Neekesh V. Dharia

The paper identifies a core regulatory circuit in rhabdomyosarcoma and shows that targeting two co-activators synergistically inhibits tumor growth.

The paper develops ALTitude, a machine learning model to predict ALT status from whole genome sequencing data, identifies SMARCAL1 as a therapeutic target in ALT-driven cancers.

The paper reconstructs a sparsely interconnected transcriptional hierarchy in leukemia cells stabilized by incoherent feed-forward loops and shows inhibitors disrupt core regulators' programs.

The paper identifies transcription factors regulating MHC-II expression in AML and shows their role in immune evasion and relapse.

The paper identifies a modular core regulatory circuitry in AML that enforces oncogene expression in KMT2A-rearranged leukemias.

The paper develops CERES, a computational method to correct copy-number effects in CRISPR-Cas9 essentiality screens, improving specificity in cancer cell line studies.