Daehyuk's Seminars
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This event has been cancelled!
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"The role of nuclear-enriched long non-coding RNA in hypoxia response and cancer progression"
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"Role of RNA Helicase MOV10 and its phosphorylation in mRNA regulation."
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Nicole King, PhD Investigator, Howard Hughes Medical Institute; Department of Genetics, Genomics and Development; University of California, Berkeley "Intrinsic and extrinsic regulators of choanoflagellate cell physiology"
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Jian Ma, PhD Ray and Stephanie Lane Professor of Computational Biology, School of Computer Science; Carnegie Mellon University "Machine learning for spatial genomics"
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A ceremony celebrating the winners and finalists in the 2022 School of Chemical Sciences Science Image Challenge. SCS Director Dr. Paul Kenis will deliver remarks around 4:30 p.m.
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Jennifer Kuzma, PhD Goodnight-NC GSK Foundation Distinguished Professor, School of Public and International Affairs; Co-Director, Genetic Engineering & Society Center; North Carolina State University "The Macro-Dynamics of the History of U.S. Oversight for Biotechnology in Agriculture and the Environment : What have we learned?"
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The Spatial Omics Initiative / CAIM monthly working group brings together researchers from different disciplines to enable breakthroughs in genomic biology by developing new ways to embed omics data in space, and to facilitate the matching of biological problems to quantitative methods.
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The Center for Artificial Intelligence and Modeling (CAIM) monthly working group facilitates the matching of biological problems to quantitative methods, covering such topics as single-cell and spatial transcriptomics, biomolecular networks in space and time explored using single-cell biophysics, microbiome dynamics and methods for control, and cancer genomics.
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The Spatial Omics Initiative monthly working group brings together researchers from different disciplines to enable breakthroughs in genomic biology by developing new ways to embed omics data in space, jointly with CAIM.
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The Henikoff Lab focuses on better understanding inheritance that does not depend on DNA sequence by applying genomic tools to the study of proteins of the epigenome: histones, transcription factors, nucleosome remodelers, and RNA polymerase II.
