CISC 841 Bioinformatics (Spring 2006)

Time and Place

Lectures: Tuesday and Thursday 2:00 PM - 3:15 PM; Smith 203

Web page: http://www.cis.udel.edu/~lliao/cis841s06

Course Staff and Contact

Staff

Name

Office

Email

Phone

Office Hours

Instructor

Li Liao

Rm 204, 77 E. Delaware Ave.

lliao@cis.udel.edu

831-3500

Tuesdays and Thursdays 3:30-4:30PM, or by appointment

Course Description

This course covers advanced topics and current research in bioinformatics. Focus is given to probability and statistics based methods and models, including hidden Markov models and support vector machines, that analyze biological data, including biosequences, microarray gene expression, protein-protein interaction, and structural information, for tasks like detection of homologs, prediction of functional and structural signatures, and inference of regulatory networks.

Textbook

No required text for the course. But the following books together cover most topics.

  • Biological Sequence Analysis by R. Durbin, S. Eddy, A. Krogh and G. Mitchison, (Cambridge University Press, 1998)
  • Bioinformatics: The Machine Learning Approach, by Pierre Baldi and Soren Brunak, 2nd Edition (MIT Press, 2001)
  • Introduction to Support Vector Machines and Other Kernel-based Learning Methods, by Cristianini and Shawe-Taylor (Cambridge University Press, 2000).
  • Kernel Methods in Computational Biology (Computational Molecular Biology), by Bernhard Schölkopf , Koji Tsuda, Jean-Philippe Vert (Eds), MIT Press 2004.

Additional readings from tutorials, and review/research papers will be provided.

Prerequisites

  • CISC 220 (or Knowledge of common data structures and algorithms, and programming experience with a major language such as C or Java).
  • Familiarity with basic concepts in probability and statistics, and linear algebra (such as vectors space, dot product, etc.)
  • CISC 667 Intro to Bioinformatics is not a prerequisite yet, but is strongly recommended.

Course work and Grading

  • Homework assignments 30%
  • Mid-term exam 20%
  • Final project and presentation 40% (Students will work, either individually or as a team, on a research-oriented project. The projects should typically consist of writing a program (or using/modifying an existing one), running experiments on real/simulated biological data, and writing a technical report with discussion on the results.)
  • Class participation 10%.
  • Programming languages: Perl (strongly recommended), C/C++, or Java.
  • Late assignments will be penalized 15% per class meeting, and will not be accepted more than two class meetings late.

Policy on Academic Dishonesty

The homework assignments in this class should be performed individually. You are permitted to discuss with other students on any conceptual problems, but the work handed in must be entirely your own. For the project assignments, if it is a team work, each team member's contribution should be clearly stated in the project report. Any evidence of academic dishonesty will be handled as stated in the Official Student Handbook of the University of Delaware. If you are in doubt regarding the requirements, please consult with me before you complete any requirement of this course.