Mohammad Fallahi‐Sichani

The paper develops an ODE model of the AP-1 network to explain population-specific state distributions and validates its predictions through experiments on melanoma cells.

Complex-level DepMap dependency modeling across 42 cancer types nominates Set1C/COMPASS as melanoma-enriched; CXXC1 knockdown lowers H3K4me3, curbs proliferation, and suppresses MYC/E2F programs in responsive melanoma lines.

This study identifies DRP1 reactivation as a mechanism of resistance to MEK inhibition in pancreatic cancer cells and shows that inhibiting DRP1 can restore sensitivity to trametinib.

This study identifies cell competition as a key driver of gliomagenesis by showing that pre-malignant OPCs outcompete wildtype cells, and inhibiting this process reduces tumor growth.

The paper identifies distinct PI3K and p38 pathways mediating neuregulin-1-induced changes in cardiomyocyte size and shape through systems analysis.

The paper identifies metabolic state vulnerabilities in cancer cell lines and discovers synthetically lethal associations between metabolism, mutations, and therapeutic targets.

The paper shows that the AP-1 transcription factor network explains cellular plasticity in melanoma by regulating differentiation states and responses to MAPK inhibitors.

The paper identifies epigenetic inhibitors that target specific differentiation states in melanoma cells, improving MAPK inhibitor efficacy based on tumor cell differentiation and MAPK activity.

This paper introduces probabilistic phenotype metrics to assess drug efficacy and combination effectiveness by analyzing single-cell responses, showing they reduce bias and improve sensitivity to heterogeneity.