Dilafruz Juraeva

CONET infers tumor evolutionary trees and copy number calls from single-cell data using a probabilistic model with MCMC and regularization.

The paper develops a deep learning model called DEERS to predict kinase inhibitor efficacy in cancer cell lines, achieving high accuracy and providing interpretable insights into drug response mechanisms.

The paper evaluates feature selection strategies for drug sensitivity prediction, finding that prior knowledge-based methods outperform genome-wide approaches for drugs targeting specific genes and pathways.