Daniel James McGrail

eSIG-Net predicts how single mutations affect protein interactions using a sequence-based interaction language model, outperforming existing methods.

This study shows that succinate dehydrogenase supports de novo purine synthesis in cancer cells, and its inhibition reduces proliferation by impairing purine biosynthesis and inducing a compensatory salvage pathway.

This study identifies RNA binding proteins as novel drivers of homologous recombination deficiency in tumors, expanding the known genetic causes beyond BRCA1/2 mutations.

This study uses single-cell RNA-seq based transfer learning to prioritize synergistic drug combinations for cancer treatment by aligning patient tumor cells with similar cell lines.

e-MutPath identifies edgetic mutations that perturb functional pathways, revealing cancer vulnerability genes and drug targets through network-based analysis.