Bioinformatics Centre and ARIS Cell

Madras Veterinary College, Chennai-600007

Education

M.Sc. BIOINFORMATICS

Bioinformatics is a new emerging discipline that has emerged from the requirements to elucidate the biologically useful information. The focus of bioinformatics is dealing with the flood of information, coming from academic, industry and government labs and turning it into useful knowledge.

The aim of the course is to provide students with high quality Post Graduate Education in Bioinformatics, which meets the needs of Biotechnology, Genetics, Biochemistry, Microbiology and Pharmaceutical industries for Research and Development

Prospectus for Postgraduate

  • Qualification/Eligibility
  • Course Duration
  • Course Fee
  • Course Content
  • Syllabus
Qualification/Eligibility

Graduates with a minimum qualification of B.F.Sc., M.B.B.S., B.D.S., B.Sc.(Agriculture), B.Sc.(Horticulture), B.Sc (Forestry), B.Sc. degree in Biophysics / Botany / Zoology / Biology / Genetics / Biochemistry / Physics / Chemistry / Biotechnology / Bioinformatics / Microbiology / Life Sciences or equivalent of Indian or foreign university.

Course Duration

The duration of the course is two years comprising of four semesters

Course Fee
Semester Fee * (Rs.)
First : 18,025.00
Second : 15,300.00
Third : 16,200.00
Fourth : 15,300.00
Course content
Sl. No. Subject Code   Subject   Credit   Semester   Type
1  *BIF601   Introduction to Bioinformatics 2+1 I Major
2   BIF613   Biomolecular Sequence Analysis 1+1 Major
3   BIF606   Concepts in computing 2+2 Major
4   BIF608   Basic Molecular Biology 3+0 Minor
5 **BIF610   Genetics and Immunology 3+0 Minor
6   BIF605   Statistics for Bioinformatics 2+1 Minor
7   BIF609   Mathematics for Bioinformatics 2+0 Minor
8   BIF619   Master Seminar 1+0 Major

Total credit 21(16+5)  |  Major 8, Minor 13

Sl. No. Subject Code   Subject   Credit   Semester   Type
1  *BIF603   Techniques in Bioinformatics 0+2 II Major
2   BIF611   Introduction to Database System 2+1 Major
3   BIF617   Comparative and Functional Genomics 2+1 Major
4   BIF615   Biological Databanks and Data Mining 1+2 Major
5   BIF604   Biological Chemistry 3+0 Minor
6   BIF607   Programming languages for Bioinformatics 2+2 Minor

Total credit 18(10+8)  |  Major 11, Minor 7

Sl. No. Subject Code   Subject   Credit   Semester   Type
1  *BIF602   Advanced Bioinformatics 2+1 III Major
2   BIF614   Dynamic web design 1+2 Minor
3   BIF618   Pharmacogenomcis and IPR 2+1 Major
4   BIF616   Molecular Modelling andDrug Design 2+2 Major
5   BIF612   Computattional and System Biology 2+2 Major

Total credit 17 (9+8)  |  Major 14, Minor 3


IV semester

Project 0+12

Syllabus

Objective

To impart an introductory knowledge about the subject of Bioinformatics to the students studying any discipline of science.

Theory

UNIT-I

Introduction, biological database – primary, secondary and structural, Protein and Gene Information Resources- PIR, SWISSPROT, PDB, genebank, DDBJ. Specialized genomic resources.

UNIT-II

DNA sequence analysis, cDNA libraries and EST, ESTanalysis, pairwise alignment techniques, database searching, multiple sequence alignment.

UNIT-III

Secondary database searching, building search protocol, computer aided drug design – basic principles, docking, QSAR.

UNIT-IV

Analysis packages – commercial databases and packages, GPL software for Bioinformatics, web-based analysis tools.

Practical

  • Usage of NCBI resources
  • Retrieval of sequences/ structure from databases
  • Visualization of structures
  • Docking of ligand receptors
  • BLAST exercises.

Suggested Readings

Attwood TK & Parry-Smith DJ.2003. Introduction to Bioinformatics. Pearson Education. Rastogi SC, Mendiratta N & Rastogi P. 2004. Bioinformatics: Concepts, Skills and Applications. CBS.

Objective

To understand the usage of advanced techniques in Bioinformatics.

Theory

UNIT-I

Biological databases, database hierarchies, sequence and structure databases. Pairwise sequence alignment and database similarity searching: global and local alignments, matrices, gap penalties and statistical significance.

