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CCGM Lecture Series: Deep Genomics Models

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Date:
Jun 12, 2024
-
Event Start Time
11:00 am to
Event End Time
12:00 pm
Where:
Location - People View

United States

The Center for Computational and Genomic Medicine presents a lecture series:

Deep Genomics Models for Understanding Gene Regulation and Personal Genomes

Speaker:
Sara Mostafavi, PhD
Associate Professor, Paul Allen School of Computer Science and Engineering
University of Washington

Abstract:
Our genomes contain millions of cis-regulatory elements, whose differential activity determines cellular differentiation. The majority of disease causing genetic variants also reside in these regulatory elements, impacting their regulatory function in a subtle and context-dependent manner. Dr. Mostafavi will present recent work on applying sequence-based deep learning models for predicting and explaining regulatory function(s) from genomic DNA. She'll describe efforts in adapting these models for studying how natural genetic variation impacts cellular function, highlighting current challenges. Motivated by these results, she will describe her ongoing work in improving models' causal interpretation of non-coding genetic variation, which is required to accurately predict differential gene expression across individuals. In summary, her work shows that sequence-based deep learning approaches can uncover regulatory mechanisms while providing a powerful in-silico framework to mechanistically probe the relationship between regulatory sequence and its function.

Bio:
Dr. Mostafavi is an Associate Professor at the Paul Allen School of Computer Science and Engineering at University of Washington (UW). She is also the co-founder of the Machine Learning for Computational Biology Conference. Before joining UW, she was an Assistant Professor in the Department of Statistics and the Department of Medical Genetics at University of British Columbia, and a faculty member at the Vector Institute. Dr. Mostafavi is the recipient of a Canada Research Chair (CRC II) in Computational Biology, and a Canada CIFAR Chair in Artificial Intelligence. Dr. Mostafavi did her postdoc at Stanford CS working with Daphne Koller, and got her PhD in computer science from the University of Toronto in 2011 working with Quaid Morris. Dr. Mostafavi's research focuses developing and applying machine learning and statistical methods for understanding genome biology and function.

Host:
Tristan Hayeck, PhD
Center for Computational and Genomic Medicine

Add to Calendar 2024-06-12 11:00:00 2024-06-12 12:00:00 CCGM Lecture Series: Deep Genomics Models

The Center for Computational and Genomic Medicine presents a lecture series:

Deep Genomics Models for Understanding Gene Regulation and Personal Genomes

Speaker:
Sara Mostafavi, PhD
Associate Professor, Paul Allen School of Computer Science and Engineering
University of Washington

Abstract:
Our genomes contain millions of cis-regulatory elements, whose differential activity determines cellular differentiation. The majority of disease causing genetic variants also reside in these regulatory elements, impacting their regulatory function in a subtle and context-dependent manner. Dr. Mostafavi will present recent work on applying sequence-based deep learning models for predicting and explaining regulatory function(s) from genomic DNA. She'll describe efforts in adapting these models for studying how natural genetic variation impacts cellular function, highlighting current challenges. Motivated by these results, she will describe her ongoing work in improving models' causal interpretation of non-coding genetic variation, which is required to accurately predict differential gene expression across individuals. In summary, her work shows that sequence-based deep learning approaches can uncover regulatory mechanisms while providing a powerful in-silico framework to mechanistically probe the relationship between regulatory sequence and its function.

Bio:
Dr. Mostafavi is an Associate Professor at the Paul Allen School of Computer Science and Engineering at University of Washington (UW). She is also the co-founder of the Machine Learning for Computational Biology Conference. Before joining UW, she was an Assistant Professor in the Department of Statistics and the Department of Medical Genetics at University of British Columbia, and a faculty member at the Vector Institute. Dr. Mostafavi is the recipient of a Canada Research Chair (CRC II) in Computational Biology, and a Canada CIFAR Chair in Artificial Intelligence. Dr. Mostafavi did her postdoc at Stanford CS working with Daphne Koller, and got her PhD in computer science from the University of Toronto in 2011 working with Quaid Morris. Dr. Mostafavi's research focuses developing and applying machine learning and statistical methods for understanding genome biology and function.

Host:
Tristan Hayeck, PhD
Center for Computational and Genomic Medicine

Join (if applicable): https://teams.microsoft.com/l/meetup-join/19%3ameeting_ZmU2MDQ2MjctMDM5ZC00MDZjLWI3MzAtNmVhYmUzNjAwMjNm%40thread.v2/0?context=%7b%22Tid%22%3a%22a6112416-07b0-41a5-9bb1-d146b575c975%22%2c%22Oid%22%3a%22fc71a37a-ca38-4f56-bf1d-bb2705a52ecb%22%7d
Remote Center for Computational and Genomic Medicine jaworskis@chop.edu America/New_York public
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