Assaf Gottlieb

The paper introduces JAGWAS, a multi-phenotype GWAS tool that identifies more genetic loci for brain imaging phenotypes than single-phenotype GWAS.

This paper introduces an unsupervised deep learning method to derive brain imaging phenotypes from MRI data, identifying new genetic loci associated with these endophenotypes.

PathDSP predicts drug sensitivity using cancer pathway enrichment, outperforming existing models and providing explainable results on GDSC and CCLE datasets.

TF-TWAS integrates transcription factor polymorphism with transcriptome-wide association studies to identify genes where TF variation better explains expression than cis-regulatory variants.

The paper improves warfarin dose prediction for African Americans by integrating population-specific gene expression imputation with genetic variation data.