UNIT-II

Multiple sequence alignment and phylogenetic analysis, Microarray technology: applications,analysis of data, clustering analysis. Pharmacogenomics: introduction, applications, Genome for medicine, current and future perspectives.

UNIT-III

System modeling and metabolomics – concepts and principles. Nutrigenomics: system biology in nutrition and health arena.

UNIT-IV

Genome annotation, EST clustering, protein modeling and design.

Practical

  • Development of small database
  • Phylogenetic analysis
  • Microarray data analysis (sample data from open sources).
  • Other practical exercise based on above topics.

Suggested Readings

Baxevanis AD & Ouellettee BFF. 2001. Bioinformatics: a Practical Guide to the Analysis of Genes and Proteins. Wiley Interscience.
Mount DW Cold. 2001. Bioinformatics : Sequences and Genome Analysis. Spring Harbor Stekel D.2003. Microarray Bioinformatics. Cambridge University Press.
Tomita M & Nishioka T.2005. Metabolomics: The Frontier of Systems Biology. Springer Verlag Wong SHY.2006. Pharmacogenomics and Proteomics: Enabling the Practice of Personalized Medicine. American Association for Clinical Chemistry.

Objective

To explore the usage of various Open source software for Bioinformatics applications.

Theory

UNIT-I

Gene Information Recources: GenBank, EMBL, Protien Information Resources: Swiss-Prot, BLOCKS, Gene Prediction Tools: GENSCAN, GRAIL

UNIT-II

Structural Databases: PDB, CSD, RELIBASE, REBASE, File Format Converter Tools: BABEL, Read Seq, NCBI Resources

UNIT-III

Visualization tools – RasMol, QMol, Swiss PDB, Pymol, Modelling Tools: MODELLER, SwissPDB, Geno3D, Docking Tools: Chimera, Dock, AutoDock, GRAMM, Hex, Argus Lab.

UNIT-IV

Protromics Tools: EXPASY, CDART, 3D-Structure Optimization Tools, Sequence Analysis Tools: BLAST, FASTA, EMBOSS, TCOFFEE, Phylogenetic Analysis Tools: Phylip, NTSYS, CLUSTALW/ CLUSTALX, BIOEDIT.

Suggested Readings

Software Manuals and Help files

Objective

This is intended to prepare the non-biology students for basic concepts of biological structures and functions as well as recapitulate the knowledge of biology students.

Theory

UNIT-I

The molecular logic of living organisms; Cells and composition of living matter; Carbohydrates: monosaccharides, oligosaccharides, polysaccharides, proteoglycans and glycoproteins; Lipids:fatty acids, acylglycerols, phospholipids, sphingolipids, cholesterol and membranes.

UNIT-II

Structure and function of proteins and nucleic acids; Enzymes: details of enzyme nomenclature and classification; units of enzyme activity; coenzymes and metal cofactors; temperature and pH effects; Michaelis- Menten kinetics; Inhibitiors and activators; active site and catalytic mechanisms; covalent and noncovalent regulations; isoenzymes.

UNIT-III

Organization of metabolic system: enzyme chains, multienzyme complexes and multifunctional enzymes; anaplerotic sequences and amphibolic pathways; pacemaker enzymes and feedback control of metabolic pathways; shuttle pathways; energy charge.

UNIT-IV

Oxidation of glucose in cells: high energy bond, glycolysis, citric acid cycle and oxidative phosphorylation, metabolism of lipids, proteins and nucleic acids, signal transduction.

Suggested Readings

Geoffrey LZ, Michael Gregory E & Sitz T. 1997. Biochemistry. McGraw-Hill.
Nelson DL, Cox MM & Ocorr MOK. 2005. Lehninger’s Biochemistry. WH Freeman & Co Voet D & Voet JG. 1997. Biochemistry. John Wiley & Sons.

Objective

To understand the basic principles of statistics and mathematics and their applications in relation to Biological system.

Theory

UNIT-I

Introduction to Statistical bioinformatics, Principles of sampling from a population; Random sampling.

UNIT-II

Frequency distributions: Graphical representations and Descriptive measures; Standard Probability Distributions; Correlation and regression analysis.

UNIT-III

Hypothesis testing; Markov Models, Cluster Analysis: Hierarchical and Non-Hierarchical methods.

UNIT-IV

Phylogenetic Analysis Tools: Maximum Likelihood, Parsimony methods.

