PB4005 Bioinformatics and Computational Biology Syllabus:

PB4005 Bioinformatics and Computational Biology Syllabus – Anna University PG Syllabus Regulation 2021

COURSE OBJECTIVES:

 To get familiarized with protein three dimensional structure, modeling, docking and molecular dynamics simulations
 Understand basics concepts in Machine learning, Systems Biology approaches and informatics techniques for protein identification

UNIT I GENOME BIOINFORMATICS

Automatic analysis, alignment, comparison and annotation of biological sequences; analysis of genome evolution and variation; molecular biology databases.

UNIT II PROTEIN STRUCTURE, MODELLING AND SIMULATIONS

Protein Structure Basics, Visualization, Prediction of Secondary Structure and Tertiary Structure, Homology Modeling, Protein Protein Interactions, Molecular Docking principles and applications, Molecular dynamics simulations.

UNIT III PHARMACOINFORMATICS

Molecular library management and virtual screening, computer assisted drug design and quantitative modelling of structure-activity relationships (QSAR and 3D-QSAR)

UNIT IV BIOMEDICAL COMPUTING

Clinical and healthcare information systems, biomedical imaging analysis, studying genotype-phenotype relationships and IT support systems for healthcare decision making.

UNIT V MACHINE LEARNING, SYSTEMS BIOLOGY AND OTHER ADVANCED TOPICS

Machine learning techniques: Artificial Neural Networks Applications in Protein secondary structure prediction, Hidden Markov Models for protein and gene families, Introduction to Systems Biology, Biological networks : Protein interaction and Gene regulatory networks and network motifs Single Input Module, Dense Overlapping Regulon and Feed Forward Loops, Microarrays and Clustering techniques for microarray data analysis, Informatics techniques for analysis of Mass spectrometry data : protein identification.

TOTAL:45PERIODS

COURSE OUTCOMES:

Upon successful completion of this course, students will be able to:
1. summarise the basic procedures involved in genome assembly and annotation.
2. understand concepts in biological sequence analysis, next generation sequencing data analysis.
3. demonstrate the utility of molecular docking and simulations and analyze the results.
4. Illustrate machine learning techniques, networks in Systems biology, microarray data analysis and interpretation of results.
5. possess competence to unveil the relationship between the three-dimensional structure of bio-molecules and their biological activity.
6. have proficiency to handle macromolecular data of sequence and three-dimensional coordinates

REFERENCES:

1. David W. Mount. Bioinformatics – Sequence and Genome Analysis. Cold Spring Harbor Laboratory Press, New York
2. Finkelstein A, Ptitsyn O. Protein physics: a course of lectures. 2nd ed Academic Press. 2016.
3. PHILIP E. BOURNE Structural Bioinformatics / edited by Philip E. Bourne, Helge Weissig Hoboken, N.J. : Wiley-Liss, C 2003
4. TAYLOR, W. R. (Willie R.). Protein Geometry, Classification, symmetry and topology: a computational analysis of structure / William R. Taylor and András Aszódi Bristol: Institute of Physics Pub., Once. 2005.
5. Leach, A. Molecular Modelling: Principles and Applications. 2a. ed. Harlow: Pearson Education, 2001.

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