Machine learning for precision medicine - decoding genomes with deep learning models
Olga Troyanskaya
Professor Lewis-Sigler Institute for Integrative Genomics
& Department of Computer Science
Princeton University
Deputy Director for Genomics
Center for Computational Biology
Flatiron Institute of the Simons Foundation
A key challenge in precision medicine is to develop a complete understanding of the genomic architecture of disease. Yet the increasingly wide availability of 'omics' and clinical data, including whole genome sequencing, has far outpaced our ability to interpret these sequences. Challenges include interpreting the 98% of the genome that is noncoding to identify variants that are functional and may lead to disease, detangling genomic signals regulating cell-lineage-specific gene expression, and mapping the resulting genetic circuits and networks in disease-relevant cell-types to specific phenotypes and clinical outcomes. I will discuss computational methods that address these challenges, and highlight their applications to cancer, autism, and mental health disorders.
Date: Thursday, December 15, 2022
From 4:00pm - 5:00pm
[email protected]
This event is hosted as part of the monthly seminar series featuring leaders in precision medicine from across the nation. Presented by the Precision Medicine Resource of the Irving Institute for Clinical and Translational Research. This event is supported in part by a gift from Pfizer to Columbia