Practical

  • Computational exercises on Random Sampling
  • Construction and representation of frequency distributions
  • Descriptive measures
  • Probability distribution

Suggested Readings

Gupta SC & Kapoor VK. 2000. Fundamentals of Mathematical Statistics: A Modern Approach. S. Chand & Co.
Warren JE & Gregory RG.2005. Statistical Methods in Bioinformatics. Springer.

Objective

The Objective of this course is to introduce the basic concepts of computing with introduction to OS, graphics, networking and client-server technologies.

Theory

UNIT-I

Fundamentals of computing; Introduction to Operating Systems: WINDOWS, UNIX/Linux operating systems; Computer Security (hacking, cracking), Computer Viruses.

UNIT-II

Compuer Graphics : Visualization techniques- Software and Hardware, Interactive Graphics; Viewing in three dimension; Raster algorithms; Rendering; Animation; Image Processing with emphasis on biological systems.

UNIT-III

Computer Networking, Security of the network, Fire-walls, Network Goals, Applications Network, Network architecture, Hierarchical networks, Ethernet and TCP / IP family of protocols.

UNIT-IV

Use of INTERNET and WWW, Internet services.

Practical

  • MS – Windows
  • Linux, UNIX
  • Network design
  • Internet search
  • Graphics and animation

Suggested Readings

David FR. 1997. Procedural Elements for Computer Graphics. WCB / Mc Graw-Hill.
Foley JD & Van Dam A. 1982. Fundamentals of Interactive Computer Graphics. Addison-Wesley.
James FK & Keith WR.2006. Computer Networking: A Top- Down Approach Featuring the Internet. Prentice Hall.
Siever E.2005. Linux in a Nutshell. O’ Reilly.

Objective

Programming is a very significant area for bioinformatics and this course gives an understanding for logics of programming and command- line and graphical GDIs.

Theory

UNIT-I

Programming in C: Pointers, Pointers to functions, macro programming in C, graphs, data structure linked list, stack, queue, binary trees, threaded binary trees.

UNIT-II

File and exception handling in C, Programming in Visual Basic: Introduction to Application Development using Visual Basic; Working with Code and Forms.

UNIT-III

Variables, Procedures and Controlling Program Executor; Standard Controls; Data Access Using Data Control; Connecting to Database using VB.

UNIT-IV

Introduction to JAVA, variables, constants, control structures, input output, classes. Jar and Java applets.

Practical

  • Programming in C and Visual basic with special reference to database linking
  • Small Java applets

Suggested Readings

Brian WK & Ritchie DM.1988. C Programming Language. Prentice Hall. Kanetkar. 2002. Let us C. BPB Publications.
Microsoft Developers Network (MSDN Digital Library ). 2006. Microsoft.

Objective

To understand the basic concepts of molecular biology in order to relate to the structure and functions of biomolecules and to have an insight of chemical aspects of life.

Theory

UNIT-I

Nucleic acids as hereditary material, Genome organization in prokaryotes and eukaryotes..

UNIT-II

DNA replication, semi-conservative model, mechanism of replication in E.coli, differences in pro- and eukaryotic DNA replication.

UNIT-III

Reverse transcription, Transcription in pro- and eukaryotes, post-transcriptional changes; Ribozymes, antisense RNA, micro-RNAs.

UNIT-IV

Genetic code and translation; differences in translation process in pro-and eukaryotes; Gene regulation in prokaryotes and eukaryotes.

Suggested Readings

Gupta PK. 2003. Cell and Molecular Biology. 2nd Ed. Rastogi Publications.
Lodish H. 2003. Molecular cell Biology. 5th Ed. W.H. Freeman & Co.
Zhang MQ &Jiang T. 2002. Current Topics in Computational Molecular Biology. MIT Press.

Objective

To understand and apply fundamental concepts of mathematics as applicable in Biology and to acquaint about theoretical concepts of algebra and geometry and numerical methods.

Theory

UNIT-I

Coordinate geometry with basic concepts of 2D and 3D geometry, Vector algebra – Addition and subtraction of vectors, Dot and cross product, Scalar triple product.

UNIT-II

Matix algebra: basic definitions, matrix operations, transpose of a matrix, inverse of matrix , eigen values, Boolean algebra. Geometric and Arithmetic Progression.

UNIT-III

Solution of equation by bisection method, Iteration method, Newton Raphson method, numerical differentiation.

