ProStack developed to process and quantify patterns of geneexpression. ProStack is capable to process 2D and 3D digital images of gene expression patternsacquired with confocal microscope. It implements more than 50 operations. Each image processingprocedure is implemented as a separate module. Several modules can be joined in a complex imageprocessing scenario, and the intermediate results can be visualized during the workflow enactment.The processing operations afford tuning to ensure customization and flexibility without the loss ofefficiency. The designed workflow can be saved as a complex program module and re‐used in otherworkflows.The Prostack package was successfully applied to automatically process a wide range of experimentalimages.Poster number: 21 & 22

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 45Ivan Vladimirovich KulakovskiyInstitutionEngelhardt Institute of Molecular BiologyContact AddressStreet Address Vavilov str., 32Zip /Postal Code 119991CityMoscowCountryRussiaPhone +7 499 135 6000Fax +7 499 135 14 05E‐Mailikulakovsky@inbox.ruWebsitewww.eimb.relarn.ru/Short CVBorn12 July 1985 in Velikiye Luki, Pskov RegionMr.Sci in Computer July 2006, Moscow State University of ForestSciencePositions,Central Scientific Research Institute for Machine Building (Korolev),2005‐2006Mission Control Center, Telemetry department, Engineer2006 Engelhardt Institute of Molecular Biology <strong>Russian</strong> Academy of Sciences(Moscow), Graduate student2007 State Research Institute of Genetics and Selection of IndustrialMicroorganisms, Scientific Center GosNIIGenetika, Junior researcherLanguage skills <strong>Russian</strong> (native), English (reading)KeywordsComputational biology, bioinformatics, transcription, system biology, computerscience, databasesResearch InterestsTranscription factor binding sites: structure, models, effective prediction algorithms, experimentaldata processing. Binding site arrangement and clustering in regulatory modules. Storage andprocessing large data volumes.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkIntegrated tool for analysis of DNA‐protein binding dataAbstractResults of ChIP‐chip tiled arrays and even footprints can bring about rather extended DNAsegments, which make a challenge for protein binding motif identification with traditional techniques.At the same time, now the data of protein binding to DNA is available from many different sources ofexperimental information. Simultaneous analysis of data obtained from such sources as SELEX, ChIPchip,footprints etc can result in a much clearer signal for DNA‐protein binding than when using any ofthe data sources alone.For instance, the oligos yielded by SELEX strictly correspond to the binding protein, but theyare usually short and the binding motif in practice is often distorted. At the same time ChIP‐chip arraysgive functional binding motifs, often in vivo, but the resulting sequences are long and can containbinding signals for proteins, different from the test protein.Our objective was to make an integrated tool for incorporating different types ofexperimental data into the single protein binding model. For a binding model we have selected thePositional Weight Matrix (PWM), which is traditional motif model for transcription factor binding sites(TFBS) at DNA. We paid a particular attention to identify the length of a binding signal, the problem,which is not solved in many signal identification tools.The core of the algorithm is SeSiMCMC Gibbs sampler, which is used to construct theanchored optimal multiple local alignment (MLA) of the raw sequence data. “The anchored” heremeans that the any sequence included into MLA should overlap with the anchor sequence initiallyseeded into the data. This layout allowed us to incorporate simultaneously the data of SELEX, which areused as anchors in ChIP‐chip sequences. The resulting MLA thus corresponds to the binding signal forthe correct protein.We have tested our system for several TFBS of Human and Drosophila fly. In result now wecan map specific site occurrences at genome sequences within mapped ChIP‐chip resulting regions aswell as we can detect genome wide putative TFBS rich regions, which were not covered by ChIP‐chipresults. This opens a view to compare ChIP‐chip results obtained in different experimental environmentand study tissue‐specific gene expression.Poster number: 23

46 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyAlexey Lagunin, Ph.D.InstitutionInstitute of Biomedical Chemistry RAMSContact AddressStreet Address Pogodinskaya Str., 10Zip /Postal Code 119121CityMoscowCountryRussiaPhone +7 495 247‐3029Fax +7 495 245‐0857E‐Mailalexey.lagunin@ibmc.msk.ruWebsitewww.ibmc.msk.ruShort CV2006‐ Present Leading Scientist of Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.2004‐2006 Senior Scientist of Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.2002‐2004 Research Scientist of Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.2001‐2002 Junior Scientist of Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.2001 Ph.D. degree in Biochemistry1998‐2001 PhD Student of Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.1992‐1998 Student of <strong>Russian</strong> State Medical UniversityAwards2007 the Award for young scientists for the best research at V.N. OrekhovichInstitute of Biomedical Chemistry, <strong>Russian</strong> Academy of Medicinal Science2001 the Award for young scientists for the best research at V.N. OrekhovichInstitute of Biomedical Chemistry, <strong>Russian</strong> Academy of Medicinal Science2004 the Stipend for young scientists of Regional Social Fund of Native MedicineAssistanceResearch InterestsBioinformatics, system biology, chemoinformatics, structure‐activity relationships analysis, medicinalchemistry.Five most important publicationsPoroikov V., Filimonov D., Lagunin A., Gloriozova T., Zakharov A. PASS: identification of probabletargets and mechanisms of toxicity. SAR QSAR Environ Res. 2007, 18(1‐2):101‐110.Kolpakov F., Poroikov V., Sharipov R., Kondrakhin Yu., Zakharov A., Lagunin A., Milanesi L., Kel A.CYCLONET—an integrated database on cell cycle regulation and carcinogenesis. Nucleic AcidsResearch, 2007, v. 35, D550–D556Lagunin A.A., Dearden J.C., Filimonov D.A., Poroikov V.V. Computer‐aided rodent carcinogenicityprediction. Mutation Research, 2005, v.586, p.138–146.Poroikov V., Lagunin A., Filimonov D. Pharmaexpert: Diseases, Targets and Ligands – Three in One.Proceedings of the 15 th European Symposium on Structure‐Activity Relationships (QSAR) andMolecular Modeling, Ed. by Esin Aki (SENER), Ismail Yalcin, Istanbul, September 05‐10, 2004, p.514‐515.Lagunin A.A., Gomazkov O.A., Filimonov D.A., Gureeva T.A., Dilakyan E.A., Kugaevskaya E.V., ElisseevaYu.E., Solovyeva N.I., Poroikov V.V. Computer‐Aided Selection of Potential AntihypertensiveCompounds with Dual Mechanism of Action. J. Med. Chem., 2003, v.46, p.3326‐3332.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkPharmaExpert: Selection of potential antineoplastic agentsAbstractComputer program PASS predicts ~3300 kinds of biological activity including 378 pharmacotherapeuticeffects, 2756 mechanisms of action, 50 toxic/side effects and 121 metabolic terms on the basis ofstructural formula of chemical compound with average accuracy ~93%(http://www.ibmc.msk.ru/PASS). PharmaExpert interprets PASS predictions taking into considerationknown mechanism‐effect(s) and effect‐mechanism(s) relationships, and provides a flexible mechanismfor selection of compounds with desirable kinds of biological activity in libraries of chemicalcompounds. Knowledgebase of the current version of Since PASS predictions contain a plethora ofinformation about probable biological actions of chemical compounds, using PharmaExpert it ispossible to select compounds with the required multiple mechanisms of action. The study is supportedby FP6‐grant LSHB‐CT‐2007‐037590 (Net2Drug).Poster number: 24

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 47Dr. Inna LavrikInstitution<strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address INF280Zip /Postal Code D69120CityHeidelbergCountry<strong>German</strong>yPhone 49‐6221‐423765Fax 49‐6221‐411715E‐Maili.lavrik@dkfz.deWebsitehttp://www.dkfz.de/en/immungenetik/Inna_group/Inna_englisch.htmlShort CVPh.D. student Department of Chemistry of Natural Compounds, Moscow Lomonosov StateUniversity, RussiaResearch Assitant Research Assitant, Depar Department of Chemistry of Natural Compounds,Moscow State UniversityDocentDepartment of chemistry of natural compounds, Moscow Lomonosov StateUniversity, RussiaSince 2000Scientist, Division of Immunogenetics, Head Prof. Dr P. H. Krammer, DKFZ,Heidelberg,2004 Project leader, Division of Immunogenetics, Tumorimmunology Programme,DKFZ, Heidelberg2007 Project leader, SBCancer, Bioquant, DKFZ, HeidelbergAwards1997 <strong>Russian</strong> state prize for young scientistsResearch InterestsSystems biology of apoptosisDeath receptorsCancer cellsCaspasesFive most important publicationsBentele M*, Lavrik I *, Ulrich M, Stosser S, Heermann DW, Kalthoff H, Krammer PH, Eils R.Mathematical modeling reveals threshold mechanism in CD95‐induced apoptosis. J Cell Biol2004;166:839‐851.Golks A, Brenner D, Krammer PH, Lavrik IN. The c‐ FLIP‐NH2 terminus (p22‐FLIP) induces NF‐kappaBactivation. J Exp Med 2006; 203:1295‐1305.Krammer PH, Arnold R, Lavrik IN. Life and Death of T cells. Nat Rev Immunol 2007; 7:532‐542.Lavrik IN, Golks A, Riess D, Bentele M, Eils R, Krammer PH. (2007). Analysis of CD95 thresholdsignaling: Triggering of CD95(FAS/APO‐1) at low concentrations primarily results in survival signaling. JBiol Chem. 18: 13664‐13671.Lavrik IN, Golks A, Krammer PH. Caspases: Pharmacological manipulation of cell death. J ClinInvestigations. 2005; 115(10): 2665‐2672.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x) a talkTitle of poster / talkLife/Death decision on CD95 by systems biology approachesAbstractCD95 (APO‐1/Fas) is well known as a mediator of apoptosis, however evidence off non‐apoptoticfunctions is accumulating. We investigated NF‐κB activation and apoptosis upon CD95 stimulation andestablished an integrated kinetic mathematical model of CD95‐mediated life and death signalling.Systematic model reduction resulted in a surprisingly simple model well approximating experimentallyobserved dynamics. The model postulates that the missing link in CD95‐mediated NF‐κB activation isthe binding of p43‐FLIP to the IKK complex. This prediction was validated experimentally. Furthermore,we demonstrated that the CD95 signalling pathways already diverge at the Death‐Inducing SignallingComplex (DISC). Model and experimental analysis of protein assembly in the DISC showed that a subtlebalance of c‐FLIPL and procaspase‐8 at this multi‐protein complex determines life/death decisions in anon‐linear way. This is the first mathematical model explaining the complex dynamics of CD95‐mediated apoptosis and survival signalling.

48 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyVsevolod Jurievich Makeev, PhDInstitutionGosNIIgenetikaContact AddressStreet Address 1st Dorozhny proezd, 1Zip /Postal Code 113545CityMoscowCountryRussiaPhone +7 495 315 0156Fax +7 495 315 0501E‐MailMakeev@genetika.ruWebsitehttp://bioinform.genetika.ruShort CVBorn19 August 1967 in Fryazino, Moscow Region, RussiaM.Sci in Physics January 1990, Moscow State UniversityPhD in Physics and March 1996, Moscow State UniversityMathematicsPositions,Lebedev Physical Institute, <strong>Russian</strong> Academy of Sceinces. Research Assistant1990‐19931993‐2000 Engelhardt Institute of Molecular Biology, <strong>Russian</strong> Academy of Sciences, FellowResearcher2001 State Research Institute of Genetics and Selection of IndustrialMicroorganisms, Scientific Center GosNIIGenetika, Head of the LabReviewerNucleic Acid Research, Bioinformatics, BMC Genomics, BMC Bioinformatics,PLOS Biology, J. of Biology, Molecular Systems Biology, J. of Bioinformatics andComputational Biology, J. of Theoretical Biology, Biokhimia (russ),Biotekhnologiya (russ), Biofizika (russ), Molekulyanaja Biologiya (russ)Grant Reviewer INTAS, ERA‐NET, FP6, FP7Language skills <strong>Russian</strong> (native), English (fluent), <strong>German</strong> (reading), French (reading)KeywordsBioinformatics, system biology, genomics, statistical methods, computerscience, biophysics, transcription, protein‐DNA interaction, protein‐proteininteractionResearch InterestsGrammatics of location of transcription factor binding sites in regulatory regions: binding signalidentification, site clustering, overlapping, periodical patterns. Genome evolution, role of nucleotidesubstitution, repeat expansion and dupications. DNA‐protein and protein‐protein interaction, role ofions and water.Five most important publications1. Boeva V, Regnier M, Papatsenko D, Makeev V. (2006) Short fuzzy tandem repeats in genomicsequences, identification, and possible role in regulation of gene expression.Bioinformatics. Mar 15;22(6):676‐84.2. Favorov AV, Gelfand MS, Gerasimova AV, Ravcheev DA, Mironov AA, Makeev VJ. (2005) A Gibbssampler for identification of symmetrically structured, spaced DNA motifs with improved estimation ofthe signal length. Bioinformatics. May 15;21(10):2240‐5.3. Kotelnikova EA, Makeev VJ, Gelfand MS. Evolution of transcription factor DNA binding sites. Gene.347, 255‐263, (2005).4. Lifanov, A.P, Makeev, V.Ju, Nazina, A., Papatsenko, D.A (2003) "Homotypic regulatory clusters inDrosophila". Genome Research, vol 13(4), pp. 579‐88.5. Ramensky V.E, V.Ju Makeev, M.A. Roytberg, and V.G. Tumanyan (2000) A Bayesian approach to DNAsegmentation. J Comput Biol. 7(1‐2):215‐31.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x) a talkTitle of poster / talkDeciphering complex regulatory regions in eukaryotic genomesAbstractTranscriptional initiation in eukaryotes is controlled by sophisticated complexes of transcription factorproteins bound at DNA. To study regulation of gene expression in silico one needs to combineexperimental data from different sources (footprint, SELEX, ChIP‐chip, etc) on the basis of modelsignals recognized by different transcription factors. We present the system, which gives anopportunity to construct and verify the motif models using several combined experimental datasources, including footprinting, SELEX and ChIP‐chip experiments, map the result to the genome andstudy the architecture of regulatory modules.The integrated system includes the database of genomes and programs for multiple alignment, signalrecognizing (SeSiMCMC Gibbs sampler) and estimation of statistical significance of a motif model(AhoPro word analyser). Some results on genome wide binding signal recognition is presented,including signals found in CpG islands, and compared to the experimental data on transcriptioninitiation.

