| 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.
||This quarter's discussion will focus on an assortment of student-selected topics.|
|01/07||---- Organizational Meeting ----|
|01/14||Daniel; Wang||Estimating Immune Cell Content From Bulk + sc RNAseq||Details|
|01/28||Ian; Noble||Polypharm Side Effects & Graph Convolutional Nets||Details|
|02/04|Gabe; Ruzzo |***Snow Day*** |Dynamic Network Prediction |Details|
|02/11|Shunfu; Kanan |***Snow Day*** |Comparative analysis of single-cell RNA-seq |Details|
|02/25||Alex; Ruzzo||A Predictive Model of Transcription||Details|
|03/04||Nao; Ruzzo||DeepVariant (Deep learning for SNP calling)||Details|
|03/11||Johannes; Ruzzo||DeepSEA (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.
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.
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.
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
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.
- 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
(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.)
- 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.
| Other Seminars
||Past quarters of CSE 590C|
COMBI & Genome Sciences Seminars
Microbiology Department Seminars
||Molecular Biology for Computer Scientists, a primer by Lawrence Hunter (46 pages)|
A comprehensive FAQ at bioinformatics.org, 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