UNIT-IV

Numerical integration- Trapezoidal rule, Simpson's 1/3 and 3/8 rules, Runga Kutta method of nth order. Fast Fourier transformation.

Suggested Readings

Babu CA & Seshan CR. 2006. New Engineering Mathematics. Narosa Publishing House.
Datta KB. 2002. Matrix and Linear Algebra. Prentice Hall.
Narayan S. 1980. Matrix Algebra. S Chand & Co.
Rao S. 2006. Numerical Methods for Scientists and Engineers. Prentice Hall.

Objective

To learn the basic concepts of genetics and immunology.

Theory

UNIT-I

Genetics- Science of genetics – objectives, terminologies methods; Mendelian principles of inheritance, sex linked inheritance; Concept of linkage maps and recombination; Mutations – molecular, gene/point and chromosomal.

UNIT-II

Phenotype and genotype relationships, role of environment, from gene to phenotype, gene Interactions. Study of quantitative traits. Genetics of populations, genetics and evolution. Genetics and diseases.

UNIT-III

Immunology – Overview of immune system, innate and acquired immune system; Structure and function of antibody molecule and TCR; Genetics of antibody diversity; MHC I and II, Polymorphism; Characteristics of B cell and T cell antigens; MHC Peptide interaction; Affinity maturation.

UNIT-IV

Autoimmunity and molecular mimicry; Ligand – receptor interaction in the light of protein structure in immune system; Use of bioinformatics in immunology and vaccine development.

Suggested Readings

Johnson RL. 2006. Genetics. Twenty-first Century Books.
Male D. 2003. Immunology. Open University Worldwide.
Stansfield WD. 2002. Genetics. McGraw-Hill.

Objective

To familiarize the concept of RDBMS and to apply the database techniques to biological databanks.

Theory

UNIT-I

Data Abstraction; Data Models; Instances and Schemes; E-R Model Entity and entity sets; Relations and relationship sets; E-R diagrams; Reducing E-R Diagrams to tables; Network Data Model: Basic concepts; Hierarchical Data Model: Basic concepts.

UNIT-II

Multimedia Databases – Basic concepts and Applications; Indexing and Hashing; Basic concepts (ISAM, B+ Tree indexed files, B Tree indexed files, Static Hash functions, Dynamic Hash functions); Text Databases; Introduction to Distributed Database Processing, Data Security.

UNIT-III

MySQL/MS – Access – Select Statements; Data Definition Statements; Data Manipulation Statements; Data Control Statements; Other Database Objects (Views, Sequences, Synonyms); Introduction to Application Development using Visual Basic;Working with Code and Forms; Variables.

UNIT-IV

Procedures and Controlling Program Executor; Standard Controls; Data Access Using Data Control; Connecting to Oracle Database using Visual Basic.

Practical

  • Practical exercise using MySQL
  • Design of database in MS-Access and MySQL.
  • Database linking.

Suggested Readings

Date CJ. 1986. Introduction to Database Systems. Addison-Wesley.
Korth H & Silberschatz A. 2002. Database System Concepts. McGraw-Hill.
Martin D. 1986. Advanced Database Techniques. MIT Press.

Objective

To understand the computational aspects of structural biology; to familiarize the usage of software for 3D structures of nucleic acids and proteins and to translate the sequence to protein structure.

Theory

UNIT-I

Methods of single crystal X-ray Diffraction of macromolecules, NMR of macromolecules Anatomy of Proteins – Ramachandran plot, Secondary structures, Motifs, Domains, Tertiary and quaternary structures.

UNIT-II

Anotomy of DNA: A, B, Z DNA, DNA bending etc.; RNA structure; Structure of Ribosome; Principles of Protein Folding; Structural data banks – Protein Data Banks, Cambridge small molecular crystal structure data bank.

UNIT-III

Method for Prediction of Secondary and Tertiary structures of Proteins, DNA, RNA, Fold recognition, Ab initio methods for structure prediction; Homology modeling, Methods for comparison of 3D structures of proteins.

UNIT-IV

Molecular interactions of Protein - Protein with special reference to single transduction and antigen- antibody interaction, Protein – DNA, Protein – carbohydrate, DNA – small molecules. System modeling and metabolomics – concepts and Principles.