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 49Anna MatveevaInstitutionSPbSPUContact AddressStreet Address 3 Shkolnaya Street, Apartment 28Zip /Postal Code 197183CitySaint‐PetersburgCountryRussiaPhone +7 812 4962458Fax +7 812 5962831E‐Mailanya@odd.bio.sunysb.eduShort CV2001 – 2007 Student in Biophysics Department, The Faculty of Physics and Mechanics,St.Petersburg State Polytechnical University (SPbSPU)2007 M.Sc. in Physics, awarded with a diploma from SPbSPU2004 – 2005 SPbSPU The Faculty of Physics and Mechanics, The research laboratory ofBiophysics Department – Research assistant2005 – present SPbSPU The Department of Computational Biology, Center for AdvancedStudies of SPbSPU– ResearcherAwards2007 Medal “For devotion to science”2006 The Best Poster Award at the NanoBio’06 Conference2005 Medal “For devotion to science”2004 The Best Report Award at the Polytechnic Symposium “Young Scientists –Industry of the Northwest Region”Research InterestsImage processing, biological analysis of quantitative gene expression data. Early development ofDrosophila melanogaster, segmentation gene network. Transcriptional regulation of the segmentationgenes, mechanisms of gene silencing.Five most important publicationsA. Matveeva, K. Kozlov and M. Samsonova (2006). Methodology for Building of Complex Workflowswith PROSTAK package and iSIMBioS. Proceedings of the 5th International Conference onBioinformatics of Genome Regulation and Structure (BGRS'2006), July 16‐22, 2006, Novosibirsk, Russia.V. 2, 204‐208.A. Matveeva, K. Kozlov, M.Samsonova (2006). Extraction of quantitative gene expression data from theimages of gene expression patterns with ProStack and iSIMBioS. Proc. of the 4rd TICSP <strong>Workshop</strong> onComputational Systems Biology (WCSB 2006), Tampere, Finland, 12‐13 June, 2006, 65‐68.A.D. Matveeva, T.P. Sankova (2004). The frequency of encounter of the different alleles VDR gene ingroup of osteoporotic patients and their family members. The All‐<strong>Russian</strong> Interuniversity Scientific andTechnical Conference, Saint‐Petersburg, Russia, December 4, 2004,149.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkModeling the expression of the Drosophila even‐skipped (eve) gene driven by its proximal 1.7 kbupstream region.AbstractA central problem in modern molecular genetics is that of understanding how DNA regulatorysequences control gene expression. Metazoan regulatory regions are extremely complex andqualitatively different from those of prokaryotes. For example, the regulatory regions of genescontrolling development in Drosophila are large and consist of groups of binding sites, called as cisregulatorymodules (CRMs), each controlling some aspects of gene expression.The goal of our work is to understand the role of proximal 1.7 kb upstream regulatory sequence in theregulation of the Drosophila even‐skipped (eve) gene in terms of binding sites. To do this we 1)quantitatively monitor gene expression at high resolution in space in time, 2) characterize eachtranscription binding site and 3) construct a new quantitative and predictive model of transcriptionalreadout. We predicted the organization and function of the proximal 1.7 kb eve upstream regulatorysequence. The best model with lowest rms (8.66) was built with in silico addition the Sloppy‐pairedbinding site and assigning to Hunchback a role of repressor.Poster number: 25

50 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyJulia MedvedevaInstitutionGosNIIgenetikaContact AddressStreet Address 1, 1st Dorozhnyj pr.Zip /Postal Code 113545CityMoscowCountryRussiaPhone (7495)3150156Fax (7495)3150105E‐Mailju.medvedeva@gmail.comShort CVSeptember 1995 ‐ Moscow State University, studentMay 2003August 2003 ‐ Enhelgardt Institute of Molecular Biology, technicianOctober 2005November 2005 – GosNIIgenetika, PhD studenttill nowApril 2007 – till now GosNIIgenetika, researcherResearch InterestsI’m deeply interested in bioinformatics and genome sequence analysis. Now I’m studying CpG islandsin genomes of different vertabrates, their sequence structure and properties. In spite of the fact thatCpG islands in different gene region demonstrate diferent level of methylation, they could play similarregulatory function, probably as regions with clusters of protein binding sites (for ex. Sp1, CTCF) orstructural regions appropriate for origins of DNA replication.Five most important publicationsMedvedeva Yu., Rychkov A., Oparina N. Imprinted genes in human and mouse genomes: detailedanalysis of CpG islands // Moscow Conference on Computational Molecular Biology (MCCMB'05), july2005, Moscow, RussiaMedvedeva Yu., Fridman M., Oparina N., Makeev V. CpG islands distribution in the human genome //Genomics, Proteomics and Bioinformatics, april 2006, Almaty, KhazahstanMedvedeva Yu., Abnizova I., Naumenko F., Oparina N., Makeev V Identification of CpG islandboundaries // Moscow Conference on Computational Molecular Biology (MCCMB’07), july 2007,Moscow, RussiaContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talkReduced level of synonimous substitution in CpG containing codons suggests functional role ofintragenic and 3’ CpG islands in human genesAbstractCpG islands (CGIs) are usually defined as DNA segments that are longer than 200 bp, have over 50% ofG+C content, and have CpG frequency of at least 0.6 of that statistically expected [1]. Most of thestudies focused on CpG islands considered CGIs associated with 5' gene regions. Generally, suchislands are more than 1 kb long, can cover the promoter, TSS, the first coding exon and have strongerparameters of G+C content and Obs/Exp [2]. The methylation status of such CGIs is believed toinfluence the transcription level of a corresponding gene.Contrary to the widespread opinion only 50% of CGIs are located near TSS. About 20%gene‐associated CGIs are disposed in internal and 3’ terminal gene regions. Internal exons display lessoverlapping with CGIs than exons in 5’ regions and to some extend exons in 3’ regions of the genes.CGIs associated with 3’ region of the gene are more often overlapped with coding exons than with 3'UTR [1].Thus, the question arises if CGIs overlapping with protein‐coding regions are in fact theresult of selection at the protein level. In this work we compared selection at genome and proteinlevels by studying substitution rate between human and mouse orthologs in CpG sites belonging to 5’‐assosiated, intragenic and 3’‐assosiated CGIs. To this end we compared the substitution rate in exonsoverlapping and not overlapping with CGIs separately for non‐CpG containing codons (the background)and CpG containing codons.Using dn/ds test we came to the following conclusions:1. CpG island decrease the substitution rate in СpG pairs at synonymous sites approximatelytwo‐fold.2. Effect of CGI does not depend on the exon location within the gene: 5’‐assosiated,intragenic and 3’‐assosiated CGIs protect CpG sites from methylation and probably play the sameregulatory role in gene functioning.References:[1] Gardiner‐Garden, M. & Frommer, M. 1987. CpG islands in vertebrate genomes. J. Mol.Biol. 196,261–282.[2] Ponger L., Duret L., Mouchiroud D. 2001. Determinants of CpG Islands: Expression in Early Embryoand Isochore Structure. Genome Research. 11, 1854–1860.[3] Ina, Y. 1995. New methods for estimating the numbers of synonymous and nonsynonymoussubstitutions. J. Mol. Evol. 40, 190–226.(This work is a joint study with M.Fridman, N.Oparina, D.Malko, E.Ermankova, I.Kulakovsky, V.Makeev)Poster number: 26

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 51Natalia MedvedevaGraduate StudentInstitutionMSU CMCContact AddressStreet Address Marshala Nedelina 40‐13Zip /Postal Code 121471CityMoscowCountryRussiaPhone +79163359813E‐Mailsolnush@gmail.comShort CV2003 ‐ present Moscow State University, Faculty of Computational Mathematics andCyberneticsResearch InterestsApplication of mathematics to biologyModel IdentificationComputational modellingFive most important publicationsBocharov GA, Medvedeva NA. (2008) Model identification in immunology: computational approachesto sensitivity and information‐theoretic complexity analyses. In: “Numerical methods, parallelcomputing and information technologies” Eds. Vl.V. Voevodin and E.E.Tyrtyushnikov. MSU: Moscow (in<strong>Russian</strong>)Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talkSensitivity analysis of the mathematical model of type I interferon response to MHV infection in miceAbstractSensitivity analysis is an important element in the development of a mathematical model. There aredifferent approaches for solving this problem. One of them, the Latin hypercube sampling was used forperforming sensitivity analysis of the mathematical model of type I interferon response to MHVinfection in mice. It is a type of stratified Monte Carlo sampling. This technique with using partialcorrelation coefficients allows to rank the model parameters according their influence on outputvariables of the model.Poster number: 27

52 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyEugeniy MetelkinInstitution(1) Institute for Systems Biology SPb (2) Moscow State UniversityContact AddressStreet Address Leninskie Gory, 1/73, AN Belozerski IPCB Moscow State UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailmetelkin@insysbio.ruWebsitewww.insysbio.ruShort CV1998‐2004 Faculty of Physics, Biophysical Department, Moscow State University2004‐2007 PhD Courses, Faculty of Physics, Biophysical Department, Moscow StateUniversity2004‐present Institute for Systems Biology SPbResearch InterestsResearch Interests of mine are focused in areas of Systems Biology and Bioinformatics and scientificprogramming with especial focus on quantitative description of biological processes and theirapplication to biotechnology and biomedicine. Areas of expertise:Modeling of cellular metabolismModeling of gene regulatory networksMethods and software for control of industrial biotechnology processesMethods and software for drug safety assessmentMethods and software for kinetic modelingFive most important publicationsMetelkin E., Goryanin I., Demin O. Mathematical modeling of mitochondrial adenine nucleotidetranslocase. Biophys. J (2006) v.90 p.423‐432Goryanin II, Lebedeva GV, Mogilevskaya EA, Metelkin EA, Demin OV. Cellular kinetic modeling of themicrobial metabolism. Methods Biochem Anal (2006) 49, 437‐488Demin O.V., Plyusnina T.Y., Lebedeva G.V., Zobova E.A., Metelkin E.A., Kolupaev A.G., Goryanin I.I.,Tobin F. Kinetic modelling of the E. coli metabolism. IN: Topics in Current Genetics (2005) 31‐67, Eds.Alberghina L., Westerhoff H.V. , SpringerContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkEncyclopaedia of stem cells: reconstruction of transformation pathways, signaling networks andprediction of biomarkersAbstractThis information system can be used for the following purposes:1) as the tool for research. The potential users are pharmaceutical companies that work at new drugsof cancer, osteoporosis, blood diseases; biological, medical and pharmaceutical research institutes;clinics; stem cells banks.2) as the guide for the stuff of stem cells companies. The potential users are clinics; pharmaceuticalcompanies; research institutes; centers of science information and libraries.3) as the visualization tool in e‐commerce. The potential users are the companies that specialized inselling of stem cells signaling proteins, antibodies of these proteins and different reagents allowing todetect different states of stem cells.4) as the tool for students training of biological, medical and pharmacological institutes. The potentialusers are biological, medical and pharmacological institutes and libraries.The main characteristics of informational system “Stem cells” are:(a) Originality of the data structure that allows being used it for researches; visualizations ofintercellular mechanisms and as the guide for the stuff of stem cells companies.(b) Technology of data collection and analysis of biological information. Our technique includes themethods of intracellular signaling pathways reconstruction on the base of published experimental dataand the software that handles data automatically for visualization and modeling of signalingtransduction.(c) Fullness of the data concerning stem cells functioning. This information includes the biological andmedical aspects of stem cells functioning.Poster number: 28

