AY 2007-2008/Sem-1/Computational Biology

From IIITM-k-wiki

Contents 1 Objective 2 Instructors 3 Location 4 Class Schedule 5 Credits 6 Who can register 7 Prerequisites 8 Tentative Syllabus 8.1 Mathematics and Computation 8.2 Biology 9 Structure of Course 10 Lecture Schedule 11 Evaluation 12 Class participants 13 Queries 14 /Endsem Assignments 14.1 MUSCLE 14.2 Mutual Information Plots 14.3 CFGs for secondary t-RNA structures 14.4 Exact Matching Algorithm 15 Mapping of Problems to Students 16 /Resources

Objective

Computional Biology is a new and exciting interdisciplinary area that borrows from computer science, biology, chemistry and mathematics to study and model biological phenomenon at the cellular and genomic level. The course is an introduction to computational methods used in building computational models of biological systems. The focus will be on devising and analysing efficient algorithms to model problems in biology, biochemistry and medicine. The objective of this course is to introduce the necessary mathematical frameworks and how they are pplied to understanding biological structures. For example, algorithms involved in identifying and classifying gene patterns, numerical techniques that go into searching for sequence patterns. The techniques presented here will equip the learner to handle problems in bioinformatics, genomics, drug design and such others.

A background in Biology will be useful, but not necessary. All necessary concepts of biology will be introduced in the class.

Instructors

M S Gopinathan, Emeritus Professor, IIITM-K

V Sundarapandian, Professor, IIITM-K

Venkatesh Choppella, Associate Professor, IIITM-K

Associate Instructor: Sivchand Koripella, Systems Engineer, IIITM-K

Location

IIITM-K, Park Centre, Technopark

Class Schedule

Friday 9:00am - 1pm Park Centre Lab 1

Credits

3 (3 contact hours per week)

Who can register

This course is open to students pursuing Masters or PhD degrees in basic sciences, mathematics or computer sciences or ITin any recognised University/Institute. The course is also open to PGDIT students of IIITM-K.

Prerequisites

This course assumes that you have the ability to absorb basic mathematical concepts like probability theory, sets, and graphs and computer algorithms even if you haven't studied them formally. Basic knowledge of biology will be helpful, but not necessary.

Tentative Syllabus

Mathematics and Computation

• Basic Probability and Statistics
• Markov Processes
• Dynamic Programming
• Genetic Algorithms
• Exact and Approximation algorithms
• data structures (strings and trees)
• Regression Analysis
• Programming

Biology

Basic biochemistry: structure of amino acids, proteins and genes

• Evolution, Mutation
• Comparative Genomics
• Gene Expression and Regulation
• Proteomics
• Neuroinformatics

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Structure of Course

This is a seminar course where lectures will be given both by faculty and students. Problem solving, Term Papers and a Project is incorporated.

Lecture Schedule

• Week 1 Sep 07: /Introduction to Molecular Biology (MSG)
• Week 2 Sep 14: /Intro to Molecular Biology (contd) (MSG)
• Week 3 Sep 21: /Sequence similarity (VC)
• Week 4 Sep 28: /Grammars and Automata (VC)
• Week 5 Oct 05: /Grammars .. contd. (VC)
• Week 6 Oct 12: Midterm exam week
• Week 7 Oct 19: /Holiday
• Week 8 Oct 26: /RNA Seconday Structre Prediction (MSG)
• Week 9 Nov 02: /Basic Probability, Entropy, Relative Entropy and Mutual Information- (VS)
• Week 10 Nov 09: /Multiple sequence alignment (MSG)
• Week 11 Nov 16: /Systems Biology 1: Intro and Differential Eqns. (MSG)
• Week 12 Nov 23: /Systems Biology 2: Automata models 2 (MSG/VC)
• Week 13 Nov 30: Project Seminars

Evaluation

Evaluation will be based on the following:

• Class Participation 10%
• Term paper along with lectures 20%
• Midterm 20%
• Project and Project report 30%
• Final Exam 20%

'The above evaluation weights will be revised'. Midterms will have increased weight. Venkatesh 21:51, 6 October 2007 (IST)

Class participants

• Sukant Mid-Term Assignment
• Ajay
• Sandeep

 REPORT ON CYK ALGORITHM (mid-term paper MSIT 2006-2008 3rd semester)[1]

 REPORT ON tRNA SEQUENCE GENERATION (END-TERM paper MSIT 2006-2008 3rd semester)[2] 
(link for code : svn://godavari.iiitmk.ac.in/users/students/sandeep-pg6/trunk)

• Naveen
• Venkatesh
• Ashalatha

Queries

/Endsem Assignments

Written document (LaTex) with screen shots of figures mus be submitted. Due Date 10:00am, Tue 11 December, 2007.

MUSCLE

• Write a term paper on the MUSCLE algorithm for multiple

sequence analysis, emphasising the algorthmic complexity of the various steps.

• Use the webserver programme MUSCLE to arrive at a

consensus structure for RNA sequences taken from various species (re: Computational Biochemistry , Stan Sai, p.280)

Term Paper for MUSCLE Algorithm

Sequence_output by MUSCLE

Mutual Information Plots

Write a program to obtain the Mutual Information plot of a pre-aligned set of RNA sequences and to arrive at a consensus structure. The End Term submission is [[3]]

CFGs for secondary t-RNA structures

Derive a Context Free Grammar, its agorithm and implement its code to get the secondary structure of a t-RNA using canonical pairing. Draw the parse tree.

'Report on trna sequence genaration'[4]

'Link for the code in svn is given as'[svn://godavari.iiitmk.ac.in/users/students/sandeep-pg6/trunk]

Exact Matching Algorithm

Complete the implementation of the preprocessing-based exact match algorithm.

Report on Exact String Matching Algorithms

Mapping of Problems to Students

• MUSCLE: Sukanto
• Mutual Information Plots: Naveen
• CFGs: Sandeep
• Exact Matching: Ajay

/Resources

To be completed