Practical

  • Usage of softwares for above topics
  • Molecular Visualization tools: RasMol, QMol, Swiss PDB, Pymol
  • Biomolecular Interaction Databases: BIND, DIP
  • 4. Structure Similarity Search Tools: CN3D, Vast Search

Suggested Readings

Fall CP. 2002. Computational Cell Biology. Springer.
Tsai CS. 2003. Computational Biochemistry. John Wiley & Sons.
Waterman MS. 1995. Introduction to Computational Biology: Maps, Sequences and Genomes. CRC Press.

Objective

To understand the local and multiple alignment concepts and to carry out multiple sequence alignment.

Theory

UNIT-I

Analysis of protein and nucleic acid sequences, multiple alignment programs.

UNIT-II

Development of programs for analysis of nucleic acid sequences, Use of EMBOSS package.

UNIT-III

Phylogenetic analysis – Elements of phylogenetic models, tree interpretation, tree data analysis, alignment – building data model.

UNIT-IV

Extraction of phylogenetics data sets, Distance and character based methods.

Practical

  • EMBOSS
  • File Format Converter Tools: BABEL, ReadSeq
  • Phylogenetic Analysis Tools: Phylip, NTSYS, PAUP
  • CLUSTALW/CLUSTALX.

Suggested Readings

Baxevanis AD & Ouellettee BFF. 2001. Bioinformatics: a Practical Guide to the Analysis of Genes and Proteins. Wiley Interscience.
Mount DW. 2001. Bioinformatics: Sequence and Genome Analysis. Spring Harbor, CSHL Press.
Nei M & Kumar S. 2000. Molecular Evolution and Phylogenetics. Oxford University Press.
Salemi M & Vandamme AM. 2003. The Phylogenetics Handbook – A Practical Approach to DNA and Protien Phylogeny. Oxford University Press.

Objective

This course teaches the basic principles and application of various technologies used in creation of dynamic web content.

Theory

UNIT-I

PERL: Strings, Numbers, and Variables. Variable Interpolation, Basic Input and Output, File handles, Making Decisions, Conditional Blocks, Loops, Combining Loops with Input, Standard Input and Output, Finding the Length of a Sequence File

UNIT-II

Pattern Matching, Extracting Patterns, Arrays, Arrays and Lists, Split and Join, Hashes, A Real – World Example, BioPERL; Applications.

UNIT-III

Creation, hosting and maintenance of web-site using HTML, XML, ASP, JSP.

UNIT-IV

Creation, hosting and maintenance of web-site PHP, PERL and CGI.

Practical

  • EMBOSS
  • Creation of Web-based applications, interactive and dynamic web-pages
  • Connecting databases using CGI scripting
  • Creation and maintenance of web-sites using HTML, XML, ASP, PHP, PERL and CGI
  • Retrieval of specific information from web-sites using CGI scripts.

Suggested Readings

Moorhouse M & Barry P. 2004. Bioinformatics, Biocomputing and Perl: An Introduction to Bioinformatics. John Wiley & Sons.
Tisdall JD. 2001. Beginning Perl for Bioinformatics. O' Reilly.

Objective

To understand the biological databases – types and formats and to learn the retrieval, deposition and analysis of sequences and structures from biological databanks.

Theory

UNIT-I

Data warehousing, data capture, data analysis; Introduction to Nucleic Acid and Protein Data Banks; Nucleic acid sequence data banks: Genbank, EMBL nucleotide sequence data bank.

UNIT-II

AIDS Virus sequence data bank, rRNA data bank, Protein sequence data banks: NBRF-PIR, SWISSPROT, Signal peptide data bank; Database Similarity Searches.

UNIT-III

BLAST, FASTA, PSI-BLAST algorithms; pair wise sequence alignment NEEDLEMAN and Wunsch, Smith Waterman algorithms; Multiple sequence alignments – CLUSTAL, Patterns, motifs and Profiles in sequences.

UNIT-IV

Derivation and searching; Derived Databases of patterns, motifs and profiles: Prosite, Blocks, Prints-S, Pfam, etc.; Primer Design.

Practical

  • Gene Information Resources
  • Protein Information Resources
  • Structural databases
  • Sequence Analysis and database similarity Search Tools: BLAST, PHI-BLAST, PSI-BLAST, FASTA, EMBOSS, CLUSTAL, TCOFFEE
  • Use of similarity, homology and alignment tools.