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 53Prof. Andrey MironovInstitutionMoscow State Univ. Department of Bioengineeringand BioinformaticsContact AddressStreet Address Lab. Bldg B, Vorobiovy Gory 1‐73,Zip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 939 4331Fax +7 (495) 939 41 95E‐Mailmironov@bioinf.fbb.msu.ruShort CV2003‐presentProfessor, Dept. of Bioengineering and Bioinformatics, Moscow StateUniversity, Moscow, Russia2001‐2003 Director of technology Moscow office Integrated Genomics Inc., Moscow,Russia1986‐2001 Head of department of Mathematical Modeling, NIIGenetica, Moscow, Russia1978‐1985 Senior Researcher in dept. of Mathematical Modeling, NIIGenetica, Moscow,USSR1972‐1978 Junior Researcher in lab.of Optimization in Mechanics in Institute of MechanicsAcademy of Science USSRAwards2007 Baev award, <strong>Russian</strong> acedemy of scienseResearch InterestsBioinformatics, Comparative genomics, RNA structure, Gene regulationFive most important publicationsMerkeev IV, Novichkov PS, Mironov AA. PHOG: a database of supergenomes built from proteomecomplements. BMC Evol Biol. 2006 Jun 22;6:52.Danilova LV, Pervouchine DD, Favorov AV, Mironov AA. RNAKinetics: a web server that modelssecondary structure kinetics of an elongating RNA. J Bioinform Comput Biol. 2006 Apr;4(2):589‐96.Tompa M, Li N, Bailey TL, Church GM, De Moor B, Eskin E, Favorov AV, Frith MC, Fu Y, Kent WJ, MakeevVJ, Mironov AA, Noble WS, Pavesi G, Pesole G, Regnier M, Simonis N, Sinha S, Thijs G, van Helden J,Vandenbogaert M, Weng Z, Workman C, Ye C, Zhu Z. Assessing computational tools for the discoveryof transcription factor binding sites. Nat Biotechnol. 2005 Jan;23(1):137‐44.Neverov AD, Artamonova II, Nurtdinov RN, Frishman D, Gelfand MS, Mironov AA. Alternative splicingand protein function. BMC Bioinformatics. 2005 Nov 7;6:266.Novichkov PS, Omelchenko MV, Gelfand MS, Mironov AA, Wolf YI, Koonin EV. Genome‐wide molecularclock and horizontal gene transfer in bacterial evolution. J Bacteriol. 2004 Oct;186(19):6575‐85.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(X) a talkTitle of poster / talkAlternative splicing and secondary structure of RNA ‐ Systematic computational study andexperimental verification of predictionsAbstractPre‐mRNA structure has been reported to impact many cellular processes, including splicing in genesassociated with human disease. In this work we examine introns of twelve Drosophila species for thepresence of conserved complementary motifs capable of forming stable RNA structures. Over 200introns with such motifs were identified, suggesting a role for secondary structures in regulation ofsplicing. Indeed, mutations that decrease base pairing affected splicing efficiency or inducedalternative splicing in 4 of 7 cases tested, while compensatory mutations that restored base pairingsuppressed these effects. Our results represent a proof of principle that naturally occurring secondarystructures can be relevant to splicing of many more genes than it is believed currently. Moreover,without the evolutionary conservation constraint, the predicted number of introns capable of formingstable RNA structures increases up to 7000, raising the intriguing hypothesis that these structurescould actually participate in splicing of every second gene in fruit flies.

54 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr Ekaterina MogilevskayaInstitutionContact AddressStreet Address(1) Institute for Systems Biology SPb (2) MoscowState UniversityLeninskie Gory, 1/73, AN Belozerski IPCB MoscowState UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailzobova@genebee.msu.suWebsitewww.insysbio.ruShort CV (keywords)2005‐present Researcher, Institute for Systems Biology SPb2007 Ph.D., Biophysical Department, Faculty of Biology, Moscow State University,Moscow. Title: Theoretical investigation of the Krebs cycle functioning andregulation in E.coli and mitochondria.2002‐2005 Post‐graduate of Biophysical Department, Moscow State University1996‐2002 Medico‐Biological Faculty, <strong>Russian</strong> State Medical UniversityAwardsParticipation in EU programmes:Research Interests (3‐5 sentences)Research Interests of Dr Mogilevskaya are focused in areas of Systems Biology and Bioinformatics withespecial focus on quantitative description of biological processes and their application tobiotechnology and biomedicine. Areas of expertise:Modeling of cellular metabolismModeling of cell signalingPathway reconstructionFive most important publications• Mogilevskaya E. A., Lebedeva G. V., Goryanin I. I., Demin O. V. Kinetic model of Escherichia coliisocitrate dehydrogenase functioning and regulation. // Biophysics, 2007, 52(1), 47‐56.• Goryanin II, Lebedeva GV, Mogilevskaya EA, Metelkin EA, Demin OV. Cellular kinetic modeling ofthe microbial metabolism. Methods Biochem Anal (2006) 49, 437‐488• Mogilevskaya E.A., Demin O.V., Goryanin I.I. Kinetic Model of Mitochondrial Krebs Cycle:Unraveling the Mechanism of Salicylate Hepatotoxic Effects // Journal of Biological Physics. –2006. ‐ V. 32. ‐ P. 245‐271.• Demin O.V., Plyusnina T.Y., Lebedeva G.V., Mogilevskaya (Zobova) E.A., Metelkin E.A., KolupaevA.G., Goryanin I.I., Tobin F. Kinetic modelling of the E. coli metabolism. IN: Topics in CurrentGenetics (2005) 31‐67, Eds. Alberghina L., Westerhoff H.V. , Springer.• Demin O.V., Lebedeva G.V., Kolupaev A.G., Mogilevskaya (Zobova) E.A., Plyusnina T.Yu., LavrovaA.I., Dubinsky A., Goryacheva E.A., Tobin F., Goryanin I.I. Kinetic Modelling as a ModernTechnology to Explore and Modify Living Cells // Modelling in Molecular Biology. NaturalComputing Series. – Springer, 2004. ‐ P. 59‐103.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a posterTitle of poster / talkApplication of kinetic modeling to understand hepatotoxic effects of salicylate.AbstractLiver injury is the serious side effect of the salicylate – an active derivative of aspirin [1]. What are themechanisms of salicylate induced hepatotoxicity and how it can be prevented? To answer thesequestions the detailed kinetic model of mitochondrial Krebs cycle is constructed. It is known thatsalicylate inhibits mitochondrial energy metabolism. It was shown [2] that in stress conditions of highenergy demand mitochondria can switch from tricarboxylic acids to alternative substrates oxidation inthe Krebs cycle. The model describes this stress situation when glutamate, malate and alphaketoglutarateare the substrates of the Krebs cycle. It was shown on the model that the inhibition ofsuccinate dehydrogenase and alpha‐ketoglutarate dehydrogenase by salicylate contributessubstantially to the cumulative inhibition of the Krebs cycle by salicylate. Whereas the uncoupling ofoxidative phosphorylation and coenzyme A consumption in salicylate transformation processes haslittle effect on the rate of substrate oxidation in the Krebs cycle. It was found that the salicylateinhibitedKrebs cycle flux can be increased by flux redirection in the Krebs cycle through increase ofcytosol glutamate and malate concentrations and depletion in cytosol alpha‐ketoglutarate andmitochondrial glycine concentrations [3].1. Bjorkman D. Nonsteroidal anti‐inflammatory drug‐associated toxicity of the liver, lower gastrointestinal tract, andesophagus. 1998. American Journal of Medicine, 105(5A), 17S‐21S.2. Kondrashova M.N. Structuro‐kinetic organization of the tricarboxylic acid cycle in the active functioning ofmitochondria. 1989. Biophysics, 34, 450‐458.3. Mogilevskaya E.A., Demin O.V., Goryanin I.I. Kinetic Model of Mitochondrial Krebs Cycle: Unraveling theMechanism of Salicylate Hepatotoxic Effects // Journal of Biological Physics. – 2006. ‐ V. 32. ‐ P. 245‐271.Poster number: 29

Dr.rer.nat. Mario S. Mommer<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 55InstitutionBIOMS / IWR / Heidelberg UniversityContact AddressStreet Address Im Neuenheimer Feld 368Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49 – 6221 ‐ 54‐8890E‐Mailmario.mommer@iwr.uni‐heidelberg.deShort CVUndergraduate Mathematics. Merida – Tuebingen – Aachen, until 12.1999PhD1.2000‐8.2005, Numerical AnalysisPostdoc9.2005‐4.2006, Univ. of UtrechtPostdoc5.2006‐present, BIOMS Postdoc, Univ. of HeidelbergResearch InterestsSpatiotemporal organization of cells and cellular processes, in particular Ca2+ signalling in neutrophils,diffusive transport within cells, and organization of the cytoskeleton and ER. Mathematical methodsfor capturing the „exotic“ behaviour typical of complex cellular processes.Five most important publicationsM. S. Mommer, A Smoothness Preserving Fictitious Domain Method for Elliptic Boundary ValueProblems. IMA J. of Num. Ana., July 2006.K. Eppler, H. Harbrecht and M. S. Mommer, A new fictitious domain method in shape optimization,Comp. Opt. Appl., October 2007.M. S. Mommer, D. Lebiedz, Modelling Subdiffusion Using Reaction Diffusion Systems, IWR Preprint7168, February 2007.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( X ) a poster( ) a talkTitle of poster / talkA model for submembrane Calcium waves in migrating neutrophilsAbstractWe have put together, from data found in the biological and biophysical literature, a mathematicalmodel that may explain the localized, submembrane Ca2+ waves that have recently been observed inmigrating neutrophils by Kindzelski and Petty (Journal of Immunology, 2003). In the model, the wavesarise from an interaction between the gating dynamics of voltage gated T‐Type Ca2+ channels, whohave a short active phase and a long refractory one, and the local depolarization caused by Ca2+ influx.We find that this model features traveling pulses among its solutions, and furthermore, that itreproduces the reflection behaviour observed when two pulses collide. All relevant parameters arewithin the ranges found in the literature.Poster number: 30

56 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyPD Dr. Margareta MuellerInstitution<strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 280Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐424533Fax +49‐6221‐424551E‐MailMa.mueller@dkfz.deWebsiteShort CV1982‐1984 University Saarland, <strong>German</strong>y, Biol. Sciences1984‐1987 Albert Ludwigs University Freiburg, <strong>German</strong>y, Masters Degree, Biol. Sciences1988‐ 1992 PhD University of California at Irvine, USA1992‐1995 Postdoctoral fellow, german Cancer Research Center (DKFZ), Heidelberg,<strong>German</strong>y1995‐2004 Research group leader in the division of Carcinogennesis and Differentiation,DKFZ, Heidelbreg <strong>German</strong>y1999 Visiting scientist Istituto di Mutagenesi e Differenziamento, Pisa, Italy2001 Appointment as C3‐Professor, University of applied sciences Hamburg,<strong>German</strong>y2004/2005 Habilitation/Venia legendi in tumor biology, Heidelberg, <strong>German</strong>ysince 2004Leader of the independent research group. Tumor and Microenvironment,DKFZ, Heidelberg, <strong>German</strong>y (12 coworkers)Awards1988‐1990 PhD scholarship german Academic Exchange Service1990‐1992 PhD scholarship, State of California1992‐1993 Research Scholarship European Union2001 travel award of the EACR2003 NIH travel award (Gordon Conference)Research InterestsGrowth factor networks in tumor stroma interactionIl‐6 signal transduction in tumor and stromal cellsFunctional connection between Inflammation, angiogenesis and tumor progressionFive most important publicationsKiessling F., Greschus S., Lichy M.P., Bock M., Fink C., Vosseler S., Moll J., Mueller M.M., Fusenig N.E.,Traupe H., Semmler W. Volumetric Computed Tomography (VCT): A Novel Technology for Non‐Invasive High Resolution Monitoring of Tumor Angiogenesis. Nature Med 2004; 10:1133‐1138Mueller M.M. Fusenig N.E. Friends or foes: Bipolar effects of the tumor stroma in cancer growth andregression. Nature Rev Cancer 2004; 4(11):839‐49.Obermueller E., Vosseler S., Fusenig N.E., Mueller M.M. Co‐operative auto‐ and paracrine functions ofG‐CSF and GM‐CSF in promoting tumor progression of skin carcinoma cells. Cancer Res 64(21):7801‐12,(2004).Mueller M.M. Inflammation in epithelial skin tumors: Old stories and new ideas. Eur J Cancer2006;42(6):735‐44Gutschalk C.M. , Herold‐Mende C., Fusenig N.E., Mueller M.M. G‐CSF and GM‐CSF promote malignantgrowth in sqaumous cell carcinomas of the head and neck. Cancer Res 2006; 66: 8026‐36

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 57Dr. Angela OberthürInstitution BIOQUANT –University of HeidelbergContact AddressStreet Address Im Neuenheimer Feld 267Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49‐6221‐54‐51204Fax +49‐6221‐54‐51438E‐Mailangela.oberthuer@bioquant.uni‐heidelberg.deWebsitehttp://www.bioquant.uni‐heidelberg.de/Short CV2002 PhD at Darmstadt University2002‐2003 Princeton University Press, Princeton NJ, USA2003‐2004 <strong>German</strong> Cancer Research Center, HeidelbergScientific Assistant to the Chairman of the Management Board2004‐2007 <strong>German</strong> Cancer Research Center , HeidelbergHead of Division Strategy Planning and Program CoordinationSince 04/2007 BIOQUANT, Heidelberg UniversityManaging DirectorResearch InterestsBIOQUANT the recently established Center for "Quantitative analysis of molecular and cellular biosystems" at the University of Heidelberg is the first research center in <strong>German</strong>y solely dedicated toSystems Biology.It is the central building of the interdisciplinary research network BIOQUANT that integrates systembiology research dispersed over the various university and non‐university research centers atHeidelberg campus. It unites experimental scientists and theoreticians under one roof, and itsobjective is to represent a platform for the constant refinement of models and the swift validation ofscientific hypotheses via experimental data.Currently, projects of four prestigious research consortia are accommodated at BIOQUANT, namelyFORSYS‐VIROQUANT funded by BMBF, the public‐ private‐partnership program BioMS, the excellencecluster CellNetworks funded by the DFG as well as parts of the <strong>Helmholtz</strong> program Systems Biology ofCancer (SBCancer).BIOQUANT's research program consists of four distinct but closely interconnected project areasdedicated to the investigation of protein machines‐ biogenesis, interaction and regulation; dynamics ofcell architecture; information processing in complex multi‐cellular networks and alteration of networksby infectious pathogens.A central technology platform at BIOQUANT is providing advanced computational methods and toolsfor data analysis, visualization and modeling as well as cutting edge technologies and equipment forquantitative analysis.

