12.07.2015 Views

Bibliography - de l'Université libre de Bruxelles

Bibliography - de l'Université libre de Bruxelles

Bibliography - de l'Université libre de Bruxelles

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

<strong>Bibliography</strong>Alard P. (1991). Calculs <strong>de</strong> surface et d’énergie dans le domaine <strong>de</strong>smacromolecules. PhD Thesis, Université Libre <strong>de</strong> bruxelles.Altintas M.M., B. Kirdar, Z.I. Önsan and K.Ö. Ülgen (2002). Cyberneticmo<strong>de</strong>lling of growth and ethanol production in a recombinant Saccharomycescerevisiae strain secreting a bifunctionnal fucion protein. Process Biochemistry,37, 1439-1445.Amrit R. and P. Saha (2005). Black box technique: A review. Proceedings ofSCC 2005, IEEE International Conference on Services Computing, Orlando,Florida, USA.Arunachalam J., V. Kanagasabai and N. Gautham (2006). Protein structureprediction using mutually orthogonal Latin squares and a genetic algorithm.Biochemical and Biophysical Research Communications, 342 (2), 424-433.Bai F.W., L.J. Chen, Z.Zhang, W.A. An<strong>de</strong>rson and M. Moo-Young (2004).Continuous ethanol production and evaluation of yeast cell lysis and viabilityloss un<strong>de</strong>r very high gravity medium conditions. Journal of Biotechnology, 110,287-293.Bailey J.E. and J.F. Ollis (1986). Biochemical engineering fundamentals. McGraw-Hill Chemical Engineering Series, 2 nd edition.Basch, P. A., U. C Singh., R. Langridge and P. A. Kollman (1987). Freeenergy calculations by computer simulation. Science, 236, 564–568.Bastin G. and D. Dochain (1990). On-line estimation and adaptive control ofbioreactors. Elsevier, Amsterdam.Berman H.M., J. Westbrook, Z. Feng, G. Gilliland, T.N. Bhat, H. Weissig,I.N. Shindyalov and P.E. Bourne (2000). The Protein Data Bank. Nucleic AcidsResearch, 28 (1), 235-242.323


324 <strong>Bibliography</strong>Bernard, O. and Bastin G. (2005). On the estimation of the pseudostoichiometricmatrix for mass balance mo<strong>de</strong>ling of biotechnological processes.Mathematical Biosciences, 193, 51-77, 2005.Birol G., P. Dorucker, B. Kirdar, Z. I. Önsan and K. Ülgen (1998).Mathematical <strong>de</strong>scription of ethanol fermentation by immobilisedSaccharomyces cerevisiae. Process Biochemistry, 33 (7), 763-771.Bogaerts Ph. (1999). Contribution à la modélisation mathématique pour lasimulation et l’observation d’états <strong>de</strong>s bioprocédés. Thèse <strong>de</strong> doctorat,Université Libre <strong>de</strong> <strong>Bruxelles</strong>.Bogaerts Ph., Castillo J. and R. Hanus (1999) A general mathematicalmo<strong>de</strong>lling technique for bioprocesses in engineering applications, SystemAnalysis Mo<strong>de</strong>ling Simulation, 35, 87-113.Bogaerts Ph. and R. Hanus (2000). Macroscopic mo<strong>de</strong>lling of bioprocesseswith a view to engineering applications. in: Focus on Biotechnology (M.Hofman and J. Anne, Eds), vol. IV Engineering and Manufacturing forBiotechnology (Ph. Thonart and M. Hofman, Eds), Kluwer Aca<strong>de</strong>micPublishers, 77-110.Bogaerts Ph., J.-L. Delcoux and R. Hanus (2003). Maximum likelihoo<strong>de</strong>stimation of pseudo-stoichiometry in macroscopic biological reaction schemes.Chemical Engineering Science, 58, 1545-1563.Buchete N.V., J.E. Straub and D. Thirumalai (2004). Development of novelstatistical potentials for protein fold recognition. Current Opinion in StructuralBiology, 14, 225-232.Brooks B.R., R.E. Bruccoleri, B.D. Olafson, D.J. Sates, S. Swaminathan andM. Karplus (1983). CHARMM: A program for macromolecular energy,minimization and dynamics calculations. Journal of Computational Chemistry,4, 187-217.Campello R.J.G.B., F.J. Von Zuben, W.C. Amaral, L.A.C. Meleiro and R.Maciel Filho (2003). Hierarchical fuzzy mo<strong>de</strong>ls within the framework oforthonormal basis functions and their application to bioprocess control.Chemical Engineering Science, 58, 4259-4270.Capriotti E., P. Fariselli and R. Casadio (2004). A neural-network-basedmethod for predicting protein stability changes upon single point mutations.Bioinformatics, 20, i63-i68.