Suggested Readings

Letovsky S. (ED). 1999. Bioinformatics: Databases and Systems. Kluwer.
LeUn D & Markel S. 2003. Sequence Analysis in a Nutshell: A Guide to common Tools and databases.
O'Reilly.
NCBI (www.ncbi.nlm.nih.gov). PUBMED (www.pubmedcentral.nih.gov) and database web-sites.

Objective

To understand the modeling of small molecules; to understand the computational chemistry principles and to familiarize the role of computers in drug-discovery process.

Theory

UNIT-I

Concepts of Molecular Modeling, Molecular structure and internal energy, Application of molecular graphics.

UNIT-II

Energy minimization of small molecular, Use of Force Fields and MM methods, Local and global energy minima. Techniques in MD and Monte Carlo. Simulation for conformational analysis, Ab initio, DFT and semi-empirical methods.

UNIT-III

Design of ligands, Drug-receptor interactions, Classical SAR/QSAR, Docking of Molecules

UNIT-IV

Role of computers in chemical research; Structure representation, SMILES; Chemical Databases, 2D and 3D structures, reaction databases, search techniques, similarity searches; Chemo informatics tools for drug discovery.

Practical

  • Modeling Tools: MODELLER, Geno3D
  • Docking Tools: Chimera, Dock, MOE, Auto Dock Tools, GRAMM, Hex, Argus Lab
  • 3D-Structure Optimization Tools: CHEMSKETCH, CHEM 3D, ISIS Draw, CHEMDRAW

Suggested Readings

Bunin BA. 2006. Chemoinformatics: Theory, Practice and Products. Springer.
Gasteiger J &Engel T. 2003. Chemoinformatics: A Textbook. Wiley-VCH.
Hinchliffe A. 2003. Molecular Modelling for Beginners. John Wiley & sons.
Leach AR. 1996. Molecular Modelling: Principles and Applications. Longman.

Objective

To understand the genomic and proteomic concepts and to learn the usage of various algorithms and programmes in analysis of genomic and proteomic data.

Theory

UNIT-I

A brief account of recombinant DNA technology, PCR and molecular marker techniques. Genomics – Whole genome analysis, Comparative and functional genomics.

UNIT-II

Pathway analysis, Repeat analysis, Human genetic disorders, Candidate gene identification, Linkage analysis, Genotyping analysis.

UNIT-III

Concepts of Pharmacogenomics Proteomics – Introduction to basic Proteomics technology, Bioinformatics in Proteomics, Gene to Protein Function: a Roundtrip.

UNIT-IV

Analysis of Proteomes, Analysis of 2-D gels, Protein to Disease and vice versa, Human Genome and science after Genome era. SAGE.

Practical

  • Gene Prediction Tools: GENSCAN, GRAIL, FGENESH
  • NCBI Genomic Resources
  • Proteomics tools: EXPASY, CDART

Suggested Readings

Azuaje F & Dopazo J. 2005. Data Analysis and Visualization in Genomics and Proteomics. John Wiley &Sons.
Jolles P & Jornvall H. 2000. Proteomics in Functional Genomics: Protein Structure Analysis. Birkhauser.

Objective

To understand the translation of Bioinformatics into commercial gains; to familiarize the concepts of microarray – data acquisition and analysis and learn the IPR issues in Biological science with special emphasis on bioinformatics.

Theory

UNIT-I

Bioinformatics companies, Genomes, transcriptomes and proteomes – their applications in medicine and agriculture, disease monitoring, profile for therapeutic molecular targeting.

UNIT-II

Diagnostic drug discovery and genomics. Pharmacogenomics and its application. SNPs and their applications. Microarray and genome wide expression analysis: Introduction to basic microarray technology, Bioinformatics in microarrays, Getting started – target selection.

UNIT-III

Customised microarray design, Image processing and quantification, Normalization and filtering, Exploratory statistical analysis, Public Microarray data resources.

UNIT-IV

Patenting and data generation from patent literature for commercial benefits. IPR and bioinformatics. Bioinformatics patents.

Practical

  • Microarray Analysis Tools: MAGIC Tool
  • Stanford Microarray Database
  • Gene Expression Omnibus
  • Creation of an On-line company.

Suggested Readings

Blalock EM. 2003. A Beginner's Guide to Microarrays. Springer.
Catania M. 2006. An A-Z Guide to Pharmacogenomics. American Association for Clinical Chemistry.
Chakraborty C &Bhattachary A. 2005. Pharmacogenomics. Biotech Books.
Stekel D. 2003. Microarray Bioinformatics. Cambridge University Press.