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        "event_title":"Pathways Into Teaching-Marshall Teacher Residency",
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        "description":"The Pathways Into Teaching workshop is an overview of the various pathways into teaching, including Master's programs, Intern Programsand Teacher Residencies. This workshop is perfect for anyone considering a career in education and will be facilitated by representative from the Marshall Teacher Residency Program.",
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        "time_zone":"America\/Detroit",
        "event_title":"Algebraic Geometry Seminar: Hom schemes for algebraic groups",
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        "combined_title":"Algebraic Geometry Seminar: Hom schemes for algebraic groups: Sean Cotner (U. Michigan)",
        "event_subtitle":"Sean Cotner (U. Michigan)",
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        "description":"Grothendieck showed that morphisms of projective varieties are parameterized by a scheme. This fails tremendously for affine varieties. However, group structures tend to be rigidifying, and indeed homomorphisms of affine groups are sometimes also parameterized by a scheme. In this talk, I will discuss the general problem of parameterizing homomorphisms of algebraic groups, both over a field (at first) and over a general base (by the end). Over a field, the main result has a surprisingly elementary proof, which we will describe. We will also give several examples throughout which illustrate strange phenomena that crop up.",
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        "event_title":"DCMB \/ CCMB Weekly Seminar featuring Christina Leslie, PhD (of Memorial Sloan Kettering Cancer Center)",
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        "combined_title":"DCMB \/ CCMB Weekly Seminar featuring Christina Leslie, PhD (of Memorial Sloan Kettering Cancer Center): Advances in predictive models for single-cell and regulatory genomics",
        "event_subtitle":"Advances in predictive models for single-cell and regulatory genomics",
        "event_type":"Lecture \/ Discussion",
        "event_type_id":"13",
        "description":"Abstract:\r\n\r\nThe last several years have brought notable successes in the application of machine learning approaches, and especially deep learning models, to problems in single-cell and regulatory genomics.  The advent of single-cell chromatin accessibility (scATAC-seq) and multiome (scRNA+ATAC-seq) brings new machine learning challenges and opportunities to link chromatin state to developmental trajectories, gene regulation, and even higher order chromatin organization. We will present recent models from our group to exploit these new single-cell data modalities: CellSpace, a sequence-informed embedding algorithm for scATAC-seq that learns biologically meaningful latent structure while mitigating batch effects; SCARlink, a gene-level regression model for multiome data that identifies cell-type-specific enhancers and enables interpretation of disease-associated genetic variants; and ChromaFold, a deep learning model that predicts the 3D contact map from scATAC-seq alone.\r\n\r\nhttps:\/\/umich-health.zoom.us\/j\/93929606089?pwd=SHh6R1FOQm8xMThRemdxTEFMWWpVdz09",
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        "room":"Forum Hall and NCRC #520, Room 1122",
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