58 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyKirill PeskovInstitutionContact AddressStreet Address(1) Institute for Systems Biology SPb (2) MoscowState UniversityLeninskie Gory, 1/73, AN Belozerski IPCB MoscowState UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailkirillpeskov@gmail.comWebsitewww.insysbio.ruShort CV2004‐present Research Scientist, Institute for Systems Biology SPb2004–2007 Post‐graduated Student, Institute of Theoretical and Experimental Biophysics<strong>Russian</strong> Academy of Science, Pushchino, Moscow Region, Russia.1999‐2004 Student, Biophysical Department, Faculty of Biology, Moscow State UniversityAwardsParticipation in EU programmes:Research InterestsResearch Interests of Mr. Peskov are focused in areas of Systems Biology and Bioinformatics andscientific programming with especial focus on quantitative description of biological processes and theirapplication to biotechnology and biomedicine. Areas of expertise:Modeling of cellular metabolismModeling of cell signalingModeling of gene regulatory networksPathway reconstructionMethods and software for control of industrial biotechnology processesMethods and software for drug safety assessmentMethods and software for kinetic modelingContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X ) a posterTitle of poster / talkKinetic modeling of Escherichia coli central carbon metabolism.AbstractThe understanding of a complex network of genetic and metabolic regulations is a great challenge ofsystem study of Escherichia coli metabolism. Indeed, it is rather difficult to estimate the contribution ofdifferent types of regulations to intracellular dynamics on the one hand and, on the other, tounderstand the role of all possible interactions between metabolic and genetic networks. One of theways to cope with the problems is to use the kinetic modeling approach to integrate different types ofexperimental data and understand more about regulatory behavior of the intracellular system [1‐3].Additionally, kinetic modeling allows us to simulate interactions between metabolic and geneticnetworks and predict complex dynamic behavior, which is typical for central carbon Escherichia colimetabolism. The main idea of our approach is a detailed mechanistic description of all elementarybiochemical interactions, e. g. rate equations of single enzymes, elements of metabolic and geneticregulations [4‐6]. This significantly increases the predictive power of in silico modeling and extends thepossible range of applications [4].The aims of this investigation could be briefly formulated in the following way:Pathway reconstruction of central carbon metabolism and its metabolic and genetic regulationnetworksDevelopment of kinetic modelDetail mathematical description of each elementary step of the model (rates of reaction of theindividual enzymes, elements of metabolic and genetic regulation).Maximal level of model verification with different types of experimental data (both in vitro and invivo).Model analysis and predictions.During these work we have obtained several interesting prediction about functioning of central carbonEscherichia coli metabolism concerning metabolic and genetic regulation of this pathway.References:1. M. Santillan and M. C. Mackey, "Influence of catabolite repression and inducer exclusion on thebistable behavior of the lac operon.," Biophys J. 86, 1282‐1292 (2004).2. C. Chassagnole, N. Noisommit‐Rizzi, J. W. Schmid, K. Mauch and M. Reuss, "Dynamic modeling ofthe central carbon metabolism of Escherichia coli," Biotechnol Bioenerg. 79, 53‐73 (2002).3. M. M. Altintas, C. K. Eddy, M. Zhang, J. D. McMillan and D. S. Kompala, "Kinetic modeling tooptimize pentose fermentation in Zymomonas mobilis.," Biotechnol Bioenerg 94, 273‐295 (2006).4. I. I. Goryanin, G. V. Lebedeva, E. A. Mogilevskaya, E. A. Metelkin and O. V. Demin, "Cellular kineticmodeling of the microbial metabolism. ," Methods Biochem Anal 49, 437‐488 (2006).5. E. Mogilevskaya, I. I. Goryanin and O. V. Demin, "Kinetic model of mitochondrial Krebs cycle:unraveling the mechanism of salicylate hepatotoxic effects," J Biol Phys. 32, 245–271 (2006).6. E. Metelkin, I. Goryanin and O. Demin, "Mathematical Modeling of Mitochondrial AdenineNucleotide Translocase," Biophys J. 90, 423‐432 (2006).Poster number: 32

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 59Prof. Dr. Vladimir PoroikovInstitutionInstitute of Biomedical Chemistry RAMSContact AddressStreet Address Pogodinskaya Str., 10Zip /Postal Code 119121CityMoscowCountryRussiaPhone +7 495 245‐2753Fax +7 495 245‐0857E‐Mailvladimir.poroikov@ibmc.msk.ruWebsitehttp://ibmc.msk.ru/en/departments/drug_design/Short CV2000 Professor (Biochemistry), High Attestation Comission of Russia1995 D.Sci. Degree (Pharmacology), NRC BAC1981 Ph.D. Degree (Biophysics), MSU1998 ‐ present Vice‐Director (Research), Institute of Biomdical Chemistry of Rus. Acad. Med.Sci. (IBMC), Moscow, Russia1995 ‐ present Head of Laboratory for Structure‐Function Based Drug Design, IBMC1996 ‐ present Professor, Medical & Biological Faculty of <strong>Russian</strong> State Medical University,Moscow, Russia1974 ‐ 1995 National Recearch Center for Biologically Active Compounds (NRC BAC),Staraya Kupavna, Moscow Region, Russia (the last position – Head ofDepartment for Drug Design and Marketing)1968 ‐ 1974 Student, Physical Faculty, The M.V. Lomonosov Moscow State University(MSU), RussiaAwards2005 Diploma of Cambridge Biographic Institute (Leading Scientist in Bioinformaticsand Computer‐Aided Drug Discovery)2004 Diploma of <strong>Russian</strong> Academy of Medical Sciences2001‐2003 Special Stipend for Outstanding <strong>Russian</strong> Scientists awarded by the <strong>Russian</strong>Academy of Sciences2001 Gold Medal “For Scientific Partnerships”1997 Medal "850 Years of Moscow"1968 Gold Medal on School GraduationResearch InterestsBioinformatics, chemoinformatics, molecular modelling, (Q)SAR/(Q)SPR, computer‐aided drugdiscovery, systems biology.Five most important publicationsPoroikov V., Filimonov D., Lagunin A., Gloriozova T., Zakharov A. (2007). PASS: Identification ofprobable targets and mechanisms of toxicity. SAR & QSAR in Environmental Research., 18 (1‐2), 101‐110.Fomenko A.E., Filimonov D.A., Sobolev B.N., Poroikov V.V. (2006). New approach to predict enzymefunction without the alignment. OMICS: A Journal of Integrative Biology, 10 (1), 56‐65.Filimonov D.A., Poroikov V.V. (2005). Why relevant chemical information cannot be exchanged withoutdisclosing structures. J. Comput.‐Aided Mol. Design, 19 (9‐10), 705‐713.Geronikaki A., Dearden J., Filimonov D., Galaeva I., Garibova T., Gloriozova T., Krajneva V., Lagunin A.,Macaev F., Molodavkin G., Poroikov V., Pogrebnoi S., Shepeli F., Voronina T., Tsitlakidou M., Vlad L.(2004). Design of new cognition enhancers: from computer prediction to synthesis and biologicalevaluation. J. Med. Chem., 47 (11), 2870‐2876.Poroikov V.V., Filimonov D.A., Borodina Yu. V., Lagunin A.A., Kos A. (2000). Robustness of biologicalactivity spectra predicting by computer program PASS for non‐congeneric sets of chemical compounds.J. Chem. Inform. Comput. Sci., 40 (6), 1349‐1355.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(X) a talkTitle of poster / talkBio‐ and chemoinformatics of multitargeted anticancer drugsAbstractDue to the progress in postgenomic studies it became obvious that many diseases have a complexetiology, and the multitargeted drug concept appears, according which such remedies have someadvantages comparing to the monotargeted medicines. Discovery of new multitargeted drugs can bemade by prediction of biological activity spectra with computer system PASS, which predicts morethan 3,000 biological activity types and molecular mechanisms of action with average accuracy about95%. Potential of bioinformatics and computer‐aided drug discovery methods in definition ofprospective sets of particular molecular targets and identification of lead substances for futureanticancer multitargeted drugs in the databases of available chemical compound samples will bediscussed.This work is supported by FP6 (LSHB‐CT‐2007‐037590 ‐ Net2Drug, ISTC/BTEP (3197/111),RFBR (05‐07‐90123, 06‐03‐08077, 06‐03‐39015).

60 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyKsenia PougachUndergraduate studentInstitutionIMG RASContact AddressStreet Address 2 Kurchatov Sq.Zip /Postal Code 123182CityMoskowCountryRussiaPhone 8 909 622 78 14E‐Mailxenik‐alt@mail.ruShort CVPersonalBorn December 17 th , 1985, Russia, SingleCitizenshipRussiaCurrent position Student at Moscow State UniversityAddressRussia, 119991, Moscow, Leninskie gori, MSU, 1 build.12Phone (7)(495)196‐02‐15E‐mailxenik‐alt@mail.ruEducationM.S., Molecular Biology, 2008, Moscow State University, RussiaResearch InterestsTranscription regulation in prokariotesMicroarraysRNAPBacteriophagesRNAiContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will preparea posterTitle of poster / talkComparative analysis of gene expression strategy in T‐even phagesAbstractOur long‐term goal is to understand the function and regulation of cellular DNA‐dependent RNApolymerase (RNAP) in molecular detail. Bacterial viruses‐‐phages‐‐evolved elaborate mechanisms toregulate host transcription to make it serve the needs of the virus. The variety of phages and thenumber of regulatory mechanisms that they evolved exceeds the variety of bacterial regulatorymechanisms by orders of magnitude. Phage regulatory systems are usually compact, robust, andefficient (i.e., phage‐encoded proteins are small, they interact with host RNAP tightly, and theirregulatory effects are strong). The goal of this research is to uncover phage‐induced modifications ofbacterial host RNAP, to study them in vitro, and to determine the role of these modifications in viraldevelopment. In vitro, RNAP sites that are targeted by phage regulators will be identified and themechanisms of action of phage regulators will be determined using discriminatory biochemical assays.In vivo, genetic and genomic approaches will be used to understand the biological consequences ofRNAP modifications by phage‐encoded factors. Comparative analysis of transcription regulation inseveral relatives of T4, a classical phage known to rely on extensive modification of host RNAP byphage‐encoded proteins for expression of phage genes, will be performed. The goal is to determinehow T4 relatives that lack transcription factors that are essential for T4 development express theirgenes in a coordinate manner.Poster number: 33

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 61Dr. Vasily RamenskyInstitutionEngelhardt Institute of Molecular Biology of<strong>Russian</strong> Academy of SciencesContact AddressStreet Address Vavilova, 32Zip /Postal Code 119991CityMoscowCountryRussiaPhone +7‐499‐135‐6000Fax +7‐499‐135‐1405E‐Mailramensky@imb.ac.ruWebsitehttp://www.imb.ac.ru/~ramensky/Short CVBioinformatics; systems biology; molecular evolution; drug design; proteinstructure and functionAwards2002‐2003 V.A.Engelhardt award for young scientists; EIMB RAS2006‐2007 "Human molecular Polymorphism" grant program from <strong>Russian</strong> Academy ofSciences; principal investigatorResearch InterestsPrediction of functional effect of amino acid variation in proteins: PolyPhen (PolymorphismPhenotyping)Computational drug designProtein structure and evolutionCompositional analysis of DNA sequences: BASIO (Bayesian Approach to Sequence segmentatIOn)Five most important publications1. S.R.Sunyaev, V.E.Ramensky, P.Bork. (2000) Towards a structural basis of human non‐synonymoussingle nucleotide polymorphisms. Trends Genet, Vol.16, No.5, pp. 198‐200.2. V.E.Ramensky, V.Ju.Makeev, M.A.Roytberg, V.G.Tumanyan (2001) Segmentation of long genomicsequences into domains with homogeneous composition with BASIO software. Bioinformatics, Vol.17,No.11, pp.1065‐1066.3 V.Ramensky, P.Bork, S.Sunyaev (2002) Human non‐synonymous SNPs: server and survey. NucleicAcids Res., Vol. 30, pp.3894‐3900.4.V. Ramensky, A. Sobol, N. Zaitseva, A.Rubinov, V.Zosimov (2007) A novel approach to local similarityof protein binding sites substantially improves computational drug design results. Proteins. Vol 69,pp.349‐3575. E. Reuveni, V.Ramensky, C.Gross (2007) Mouse SNP Miner: an annotated database of mousefunctional single nucleotide polymorphisms. BMC Genomics. Vol. 8, pp.24.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talkComputational drug design based on a novel approach to local similarity of protein binding sitesAbstractWe present a novel notion of binding site local similarity based on the analysis of complete proteinenvironments of ligand fragments. Comparison of a query protein binding site (target) against the 3Dstructure of another protein (analog) in complex with a ligand enables ligand fragments from theanalog complex to be transferred to positions in the target site, so that the complete proteinenvironments of the fragment and its image are similar. The revealed environments are similarityregions and the fragments transferred to the target site are considered as binding patterns. The set ofsuch binding patterns derived from a database of analog complexes forms a cloud‐like structure(fragment cloud), which is a powerful tool for computational drug design. It has been shown onindependent test sets that application of fragment clouds to self‐docking and screening dramaticallyimproves the results and enables reliable reproduction of experimental ligand optimization results.Poster number: 34

