AY 2007-2008/Sem-2/ITM126 Computational Biology
From IIITM-k-wiki
Contents |
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
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
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.
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%
