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  CSE 590CWi '21:  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, (by zoom)
Zoom Link: https://washington.zoom.us/j/99957044876  (Ask Ruzzo for password.)
Organizers: Su-In Lee, Sara Mostafavi, Bill Noble, Larry Ruzzo, Chris Thachuk, Sheng Wang, 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
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 Theme This quarter's discussion will focus (loosely) on single-cell -omics and multi-omic integration. See suggested papers below, or propose another one.
 Schedule
 Date  Presenters/Participants Topic Details
01/04---- Organizational Meeting ---- Video
01/11Ayse; LarryOverview of Single Cell OmicsDetails;  Slides;  Video;  Chat
01/18Holiday
01/25Lee, Ethan; LarryBiologically Interpretable Deep Learning On Single-Cell DataDetails;  Slides;  Video;  Chat
02/01Ashley, Addie; ShengSC Integration with Transfer LearningDetails;  Slides;  Video
02/08Johannes, Aji; YuliangBenchmarking SC Network Inference MethodsDetails;  Slides;  Video
02/15Holiday
02/22No Class: Instead, check out the CSE colloquium, Zoom link here.
03/01Erin; LarrySequence Motif Learning & RepresentationDetails;  Slides;  Video
03/08No Class
 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.  


01/04:   -- ---- Organizational Meeting ----

01/11: Overview of Single Cell Omics -- Ayse; Larry
Suggested reading:

Other reviews, if you want more:
  • QR Xing, NO Cipta, K Hamashima, YC Liou, CG Koh, YH Loh, "Unraveling Heterogeneity in Transcriptome and Its Regulation Through Single-Cell Multi-Omics Technologies." Front Genet, 11, (2020) 662. [offcampus]

01/18:   -- Holiday

01/25: Biologically Interpretable Deep Learning On Single-Cell Data -- Lee, Ethan; Larry

02/01: SC Integration with Transfer Learning -- Ashley, Addie; Sheng

02/08: Benchmarking SC Network Inference Methods -- Johannes, Aji; Yuliang

02/15:   -- Holiday

02/22:   -- No Class: Instead, check out the CSE colloquium, Zoom link here.

03/01: Sequence Motif Learning & Representation -- Erin; Larry

03/08:   -- No Class

 Other Papers Other suggested topics/papers: See suggested papers below, or propose another one. (Contact ruzzo at uw.edu.)
  • Bill suggests:
    • Y Baran, A Bercovich, A Sebe-Pedros, Y Lubling, A Giladi, E Chomsky, Z Meir, M Hoichman, A Lifshitz, A Tanay, "MetaCell: analysis of single-cell RNA-seq data using K-nn graph partitions." Genome Biol, 20, #1 (2019) 206. [offcampus]
  • Ayse suggests:
    • R Argelaguet, B Velten, D Arnol, S Dietrich, T Zenz, JC Marioni, F Buettner, W Huber, O Stegle, "Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets." Mol Syst Biol, 14, #6 (2018) e8124. [offcampus]
  • Su-In suggests an image genomics paper:
    • B He, L Bergenstr√•hle, L Stenbeck, A Abid, A Andersson, √Ö Borg, J Maaskola, J Lundeberg, J Zou, "Integrating spatial gene expression and breast tumour morphology via deep learning." Nat Biomed Eng, 4, #8 (2020) 827-834. [offcampus]
 Other Seminars Past quarters of CSE 590C
COMBI & Genome Sciences Seminars
 Resources 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


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