62 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Babette RegiererInstitutionUniversity of PotsdamContact AddressStreet Address Karl‐Liebknecht‐Str. 24‐25, House 20Zip /Postal Code 14476CityPotsdam‐GolmCountry<strong>German</strong>yPhone +49 331 977 2811Fax +49 331 977 70 2811E‐Mailregierer@uni‐potsdam.deWebsitewww.forsys.deShort CV1994‐1997 PhD at Max Planck Institute for Molecular Plant Physiology (Potsdam)1997‐2000 Postdoc in EU‐Project ““Phosphate and Crop Productivity” (Potsdam)2000‐2001 Coordinator of the “Interdisciplinary Network for Human Genome Research”(Berlin)2002‐2003 Scientific Manager at Max Planck Institute for molecular Genetics (Berlin) inDep. Vertebrate Genomics of Prof. Hans Lehrach2003‐2007 Scientific Coordinator of the Interdisciplinary Center “Advanced ProteinTechnologies” at University of Potsdam2008‐ Scientific Manager of the Program “FORSYS – Research Units for SystemsBiology” in <strong>German</strong>yResearch InterestsSystems Biology in different model systems (human, animals, plants and microorganisms) andtechnology development.Five most important publicationsGeigenberger P, Regierer B, Nunes‐Nesi A, Leisse A, Urbanczyk‐Wochniak E, Springer F, van Dongen JT,Kossmann J, Fernie AR (2005) Inhibition of de novo pyrimidine synthesis in growing potato tubers leadsto a compensatory stimulation of the pyrimidine salvage pathway and a subsequent increase inbiosynthetic performance. Plant Cell. 17(7):2077‐88. Epub 2005 Jun 10.Zimmermann P, Kossmann J, Frossard E, Amrhein N, Bucher M (2004) Differential expression of threepurple acid phosphatases from potato. Plant Biol (Stuttg) 6(5), 519‐28Geigenberger P, Regierer B, Lytovchenko A, Leisse A, Schauer N, Springer F, Kossmann J, Fernie AR(2004) Heterologous expression of a ketohexokinase in potato plants leads to inhibited rates ofphotosynthesis, severe growth retardation and abnormal leaf development. Planta 218(4), 569‐78Regierer B, Fernie AR, Springer F, Perez‐Melis A, Leisse A, Koehl K, Willmitzer L, Geigenberger P,Kossmann J (2002) Starch content and yield increase as a result of altering adenylate pools intransgenic plants. Nat Biotechnol Dec, 20(12):1256‐60van Voorthuysen, T, Regierer, B, Springer, F, Dijkema, C, Vreugdenhil, D, Kossmann, J, (2000)Introduction of polyphosphate as a novel phosphate pool in the chloroplast of transgenic potato plantsmodifies carbohydrate partitioning. J. Biotech., 77, 65‐80Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talk“FORSYS – Research Units for Systems Biology”A new research program for Systems Biology in <strong>German</strong>yAbstractThe <strong>German</strong> Federal Ministry of Education and Research (BMBF) has launched a new initiative forSystems Biology "FORSYS ‐ Research Units on Systems Biology" to complement the existing researchprograms in <strong>German</strong>y. The FORSYS centers enable the networking of relevant scientific areas underone roof and in close connection to the regional cooperating institutions which together form theintellectual and technological basis. The centers at the locations of Freiburg, Heidelberg, Magdeburgand Potsdam started the work in 2007. One focal point of the FORSYS programme is the promotion ofyoung talented researchers by establishment of junior research groups as an excellent basis for futurecareers in Systems Biology. For early stage researchers the FORSYS units offer dedicated mastercourses and structured doctoral programs in Systems Biology.Poster number: 35

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 63Seong‐Hwan Rho, Ph.DInstitutionFreiburg Center for Data Analysis and Modeling(FDM)Contact AddressStreet Address Hermann‐Herder‐Str. 3AZip /Postal Code 79104CityFreiburgCountry<strong>German</strong>yPhone +49 761 203 8539Fax +49 761 203 8539E‐Mailshrho@fdm.uni‐freiburg.deShort CV2007‐present Postdoc, Systems biology, FDM, <strong>German</strong>y2005‐2007 Postdoc, Systems biology, Sytems Biology Institute, Korea1998‐2005 Ph.D., Structural biology, Gwangju Institute of Science and Technology, Korea1996‐1998 M.S., Electrophysiology. Gwangju Institute of Science and Technology, Korea1991‐1996 B.S., Electrical engineering, Seoul National University, KoreaResearch InterestsSystems biology of eukaryotic systems, quantitative modeling of cellular signaling and experimentaldesignBioinformatics and statistical analysis, network inference of transcriptomics and proteomics dataProtein structure modeling and design; ion channels, proteasesFive most important publicationsRho, S.H., Park, H.H., Kang, G.B., Im, Y.J., Kang, M.S., Lim, B.K., Seong, I.S., Seol, J., Chung, C.H., Wang,J., et al. (2007). Crystal structure of Bacillus subtilis CodW, a noncanonical HslV‐like peptidase with animpaired catalytic apparatus. Proteins. (in press)Hong, S.E., Rho, S.H., Yeom, Y.I., and Kim do, H. (2006). HCNet: a database of heart and calciumfunctional network. Bioinformatics 22, 2053‐2054. (co‐first author)Lee, E.H., Rho, S.H., Kwon, S.J., Eom, S.H., Allen, P.D., and Kim do, H. (2004). N‐terminal region ofFKBP12 is essential for binding to the skeletal ryanodine receptor. J Biol Chem 279, 26481‐26488.Rho, S., Lee, H.M., Lee, K., and Park, C. (2000). Effects of mutation at a conserved N‐glycosylation sitein the bovine retinal cyclic nucleotide‐gated ion channel. FEBS Lett 478, 246‐252.Rho, S.H., and Park, C.S. (1998). Extracellular proton alters the divalent cation binding affinity in a cyclicnucleotide‐gated channel pore. FEBS Lett 440, 199‐202.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkTracing down the EpoR mediated pathway in the hematopoietic systemAbstractThe serine/threonine protein kinase Akt/PKB downstream of erythropoietin receptor (EpoR) plays animportant role in red blood cell development by controlling proliferation and differentiation oferythroid progenitor cells. Previous studies have identified multiple pathways involved in EpoR‐Aktsignaling, being the PI3‐kinase as a major and direct activator of Akt along with possible or indirectcontributions from other proteins, such as Gab2, K‐ras, and IRS‐2, etc. The detailed contribution byeach signaling molecule, however, is yet to be established.The goal of our study is to understand the detailed Akt activation mechanism in the hematopoieticsystem upon EpoR stimulation by utilizing a data‐based quantitative modeling approach. To this end,the quantitative information of signaling proteins in the EpoR signal transduction was obtainedexperimentally from two distinct cellular systems; BaF3 cell line, a murine pro B cell line lacking EpoRand dependent on Interleukin‐3 (IL‐3) for growth, and CFU‐E cells, murine fetal liver erythroidprogenitors with highly expressed EpoRs that undergo normal terminal proliferation anddifferentiation.Attenuation of the activated Akt was observed only in BaF3 cells expressing ectopic EpoRs, but not inCFU‐E cells. BaF3 cells have higher amount of PTEN and SHIP1 proteins that are known as negativefeedback regulators of PI3‐kinase pathway. Our model including PTEN or SHIP1 could successfullyexplain the quantitative difference in Akt activation between BaF3 and CFU‐E cells and, thus, supportsthe existence of negative feedback regulation of PI3K activity in the hematopoietic system, too.The traditional model assuming that PI3K accounts for most of the activation of Akt was failed to fitthe experimental data obtained from BaF‐3 cells with a series of mutant EpoRs. A new model includinga feedforward loop to amplify the signal through PI3K is proposed and it is now under testing byexperiments.http://web.mit.edu/ccr/faculty/pages/lodish.htmPoster number: 36

64 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Carlos SalazarInstitution<strong>German</strong> Cancer Research Center (DKFZ)Contact AddressStreet Address Im Neuenheimer Feld 280 (B086)Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49 6221 54 51383Fax +49 6221 54 51487E‐Mailc.salazar@dkfz‐heidelberg.deShort CV2007‐ Postdoc at the <strong>German</strong> Cancer Research Center, Heidelberg2005 ‐ 2007 Postdoc at the group of Theoretical Biophysics, Humboldt University andbiochemical research at the Leibniz Institute of Molecular Pharmacology, Berlin2002 ‐ 2005 PhD studies in Theoretical Biophysics at Humboldt University Berlin2000 ‐ 2002 Studies of Biophysics at Humboldt University Berlin, <strong>German</strong>y1997 ‐ 2000 Teaching assistant at the Department of Physical Chemistry, University ofHavana1992 ‐ 1997 Studies of Chemistry at University of Havana, CubaAwards2000 ‐ 2002 Scholarship from the <strong>German</strong> Academic Exchange Service (DAAD)1999 Annual award given by the Rector of the University of Havana1997 Best graduating student of University of Havana in the area of academic resultsResearch InterestsMy research focuses on the regulation of signal transduction networks controlling transcriptionalactivity. Current projects include: 1) ligand binding and activation of T cell receptor, 2) activation ofthe PI3K/Akt signaling pathway, 3) initiation of DNA replication in yeast, 4) regulation of proteinactivity by multisite phosphorylation, 5) hierarchical organization of metabolic networks.Five most important publicationsMatthaus F.*, Salazar C.* and Ebenhöh O.* (2008) Biosynthetic potentials of metabolites and theirhierarchical organization. PLoS Comput. Biol. (to appear)Salazar C.*, Politi A.Z.* and Höfer T. (2008) Decoding of calcium oscillations by phosphorylation cycles:analytic results. Biophys J., 94 (doi:10.1529/biophysj.107.113084)Salazar C. and Höfer T. (2007) Versatile regulation of multisite protein phosphorylation by the order ofphosphate processing and protein‐protein interactions. FEBS J. 274, 1046‐1061Salazar C. and Höfer T. (2005) Activation of the transcription factor NFAT1: Concerted or modularregulation? FEBS Lett. 579, 621‐626Salazar C. and Höfer T. (2003). Allosteric regulation of the transcription factor NFAT1 by multiplephosphorylation sites: A mathematical analysis. J. Mol. Biol. 327, 31‐45*equal contributionContribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkRegulation of the initiation of DNA replication by multisite protein phosphorylationAbstractProtein phosphorylation at several sites is a common regulatory mechanism in cell signaling and cellcycle regulation that may impose a certain activation threshold or allow the synchronization ofmolecular events. Using experimental data and mathematical modeling, we studied the role ofmultisite phosphorylation in regulating the initiation of DNA replication. DNA replication is initiatedsimultaneously at several origins, whose firing is controlled by S‐CDK through the multiplephosphorylation of the substrates Sld2 and Sld3. Our kinetic analysis shows that multiplephosphorylation serves as a timing device, ensuring concerted firing of replication origins. Randomphosphorylation is found to be a more robust timer than sequential phosphorylation and, indeed, arandom mechanism has been implicated experimentally in Sld2 phosphorylation. Taken together, ourresults show that the order in which several phosphorylation sites are modified by the enzymes iscrucial for an optimal regulation of the cell cycle.Poster number: 37

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 65Dr. Maria SamsonovaInstitutionSt.Petersburg State Polytechnical UniersityContact AddressStreet Address PolytekhnichaskayaZip /Postal Code 195251CitySt.PetersburgCountryRussiaPhone +7‐812‐596‐2831Fax +7‐812‐596‐2831E‐Mailsamson@spbcas.ruWebsitehttp://urchin.spbcas.ru/site/index.htmShort CV1972 Graduated Dept. of Genetics, Leningrad State University1979 PhD in Biology, Leningrad State UniversityAwards1999 SGI Outstanding Speaker Award at the ISMB’99 conferenceResearch Interestssystems biology and developmental biologyFive most important publicationsSurkova, S., Kosman, D., Kozlov, K. N., Manu Manu, Myasnikova, E., Samsonova, A., Spirov, A.,Vanario‐Alonso, C. E., Samsonova, M., Reinitz, J.(2008) Characterization of the Drosophila segmentdetermination morphome. Dev. Biol., 313, 844‐862.Ekaterina Myasnikova, Maria Samsonova, David Kosman and John Reinitz (2005). Removal ofbackground signal from in situ data on the expression of segmentation genes in Drosophila.Development, Genes and Evolution, 215(6):320‐326.Johannes Jaeger, Svetlana Surkova, Maxim Blagov, Hilde Janssens, David Kosman, Konstantin N.Kozlov, Manu, Ekaterina Myasnikova, Carlos E. Vanario‐Alonso, Maria Samsonova, David H. Sharp, andJohn Reinitz (2004). Dynamic control of positional information in the early Drosophila embryo. Nature,430:368‐371.Johannes Jaeger, Maxim Blagov, David Kosman, Konstantin N. Kozlov, Manu, Ekaterina Myasnikova,Svetlana Surkova, Carlos E. Vanario‐Alonso, Maria Samsonova, David H. Sharp, and John Reinitz (2004).Dynamical analysis of regulatory interactions in the gap gene system of Drosophila melanogaster.Genetics, 167:1721‐1737.E. Myasnikova, A. Samsonova, M. Samsonova and J. Reinitz. Support vector regression applied to thedetermination of the developmental age of a Drosophila embryo from its segmentation geneexpression patterns (2002). Bioinformatics, 18, S87‐S95.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a talkTitle of poster / talkVariation and canalization of gene expression in the Drosophila blastodermAbstract:Here we investigate the mechanisms of canalization and embryonic regulation in the morphogeneticfield that controls the segment determination in {\em Drosophila}. The data used for thischaracterization are quantitative with cellular resolution in space and about 6.5 minutes resolution intime. At cycle 13 and the early time classes of cycle 14A the patterns of zygotic segmentation genesshow considerable variation in amplitude, the way, time and sequence of domain formation, as well assignificant positional variability. Nevertheless, this variation is dynamically reduced, or canalized by theonset of gastrulation. We use the dynamical theory framework to understand this behavior.

