Instructor:         Mohammed J. Zaki
Office:               Lally Bldg 307
Phone:               x6340
Email:                zaki.AT.cs.rpi.edu
Class Hours:     Lally 02, MR 10:00-11:50am
Office Hours:    MR 12-1pm, or by appointment
Web Page:         http://www.cs.rpi.edu/~zaki/bioinfo/
 

Introduction
Computational Biology and Bioinformatics deal with the science of storing, extracting, organizing, analyzing, and interpreting biological data. Its importance has increased with the technology of DNA sequencing, microarrays, as well as the widespread understanding that genes and proteins act in networks. The goal of this course is to introduce the main topics in computational biology and bioinformatics. The coverage is divided into three main topics: sequence analysis (SEQ), structure analysis (STR) and systems biology (SB). Topics within SEQ cover some of the basic concepts like sequence alignments, motif finding, and phylogenetic trees, as well as newer topics related to whole genome comparisons. STR covers aspects of protein structure prediction, structure alignment, and structural motifs. Finally SB covers some of the emerging problems dealing with all kinds of biological networks including regulatory networks, protein networks, metabolic networks and signaling networks.

Text
There is no required text for the course. Relevant reading material will be distributed in paper or electronically.

Class Format and Requirements

Requirements: It is assumed that students some equivalent of Discrete Math and Data Structures and Algorithms. A course in probability and statistics will be helpful. Prior knowledge of molecular biology is not assumed; all necessary concepts will be covered in class.

Exams: There will be two exams. See class schedule for tentative dates. There will be no separate finals.

Reading: Students will be required to read some classic or latest papers in bioinformatics to supplement class material. Material in these papers will be on the exams.

Homeworks: There will be about 4-5 homework assignments. Some of these will involve algorithm implementation, while others will involve application of techniques.

The final grade will be determined as follows:
    50% exams (25% per exam)
    40% homeworks
    10% class participation

Timeline for Topics
See the course website for a tentative timeline. There might be a change in the topics as we progress during the semester.

Academic Integrity
The school takes cases of academic dishonesty very seriously, resulting in an automatic "F" grade for the course if anyone is caught cheating. Students should familiarize themselves with the relevant portion of the Rensselaer Handbook on this topic.