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  CSE 590CWi '19:  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.
When/Where: Mondays, 3:30 - 4:50, MEB 234 (room info)
Organizers: Sreeram Kannan, Bill Noble, Larry Ruzzo, Yuliang Wang
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 an assortment of student-selected topics.
 Date  Presenters/Participants Topic Details
01/07---- Organizational Meeting ----
01/14Daniel; WangEstimating Immune Cell Content From Bulk + sc RNAseqDetails
01/28Ian; NoblePolypharm Side Effects & Graph Convolutional NetsDetails
02/04Gabe; Ruzzo***Snow Day*** Dynamic Network PredictionDetails
02/11Shunfu; Kanan***Snow Day*** Comparative analysis of single-cell RNA-seqDetails
02/25Alex; RuzzoA Predictive Model of TranscriptionDetails
03/04Nao; RuzzoDeepVariant (Deep learning for SNP calling)Details
03/11Johannes; RuzzoDeepSEA (Deep learning for chromatin code)Details
 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.  

01/07:   -- ---- Organizational Meeting ----

01/14: Estimating Immune Cell Content From Bulk + sc RNAseq -- Daniel; Wang

  • M Schelker, S Feau, J Du, N Ranu, E Klipp, G MacBeath, B Schoeberl, A Raue, "Estimation of immune cell content in tumour tissue using single-cell RNA-seq data." Nat Commun, 8, #1 (2017) 2032. [offcampus]

01/21:   -- Holiday

01/28: Polypharm Side Effects & Graph Convolutional Nets -- Ian; Noble

02/04: ***Snow Day*** Dynamic Network Prediction -- Gabe; Ruzzo

02/11: ***Snow Day*** Comparative analysis of single-cell RNA-seq -- Shunfu; Kanan

02/18:   -- Holiday

02/25: A Predictive Model of Transcription -- Alex; Ruzzo

  • R Bonneau, MT Facciotti, DJ Reiss, AK Schmid, M Pan, A Kaur, V Thorsson, P Shannon, MH Johnson, JC Bare, W Longabaugh, M Vuthoori, K Whitehead, A Madar, L Suzuki, et 6 al., "A predictive model for transcriptional control of physiology in a free living cell." Cell, 131, #7 (2007) 1354-65. [offcampus]

03/04: DeepVariant (Deep learning for SNP calling) -- Nao; Ruzzo

  • R Poplin, PC Chang, D Alexander, S Schwartz, T Colthurst, A Ku, D Newburger, J Dijamco, N Nguyen, PT Afshar, SS Gross, L Dorfman, CY McLean, MA DePristo, "A universal SNP and small-indel variant caller using deep neural networks." Nat. Biotechnol., 36, #10 (2018) 983-987. [offcampus]

03/11: DeepSEA (Deep learning for chromatin code) -- Johannes; Ruzzo

 Other Papers Other suggested topics/papers that didn't fit the schedule:
  • Alex suggested: gene regulatory network inference and the applications of GRNs in understanding biological phenomena could be an interesting theme. In addition to two already picked for presentation on 2/4 and 2/25, other potentially relevant papers include:
    • JS Desai, RC Sartor, LM Lawas, SVK Jagadish, CJ Doherty, "Improving Gene Regulatory Network Inference by Incorporating Rates of Transcriptional Changes." Sci Rep, 7, #1 (2017) 17244. [offcampus]
  • Yuliang suggested transcriptomic profiling of the tumor microenvironment, including our 1/14 paper (a computational benchmarking of several methods aimed at enumerating immune cell infiltration in the tumor microenvironment) and
    • E Azizi, AJ Carr, G Plitas, AE Cornish, C Konopacki, S Prabhakaran, J Nainys, K Wu, V Kiseliovas, M Setty, K Choi, RM Fromme, P Dao, PT McKenney, RC Wasti, et 4 al., "Single-Cell Map of Diverse Immune Phenotypes in the Breast Tumor Microenvironment." Cell, 174, #5 (2018) 1293-1308.e36. [offcampus]
    (single cell RNA-seq of several breast cancer samples from different subtypes. It's biologically interesting, and there is also some computational method (clustering, batch effects etc.) discussed.)
 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 comprehensive FAQ at, including annotated links to online tutorials and lectures.
CSE 527: Computational Biology
CSEP 527: 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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