
CS 594, Special Topics in Computer Science
Fall Term, 2003

Topic: Algorithmic Methods for Bioinformatics
Section Number: 31234
Time and Place:
Mondays and Wednesdays, from 3:40 to 4:55pm
Rm 206, Claxton Building
Textbook:
Introduction to Computational Molecular Biology
Joao Meidanis & Joao Carlos Setubal
PWS Publishing Company, Boston
ISBN 0534952623
Overview
This class is intended primarily for CS and GST students, and is focused on
fundamental computational tools for bioinformatics.
It may also be of interest to students from ECE and Mathematics.
Three hours credit will be given.
Requisite complexitytheoretic issues will be reviewed, including: asymptotics
and order notation; P, NP and NPcompleteness; fixedparameter
tractability and fast exact algorithms; and search, decision, optimization
and approximation.
Algorithmic paradigms of widespread biological relevance will be emphasized.
These include: dynamic programming and space management; parallel and grid
computing; and simulation and the use of fast heuristic algorithms.
Selection of individual topics from biology will be based in part on student
interest and background.
Class format will be informal lecture and discussion.
Outside reading and class participation will be expected.
Guest lecturers from GST, ORNL and elsewhere are scheduled to assist.
The textbook will be augmented with the liberal use of research papers and
other publications.
Special Notes
(1) This will be the first time this course is offered.
As such, a major aim is to develop a core list of subjects so that, if there
is sufficient student interest, this may evolve into a regular,
mainstream CS/GST offering.
(2) For students who need 600 rather than 500 level hours, this course may be
taken as CS680, Section 31323.
(3) Students interested in this class are encouraged to participate in a
journal club being organized by
Dr. J. Snoddy.
It is listed as BCMB 608, Section 21565, and will meet in Claxton 205 from
2:303:30 on Mondays.
For more information visit the
journal club page.
(4) For students unsure of the importance of foundational computational
techniques in the setting of GST, a
little testimonial is humbly provided (with permission).
Lectures
Some Computational Fundamentals
Mathematical Preliminaries: Lecture 2
A Little Complexity Theory: Lecture 3
A Little More Complexity Theory: Lecture 4
Will It Ever End?: Lecture 5
Some Biological Fundamentals
Biology at Last!: Lecture 6
More Biology: Lecture 7
A Light Day: Lecture 8
Back to Biology: Lecture 9
Course Content Update: Lecture 10
Back to the Grind
Recurrence Relations: Lecture 11
Last Take on Biological Fundamentals: Lecture 12
Dynamic Programming
Introduction: Lecture 13
Continued: Lecture 14
Applications, Treewidth: Lecture 15
Applications, Sequence Alignment: Lecture 16
Gene Regulatory Network Modeling
Digraphs and Bayesian Networks: Lecture 17
DEs and Stochastic Methods: Lecture 18
Homework Review and Team Presentations: Lecture 19
Statistics for Bioinformatics: Lecture 20
The Human Genome Project: Lecture 21
An Introduction to Proteomics: Lecture 22
Computational Gene Finding: Lecture 23
Analysis of Differential Gene Expression Data: Lecture 24
Evolutionary Biology: Lecture 26