<strong>Bibliography</strong> 325Capriotti E., P. Fariselli and R. Casadio (2005). I-Mutant2.0: predictingstability changes upon mutation from the protein sequence or structure. NucleicAcids Research, 33, W306-W310.Chen L. and G. Bastin (1996). Structural i<strong>de</strong>ntifiability of the yieldcoefficients in bioprocess mo<strong>de</strong>ls when the reaction rates are unknown. Math.Biosci., 132, 35-67.Chen L., O. Bernard, G. Bastin and P. Angelov (2000). Hybrid mo<strong>de</strong>lling ofbiotechnological processes using neural networks. Control EngineeringPractice, Volume 8, Issue 7, 821-827.Chen L., Y. Hontoir, D. Huang, J. Zhang, A. J. Morris (2004a). Combiningfirst principles with black-box techniques for reaction systems. ControlEngineering Practice, 12, 819-826.Chen L., S.K. Nguang, X.D. Chen and X.M. Li (2004b). Mo<strong>de</strong>lling andoptimization of fed-batch fermentation processes using dynamic neural networksand genetic algorithms. Biochemical Engineering Journal, 22, 51-61.Choi D.-J. and H. Park (2001). A hybrid artificial neural network as asoftware sensor for optimal control of wastewater treatment process. WaterResearch, Vol. 35 (16), 3959-3967.Costa A. C., T.L.M. Alves, A.W.S. Henriques, R. Maciel Filho and E.L.Lima (1998). An adaptative optimal control scheme based on hybrid neuralmo<strong>de</strong>lling. Computers chem.. Engineering, vol. 22, 859-862.Creighton T.E. (1993). Proteins: structures and molecular properties. W.H.Freeman and Company, New York.Cruz A.J.G., A.S. Silva, M.L.G.C. Araujo, R.C. Giordano and C.O. Hokka(1999). Mo<strong>de</strong>lling and optimization of the cephalosporin C productionbioprocess in a fed-batch bioreactor with invert sugar as substrate. ChemicalEngineering Science, 54, 3137-3142.Cybenko G. (1989). Approximation by superpositions of a sigmoidalfunction. Mathematics of Control, Signals, and Systems. 2 (4), 303-314.Dalai M., E. Weyer and C. Campi (2005). Parametric I<strong>de</strong>ntification ofNonlinear Systems: Guaranteed Confi<strong>de</strong>nce Regions. Proceedings of the 44 thIEEE Conference on Decision and Control, and the European ControlConference 2005, Seville, 6418-6423.


326 <strong>Bibliography</strong>Dantigny Ph. (1995). Mo<strong>de</strong>ling of the aerobic growth of Saccharomycescerevisiae on mixtures of glucose and ethanol in continuous culture. Journal ofBiotechnology, 43, 213-220.<strong>de</strong> Andrès-Toro B., J.M. Giron-Sierra, J.A. Lopez-Orozco, C. Fernan<strong>de</strong>z-Con<strong>de</strong>, J.M. Peinado and F. Garcia-Ochoa (1998). A kinetic mo<strong>de</strong>l for beerproduction un<strong>de</strong>r industrial operational conditions. Mathematics and Computersin Simulation, 48, 65-74.<strong>de</strong> Assis A. J. and R. M. Filho (2000). Soft sensors <strong>de</strong>velopment for on-linebioreactor state estimation. Computers and Chemical Engineering, 24, 1099-1103.Dehouck Y., D. Gilis and M. Rooman (2004). Database-<strong>de</strong>rived potentials<strong>de</strong>pen<strong>de</strong>nt on protein size for in silico folding and <strong>de</strong>sign. Biophysical Journal,87, 171-181.Dehouck Y. (2005). Développement <strong>de</strong> potentiels statistiques pour l'étu<strong>de</strong> insilico <strong>de</strong> protéines et analyse <strong>de</strong> structurations alternatives. PhD Thesis,Université Libre <strong>de</strong> <strong>Bruxelles</strong>.Dehouck Y., D. Gilis and M. Rooman (2006). A new generation of statisticalpotentials for proteins. Biophysical Journal, 90, 4010-4017.Di Serio M., R. Tesser and E. Santacesaria (2001). A kinetic and masstransfer mo<strong>de</strong>l to simulate the growth of baker' s yeast in industrial bioreactors.Chemical Engineering Journal, 82, 347-354.Di Serio M., E. De Alteriis, P. Parascandola, E. Santacesaria (2001). Ageneral kinetic and mass transfer mo<strong>de</strong>l to simulate the baker’s yeast growth inbioreactors. Catalysis Today, 66, 437-445.Dutta J.R., P.K. Dutta and R. Banerjee (2005). Mo<strong>de</strong>ling and optimizationof protease production by a newly isolated Pseudomonas sp. Using geneticalgorithm. Process Biochemistry, 40, 879-884.Eriksson, A. E., W. A. Baase, X.-J. Zhang, D. W. Heinz, M. Blaber, E. P.Baldwin and B. W. Matthews (1992). Response of a protein structure to cavitycreatingmutations and its relation to the hydrophobic effect. Science, 255, 178–183.Eya H., K. Mishima, M. Nagatani, Y. Iwai and Y. Arai (1994). Measurementand correlation of solubilities of oxygen in aqueous solutions containingglucose, sucrose and maltose. Fluid Phase Equilibria, 97, 201-209.


