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  CSE 590CWi '15:  Reading & Research in Comp. Bio.
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 Course Info    CSE 590C is a weekly seminar on Readings and Research in Computational Biology, open to all graduate students in computational, biological, and mathematical sciences.
Mondays, 3:30 - 4:50,  EE1 031  1/26 and earlier
EE1 026  2/02 and after
Organizers: Joe Felsenstein, Su-In Lee, Bill Noble, Larry Ruzzo, Cole Trapnell
Credit: 1-3 Variable
Grading: Credit/No Credit. Talk to the organizers if you are unsure of our expectations.
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 Theme This quarter's discussion will focus on, roughly, "dealing with high dimensional data in biology."
 Date  Presenters/Participants Topic Details Where
01/05---- Organizational Meeting ----EE1 031
01/12Katie; RuzzoMetagenomicsDetails
01/26Jacob; NobleDeep LearningDetails
02/02Scott, Daniel, Haoran; RuzzoCompressed Sensing for GWASDetailsEE1 026
02/09Aaron, Max; TrapnellAlt SplicingDetails
02/23Safiye; LeeNetwork FusionDetails
03/02Alex; RuzzoT cell signalingDetails
03/09Nao, Ning; LeeCancer ProgressionDetails
 Papers, etc.

  Note on Electronic Access to Journals

The UW Library is generally a paid subscriber to non-open-access journals we cite. You can freely access these articles from on-campus computers. For off-campus access, follow the "[offcampus]" links below or look at the library "proxy server" instructions. You will be prompted for your UW net ID and password.  

01/05: ---- Organizational Meeting ----

01/12: Metagenomics -- Katie; Ruzzo
Metagenomic data is inherently high-dimensional, and this is representative:

  • MI Smith, T Yatsunenko, MJ Manary, I Trehan, R Mkakosya, J Cheng, AL Kau, SS Rich, P Concannon, JC Mychaleckyj, J Liu, E Houpt, JV Li, E Holmes, J Nicholson, et 4 al., "Gut microbiomes of Malawian twin pairs discordant for kwashiorkor." Science, 339, #6119 (2013) 548-54. [offcampus]

01/19:   -- Holiday

01/26: Deep Learning -- Jacob; Noble
The original deep learning paper:

perhaps augmented by snippets from more recent biological applications such as:

02/02: Compressed Sensing for GWAS -- Scott, Daniel, Haoran; Ruzzo
GWAS is a well studied area where "high dimensionality" relative to sample sizes is the rule. This paper shows that sparse regression methods work well once enough samples are present, going through a phase transition in performance, and may be relevant to anyone using sparse regression:

Also .

02/09: Alt Splicing -- Aaron, Max; Trapnell

02/16:   -- Holiday

02/23: Network Fusion -- Safiye; Lee

03/02: T cell signaling -- Alex; Ruzzo

  • S Krishnaswamy, MH Spitzer, M Mingueneau, SC Bendall, O Litvin, E Stone, D Pe'er, GP Nolan, "Systems biology. Conditional density-based analysis of T cell signaling in single-cell data." Science, 346, #6213 (2014) 1250689. [offcampus]

03/09: Cancer Progression -- Nao, Ning; Lee

  • AP Parikh, RE Curtis, I Kuhn, S Becker-Weimann, M Bissell, EP Xing, W Wu, "Network analysis of breast cancer progression and reversal using a tree-evolving network algorithm." PLoS Comput. Biol., 10, #7 (2014) e1003713.
 Other Papers Other suggested papers that didn't fit the schedule:
 Other Seminars Past quarters of CSE 590C
COMBI & Genome Sciences Seminars
Biostatistics Seminars
Microbiology Department Seminars
 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.
A comprehensive FAQ at, including annotated links to online tutorials and lectures.
CSE 527: Computational Biology
CSEP 590A: 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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