Introduction to Computational Molecular BiologyGENOME 541
Department of Genome Sciences
University of Washington
Spring Quarter, 2013
This is the second quarter of a two-quarter introduction to computational methods for analyzing biological data. The course surveys a variety of subfields in computational biology, including various types of sequence analyses—phylogenetic footprinting, searching for non-coding RNAs, motif discovery—as well as microarray analysis, proteomics, systems biology, computational cell biology and computational structural biology.
Please click on the links above for email addresses and office locations.
Meeting times and locations
Tuesday and Thursday, 10:30 - 11:50 am, Foege Building S110.
GENOME 540 or permission of instructor.
Students must be able to write computer programs for data analysis. Some prior exposure to probability, statistics and molecular biology is highly desirable.
No textbook is required for this class.
- The entire course grade is based on the homework assignments, which are due weekly. No tests or exams.
- The homework assignments involve writing programs for data analysis, and running them on a computer that you have access to (we cannot provide computers). We don't require a specific language.
- Late homework will be accepted, but penalized. Specifically, each assignment is worth 100 points, from which 10 points will be deducted for each day (or fraction thereof) that you turn it in late. The maximum deduction for being late is 60 points (even if you are more than 6 days late).
- It is OK to run your program on someone else's input data file, and compare outputs to see if you get the same results. However it is not OK to share programs, or to get someone else to debug your program. A key part of the course is being able to write and debug your own programs for data analysis.
- Homework assignments should be turned in using the Catalyst Tools Dropbox.
10% for each homework assignment.
The course home page can be found at http://noble.gs.washington.edu/~noble/genome541 .
Date Instructor Topic References Homework
Tue Apr 2 Noble Predicting protein function from heterogeneous data (Part 1) (Noble 2006) Thu Apr 4 Noble Predicting protein function from heterogeneous data (Part 2) (Brown et al. 2000) (Ramaswamy et al. 2001) (Lanckriet et al. 2004) Homework #1 Tue Apr 9 Noble Motif discovery (D'Haeseleer 2006) (Noble 2009) Thu Apr 11 Noble Protein identification from tandem mass spectra (Sadygov et al. 2004) (Marcotte 2007) Homework #2 Tue Apr 16 Borenstein Complex biological networks Thu Apr 18 Borenstein Complex biological networks Homework #3 Tue Apr 23 Tompa Comparative sequence analysis and phylogenetic footprinting Thu Apr 25 Tompa Comparative sequence analysis and phylogenetic footprinting Homework #4 Tue Apr 30 Bloom Phylogenetic inference: what can it tell us about the origins of new influenza strains such as H7N9? Homework #5 is described. Thu May 2 Bloom What type of evolutionary process is being assumed in phylogenetic inference? The concept of evolutionary distance and the molecular clock. Tue May 7 Bloom Likelihood calculations on a tree. Bayesian phylogenetics. Homework 5 is due before class, and is briefly discussed. Homework 6 is described. Thu May 9 Bloom Bayesian phylogenetics continued. Introduction to BEAST. Inference of ancestral states (if time is available). Tue May 14 Lee Reconstructing the transcriptional regulatory network I Thu May 16 Lee Reconstructing the transcriptional regulatory network II Homework #7 Tue May 21 Lee Statistical genetics I (Genome-wide association studies) Thu May 23 Lee Statistical genetics II (Haplotype reconstruction) Homework #8 Tue May 28 Bradley Protein structure Thu May 30 Bradley Protein sequence analysis Homework #9 Tue Jun 3 Bradley Molecular modeling Thu Jun 5 Bradley Nucleic acid structure Homework #10