<strong>Bibliography</strong> 327Ferentinos K.P. (2005). Biological engineering applications of feedforwardneural networks <strong>de</strong>signed and parametrized by genetic algorithms. Neuralnetworks, 18 (7), 934-950.Fersht A.R. and L. Serrona (1993). Principles of protein stability fromprotein engineering experiments. Current Opinion in Structural Biology, 3, 75-83.Feyo <strong>de</strong> Azevedo S., B. Dahm and F. R. Oliveira (1997). Hybrid mo<strong>de</strong>llingof biochemical processes: A comparison with the conventional approach.Computers and Chemical Engineering, 21, suppl., 751-756.Gadkhar K.G., S. Mehra and J. Gomes (2005). On-line adaptation of neuralnetworks for bioprocess control. Computers and Chemical Engineering, 29,1047-1057.Ghaly A.E., M. Kamal and L.R. Correia (2005). Kinetic mo<strong>de</strong>lling ofcontinuous submerged fermentation of cheese whey for single cell proteinproduction. Bioresource technology, 96, 1143-1152.Gilis D. and M. Rooman (1996). Stability changes upon mutation of solventaccessibleresidues in proteins evaluated by database-<strong>de</strong>rived potentials. Journalof Molecular Biology, 257, 1112-1126.Gilis D. and M. Rooman (1997). Predicting protein stability changes uponmutation using database-<strong>de</strong>rived potentials: solvent accessibility <strong>de</strong>termines theimportance of local versus non-local interactions along the sequence. Journal ofMolecular Biology, 272, 276-290.Gilis D. and M. Rooman (2000). PoPMuSiC, an algorithm for predictingprotein mutant stability changes. Application to prion proteins. ProteinEngineering, 13 (12), 849-856.Glassey J., M. Ignova, A.C. Ward, G.A. Montague and A.J. Morris (1997).Bioprocess supervision: neural networks and knowledge based systems. Journalof Biotechnology, 52, 201-205Goodwin G.C. and R.L. Payne (1977). Dynamic system i<strong>de</strong>ntification:experiment <strong>de</strong>sign and data analysis. Aca<strong>de</strong>mic Press, New York.Gourlay M.D., J. Kendrick and F.J.J. Leusen (2007). Conformationalanalysis of ephedrine using molecular mechanical, semi-empirical and ab initioquantum mechanical methods. Journal of Molecular Structure: THEOCHEM,article in press.


