Syllabus

Module 1: Storing Biological Data (10 Contact Hours)
DNA Sequencing, Protein Sequencing, Genomic Sequencing, Submission of sequences to databases, sequence accuracy, Storing biological data in databases, Flat files Formats, GenBank DNA sequence entry, EMB library, FASTA, SwissProt etc.
Module 2: Dynammic Programming (7 Contact Hours)
Longest Common Subsequence, Needleman-Wunsch, Smith-Waterman, Hirschberg, Nussinov
Module 3: Phylogenetic Analysis and Clustering (7 Contact Hours)
Parsimony based methods: Fitch and Sankoff Distance based methods: UPGMA, Neighbour Joining, Boostrap K-means clustering Markov Clustering
Module 4: Biological Networks Reconstruction (6 Contact Hours)
Basics of biological network reconstruction, Wagner Algorithm and Gillespe Algorithm
Module 5: Protein Classification and Structure Prediction (6 Contact Hours)
Protein structure, classification, structure databases, structure alignment, structure modeling and prediction

To understand and learn about principles that govern the engines of majority of bioinformatics tools and softwares.

1. Students will be able to learn about the principles of collection and storage of biological data 2. Students will be able to understand and interpret various bioinformatics flat files. 3. Students will be able to understand the core algorithms of various bioinformatics tools 4. Students will be able synthesize a workflow for nucleotide sequence analysis and protein structure prediction.

Pevsner J, Bioinformatics and Functional Genomics, Wiley-Blackwell, USA , ISBN: 978-81-265-3834-8

Lesk AM, Introduction to Bioinformatics, Oxford University Press

Mount DW, Bioinformatics: Sequence and Genome Analysis, Cold Spring Harbor Laboratory Press

Attwood T and Parry-Smith D, Introduction to Bioinformatics, Prentice Hall