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Activity Number: 397 - Statistical Learning for Epigenomics Data
Type: Topic Contributed
Date/Time: Tuesday, July 31, 2018 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract #330451
Title: Inferring the Impact of Genetic Variation on Regulatory Networks
Author(s): Sara Mostafavi*
Keywords: Computational Genomics; Gene Regulation; Gene and Environment Interaction; Gene Expression Patterns

The last decade has seen a tremendous increase in the availability of varied types of genomics data. Specifically, generation of multi-omic datasets is well underway in large cohort studies, with the goal of identifying interpretable genomics patterns that are associated with rare and complex human traits. Here, we describe recent approaches for integrating such multi-omics datasets, in order to predict the impact of genetic variation at multiple cellular traits, with the ultimate goal of utilizing such predictions in order to understand genomics of rare and common human disease.

Authors who are presenting talks have a * after their name.

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