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Haky Im | Integrating multiple omic data to improve mechanistic understanding and prediction
Description:
Explore integrating multiple omic data to enhance mechanistic understanding and prediction in this 39-minute lecture from the Computational Genomics Summer Institute. Delve into cutting-edge research on polygenic transcriptome risk scores, their ability to translate genetic results between species, and improve portability across ancestries. Examine the exploitation of GTEx resources to decipher mechanisms at GWAS loci. Learn about BrainXcan, a novel approach to identify brain features associated with behavioral and psychiatric traits using large-scale genetic and imaging data. Gain insights into the latest advancements in computational genomics and their applications in understanding complex traits and diseases.

Integrating Multiple Omic Data to Improve Mechanistic Understanding and Prediction

Computational Genomics Summer Institute CGSI
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