328 <strong>Bibliography</strong>Graefe J., Ph. Bogaerts, J. Castillo, M. Cherlet, J. Wérenne and R. Hanus(1999). A new training method for hybrid mo<strong>de</strong>ls of bioprocesses. BioprocessEngineering, 21, 423-429.Gromiha M.M., J. An, H. Kono, M. Oobatake, H. Uedaira, P. Prabakaran andA. Sarai (2000). ProTherm, version 2.0: thermodynamis database for proteinsand mutants. Nucleid Acids Res., 28, 283-285.Grosfils A., A. Van<strong>de</strong> Wouwer, A. Gaspar, T. Dauvrin and Ph. Bogaerts(2004). Systematic <strong>de</strong>coupled i<strong>de</strong>ntification of pseudo-stoichiometry, lysis rateand kinetics for a xylanase production. Proceedings of the 9 th Symposium onComputer Applications in Biotechnology, Nancy (France).Grosfils A., A. Van<strong>de</strong> Wouwer and Ph. Bogaerts (2005). Hybrid neuralnetwork mo<strong>de</strong>ls of bioprocesses: a comparative study. Proceedings of the 16 thIFAC world congress, Prague.Grosfils A., A. Van<strong>de</strong> Wouwer and Ph. Bogaerts (2007a). Systematic<strong>de</strong>coupled i<strong>de</strong>ntification of pseudo-stoichiometry, <strong>de</strong>gradation rates and kinetics.Computer & Chemical Engineering, article in press.Grosfils A., A. Van<strong>de</strong> Wouwer and Ph. Bogaerts (2007b). On a generalmo<strong>de</strong>l structure for macroscopic biological reaction rates. Journal ofBiotechnology, article in press.Guerois R., J.E. Nielsen and L. Serrano (2002). Predicting changes in thestability of proteins and protein complexes : a study of more than 1000mutations. Journal of Molecular Biology, 320, 369-387.Hao M.H. and H.A. Sheraga (1996). How optimization of potential functionsaffects protein folding. Proceedings of the National Aca<strong>de</strong>my of Sciences (USA),93, 4984-4989.Haag J.E.(2003). Dynamic mo<strong>de</strong>lling and state estimation of complexbioprocesses. Theoretical issues and applications. PhD Thesis. FacultéPolytechnique <strong>de</strong> Mons.Haag J.E., Van<strong>de</strong> Wouwer A & Bogaerts Ph. (2005). Dynamic mo<strong>de</strong>lling ofcomplex biological systems: A link between metabolic and macroscopic<strong>de</strong>scription. Mathematical Biosciences, 193, 283-291.Häfele M., A. Kienle, M. Boll and C.-U. Schmidt (2006). Mo<strong>de</strong>ling andanalysis of a plant for the production of low <strong>de</strong>nsity polyethylene. Computers &Chemical Engineering, article in press.


<strong>Bibliography</strong> 329Hanomolo A., Ph. Bogaerts, J. Graefe, M. Cherlet, J. Wérenne, R. Hanus(2000). Maximum likelihood parameter estimation of a hybrid neural-classicalstructure for the simulation of bioprocesses. Mathematics and Computer inSimulation, 51, 375-385.Haykin S. (1999). Neural Networks: A comprehensive foundation, PrenticeHall, 2d edition.Hellinga H.W. (1998). Computational protein engineering. Nature StructuralBiology, 5, 525-527.Holmberg A. (1983). On the accuracy of estimating the parameters of mo<strong>de</strong>lscontaining Michaelis-Menten type nonlinearities. Mo<strong>de</strong>lling and data analysisin biotechnology and medical engineering (Vansteenkiste G. C. and Young P.C.,eds.), North-Holland, Amsterdam,202.Huang L.-T., K. Saraboji, S.-Y. Ho, S.-F. Hwang, M.N. Ponnuswamy and M.M. Gromiha (2007). Prediction of protein mutant stability using classificationand regression tool. Biophysical Chemistry, 125, 462-470Hulhoven X. and Ph. Bogaerts (2002). Hybrid full horizon-asymptoticobserver for bioprocesses. Proceedings of the 15 th Triennial World Congress,Barcelona, Spain.James S. R. Ledge and H. Bu<strong>de</strong>man (2002). Comparative study of black-boxand hybrid estimation methods in fed-batch fermentation. Journal of ProcessControl 12, 113-121.Jayachandran G., V. Vishal, A.E. Garcia and V.S. Pan<strong>de</strong> (2006). Localstructure formation in simulations of two small proteins. Journal of StructuralBiology, article in press.Jones K. D. and D. S. Kompala (1999). Cybernetic mo<strong>de</strong>l of the growth ofSaccharomyces cerevisiae in batch and continuous cultures. Journal ofBiotechnology, 71, 105-131.Karakuzu C., M. Türker and S. Öztürk (2006). Mo<strong>de</strong>lling, on-line stateestimation and fuzzy control of production scale fed-batch baker’s yeastfermentation. Control Engineering Practice, 14, 959-974.Karim M.N., T. Yoshida, S.L. Rivera, V.M. Saucedo; B. Eikens and Gyu-Seop OH (1997). REVIEW: Global and Local Neural Network mo<strong>de</strong>ls inBiotechnology: Application to Different Cultivation Processes. Journal ofFermentation and Bioengineering, Vol. 83, n°1, 1-11.


