The MBC information booklet - RMIT University

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$journal of latex class files, vol. 6, no. 1, january ... - RMIT University$

Chapter 4: Bioinformatics 4.2.2 MATH1300— Analysis of Medical Data 4.2.3 BIOL2034— Bioinformatics 4.2.4 COSC2151— Introduction to Computational Biology 22 Course Description This course aims to deliver postgraduate researchers the skills needed to analyse data specifically in a medical context. It covers both statistical and epidemiological techniques using a computer based approached, with all methods described from their foundation. Pre-requisite Courses and Assumed Knowledge and Capabilities This course assumes that the students have: • Basic IT skills including web browsing, e-mail, Windows based program usage, and the ability to use a word-processor for report writing • Fundamental mathematical skills to a graduate high-school standard • A basic knowledge of medical terminology For more information on the course, go to www.rmit.edu.au/courses2006/029566. Note: This course is offered by the School of Applied Sciences. Course Description Bioinformatics is the computational management and use of biological information to solve biological problems. This course will deliver descriptions of this rapidly evolving field, and facilitate user access to and manipulation of the biological data. Topics will include descriptions of genetic and biological databases and relevant tools available to retrieve and analyse the information within these. Descriptions of various techniques, such as evolutionary analysis, data mining, protein structure/function and computational drug discovery will be given. RMIT staff and external scientists working in the field will deliver topics. This course is designed to enable students to evaluate data using bioinformatics, and to better identify potential uses and opportunities of this data within their industry context. Students will gain an appreciation of the potential of new technologies to their industry sector. Pre-requisite Courses and Assumed Knowledge and Capabilities • BIOL2184 Advanced Molecular Biology (or equivalent) For more information on the course, go to www.rmit.edu.au/courses2006/028321. Aim As the rate of acquisition of biological data increases exponentially, the management, interrogation and manipulation of this data becomes a complex process that requires novel software solutions. These solutions are the driving force behing Computational Biology, lying at the intersection between the biological and IT fields. There is a requirement for methodology to facilitate the acqusition, storage and retrieval of data, the analysis of this data and computationally complex tasks such as the prediction of macromolecular structure. This course will introduce these concepts and demonstrate some of the computational techniques currently available. Objectives The objectives of this course are as follows: • Introduce the aims and uses of computational biology. • Describe the sources of data, in particular from the characterisation of genomes and proteomes. • Describe how biological information is stored and accurately retrieved. • Introduce computational algorithms that can be used for querying and manipulating biological data. • Study some of the practical uses of these algorithms. Prerequisites • COSC1321 Computing Fundamentals Syllabus • Genomics, proteomics and bioinformatics. - Introduction to the biological revolution. Data acquisition and storage. Databases- format and querying. The challenges in Computational Biology.
Chapter 4: Bioinformatics • Computational Biology Algorithms I. - Dynamic programming and molecular dynamics. • Computational Biology Algorithms II. - Sequence alignment algorithms. • Practical uses of computational algorithms. - DNA and protein alignment. Finding homologs, evolutionary analysis. Protein folding, predicition of protein structure/function. Future directions. 23
Page 3 and 4: INFORMATION BOOKLET For Local and I
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