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Dhirubhai Ambani Institute of Information and Communication Technology

Course Description
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Gupta Lab
Instructor's Page

DA-IICT Moodle

IT 471 - Topics in Bioinformatics

Manish K Gupta Room 2209 FB 2 mankg [at] daiict.ac.in Phone: 91-79-30150549

Teaching Assitant


This course covers basic machine learning techniques that are used in molecular biology. We will also see how we can apply them in solving the mysteries of the living systems.

Tentative Course Content

Overview of Molecular Biology, Refresher of Probability-Statistics and Optimization, Hidden Markov Model (HMM), Stochastic Context-Free Grammar (SCFG), Least Square Regression, Neural Network, Support Vector Machine (SVM), Applications of these techniques such as in finding non-coding RNAs, RNA folding, RNA secondary structure classification, Protein folding and misfolding, Gene Regulatory Networks (GRN)

Text Book

There is no specific text book but the following books will be helpful. Specially the book by Pevzner. We will provide many additional material such as videos, handouts etc during the course. You do not have to purchase any book.

  1. Pierre Baldi and Soren Brunak, Bioinformatics: The Machine Learning Approach, The MIT press, 2001
  2. Bernhard Scholkopf, Koji Tsuda and Jean-Philippe Vert, Kernel Methods in Computational Biology, The MIT press, 2004
  3. Pavel A. Pevzner, Computational Molecular Biology, An Algorithmic Approach, The MIT press, 2001
  4. Neil C. Jones and Pavel A. Pevzner, An Introduction to Bioinformatics Algorithms, Indian reprint by Ane Books, 2005
  5. Nello Cristianini and Matthew W. Hahn, Introduction to Computational Genomics: A Case Studies Approach, 2007, Cambridge University Press
  6. David Mount, Bioinformatics: Sequence and Genome Analysis, CSHL Press, 2004
  7. Dan Gusfield, Algorithms on Strings, Trees and Sequences, CUP, 1997
  8. Helen C. Causton, John Quackenbush and Alvis Brazma, Microarray Gene Expression Data Analysis:A Beginner's Guide, Blackwell Publishing, 2003
  9. Scott Markel and Darryl Leon, Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases, O'Reilly, 2003
  10. R. Durbin, S. Eddy, A. Krogh and G. Mitchison, Biological Sequence Analysis, 1998, CUP
  11. Philip E. Bourne and Helge Weissig, Structural Bioinformatics, John Wiley & Sons, 2003
  12. Michal Gerhard, Biochemical Pathways: An Atlas of Biochemistry and Molecular Biology, Wiley-Spektrum, 1998

Suggested Online Material:

  1. Ron Shamir, Algorithms in Molecular Biology, Course Archive, http://www.cs.tau.ac.il/~rshamir/algmb.html
  2. T. A. Brown, Genome (online book) http://www.ncbi.nlm.nih.gov/books/bv.fcgi?call=bv.View..ShowTOC&rid=genomes.TOC&depth=2

 Additional Material:

  1. http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Books (NCBI online book shelf)
  2. http://www.web-books.com/MoBio/ (Molecular Biology Web Book)
Mark Distribution (Tentative)

Assignments - 20%
Exams -50%
Projects -30 %


Group-D, Tue (11:00), Wed (9:30), Fri (11:00), CEP 106