330 <strong>Bibliography</strong>Khatun J., S.D. Khare and N.V. Dokholyan (2004). Can contact potentialsreliably stability of proteins? Journal of Molecular Biology, 336, 1223-1238.Kocher J.-P., M. Prévost, S.J. Wodak and B. Lee (1996). Properties of theprotein matrix revealed by the free energy of cavity formation. Structure, 4,1517-1529.Komives C. and R. S Parker (2003). Bioreactor state estimation and control.Current Opinion in Biotechnology, Vol. 14, 5, 468-474Kompala D.S., D. Ramkrishna, N.B. Jansen and G.T. Tsao (1986).Investigation of bacterial growth on mixed substrate: experimental evaluation ofcybernetic mo<strong>de</strong>ls. Biotechnology Bioengineering, 28, 1044-1055.Kompala D. S. (1999). Cybernetic mo<strong>de</strong>lling of spontaneous oscillations incontinuous cultures of Saccharomyces cerevisiae. Journal of Biotechnology, 71,267-274.Kulkarni S.G., A.K. Chaudhary, S. Nandi, S.S. Tambe, B.D. Kulkarni(2003). Mo<strong>de</strong>ling and monitoring of batch processes using principal componentanalysis (PCA) assisted generalized regression neural networks (GRNN).Biochemical Engineering Journal, 18, 193-210.Kwasigroch J.M., D. Gilis, Y. Dehouck and M. Rooman (2002). PoPMuSiC,rationally <strong>de</strong>signing point mutations in protein structures. Bioinformatics,18(12), 1701-1702.Lazaridis T. and M. Karplus (2000). Effective energy functions for proteinstructure prediction. Current Opinion in Structural Biology, 10, 139-145Lei F., M. Rotbøll and S. B. Jørgensen (2001). A biochemically structuredmo<strong>de</strong>l for Saccharomyces cerevisiae. Journal of Biotechnology, 88, 205-221.Lehninger A.L., D.L. Nelson and M. M. Cox (1993). Principles ofBiochemistry, 2nd edition, Worth publishers, New York.Lennox B., G.A. Montague, A.M. Frith, C. Gent and V. Bevan (2001).Industrial application of neural networks – an investigation. Journal of ProcessControl, 11(5), 497-507.Linko P. and Y. Zhu (1991).Neural network programming in bioprocessvariable estimation and state prediction. Journal of Biotechnology, 21, 3, 253-269


<strong>Bibliography</strong> 331Linko S., J. Luopa, Y.-H. Zhu (1997). Neural networks as software sensorsin enzyme production. Journal of Biotechnology, 52, 257-266.Linko S., Y-H. Zhu and P. Linko (1999). Applying neural networks assoftware sensors for enzyme engineering. TIBTECH, 17, 155-162.Liu Y.-C., F.-S; Wang and W;-C. Lee (2001). On-line monitoring andcontrolling system for fermentation processes. Biochemical EngineeringJournal, 7, 17-25.Ljung L. (1987). System i<strong>de</strong>ntification-theory for the user. Prentice-Hall,Englewood Cliffs.Ljung L. (2001). Black-box mo<strong>de</strong>ls from Input-output Measurements.Proceedings of IEEE Instrumentation and Measurements TechnologyConference, Budapest, Hungary.Lodish H., D. Baltimore, A. Berk, S L. Zipursky, P. Matsurdaira and J.Darnell (1995). Molecular cell Biology. 3rd edition, Scientific American Books,New York.Loose C., J.L. Klepeis and C.A. Floudas (2004). A new pairwise foldingpotential based on improved <strong>de</strong>coy generation and si<strong>de</strong>-chain packing. Proteins:Structure, function and Genetics, 54, 303-314.Lübbert A. and R. Simutis (1994). Using measurement data in bioprocessmo<strong>de</strong>lling and control. Trends in Biotechnology, 12 (8), 304-311Maier U., M. Losen and J. Büchs (2004). Advances in un<strong>de</strong>rstanding andmo<strong>de</strong>lling the gas-liquid mass transfer in shake flasks. Biochemical EngineeringJournal, 17, 155-167.Meltser M., M. Shoham and L.M. Manevitz (1996). ApproximatingFunctions by Neural Networks: A constructive solution in the uniform norm.Neural Networks, 9 (6), 965-978.Mishima K., N. Matsuo, A. Kawakami, N. Komorita, M. Nagatani and M.Ouchi (1996). Measurement and correlation of solubilities of oxygen in aqueoussolutions containing galactose and fructose. Fluid Phase Equilibria, 118, 221-226.Mishima K., N. Matsuo, A. Kawakami, T. Tokuyasu, S. Oka and M.Nagatani (1997). Measurement and correlation of solubilities of oxygen inaqueous solutions containing ribose and raffinose. Fluid Phase Equilibria, 134,277-283.