66 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Johannes P. SchlöderInstitutionInterdisciplinary Center for Scientific Computing(IWR) ‐ University of HeidelbergContact AddressStreet Address Im Neuenheimer Feld 368Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49 6221 54 8239Fax +49 6221 54 5444E‐Mailschloeder@iwr.uni‐heidelberg.deWebsitehttp://www.iwr.uni‐heidelberg.de/~Johannes.Schloeder/Short CVsince 2007Member of “Heidelberg Graduate School of Mathematical and ComputationalMethods for the Sciences”since 2007Academic Director at IWRsince 2001Participation in International Ph.D. Training Group“Complex Processes: Modeling, Simulation and Optimization”,Heidelberg‐Warsaw1993‐1995 Member of Research Center“Reactive Flow, Diffusion and Transport” (SFB359)University of Heidelbergsince 1992Senior researcher at theInterdisciplinary Center for Scientific Computing (IWR)University of Heidelberg1989‐1992 Teaching assistant at the Institute for Mathematics,University of Augsburg1987‐1989 Research assistant at the Institute for Applied Mathematics,Department of Applied Analysis, University of Bonn1987 Ph.D. in Applied Mathematics, University of Bonn1980‐1987 Scientific collaborator at theInstitute for Applied Mathematics and Research Center“Applied Optimization and Approximation” (SFB 72)University of BonnResearch InterestsModeling, simulation and optimization of dynamic processes; numerical methods for large‐scaleconstrained optimisation, optimal control, real‐time optimisation and nonlinear model predictivecontrol; numerical methods for parameter and state estimation, optimum nonlinear experimentaldesign and optimization under uncertainty; applications in aerospace, mechanics, biomechanics androbotics; chemical engineering, reaction kinetics, biophysics, environmental physics, epidemiology andsystems biology.Five most important publications1. Bock HG, Kostina E, Schlöder JP (2007):Numerical Methods for Parameter Estimation in Nonlinear Differential Algebraic EquationsGAMM Mitt. 30, 2: 376‐408.2. Diehl M, Bock HG, Schlöder JP (2005):A real‐time iteration scheme for nonlinear optimization in optimal feedback control.SIAM J. on Control and Optimization 43:1714‐1736.3. Bock HG, Körkel S, Kostina EA, Schlöder JP (2004):Numerical Methods for Optimal Control Problems in Design of Robust OptimalExperiments for Nonlinear Dynamic Processes.Optimization Methods and Software 19:327‐338.4. Leineweber DB, Bauer I, Bock HG, Schlöder JP (2003):An Efficient Multiple Shooting Based SQP Strategy for Large‐Scale Dynamic ProcessOptimization. Part I: Theoretical Aspects, Part II: Software Aspects and Applications.Comput. Chem. Engng. 27:137‐174.5. Dieses A, Schlöder JP, Bock HG, Richter O (2002):Optimal Experimental Design for Parameter Estimation in Column Outflow Experiments.Water Resources Research 38:1186ff.

Dr. Sebastian M. Schmidt<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 67InstitutionForschungszentrum Jülich GmbHContact AddressStreet Address Wilhelm‐Johnen‐StraßeZip /Postal Code 52428CityJülichCountry<strong>German</strong>yPhone +49‐2461 61‐3901Fax +49‐2461 61‐2640E‐Mails.schmidt@fz‐juelich.deWebsitewww.fz‐juelich.deShort CV (keywords)Since 2007Member of the Board of Directors representing the areas of „Key Technologiesand Structure of Matter“ at Research Centre Jülich2006 ‐2007 Managing director and head of the area of “research” in the <strong>Helmholtz</strong>Association2002‐2005 Scientific officer at the head office of the <strong>Helmholtz</strong> Association2001 Habilitation at the universities of Tübingen and Rostock, <strong>German</strong>y2000‐2002 Leader of an Emmy Noether Research Group at the University of Tübingen,<strong>German</strong>y1999‐2000 Alexander von Humboldt fellow at Argonne National Laboratory, USA1997‐1998 University assistant at University of Rostock, <strong>German</strong>y1995‐1996 Minerva Fellow at the University of Tel Aviv, Israel1995 PhD with the title of “Dr. rer. nat.” in theoretical physics at the University ofRostock, <strong>German</strong>yAwards1999 Fellowship by the Alexander von Humboldt Foundation1995 Minerva FellowshipResearch InterestsResearch ManagementKey TechnologiesStructure of MatterFive most important publicationsAlkofer R, Hecht MB, Roberts CD, Schmidt SM, Vinnik DV. Pair creation and an x‐ray free electron laser.PHYSICAL REVIEW LETTERS 87:193902 (2001)Blaschke D, Grigorian H, Poghosyan G, Roberts CD, Schmidt SM. A dynamical, confining model and hotquark stars. PHYSICS LETTERS B 450:207‐214 (1999)Blaschke DB, Prozorkevich AV, Roberts CD, Schmidt SM, Smolyanski SA. Pair production and opticallasers. PHYSICAL REVIEW LETTERS 96:140402 (2006)Blaschke D, Roberts CD, Schmidt S: Thermodynamic properties of a simple, confining model. PHYSICSLETTERS B, 425:232‐238 (1998)Roberts CD, Schmidt SM: Dyson‐Schwinger equations: Density, temperature and continuum strongQCD. PROGRESS IN PARTICLE AND NUCLEAR PHYSICS, 45:S1‐S103 (2000)

68 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyUrsula SchöttlerInstitutionDeutsches KrebsforschungszentrumContact AddressStreet Address Im Neuenheimer Feld 280Zip /Postal Code 69120CityHeidelbergCountry<strong>German</strong>yPhone +49 6221 42‐2651Fax +49 6221 42‐2840E‐Mailu.schoettler@dkfz‐heidelberg.deWebsitewww.dkfz.deShort CVBiology teacher by training.1970‐1978 Adult education in language training, Cairo, EgyptProject management, Cairo, Egypt1978‐1987 Teaching, project management, fundraising event managementAccra, Ghana1988‐1992 Assistant to CEO, ORPEGEN Pharma GmbH Heidelberg,Office and project managementsince 1988Language trainer, adult education1992‐2007 Admin. Assistant to Chairman of DKFZManagement of international conferencessince 2007Coordinator, International Services DKFZSpecial InterestsIntercultural and interdisciplinary communication and managementInternational conference and project management

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 69Prof. Dr. Klaus SchughartInstitution<strong>Helmholtz</strong> Centre for Infection ResearchContact AddressStreet Address Inhoffenstraße 7Zip /Postal Code 38124CityBraunschweigCountry<strong>German</strong>yPhone 0049 (0) 531 6181 1100Fax 0049 (0) 531 6181 1199E‐MailKlaus.Schughart@helmholtz‐hzi.deWebsitewww.helmholtz‐hzi.deShort CVsince 1.8.06Head of Dept. Experimental Mouse Genetics (<strong>Helmholtz</strong> Center for InfectionResearch, Braunschweig) and Professorship at the University of VeterinaryMedicine, Hannover (TiHo)2002 ‐ 2006 Head of Scientific Controlling and Deputy Scientific Director at the <strong>Helmholtz</strong>Center for Infection Research, Braunschweig1997 ‐ 2001 Head of Dept of Molecular and Cellular Biology, Transgene S.A., Strasbourg1995 ‐ 1996 Project Leader at Institute of Mammalian Genetics, GSF Munich1990 ‐ 1995 Group Leader at Max‐Planck‐Institute of Immune Biology, Freiburg1987 ‐ 1989 Postdoc in Dept. of Biology, Yale University, New Haven (Dr. F.H. Ruddle)1986 PhD at the Institute of Genetics, University of Cologne1983 Diploma in Biology at University of CologneAwards1986 Fellowship from the Boehringer Ingelheim Fonds1987‐1988 Postdoctoral Research fellowship of the <strong>German</strong> Research FoundationResearch InterestsWe are using mouse genetic reference populations (recombinant inbred lines and various laboratorystrains) to identify gene regulatory networks in immune cells. Whole genome expression profiling fromdifferent T‐cell populations is performed and bioinformatics tools are used to identify expressionQuantitative Traits (eQTLs). In addition, our laboratory is studying the host susceptibility to infectionswith influenza A virus in the mouse model system, using the same genetic reference populations andwhole genome expression profiling.We are looking for collaborations to further explore our large data sets from T cells and infectionstudies to develop in silico models of gene interaction circuits.Five most important publications(1) Schughart K., and Churchill G. (2007). 6th Annual Meeting of the Complex Trait Consortium.Mammalian Genome: 18:683‐5.(2) Streicher J., Donat M.A., Strauss B., Sporle R., Schughart K., Mueller G.B. (2000). Computer‐basedthree‐dimensional visualization of developmental gene expression. Nature Genetics 25:147‐52.(3) Hrabé de Angelis M., … Schughart K., Wolf E., and Balling R. (2000) Genome wide large scaleproduction of mutant mice by ENU mutagenesis. Nature Genetics 25, 444‐447.(4) Schughart, R. Bischoff, U.B. Rasmussen, D. Ali Hadji, F. Perraud, N. Accart, O. Boussif, N. Silvestre, Y.Cordier, A. Pavirani, M. Courtney, H.V.J. Kolbe (1999) Solvoplexes, a new type of non‐viral vectors forintrapulmonary gene delivery. Human Gene Therapy 10, 2891‐2905.(5) R. Spoerle and K. Schughart (1998). Paradox segmentation along inter‐ and intrasomitic borderlinesis followed by dysmorphology of the axial skeleton in the open brain (opb) mouse mutant.Developmental Genetics 22, 359‐373.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(please indicate)(X) a talkTitle of poster / talkSystems Genetics for Infection and ImmunityAbstractRegulatory T cells (T‐reg) play an important role for the proper coordination of the differentcomponents of the immune response. The absence of T‐reg cells results in severe allergies and autoimmunediseases. So far, only a few genes and pathways are known that are involved in T‐regdifferentiation and maintenance. We have collected T‐reg cells from 40 different recombinant inbredmouse lines and determined their expression patterns in whole genome arrays. Each of the BXDmouse strains has a slightly different genetic background and, therefore, the transcriptional expressionprofiles of many genes vary from strain to strain. Since the genotypes of all strains are known, it ispossible to identify upstream regulatory loci for all transcripts that differ in expression levels andwhich have a genetic component. In this way, single regulatory interactions can be described asexpression Quantitative Traits (eQTLs). Furthermore, differences in expression profiles of whole sets ofgenes that are controlled by the same genomic locus can be identified as groups of co‐regulated genes.In the next step, we want to use these data, and additional data from infection studies, to buildcomputer models of gene regulatory pathways in infection and immunity.

