CH391L

CH391L Bioinformatics

Course unique #: 52990
Lectures: Tuesday/Thursday 12:30 – 2:00 PM in WEL 3.402
Instructor: Edward Marcotte, marcotte@icmb.utexas.edu

• Office hours: Wednesdays 2:00 – 3:00 PM in MBB 3.210AA Phone: 471-5435
  

TA: Taejoon Kwon, taejoon.kwon at mail dot utexas dot edu

• TA Office hours: Tuesday/Thursday 10:00 – 11:00 AM in MBB 3.210A Phone: 232-3919
  

Lectures & Handouts

Feb 24, 2011 - Gene finding

• The GENSCAN paper

Feb 22, 2011 - HMMs and gene finding

• Fly cell Markov chains

Feb 17, 2011 - HMMs

• HMM primer
• Problem Set 2, due Feb. 24, 2011
• State sequences
• Soluble sequences
• Transmembrane sequences

Feb 15, 2011 - Profiles

• A commentary on computational challenges arising from DNA sequencing
• The remarkable growth of Genbank, and similarly, UniProt

Feb 10, 2011 - BLAST

• The original BLAST paper
• Teaching BLAST
• The protein homology graph paper. Just for fun, here's a link to a stylized version we exhibited in the engaging Design and the Elastic Mind show at New York's Museum of Modern Art.

Feb 8, 2011 - Sequence Alignment III

• A few examples of proteins with internally repetitive sequences: 1, 2, 3
• Repeats in the human genome, tallied here

Feb 3, 2011 - Sequence Alignment II

• An example of dynamic programming using Excel, created by Michael Hoffman (a former CH391L student; you can read more about Michael here)
• Dynamic programming primer

Jan 27, 2011 - Sequence Alignment I

• Taejoon's presentation file
• BLOSUM primer
• The original BLOSUM paper (hot off the presses from 1992!)

Jan 25, 2011 - Perl primer

• Problem Set 1, due Feb. 8, 2011
• E. coli genome
• T. volcanium genome (to a student who asked me about 'a strange character' in this file, I checked this file and found no strange 'character' in this file. -- Taejoon)
• 3 mystery genes (for Problem 5): Mgene1, Mgene2, Mgene3

Syllabus & course outline

Course syllabus

An introduction to computational biology and bioinformatics. The course covers typical data, data analysis, and algorithms encountered in computational biology. Topics will include introductory probability and statistics, basics of programming, protein and nucleic acid sequence analysis, genome sequencing and assembly, protein structure prediction, analysis of DNA microarray data, data clustering, biological pattern recognition, and biological networks.

Open to graduate students and upper division undergraduates in natural sciences and engineering.
Prerequisites: Basic familiarity with molecular biology, statistics & computing, but realistically, it is expected that students will have extremely varied backgrounds.

Note that this is not a course on practical sequence analysis or using web-based tools. Although we will use a number of these to help illustrate points, the focus of the course will be on learning the underlying algorithms and exploratory data analyses and their applications.

Most of the lectures will be from research articles and handouts, with some material from the...
Recommended text (for sequence analysis): Biological sequence analysis, by R. Durbin, S. Eddy, A. Krogh, G. Mitchison (Cambridge University Press),

For non-molecular biologists, I highly recommend (really!) The Cartoon Guide to Genetics (Gonick/Wheelis)
For biologists rusty on their stats, The Cartoon Guide to Statistics (Gonick/Smith) is also very good.

Some online references:
An online bioinformatics course Various bioinformatics algorithms Assorted bioinformatics resources on the web
Online probability texts: #1, #2, #3

No exams will be given. Grades will be based on 4 problem sets (given every 2 weeks and counting 15% each towards the final grade) and a course project (40% of final grade), which can be individual or collaborative. If collaborative, cross-discipline collaborations are encouraged. The course project will consist of a research paper or project on a bioinformatics topic chosen by the student (with approval by the instructor) containing an element of independent computational biology research (e.g. calculation, programming, database analysis, etc.). This will be turned in as a link to a web page.

The final project is due on May 3, 2011.

From TA

• If you don't have a unix/linux account to do the homework and/or project, send email to 'taejoon.kwon at mail dot utexas dot edu'.
• CH391L/Connecting_Server (If you don't know how to use the account info, this are the instructions.)
• If you are having trouble transferring files from your computer to server, here are some GUI programs that can help you:
  • http://winscp.net/eng/index.php (WinSCP, Windows)
  • http://cyberduck.ch/ (CyberDuck, Mac)
  • http://filezilla-project.org/ (FileZilla, all platforms)
• CH391L/PERL_Programming Basic information about PERL programming environment
• CH391L/NucleotideFrequency PERL program to count nucleotide/dinucleotide frequency (Homework 1).
• CH391L/BLOSUM PERL program for BLOSUM scoring matrix analysis (Homework 1).
• CH391L/DynamicProgramming PERL example code for dynamic programming.
• CH391L/HiddenMarkovModel PERL example code for HMM (Viterbi Algorithm).