332 <strong>Bibliography</strong>Miyazawa, S. and L Jernigan (1994). Protein stability for single substitutionmutants and the extent of local compactness in the <strong>de</strong>natured state. Protein Eng.7, 1209–1220.Montague G. and J. Morris (1994). Neural-network contributions inbiotechnology. Trends in Biotechnology, 12, 312-324.Montesinos J.L., M.A. Gordillo, F. Valero, J. Lafuente, C. Sola and B.Valdman (1997). Improvement of lipase productivity in bioprocesses using astructured mathematical mo<strong>de</strong>l. Journal of Biotechnology, 52, 207-218.Moo-Young M. (éditeur) (1995). Comprehensive Biotechnology – ThePrinciples, Applications and Regulations of Biotechnology in Industry,Agriculture and Medicine (Vol. I: The principles of Biotechnology: ScientificFundamentals; Vol. II: The principles of Biotechnology: EngineeringConsi<strong>de</strong>rations).Mu Y., G. Wang and H Yu (2005). Kinetic mo<strong>de</strong>ling of batch hydrogenproduction process by mixed anaerobic cultures. Bioresource Technology, 97,1302-1307.Muñoz, V. and. Serrano (1994). Intrinsic secondary structure propensities ofthe amino acids, using statistical f-y matrices: comparison with experimentaldata. Proteins: Struct. Funct. Genet. 20, 301–311.Narang A., A. Konopka and D. Ramkrishna (1997). Dynamic analysis of thecybernetic mo<strong>de</strong>l for diauxic growth. Chemical Engineering Science, 52 (15),2567-2578.Nel<strong>de</strong>r J.A. and R. Mead (1965). A simplex method for functionminimization. Computer J., 7, 308-313.Norgaard M., O. Ravn, N. K. Poulsen and L. K. Hansen (2000). NeuralNetworks for Mo<strong>de</strong>lling and Control of Dynamic Systems: A Practionner’sHandbook. Springer, London.Oliveira R., J. Peres and S. Feyo <strong>de</strong> Azevedo (2004). Hybrid mo<strong>de</strong>lling offermentation processes using artificial neural networks: a study on i<strong>de</strong>ntificationand stability. Proceedings of the 9 th Symposium on Computer Applications inBiotechnology, Nancy (France).Oliveira R. (2004). Combining first principles mo<strong>de</strong>lling and artificial neuralnetworks: a general framework. Computers and Chemical Engineering, Vol. 28,5, 755-766.


<strong>Bibliography</strong> 333Oussar Y., I. Rivals, L. Personnaz and G. Dreyfus (1998). Training waveletnetworks for nonlinear dynamic input–output mo<strong>de</strong>lling. Neurocomputing, 20,(1-3), 173-188.Parthiban V., M.M. Gromiha and D. Schomburg (2006). CUPSAT:predictionof protein stability upon point mutations. Nucleic Acids Research, 34, W239-W242.Parthiban V. M.M. Gromiha, C. Hoppe and D. Schomburg (2007). Structuralanalysis and prediction of protein mutant stability using distance and torsionpotentials: role of secondary structure and solvent accessibility. Proteins, 66, 41-52.Perrier M., S.F. <strong>de</strong> Azevedo, E.C. Ferreira and D. Dochain (2000). Tuning ofobserver-based estimator: theory and application to the on-line estimation ofkinetic parameters. Control Engineering Practice, 8, 377-388.Pillardy J., C. Czaplewski, A Liwo, J. Lee, D.R. Ripoll, R. Kazmierkiewicz,S. Oldziej, W.J. We<strong>de</strong>meyer, K.D. Gibson, Y.A. Arnautova, J. Saun<strong>de</strong>rs, Y.J.Ye and H.A. Scheraga (2002). Recent improvements in prediction of proteinstructure by global optimization of a potential energy function. Proceedings ofthe National Aca<strong>de</strong>my of Sciences (USA), 98, 2329-2333.Psichogios D. C. and L. H. Ungar, (1992). A hybrid neural network-firstprinciples approach to process mo<strong>de</strong>lling. A.I.Ch.E Journal, Vol. 38, 10, 1499-1511.Provost A. and G. Bastin (2004). Dynamic metabolic mo<strong>de</strong>lling un<strong>de</strong>r thebalanced growth condition. Journal of Process Control, 14, 717-728.Rooman M.J. and S.J. Wodak (1995). Are database-<strong>de</strong>rived potentials validfor scoring both forward and inverted protein folding? Protein Engineering, 8,849-858.Ribes J., K. Keesman and H. Spanjers (2004). Mo<strong>de</strong>lling anaerobic biomassgrowth kinetics with a substrate threshold concentration. Water research, 38,4502-4510.Rose A.H. and J.S. Harrison (1995). The yeasts, London : Aca<strong>de</strong>mic Press,2 nd edition.Rose G.D., A.R. Geselowitz G.J. Lesser, R.H. Lee and M.H. Zehfus (1985).Hydrophobicity of amino acid residues in globular proteins. Science, 29, 834-838.