70 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologySergey SmirnovInstitutionContact AddressStreet AddressInstitute for Systems Biology SPbLeninskie Gory, 1/73, AN Belozerski IPCB MoscowState UniversityPCBZip /Postal Code 119992CityMoscowCountryRussiaPhone +7 495 783 8718Fax +7 495 783 87 18E‐Mailsmirnov‐ssv@yandex.ruWebsitewww.insysbio.ruShort CV2006‐present Research scientist of Institute for Systems Biology SPb2004 ‐ 2006 Researcher in the laboratory of Modeling of Metabolism and Bioinformatics inthe Institute of Theoretical and Experimental Biophysics (Poushchino).2002 ‐ 2004 Research officer in EMPproject company.1997 ‐ 2002 System administrator in Lvovsky Clinical and Diagnostic Center (Podolskregion).1984 ‐1997 Researcher in the Poushchino Branch of Institute of bioorganic chemistry.Research InterestsMy research interests are focused in areas of Systems Biology and Bioinformatics. General field of mywork is mathematic modeling of metabolic processes in big integral systems of organism (e.g.circulation system). Also, I have an interest in developing of special databases for scientific and appliedpurposes.Five most important publications1. Smirnov S. V., Malygin A. G., [Kinetics of DNA‐dependent RNA synthesis: coupled synthesis of di‐ andtrinucleotides in the presence of a minimum complement of substrate]. Mol Biol (Mosk), 1984,18(2):436‐46.2. Smirnov S. V., Malygin A. G., [Kinetics of DNA‐dependent RNA synthesis: couple synthesis of di‐, triandtetranucleotides in the presence of a limited set of substrates]. Mol Biol (Mosk), 1985, 19(6):1661‐8.3. Smirnov S. V., Sukharev S. A., Dmitrieva E. S., Morgunova L. V., Sadovnikov V. B., Inhibition ofneutrophil‐mediated lysis of syngeneic erythrocytes by components of blood serum and peritonealfluid. Biomed Sci., 1990, 1(5):481‐6.4. Sukharev S. A., Smirnov S. V., Pleshakova O. V., Sadovnikov V. B., [Cytotoxic activity of murineperitoneal cavity cells during inflammation in vivo]. Dokl Akad Nauk., 1995, 343(3):403‐5.5. Sukharev S. A., Smirnov S. V., Sadovnikov V. B., [Neutrophil heat shock at an inflammation focus].Dokl Akad Nauk., 1994, 335(4):515‐8.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkDevelopment of databases for Systems BiologyAbstractTwo databases concerning enzyme kinetics were developed.The first one “EnzBase” is the database for storage of data about enzyme kinetic properties andmechanisms. There are two specific features of this database suitable just for recording of kinetic data:The list of database fields is open. It allows user to write down in database any kinetic parametersfound in literature, including unique, rare and newly defined.Structure of database allows to record and store digitizing kinetic curves from referenced articles.Second database was developed for the purpose to estimate to what an extent the knowledge aboutkinetic properties of enzymes was comprehensive to date. The analysis was performed using theinformation available in Internet databases. It has been shown that relatively complete information inregard to a particular enzyme or a set of the enzymes (for instance, for a specific metabolic pathway)can be retrieved for very limited amount of organisms. As to the rest organisms, the information isavailable for highly restricted amount of the enzymes.Poster number: 38

Dr. Sergej Spirin<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 71InstitutionBelozersky Institute of MSUContact AddressStreet Address 1 Leninskije Gory, building 40Zip /Postal Code 119991CityMoscowCountryRussiaPhone +7(495)939‐5414Fax +7(495)939‐3181E‐Mailsas@belozersky.msu.ruWebsitehttp://monkey.belozersky.msu.ru/~sas/Short CVEducation: Moscow State University, Faculty of Mechanics and MathematicsPosition: Senior Researcher in Belozersky Institute of Physical and ChemicalBiology, Moscow State UniversityScientific interests: bioinformaticsResearch InterestsStructural bioinformatics, DNA‐protein interaction, algorithms in bioinformatics.Five most important publicationsLedneva R.K., Alekseevskii A.V., Vasil'ev S.A., Spirin S.A., Kariagina A.S. [Structural aspects ofhomeodomain interactions with DNA] (in <strong>Russian</strong>, 2001) Mol.Biol. (Moscow) 35 (5):764–777Alexeevski A., Spirin S., Alexeevski D., Klychnikov O., Ershova A., Titov M., Karyagina A. CluD, a Programfor Determination of Hydrophobic Clusters in 3D Structures of Protein and Protein‐Nucleic AcidsComplexes. Biophysics (Moscow), vol. 48, Suppl. 1 (2004), p. 146Karyagina A., Ershova A., Spirin S., Alexeevski A. The role of water in homeodomain‐DNA interaction.In: Bioinformatics of Genome Regulation and Structure II. (Eds. N.Kolchanov & R. Hofestaedt). NY:Springer Sc.+Bus. Media, Inc. 2005, P. 247–257.Karyagina A., Ershova A., Titov M., Olovnikov I., Aksianov E., Ryazanova A., Kubareva E., Spirin S.,Alexeevski A. Analysis of conserved hydrophobic cores in proteins and supramolecular complexes. J.Bioinf. and Comp. Biology 2006, 4 (2):357–372Sergei Spirin, Mikhail Titov, Anna Karyagina, Andrei Alexeevski. NPIDB, a Database of Nucleic Acids–Protein Interactions. Bioinformatics 2007, 23 (23):3247–3248Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(x) a poster( ) a talkTitle of poster / talkNPIDB, a database of structures of nucleic acid – protein complexesAbstractThe resource NPIDB (Nucleic acids – Protein Interaction DataBase) includes a collection of files in PDBformat containing structural information on DNA‐protein and RNA‐protein complexes, and a numberof online tools for analysis of the complexes. Those tools are: an original program CluD for analysis ofhydrophobic clusters on interfaces, programs for detecting potential hydrogen bonds and potentialwater bridges between protein and nucleic acid, visualization of structures with Jmol and Chime. Pfamand SCOP domains presented in protein chains of structures are detected. The information on thedomain types and their representatives in NPIDB is organized as a set of dynamical web pages.Update of the content is done weekly by a special program module. NPIDB is available via Internet:The work is supported by RFBR and INTAS.Poster number: 39

72 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyDr. Fabian TheisInstitution<strong>Helmholtz</strong> Zentrum MünchenContact AddressStreet Address Ingolstädter Landstraße 1Zip /Postal Code 85764CityNeuherbergCountry<strong>German</strong>yPhone +49 89 3187 2211Fax +49 89 3187 3585E‐Mailfabian.theis@helmholtz‐muenchen.deWebsitehttp://cmb.helmholtz‐muenchen.deShort CV‐ Undergraduate and graduate studies of Mathematics and Physics at the Universities of Hagen (1995‐1996), Brandeis (Boston) and Regensburg (‐2000)‐ Ph.D. in Biophysics, University of Regensburg (2002)‐ Ph.D. in Computer Science, University of Granada (2003)‐ Visiting researcher at BSI, RIKEN, Tokyo, FSU, Tallahassee, HUT, Helsinki and TUAT, Tokyo‐ Post‐Doc, Institute of Biophysics, University of Regensburg (‐2006)‐ Junior Research Group leader, MPI for Dynamics and Self‐Organization (2006‐)‐ Group leader “Computational Modeling in Biology”, <strong>Helmholtz</strong>‐Zentrum München (2007‐)Awards2003 EON Kulturpreis Ostbayern2006 Heinz Maier‐Leibnitz Award by the DFGResearch InterestsWe are interested in applying methods from biostatistics and statistical machine learning to theanalysis of biological problems, ranging from regulatory networks to neural recordings. More precisely,we are interested in statistical signal processing using information‐theoretic methods such as blindsource separation for analyzing large‐scale biomedical data sets. Methods include multivariateinformation‐theoretic data analysis, clustering, independent component analysis and variouscomputer simulations. A key application area is Systems Biology, where we are building quantitativemodels in order to explain regulatory gene networks.Five most important publicationsF.J. Theis. Towards a general independent subspace analysis. In Proc. NIPS 2006F.J. Theis and G.A. García. On the use of sparse signal decomposition in the analysis of multi‐channelsurface electromyograms. Signal Processing, 86(3):603‐623, 2006F.J. Theis and P. Gruber. On model identifiability in analytic postnonlinear ICA. Neurocomputing,64:223‐234, 2005P. Georgiev, F.J. Theis, and A. Cichocki. Sparse component analysis and blind source separation ofunderdetermined mixtures. IEEE Transactions on Neural Networks, 16(4):992‐996, 2005F.J. Theis. A new concept for separability problems in blind source separation. Neural Computation,16:1827‐1850, 2004Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x) a talkTitle of poster / talkExploratory data analysis of biological systemsAbstractSystems biology seeks to integrate different levels of information to understand how biologicalsystems function. It begins with the study of genes and proteins using high‐throughput techniquessuch as microarray measurements or mass spectrometry data. Although the experimental methods forobtaining such recordings are advanced thus generating large and multivariate data sets, theunderlying employed statistical tools have not reached this level of sophistication.In this talk, we propose to use higher‐order statistics and spatiotemporal clustering methods to extractadditional information from these large data sets. Extended multi‐dimensional inverse models areemployed to detect latent variables within the observations, which may then be analyzed using graphtheoretictechniques. The resulting methods have applications in a wide field ranging from genomics tobiomedical data analysis in general, telecommunications and financial markets, and their implicationsfor genomics, proteomics and metabolomics are yet to be fully understood.

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 73Dr. Alexey VitreschakInstitutionIITP RASContact AddressStreet Address Bolshoj Karetny pereulok 19 Mosco127994, RussiaZip /Postal Code 127994CityMoscowCountryRussiaPhone 89859688050E‐Maill_veter@mail.ruShort CVComparative genomicsGene regulationBacteriaRegulatory RNAsEvolution of regulatory systemsRiboswitchesAnalysis of gene functionT‐boxesDNA repeatsResearch InterestsPrediction of gene regulation in bacteria. Evolutionary and functional analysis of gene regulatorysystems (e.g. various riboswitches, T‐boxes and others). Analysis of repeat sequences in genomes.Five most important publications.G. Vitreschak, A.A Mironov, V.A. Lyubetsky, M.S. Gelfand. Comparaive genomic analysis of T‐boxregulatory systems in bacteria. RNA, 2008, (accepted, in print).Vitreschak AG, Rodionov DA, Mironov AA, Gelfand MS Riboswitches: the oldest mechanism for theregulation of gene expression? Trends in Genetics, 2004 Jan; 20(1):44‐50.Vitreschak AG, Rodionov DA, Mironov AA, Gelfand MS. Regulation of the vitamin B(12) metabolismand transport in bacteria by a conserved RNA structural element. RNA. 2003 Sep; 9(9):1084‐1097.Vitreschak AG, Rodionov DA, Mironov AA, Gelfand MS. Regulation of riboflavin biosynthesis andtransport genes in bacteria by transcriptional and translational attenuation. Nucleic Acids Research.2002. V. 30(14) P. 3141‐51.Rodionov DA, Vitreschak AG, Mironov AA, Gelfand MS. Comparative Genomics of Thiamin Biosynthesisin Procaryotes. New Genes and Regulatory Mechanisms. J. Biol. Chem. 2002 Dec 13;277(50):48949‐59Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X ) a poster( ) a talkTitle of poster / talkComparative Genomic Analysis of T‐Box Regulatory Systems in BacteriaAbstractThe bacteria use a wide range of regulatory mechanisms to control gene expression. While the most commonregulatory mechanism seems to be regulation of transcription by DNA‐binding proteins, there are other importantmechanisms, in particular, regulation of transcription (by premature termination) and translation (by interferencewith initiation) via formation of alternative RNA structures in 3’‐untranslated gene regions. The most frequentmechanism of RNA‐dependent regulation of amino acid operons in the Firmicutes seems to be the T‐box regulatorysystem. The T‐box is an RNA structure that is capable of binding uncharged tRNA via an interaction between thehighly conserved 5'‐UGGN‐3' sequence of the T‐box and the complementary 5'‐NCCA‐3' end of the tRNA. Thespecificity of this binding is defined by base‐pairing of the tRNA anticodon and the so‐called specifier (anti‐anti)‐codon in the T‐box structure. The bound uncharged tRNA stabilizes the antiterminator hairpin, which in turn preventsformation of the terminator and allow the gene to be expressed.Using a set of known T‐box sites, we constructed the common pattern and used it to scan available bacterialgenomes. New T‐boxes were found in various Gram‐positive bacteria (mainly Firmicutes, but also Actinobacteria),some Proteobacteria (delta‐proteobacteria), and some other bacterial groups (Deinococcales/Thermales, Chloroflexi,Dictyoglomi). The majority of T‐box‐regulated genes encode aminoacyl‐tRNA synthetases. Two other groups of T‐boxregulatedgenes are amino acid biosynthetic genes and transporters, as well as genes with unknown function.Analysis of candidate T‐box sites resulted in new functional annotations for a large number of putative amino acidtransporters as well as some genes with unknown function. We predict the specificity of amino acid transportersanalyzing the specifier codons in T‐boxes that regulate genes encoding these transporters and use other methods ofcomparative genomics to obtain additional, independent evidence.We then studied the evolution of the T‐boxes. Analysis of the constructed phylogenetic trees and changes in thespecifier codons demonstrated, that in addition to the normal evolution consistent with the evolution of regulatedgenes, T‐boxes may be duplicated, transferred to other genes, and change specificity. We observed several cases ofrecent expansion of T‐box regulons likely caused by the loss of a previously existing regulatory system, in particular,the arginine regulon in Clostridium difficile (loss of the transcriptional repressor AhrC) and methionine regulon in theLactobacillaceae (loss of the S‐box riboswitches).In some cases, T‐boxes were arranged in tandem. Predominantly this happened upstream of biosynthetic andtransport genes. The two major types of such tandems are double T‐boxes, that is, repeats of complete T‐boxstructures, and unusual “partially‐double” T‐boxes, formed by a single specifier hairpin followed by two repeatedterminator/antiterminator structures closely located to each other.Finally, we described a new structural class of T‐boxes regulating initiation of translation in the Actinobacteria. Theyare much shorter and the specifier codon is located in the loop of the hairpin, and not the bulge like in the classic T‐box structure. The T‐box‐containing hairpin may be alternative to a hairpin that masks the Shine‐Dalgarno box andthus interferes with the initiation of translation. Such T‐boxes were found upstream of the ileS genes in someActinobacteria (all Actinomycetales and Bifidobacterium longum), whereas the translation‐regulating T‐boxes of theclassical type were observed only in Thermobifida fusca and the Streptomyces spp. In other actinobacterial species, anew variant of the specifier hairpin was found.Poster number: 40

