CSE 590C,  Wi '18:  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, EE1 031 Organizers:  David Haynor, Sreeram Kannan, Su-In Lee, 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.
Email		cse590cb@cs.washington.edu Course-related announcements and discussions   Manage Your Subscription List Archives compbio-seminars@cs.washington.edu Biology seminar announcements from all around campus   Manage Your Subscription List Archives compbio-group@cs.washington.edu Computational biology discussions, conference/job postings, etc.,   Manage Your Subscription List Archives
Schedule		Date  Presenters/Participants Topic Details 01/08 ---- Organizational Meeting ---- 01/15 Holiday 01/22 Dave Generative Models for DNA Details 01/29 Damon, Shunfu Embeddings Details 02/05 Erin, Daniel RNA Velocity Details 02/12 Chethan Repurposing Drugs Details 02/19 Holiday 02/26 Safiye Embedding scRNAseq Details 03/05 Ian High Dim Neural Classification/Regresion 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.   01/08:   -- ---- Organizational Meeting ---- 01/15:   -- Holiday 01/22: Generative Models for DNA -- Dave Killoran, Lee, Delong, Duvenaud, and Frey. "Generating and designing DNA with deep generative models." (2017) https://arxiv.org/pdf/1712.06148.pdf 01/29: Embeddings -- Damon, Shunfu Wu, Fisch, Chopra, Adams, Bordes, and Weston. "StarSpace: Embed All The Things!" (2017) https://arxiv.org/abs/1709.03856 Zhang and Zhang. "EmbedJoin: Efficient Edit Similarity Joins via Embeddings." (2017) https://arxiv.org/abs/1702.00093 02/05: RNA Velocity -- Erin, Daniel La Manno, et al. "RNA velocity in single cells." (2017) https://www.biorxiv.org/content/early/2017/10/19/206052/ 02/12: Repurposing Drugs -- Chethan H Paik, B Chen, M Sirota, D Hadley, AJ Butte, "Integrating Clinical Phenotype and Gene Expression Data to Prioritize Novel Drug Uses." CPT Pharmacometrics Syst Pharmacol, 5, #11 (2016) 599-607. [offcampus] 02/19:   -- Holiday 02/26: Embedding scRNAseq -- Safiye Risso, Perraudeau, Gribkova, Dudoit, and Vert. "ZINB-WaVE: A general and flexible method for signal extraction from single-cell RNA-seq data." (2017) https://www.biorxiv.org/content/early/2017/11/02/125112/ (in press, Nature Communications) D Risso, F Perraudeau, S Gribkova, S Dudoit, JP Vert, "A general and flexible method for signal extraction from single-cell RNA-seq data." Nat Commun, 9, #1 (2018) 284. [offcampus] 03/05: High Dim Neural Classification/Regresion -- Ian Feng and Simon. "Sparse-Input Neural Networks for High-dimensional Nonparametric Regression and Classification." (2017) https://arxiv.org/abs/1711.07592
Other Papers		Other suggested topics/papers that didn't fit the schedule: Safiye suggested these papers (not exactly a single theme, but "learning gene networks" and "single-cell" are in the mix): https://academic.oup.com/bioinformatics/article/33/5/764/2557687/ [offcampus] --- Gene co-expression network learning from scRNA-seq data https://arxiv.org/abs/1706.08203 --- Low-dimensional representation from pre- and post-treatment gene expression using variational autoencoders https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5041474/ --- Learning tissue-specific gene regulatory networks without learning the networks for individual tissues Larry added a few random suggestions in case the above ideas didn't fill the quarter: DA Knowles, JR Davis, H Edgington, A Raj, MJ Favé, X Zhu, JB Potash, MM Weissman, J Shi, DF Levinson, P Awadalla, S Mostafavi, SB Montgomery, A Battle, "Allele-specific expression reveals interactions between genetic variation and environment." Nat. Methods, 14, #7 (2017) 699-702. [offcampus] YI Li, DA Knowles, J Humphrey, AN Barbeira, SP Dickinson, HK Im, JK Pritchard, "Annotation-free quantification of RNA splicing using LeafCutter." Nat. Genet., 50, #1 (2018) 151-158. [offcampus] PY Tung, JD Blischak, CJ Hsiao, DA Knowles, JE Burnett, JK Pritchard, Y Gilad, "Batch effects and the effective design of single-cell gene expression studies." Sci Rep, 7, (2017) 39921. [offcampus] YI Li, B van de Geijn, A Raj, DA Knowles, AA Petti, D Golan, Y Gilad, JK Pritchard, "RNA splicing is a primary link between genetic variation and disease." Science, 352, #6285 (2016) 600-4. [offcampus] V Kuleshov, D Xie, R Chen, D Pushkarev, Z Ma, T Blauwkamp, M Kertesz, M Snyder, "Whole-genome haplotyping using long reads and statistical methods." Nat. Biotechnol., 32, #3 (2014) 261-266. [offcampus] V Kuleshov, "Probabilistic single-individual haplotyping." Bioinformatics, 30, #17 (2014) i379-85. [offcampus]
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 bioinformatics.org, 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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