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  CSE 590CSp '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:  (Ask Ruzzo for password.)
Organizers: Su-In Lee, 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.
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 Theme Traditionally, we reserve Spring quarter for "homegrown" research --- highlights of work by researchers in the Seattle area. Our tentative Spring schedule is:
 Date  Presenters/Participants Topic Details
03/29---- Organizational Meeting ----
04/05Dr. Phil Bradley -- FHCRCLinking T cell receptor sequence to transcriptional profiles with clonotype neighbor graph analysis (CoNGA)Details;  Slides;  Video;  Chat
04/12Dr. Yeganeh Marghi -- Allen InstituteJoint identification of neuron types and type-specific activity-regulated genes with coupled autoencodersDetails;  Slides;  Video
04/19Alyssa & Jason // AlyssaHybrid Molecular-Electronic Computing // Interpreting Neural Networks for Bio SequencesDetails;  Slides;  Video;  Chat
04/26Dr. Wouter Meuleman -- Altius InstituteMapping and navigating the human regulatory genomeDetails;  Slides;  Video
05/03Prof. Hong Qian -- AMathLarge deviations theory: Data, single-cell biomarkers, and Fisher's fundamental theorem of natural selectionDetails;  Slides;  Video
05/10Erin Wilson -- CSEMay the Methanotrophs be with you Slides;  Video;  Chat
05/17David Clausen -- BiostatisticsRelative Abundance Estimation with Microbiome Data Slides;  Video
05/24Lee Organick -- CSESimilarity Search with DNADetails;  Slides;  Video
 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.  

03/29:   -- ---- Organizational Meeting ----

04/05: Linking T cell receptor sequence to transcriptional profiles with clonotype neighbor graph analysis (CoNGA) -- Dr. Phil Bradley -- FHCRC

Authors:   Stefan A. Schattgen, Kate Guion, Jeremy Chase Crawford, Aisha Souquette, Alvaro Martinez Barrio, Michael J.T. Stubbington, Paul G. Thomas, Philip Bradley

Abstract:   Multi-modal single-cell technologies capable of simultaneously assaying gene expression and surface phenotype across large numbers of immune cells have described extensive heterogeneity within these complex populations, in healthy and diseased states. In the case of T cells, these technologies have made it possible to profile clonotype, defined by T cell receptor (TCR) sequence, and phenotype, as reflected in gene expression (GEX) profile, surface protein expression, and peptide:MHC (pMHC) binding, across large and diverse cell populations. These rich, high-dimensional datasets have the potential to reveal new relationships between TCR sequence and T cell phenotype that go beyond identification of features shared by clonally related cells. In order to uncover these connections in an unbiased way, we developed a graph-theoretic approach---clonotype neighbor-graph analysis or “CoNGA”---that identifies correlations between GEX profile and TCR sequence through statistical analysis of a pair of T cell similarity graphs, one in which cells are linked based on gene expression similarity and another in which cells are linked by similarity of TCR sequence. Applying CoNGA across diverse human and mouse T cell datasets uncovered known and novel associations between TCR sequence features and cellular phenotype including the classical invariant T cell subsets; a novel defined population of human blood CD8+ T cells expressing the transcription factors HOBIT and HELIOS, NK-associated receptors, and a biased TCR repertoire, representing a potential previously undescribed lineage of “natural lymphocytes”; a striking association between usage of a specific V-beta gene segment and expression of the EPHB6 gene that is conserved between mouse and human; and TCR sequence determinants of differentiation in developing thymocytes. As the size and scale of single-cell datasets continue to grow, we expect that CoNGA will prove to be a useful tool for deconvolving complex relationships between TCR sequence and cellular state in single-cell applications.

DOI: [offcampus]

04/12: Joint identification of neuron types and type-specific activity-regulated genes with coupled autoencoders -- Dr. Yeganeh Marghi -- Allen Institute

Abstract:   Recent advances in single-cell transcriptomics revealed an enormous diversity among neuronal cells. While the previous studies confirmed the existence of broad neuron classes, they also pointed towards a complicated landscape, where neuron types often appear to overlap or form gradients in gene expression. Therefore, a crucial step toward elucidating the neuronal identity is to jointly identify the discrete and the continuous factors of variability. Taking advantage of deep learning approaches, we study this problem in a variational framework by utilizing multiple interacting autoencoders, designed to disentangle the discrete and continuous aspects of neuronal diversity. We demonstrate the application of our method to a stand-alone single cell RNA sequencing dataset, which defined over 100 transcriptomic neuron types in the mouse cortex. Our results suggest that the proposed method can refine the existing classifications of neurons by joint identification of discrete types and type-specific, activity-regulated genes.

04/19: Hybrid Molecular-Electronic Computing // Interpreting Neural Networks for Bio Sequences -- Alyssa & Jason // Alyssa

Two short talks this week:
  • Alyssa La Fleur & Jason Hoffman -- CSE,  "Hybrid Molecular-Electronic Computing for Ubiquitous Biological Sensing Applications"

  • Alyssa La Fleur -- CSE,  "Interpreting Neural Networks for Biological Sequences by Learning Masks"

04/26: Mapping and navigating the human regulatory genome -- Dr. Wouter Meuleman -- Altius Institute

Abstract:   This year marks the 20 year anniversary of the sequencing of the human genome in 2001. Since then, many large-scale data generation and analysis efforts have built upon this work by producing genome-wide maps and annotations. I will highlight several of our own efforts in this area, in particular of maps that describe the human genome in terms of functional and contextual regulatory annotations. Despite the increasing comprehensiveness, quality and utility of genomic maps over the last two decades, systems to efficiently navigate them at scale have remained lacking. This is at least in part due to the enormous growth of available genomic data, resulting in a vast underutilization of data by a confined focus on the data directly at hand. I will outline ideas for how to address this challenge in a way that combines human expertise with machine-assisted intelligence.

05/03: Large deviations theory: Data, single-cell biomarkers, and Fisher's fundamental theorem of natural selection -- Prof. Hong Qian -- AMath

Abstract:   Genomics and the physical chemistry of biomolecules are two pillars of molecular biology. One of the key branches of the latter is chemical thermodynamics, which, curiously, is quite marginalized in the current research on computational molecular biology (CMB). I shall revisit this subject, but no starting from physics nor chemistry, but rather through a result from probability, beyond the law of large numbers and central limit theorem, call large deviations theory. I shall show how our theory can be applied to Fisher's FTNS as well as to analyzing data from single cells.

05/10: May the Methanotrophs be with you -- Erin Wilson -- CSE

05/17: Relative Abundance Estimation with Microbiome Data -- David Clausen -- Biostatistics

05/24: Similarity Search with DNA -- Lee Organick -- CSE

Abstract:   In the Molecular Systems Information Lab, we use molecules to do things that silicon computers traditionally do. Recently, Callie Bee successfully designed and implemented similarity search with DNA (1). This talk will discuss her work, as well as potential future directions and implications of this work. (1)

05/31:   -- Holiday

 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, 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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