M. Duran-Frigola

The paper uses machine learning to identify chemical features associated with stage-specific antimalarial activity against Plasmodium falciparum asexual blood stages and gametocytes.

The paper hosts a DREAM Challenge to evaluate computational models for predicting drug polypharmacology using perturbational profile data from 32 kinase inhibitors.

The paper identifies actionable genomic vulnerabilities in cancer by analyzing driver alteration co-occurrence patterns and validates predictions in mice, improving drug response modeling from patient data.