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 CSE 590 CB, Sp '04: Reading & Research in Comp. Bio.
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 Course Info    CSE 590CB is a weekly seminar on Readings and Research in Computational Biology, open to all graduate students in the computer, biological, and mathematical sciences.
When/Where:  Mondays, 3:30 - 4:50, MEB 234
Organizers:  Joe Felsenstein, Bill Noble, Larry Ruzzo, Martin Tompa
Credit: 1-3 Variable
Grading: Credit/No Credit. Talk to the organizers if you are unsure of our expectations.
 Email
cse590cb@cs.washington.edu Course-related announcements and discussions
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 Schedule
 Date  Presenters/Participants Topic Papers
03/29   ---- No Meeting ----  
04/05 Amol Prakash Motif Discovery in Heterogeneous Sequence Data Papers
04/12 Nan Li Assessment of Algorithms for Discovery of Transcription Factor Binding Sites  
04/19 Zizhen Yao Clustering Gene Expression Time Series  
04/26 Amol Prakash Multidimensional Analysis of Multidimensional Mass Spectrometry Data  
05/03 Zasha Weinberg Exploiting Secondary Structure for Fast Detection of Non-Coding RNAs Abstract
05/10 John Storey Identifying Temporal Differential Gene Expression from Microarrays Abstract
05/17 Matthew Stephens Identifying Recombination Hotspots from Population-Level Patterns of Genetic Variation Abstract
05/24 Tobias Mann Primer Design for Sequencing Reactions and PCR  
05/31 Holiday ---- No Meeting ----  

 Papers, etc.

  Note on Electronic Access to Journals

Links to full papers below are often to journals that require a paid subscription. The UW Library is generally a paid subscriber, and you can freely access these articles if you do so from an on-campus computer. For off-campus access, look at the library "proxy server" instructions.  


04/05: Motif Discovery in Heterogeneous Sequence Data -- Amol Prakash

  • Amol Prakash, Mathieu Blanchette, Saurabh Sinha, Martin Tompa, Motif Discovery In Heterogeneous Sequence Data, PSB 2004
  • A.M. Moses, D.Y. Chiang, M.B. Eisen, Phylogenetic Motif Detection By Expectation Maximization On Evolutionary Mixtures, PSB 2004

04/12: Assessment of Algorithms for Discovery of Transcription Factor Binding Sites -- Nan Li

04/19: Clustering Gene Expression Time Series -- Zizhen Yao

04/26: Multidimensional Analysis of Multidimensional Mass Spectrometry Data -- Amol Prakash

05/03: Exploiting Secondary Structure for Fast Detection of Non-Coding RNAs -- Zasha Weinberg

  • Weinberg and Ruzzo, Exploiting Conserved Structure for Faster Annotation of Non-coding RNAs Without Loss of Accuracy. (To appear ISMB 2004 & Bioinformatics), Preprint.

    Abstract:  
       Motivation: Non-coding RNAs (ncRNAs) -- functional RNA molecules not coding for protein -- are grouped into hundreds of families of homologs. To find new members of an ncRNA gene family in a large genome database, Covariance Models (CMs) are a useful statistical tool, as they use both sequence and RNA secondary structure information. Unfortunately, CM searches are slow. Previously, we introduced "rigorous filters," which provably sacrifice none of CMs' accuracy, while often scanning much faster. A rigorous filter, using a profile hidden Markov model (HMM), is built based on the CM, and filters the genome database, eliminating sequences that provably could not be annotated as homologs. The CM is run only on the remainder. Some biologically important ncRNA families could not be scanned efficiently with this technique, largely due to the significance of conserved secondary structure relative to primary sequence in identifying these families. Current heuristic filters are also expected to perform poorly on such families.
       Results: By augmenting profile HMMs with limited secondary structure information, we obtain rigorous filters that accelerate CM searches for virtually all known ncRNA families from the Rfam Database and tRNA models in tRNAscan-SE. These filters scan an 8-gigabase database in weeks instead of years, and uncover homologs missed by heuristic techniques to speed CM searches.

    Supplementary data, etc...

05/10: Identifying Temporal Differential Gene Expression from Microarrays -- John Storey

   Abstract:  A common goal in DNA microarray experiments is to identify genes that are differentially expressed between two or more biological conditions. We describe a new method to accomplish this when the observations are taken over time and the goal is to detect temporal differential expression.

This is joint work with Wenzhong Xiao, Jeff Leek, and Ron Davis.

Background reading:

05/17: Identifying Recombination Hotspots from Population-Level Patterns of Genetic Variation -- Matthew Stephens

   Abstract:  There has been much recent speculation (based on patterns of Linkage Disequilibrium), and occasionally experimental confirmation (via sperm typing), that rates of recombination across the human genome vary on a fine scale. In particular, some regions of the genome appear to contain "recombination hotspots", where recombination occurs at rates several times higher than the background average rate. However, current statistical methods for inferring the presence of recombination hotspots from patterns of Linkage Disequilibrium are limited: typically they are unable to make quantitative statements about the strength of the evidence for the existence of a hotspot, or its magnitude if it does indeed exist. I will describe a new statistical method for tackling this problem, which addresses these deficiencies using a model that explicitly relates patterns of LD to the underlying recombination rate. The method will be illustrated on simulated data; on data where sperm-typing experiments have confirmed the existence of a hotspot; and on resequenced genes from the SeattleSNP project.

05/24: Primer Design for Sequencing Reactions and PCR -- Tobias Mann

 Other  Seminars Past quarters of CSE 590CB
COMBI & Genome Sciences Seminars
Applied Math Department Mathematical Biology Journal Club
Biostatistics Seminars
Microbiology Department Seminars
Zoology 525, Mathematical Biology Seminar Series

 Resources Molecular Biology for Computer Scientists, a primer by Lawrence Hunter (46 pages)
A Quick Introduction to Elements of Biology, a primer by Alvis Brazma et al.
S-Star Bioinformatics Online Course Schedule, a collection of video primers
A very comprehensive FAQ at bioinformatics.org, including annotated references to online tutorials and lectures.
CSE 527: Computational Biology
CSE 590TV: Computational Biology (Professional Masters Program)
Genome 540/541: Introduction to Computational Molecular Biology: Genome and Protein Sequence Analysis

CSE's Computational Molecular Biology research group
Interdisciplinary Ph.D. program in Computational Molecular Biology


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