Ciyue Shen

The paper uses protein mass spectrometry to analyze drug responses in ovarian cancer cells, identifies resistance mechanisms, and proposes drug combinations and single agents to overcome resistance.

The paper harmonizes single-cell perturbation datasets and introduces E-statistics for analyzing perturbation effects across diverse data sources.

The paper introduces a hybrid machine learning approach for perturbation biology to identify combinatorial therapeutic candidates using a melanoma cell line dataset.

The paper identifies in vivo eQTL interactions with cytokine levels in a lupus trial, finding novel regulatory mechanisms and potential therapeutic targets.

The paper identifies and characterizes coding and non-coding driver mutations across 2,500 cancer genomes, revealing new candidates and questioning previous findings.