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Core/Elective: Elective Semester: 4 Credits: 4
Course Description

This course introduces the study of computational problems in molecular biology. It introduces molecular biology concepts and methodologies for analyzing these data. The course is intended to cover the main aspects which are useful in studying, describing and modeling of Big data problems in the context of molecular biology.

Course Objectives

To understand computational problems in molecular biology
To study molecular structure prediction
To understand the models of DNA mapping and pathways

Course Content

Module I
Molecular Biology and Bioinformatics: Introduction to molecular biology- Nucleic acids-DNA-RNAProteins-Gene-Genome-Genetic synthesis-Translation-Transcription-Protein synthesis-Chromosomes-Maps and sequences-Human genome project.

Module II
Sequence alignment and database search: Pair-wise sequence alignment- Substitution matrixes -PAM and BLOSSUM matrices, Dot plots - Local and global alignment theory - Dynamic programming methods -FASTA and BLAST algorithms - database search using BLAST and FASTA - Similarity & distance -Similarity scores - Weight matrices - Heuristic method - Hidden Markov Models and their application in sequence analysis

Module III
Phylogenetic trees: Introduction -Dendrogram construction / Molecular Phylogenetics / Tree definitions / Optimality criteria / Distance matrix methods and maximum parsimony / Multiple sequence alignments- tree alignments, star alignments, pattern in pair wise alignment / Genetic algorithm

Module IV
DNA Micro-arrays and Gene Expression- Gene profiling- DNA Microarray technology- Gene regulatory network- Heuristic Algorithms for GRN- S-system model – Computational methods for pathways and system biology- metabolic pathways- genetic pathways- signaling pathways

Module V
Molecular Structure Prediction- RNA secondary structure prediction-Protein Folding problems-Protein threading- Protein structure analysis.


1. Zhumar Ghosh and Bibekanand Mallick. Bioinformatics: Principles and Applications., Oxford University Press; 1 edition , March 1, 2015
2. An introduction to Bioinformatics Algorithms 4th Ed: Neil James and Pavel A Pevzner, OUPress, 2014
3. Bioinformatics : Principles and Applications: Zhumur Ghosh, Bibekanand Mallick: OUPress. 2015
4. Building Bioinformatics Solutions: Concord Bessant, Darren Oakley, Ian Shadforth : OU press, 2014
5. Rastogi, S. C., Parag Rastogi, and Namita Mendiratta. Bioinformatics Methods and Applications: Genomics Proteomics and Drug Discovery 4th Ed. PHI Learning Pvt. Ltd., 2013.

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