MTech Essential Bioinformatics syllabus for 1 Sem 2020 scheme 20BBI13

Biological Databases:

Introduction to Bioinformatics, Goals, Scope, Applications in biological science and medicine and Limitations, a) Sequence Databases b) Structure Databases c) Special Databases and applications: Genome, Microarray, Metabolic pathway, motif, multiple sequence alignment and domain databases. Mapping databases – genome wide maps. Chromosome specific human maps. Applications of these databases. Database Similarity Searching: Unique Requirements of Database Searching. Heuristic Database searching, Basic Local Alignment Search Tool (BLAST), FASTA, Comparison of FASTA and BLAST, Database Searching with the Smith– Waterman Method.

Sequence Alignment:

Evolutionary basis, Homology vs Similarity, Similarity vs Identity. Types of Sequence alignment - Pairwise and Multiple sequence alignment, Alignment algorithms, Scoring matrices, Statistical significance of sequence alignment. Multiple Sequence Alignment: Scoring function, Exhaustive algorithms, Heuristic algorithms, Practical issues. Profiles and Hidden Markov Models: Position-Specific scoring matrices, Profiles, Markov Model and Hidden Markov Model.

Motifs and Domains:

Motif and Domain databases, Identification of Motifs and Domains in Multiple Sequence Alignment using Regular expressions, Motif and Domain Databases statistical models, Protein Family databases, Motif Discovery in unaligned sequences. Sequence logos. Gene and Promoter Prediction: Promoter and Regulatory elements in Prokaryotes and Eukaryotes. Promoter and Regulatory element prediction – algorithms. Gene prediction. Gene prediction in Prokaryotes and Eukaryotes. Categories of Gene Prediction Programs. Prediction algorithms. Discussions with case studies.

Predictive Methods:

Predictive methods using Nucleic acid sequence – DNA framework, Masking of repetitive DNA, predicting RNA secondary structure, Finding RNA genes, Detection of functional sites and Codon bias in the DNA. Predictive methods using protein sequence – Protein identity and Physical properties. Structure prediction - Prediction of secondary structure of protein, Antigenic sites, Active sites, Folding classes, specialized structures and Tertiary structures. Discussions with case studies. Concepts involved in Insilco Primer Designing and developing Restriction Maps.

Molecular Phylogenetics:

Phylogenetics Basics. Molecular Evolution and Molecular Phylogenetics - Terminology, Gene Phylogeny v/s Species Phylogeny, Forms of Tree Representation. Phylogenetic Tree Construction Methods and Programs - Distance-Based Methods, Character-Based Methods. Phylogenetic Tree evaluation methods. Phylogenetic analysis software and algorithms. Bootstrap methods.

Course outcomes:

At the end of the course the student will be able to:

• Understand the importance of different biological databases, tools and algorithms, and their applications.
• Apply the diverse tools to solve specific bioinformatics problems.

Question paper pattern:

The SEE question paper will be set for 100 marks and the marks scored will be proportionately reduced to 60.

• The question paper will have ten full questions carrying equal marks.
• Each full question is for 20 marks.
• There will be two full questions (with a maximum of four sub questions) from each module.
• Each full question will have sub question covering all the topics under a module.
• The students will have to answer five full questions, selecting one full question from each module.

Textbook/ Textbooks

1 Essential Bioinformatics Jin Xiong, Cambridge University Press 2006.

2 Bioinformatics Basics: Applications in Biological Science and Medicine Lukas K. Buehler Hooman H. Rashidi Tylor & Francis (CRC) 2005

Reference Books

1 Current Protocols in Bioinformatics Andreas D. Baxevanis, Wiley 2003

2 Bioinformatics and Molecular Evolution Paul G. Higgs, Teresa K. Attwood, Blackwell publishing 2005.

3 Bioinformatics: Sequence and Genome Analysis David Mount Cold Spring Harbor Laboratory Press 2004