334 <strong>Bibliography</strong>Roux B. and T. Simonson (1995). Implicit solvent mo<strong>de</strong>ls. BiophysicalChemistry, 78, 1-20.Russ W.P. and R. Ranaganathan (2002). Knowledge-based potentialfunctions in protein <strong>de</strong>sign. Current Opinion in Structural Biology, 12, 447-452.Schubert J., R. Simutis, M. Dors, I. Havlik and A. Lübbert (1994). HybridMo<strong>de</strong>lling of Yeast Production Processes – combination of a priori knowledgeon different levels of sophistication. Chemical Engineering and Technology, 17,10-20.Schubert J., R. Simutis, M. Dors, I. Havlik and A. Lübbert (1994).Bioprocess optimization and control: Application of hybrid mo<strong>de</strong>lling. Journalof Biotechnology, 35, 51-68.Serrano L., J. T Jr Kellis, P Cann, A. Matouschek, and A. R. Fersht (1992).The folding of an enzyme. II. Substructure of barnase and the contribution ofdifferent interactions to protein stability. J. Mol. Biol. 224, 783–804.Shioya S., K. Shimizu and T. Yoshida (1999). REVIEW: Knowledge-BasedDesign and Operation of Bioprocess Systems. Journal of Bioscience andBioengineering, 87 (3), 261-266.Shortle D., W. E Stites and A. K. Meeker (1990). Contributions of the largehydrophobic amino acids to the stability of staphylococcal nuclease.Biochemistry, 29, 8033–8041.Sippl M. J. (1995). Knowledge-based potentials for proteins. Curr. Opin.Struct. Biol. 5, 229–235.Simon L. and M.N. Karim (2001). Probabilistic neural networks usingBayesian <strong>de</strong>cision strategies and a modified Gompertz mo<strong>de</strong>l for growth phaseclassification in the batch culture of Bacillus subtilis. Biochemical EngineeringJournal, 7, 41-48.Simutis R., Oliveira R., Manikowski M, Feyo <strong>de</strong> Azevedo S. and Lübbert A.(1997). How to increase the performance of mo<strong>de</strong>ls for process optimization andcontrol, Journal of Biotechnology, 59, 73-89Sjöberg J. and L. Ljung (1995). Overtraining, regularization, and searchingfor minimum with application to neural networks. International Journal ofControl, 62 (6), 1391-1407.