74 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyMartin von Bergen, PhDInstitution<strong>Helmholtz</strong>‐Centre for Environmental ResearchtContact AddressStreet Address Permoser Str‐ 15Zip /Postal Code 04318CityLeipzigCountry<strong>German</strong>yPhone +49‐341‐235 1211Fax +49‐341‐235 451211E‐MailMartin.vonbergen@ufz.deShort CV1989‐1995 Studies of Biology, University of Hamburg (D), Dipl. Biol.1995‐1998 PhD, University of Hamburg, Faculty of BiologyMax‐Planck Unit for Structural Molecular Biology, HamburgPhD in Natural Sciences, thesis: "The conformation of the microtubulesassociated protein tau in Alzheimer’s disease"1998‐2001 Postdoc, Max‐Planck Unit for Structural Molecular Biology, Hamburg2001‐2002 Group Leader Proteomics, Mice and More GmbH and Co KG2002‐2006 Senior Scientist, Max‐Planck Unit for Structural Molecular Biology, Hamburg (D)Since May 2006 Head of Department of Proteomics,<strong>Helmholtz</strong>‐Centre for Environmental Research Leipzig‐Halle (D)Research InterestsBeside the general interest in the improvement of proteomic technology we are especially interestedin the combination of proteome, cytome and genome data for obtaining a systemic view of the cellularresponse to exposition to environmental stressors. A focus lies on the effects of volatile organiccompounds on cells of the respiratory tract and the immune system.Five most important publications• Gündel, U., Benndorf, D., von Bergen, M., Altenburger, R. und Küster, E. Lipovitellins aspotential biomarkers in developing zebrafish embryos: a proteomics approach. Proteomics(2007), in press• Bock, K., Benndorf, D., Mueller, A., Herbarth, O.and von Bergen, M.: Allergens fromAspergillus versicolor and their usage in diagnosis and therapy of indoor relevant mouldspore allergies. Patent application to the <strong>German</strong> Patent Agency (2007)• Santos PM, Roma V, Benndorf D, von Bergen M, Harms H, Sá‐Correia I.: Mechanistic InsightsInto the Global Response to Phenol in the Phenol‐biodegrading Strain Pseudomonas sp. M1Revealed by Quantitative Proteomics. OMICS 11(3), 233‐51 (2007)• von Bergen M, Barghorn S, Muller SA, Pickhardt M, Biernat J, Mandelkow EM, Davies P,Aebi U, Mandelkow E.: The core of tau‐paired helical filaments studied by scanning transmissionelectron microscopy and limited proteolysis. Biochemistry 23;45(20), 6446‐57(2006)• von Bergen M, Friedhoff P, Biernat J, Heberle J, Mandelkow EM, Mandelkow E.: Assembly oftau protein into Alzheimer paired helical filaments depends on a local sequence motif((306)VQIVYK(311)) forming beta structure. Proc Natl Acad Sci U S A 9;97(10), 5129‐34(2000)Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x) a talkTitle of poster / talkFrom contaminant molecule to the cellular responseAbstractTo measure the effects of environmental pollutants on cells up to now only a limited number ofendpoints were determined. To overcome these limitations we started a project in which thefundamental aspects of entrance, distribution and molecular effects will be analysed and combined inorder to obtain a more complete picture. As a model compound both for environmental pollutants andpharmaceutical compounds we chose benzo(a)pyrene. The fluorescence of this compound allows themeasurement of entrance and distribution within the cells. The experimental data will be used formodelling the different stages of the distribution.It is further known that benzo(a)pyrene binds to the arylhydrocarbon receptor (AhR) and that thebinding event induces the locomotion of the receptor from the cytosol into the nucleus, where it actsas an transcription factor for proteins involved in the detoxification pathway.By genomic and proteomic techniques we will determine the later effects of benzo(a)pyrene andcombine to obtain a model, that explains the different pathways of the cellular response. These datawill enable the identification of classifiers that allow a prediction of cellular systems on the basis ofsimplified measurements and this might be applied in the future also to the response towardspharmaceutical compounds.

<strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 75Dr. Jana WolfInstitutionHumboldt‐University BerlinContact AddressStreet Address Invalidenstr. 42Zip /Postal Code 10115CityBerlinCountry<strong>German</strong>yPhone +49 30 2093 8382Fax +49 30 2093 8813E‐Mailj.wolf@biologie.hu‐berlin.deWebsitehttp://www.biologie.hu‐berlin.de/theorybp/Short CV1989‐1994 Study of Biophysics, Humboldt‐University Berlin1994‐1995 Biochemical Research at Hoechst AG Frankfurt/M.1995‐2001 Scientist in the theoretical biophysics group of R. Heinrich, HU Berlin,2000 PhD in Theoretical Biophysics1997, 1998 Guest scientist at the Free University Amsterdam, NetherlandsNov. 1998Guest scientist at the National Institute of Bioscience and Human‐Technology,Tsukuba, Japan2001‐2003 Postdoc at Charité and the Institute for Theoretical Biology, HU Berlin2003‐2005 Postdoc at GlaxoSmithKline, Scientific Computing and Mathematical Modellinggroup, Medicines Research Centre, Stevenage, UKsince 2006Postdoc in the International Research Training Group 'Genomics and SystemsBiology of Molecular Networks' Berlin‐Boston‐Kyotofrom March 2008 Mathematical Modelling Group at the Max‐Delbrueck‐Centre, BerlinAwards2003 Leopoldina Postdoc ScholarshipResearch InterestsMammalian signal transduction pathways (NF‐κB, Wnt, EGFR)Metabolic networks (energy metabolism)Cellular oscillations (circadian rhythm, metabolic oscillations) and synchronisation effectsRobustness of cellular rhythmsFive most important publicationsJ. Wolf, S. Dronov, F. Tobin & I. Goryanin (2007), The impact of the regulatory design on the responseof EGFR‐mediated signal transduction towards oncogenic mutations. FEBS Journal 274 (21), 5505‐5517.J. Wolf, S. Becker‐Weimann & R. Heinrich (2005), Analysing the robustness of cellular rhythms, IEESyst. Biol. 2(1), 35‐41.S. Becker‐Weimann, J. Wolf, H. Herzel & A. Kramer (2004), Modeling feedback loops of the Mammaliancircadian oscillator. Biophysical Journal 87, 3023‐3034.J. Wolf, J. Passarge, O.J.G. Somsen, J.L. Snoep, R. Heinrich & H.V. Westerhoff (2000), Transduction ofintracellular and intercellular dynamics in yeast glycolytic oscillations. Biophysical Journal 78, 1145‐1153.J. Wolf & R. Heinrich (2000), The effect of cellular interaction on glycolytic oscillations in yeast. Atheoretical investigation. Biochemical Journal 345, 321‐334.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare( ) a poster(x) a talkTitle of poster / talkModelling of signalling networks for the analysis of oncogenic mutationsAbstractSignal transduction pathways play a crucial role in the regulation of various cellular functions, such asproliferation, differentiation, survival or the formation of cell‐cell contacts. Using mathematicalmodelling we here analyse two examples, that is EGF‐mediated and Wnt signalling, in order tounderstand the effect of specific oncogenic perturbations.The EGFR pathway is deregulated in about 30% of all human cancers, such as malignancies of thecolon, lung, pancreas, ovary and kidney as well as some leukemias. However, different mutations inthe EGFR‐mediated pathway are involved in different tumours. We address the question whether thismay result from the regulation structure which is known to be cell‐type specific. In our attempt we willuse a detailed computational model of the epidermal growth factor signalling network to investigatethe effect of receptor over‐expression and Ras mutations as most prominent examples under twodifferent feedback regulations.As a second example we use a mathematical model of the Wnt signalling pathway to analyse the effectof ß‐catenin mutations in hepatocellular carcinoma cells. The mutations, present in 13‐43% of thetumours, result in mutated β‐catenin protein that can‘t be phosphorylated and degraded by theaxin/APC/GSK3ß‐dependent destruction cycle.

76 <strong>Helmholtz</strong>‐<strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems BiologyAlexey ZakharovInstitution Institute of Biomedical Chemistry RAMSContact AddressStreet Address Pogodinskaya Str., 10Zip /Postal Code 119121CityMoscowCountryRussiaPhone +7 495 247‐3029Fax +7 495 245‐0857E‐Mailalexey.zakharov@ibmc.msk.ruWebsitewww.ibmc.msk.ruShort CV2005‐2008 PhD Student of Institute of Biomedical Chemistry of Rus. Acad. Med. Sci.1999‐2005 Student of <strong>Russian</strong> State Medical UniversityResearch InterestsMy research interests are quantitative structure‐activity relationships analysis using bio‐ andchemoinformatics, in application to search for new anticancer agents.Five most important publicationsCYCLONET—an integrated database on cell cycle regulation and carcinogenesis. F. Kolpakov, V.Poroikov, R. Sharipov, Y. Kondrakhin, A. Zakharov, A. Lagunin, L. Milanesi and A. Kel. Nucleic AcidsResearch, 2007, 35, Database issue, D550–D556.A new approach to QSAR modelling of acute toxicity. A.A. Lagunin, A.V. Zakharov, D.A. Filimonov andV.V. Poroikov. SAR and QSAR in Environmental Research, 2007, 18(3–4), 285–298.PASS: indentification of probable targets and mechanisms of toxicity. V.V. Poroikov, D.A. Filimonov,A.A. Lagunin, T.A. Gloriozova and A.V. Zakharov. SAR and QSAR in Environmental Research, 2007,18(1–2), 101‐110.Computer prediction of human carcinogenicity for chemical compounds according to iarc classification.A.V. Zakharov, A.A. Lagunin, D.A. Filimonov, V.V. Poroikov, QSAR and Molecular Modelling in RationalDesign of Bioactive Molecules (Euro QSAR 2004), Turkey, 211‐212.Quantitative structure‐activity relationships of cyclin‐dependent kinase 1 inhibitors. A.V. Zakharov,A.A. Lagunin, D.A. Filimonov and V.V. Poroikov. Biochemistry (Moscow) Supplemental Series B:Biomedical Chemistry. 2007, 1(1), 17–28.Contribution to <strong>Helmholtz</strong> <strong>Russian</strong>­<strong>German</strong> workshop on systems biologyI will prepare(X) a poster( ) a talkTitle of poster / talkQSAR modelling of antineoplastic activities using NIH Roadmap Data.AbstractA new and extensive database of chemical structures and their biological activities is being developedby the National Center for Biotechnology Information at NIH. The database, called PubChem, containsboth structural information from the scientific literature as well as screening and probe data from theMolecular Libraries Screening Center Network. We selected compounds with atineoplastic activitiesfrom PubChem for QSAR modelling of antineoplastic activities by GUSAR program. We obtained QSARmodels for each antineoplastic activities and validated them both by leave‐one‐out cross validationprocedure and vs. external test set. The study is supported by FP6‐grant LSHB‐CT‐2007‐037590(Net2Drug).Poster number: 41

Venue DetailsHoliday InnMoscow‐SokolnikiRusakovskaya Ulitsa 24Moscow, 107014<strong>Russian</strong> Federationphone: +7‐495‐7867373fax: +7‐495‐7867374http://www.hi‐sokolniki.ru/Transportation to and from HotelFrom Sheremetyevo (SVO) AirportDistance: 33 KM South East to HotelBy car or taxi:From the airport drive up to the Leningradskoyeshosse and turn to the Moscow Centre. Drive upto the MKAD (Moscow Ring Road). Take the exitto the MKAD East and drive up to theShchelkovskoye shosse. Turn to the MoscowCentre and drive via Bol. Cherkizovskaya Streetup to Rusakovskaya Street.By public transport:By Bus #Ш851c from Sheremetyevo‐I (07:05 ‐21:05) direction Rechnoy Vokzal metro station.Then by underground to the Teatralnaya metrostation (9 stops), change to the Okhotny Ryadmetro station and take the train to Sokolnikimetro station (6 stops). Get off Sokolniki metrostation. The Hotel is across the street.By Sheremetyevo Bus:(06:15 ‐ 21:17) to the train station Lobnya. Thenby express‐train to Savyolovskaya station,change for underground and go toMendeleevskaya metro station (1 stop) changethe line for Novoslobodakay metro station andgo to Komsomolskaya (2 stops), change for thered line, get off at Sokolniki metro station (2stops). The Hotel is across the road.From Domodedovo Airport (DME)• Distance: 54 KM North East to Hotel• Taxi Charge (one way): 2610.0 (RUR)• Time by taxi: 1,5 hour• Train Charge (one way): 300.0 (RUR)• Time by train: 40 minutes• From airport drive alond M4 Road viaKashirskoye shosse up to 3rd Ring. Enter 3rdRing and take the right. Drive straight to theturn to Rusakovskaya st.Subway:• Subway Station Name: Sokolniki• Distance: 0.1 KM South to Hotel• The hotel is located at only 2 minutes bywalk just opposite to Sokolniki metrostationDistance to Attractions:• Red Square (6 KM )• Bolshoi Theatre (6 KM)• Pushkin Museum of Arts (7.5 KM)• Christ the Saviour Cathedral (8 KM)<strong>Helmholtz</strong> <strong>Russian</strong>‐<strong>German</strong> <strong>Workshop</strong> on Systems Biology 77