Time and Place

5:00 to 6:15 PM on Tuesday and Thursday in ACTR 118

Given by

Dr. Raja Loganantharaj
The Center for Advanced Computer Studies
Contact: 482-5345 Voice and logan@cacs.louisiana.edu (e-mail)

Prerequisites

For CS and CE students: understanding of data structure and algorithms, machine learning, and database.

Outline

Bioinformatics is an interdisciplinary study that directly or indirectly helps to uncover the truth about biological processes at the molecular level. Many diverse approaches have been actively pursued including the system engineering approach to understand the underlying biological process using domain knowledge, and a very large number of data sets covering diverse features. In this course we view the computational mechanism behind different problem solving approaches that are being used in bioinformatics.

An organism needs different combinations of proteins on demand for basic survival. A cell in an organ may be viewed as a factory of making proteins. The information on how to make a protein is encoded in a DNA sequence. The process of decoding and making a protein from a chromosome is known as central dogma in molecular biology. We will focus on the following topics in this course.

Building computational models for identifying

• Promoters and the associated binding sites
• Transcription start sites
• Splice site and genes

We will also learn about sequence analysis that involves

• Pairwise alignment
• Hidden Markov Models
• Multiple sequence alignment
• Phylogenetic tree
• RNA structure analysis
• Genome Analysis and
• Microarrays Analysis
• SNP and haplotype

Text book

• Bioinformatics: Sequence and Genome Analysis by David W. Mount, 2 nd Edition, Cold Spring Harbor Laboratory Press 2004
  
• Mastering Perl for Bioinformatics by James D. Tisdall (Paperback - Jun 2003)

Other reading materials

• Biological Sequence Analysis by R. Durbin, S. Eddy, A. Krogh and G. Mitchison, Cambridge University Press 1998
• Fundamental concepts of Bioinformatics by D. E. Krane and M. L. Raymer, Benjamin Cummings, 2003
• Materials from recent conferences and magazines and journals
  

Evaluation

It is based on homework, mid term tests and a semester project. Midterm 30%, take-home final 30%, homework 10%, semester project 30% and class participation (0 to -5%). Grades: A >85, B >75%, C>65%, D>55% and the rest are F.