<strong>Bibliography</strong> 335Sjöberg J., Q. Zhang, L, Ljung, A. Benveniste, B. Delyon, P.-Y.Glorennec,H. Hjalmarsson and A. Juditsky (1995). Nonlinear Black-box Mo<strong>de</strong>lling inSystem I<strong>de</strong>ntification: a Unified Overview. Automatica, 31 (12), 1691-1724.Sonnleitner B. and O. Käppeli (1986). Growth of Saccharomyces cerevisiaeis controlled by its respiratory capacity: formulation and verification of ahypothesis. Biotechnology and Bioengineering, 28, 927-937.Specht D.F. (1990). Probabilistic neural networks. Neural Networks, 3, 109-118.Specht D.F. (1991). A General Regression Neural Network. Proceedings ofthe IEEE Transactions on Neural Networks, 2 (6), 568-576.Suykens J. A. K., J.P.L Van<strong>de</strong>walle and B.L.R. De Moor (1996). ArtificialNeural Networks for Mo<strong>de</strong>lling and Control of Non-Linear Systems. KluwerAca<strong>de</strong>mic Publishers.Suykens J.A.K. and J.P.L Van<strong>de</strong>walle (1998). Nonlinear mo<strong>de</strong>ling:advanced black-box techniques. Kluwer Aca<strong>de</strong>mic Publishers.Swarup K.S. and P.V. Simi (2006). Neural computation using discrete andcontinuous Hopfield networks for power system economic dispatch and unitcommitment. Neurocomputing, In Press, Corrected Proof, available online 2August 2006.Thompson M. and M. Kramer (1994). Mo<strong>de</strong>lling chemical processes usingprior knowledge and neural networks. AIChE J. ,40, 1328-1340.Tian Y., J. Zhang and J. Morris (2002). Optimal control of a fed-batchbioreactor based upon an augmented recurrent neural network mo<strong>de</strong>l.Neurocomputing, 48, 919-936Tidor B. and M. Karplus (1991). Simulation analysis of the stability mutantR96H of T4 lysozyme. Biochemistry, 30, 3217–3228.Tsuchiya H. M., Fredrickson A. G. and Aris R. (1966) Dynamics ofmicrobial cell populations, Adv. Chem. Eng., 6, 125-206.Tsuneda S., J. Auresenia, T. Morise and A. Hirata (2002). Dynamicmo<strong>de</strong>lling and simulation of a three-phase fluidized bed batch process forwastewater treatment. Process Biochemistry, 38, 599-604.


336 <strong>Bibliography</strong>Uchiyama K. and S. Shioya (1999). Mo<strong>de</strong>lling and optimization of amylaseproduction in a recombinant yeast fed-batch culture taking account of the cellcycle population distribution. Journal of Biotechnology, 71, 133-141.Van<strong>de</strong> Wouwer A., C. Renotte and Ph. Bogaerts (2004). Biological reactionmo<strong>de</strong>ling using radial basis function networks. Computers and ChemicalEngineering, 28, 2157-2164.van Gunsteren W. F. and A. E. Mark (1992). Prediction of the activity andstability effects of site-directed mutagenesis on a protein core. J. Mol. Biol. 227,389–395.Vanlaethem S., V. Hallouin and J. Castillo (2001). Suivi en ligne <strong>de</strong> laconsommatiob en oxygène (OUR: Oxygen Uptake Rate) par <strong>de</strong>s cultures <strong>de</strong>cellules animales. Proceedings of the « 8 e Congrès francophone <strong>de</strong> Génie <strong>de</strong>sProcédés », 17-19 octobre 2001, Nancy.Van Impe J.F. and G. Bastin (1995). Optimal adaptive control of fed-batchfermentation processes. Control Eng. Practice, vol. 3, n°7, 939-954.Van Stroe-Bienen S.A.M., A.P.M. Janssen and L.J.J. Janssen (1993).Solubility of oxygen in glucose solutions. Analytica Chimica Acta, 280,217-222.Votruba J., B. Volesky and L. Yerushalmi (1985). Mathematical mo<strong>de</strong>l ofbatch acetones-butanol fermentation. Biotechnology Bioengineering, 28, 247-255.Walter E. and L. Pronzato (1997). I<strong>de</strong>ntification of parametric mo<strong>de</strong>ls fromexperimental data. London, Springer.Warnes M.R., J. Glassey, G.A. Montague and B. Kara (1996). On Data-Based Mo<strong>de</strong>lling Techniques for Fermentation Processes. Process Biochemistry,31 (2), 147-155.Warnes M. R., Glassey J., Montague G. A., Kara B. (1998). Application ofradial basis function and feedforward artificial neural network to the Escherichiacoli fermentation process. Neurocomputing, 20, 67-82.Zaid A., H.G. Hughes, E. Porceddu and F. Nicholas (1999). Glossary ofBiotechnology and Genetic Engineering. Food and Agricultures Organization ofthe United Nations (FAO).Zinn M., B. Witholt and T. Egli (2004). Dual nutrient limited growth:mo<strong>de</strong>ls, experimental observations, and applications. Journal of Biotechnology,113, 263-279.


<strong>Bibliography</strong> 337Zorzetto L.F.M., R. Maciel Filho, and M.R. Wolf-Maciel (2000). Processmo<strong>de</strong>lling <strong>de</strong>velopment through artificial neural networks and hybrid mo<strong>de</strong>ls.Computers and Chemical Engineering, 24, 1355-1360.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!