Debarka Sengupta

Abstract Targeted therapies such as small-molecule inhibitors act by blocking proteins essential for cancer cell survival, yet omics-based modeling of drug sensitivity often lacks mechanistic grounding. We present FORGE (Factorization Of Response and Gene Essentiality), a joint matrix factorization framework that co-models drug response and target gene dependency to enable biologically informed stratification of treatment groups.

Abstract Agentic systems are proposed for clinical decision support, yet unrestricted tool access can undermine accountability and safety in precision oncology, where recommendations must be grounded in evolving guidelines, regulatory labels, and patient-specific molecular evidence.

Keywords aging bioactivity neural network transfer learning anti-aging computer vision cell morphometrics image based chronological lifespan hallmarks of aging Research topic(s) CP: Cell biology Introduction As cells age, their cellular landscape undergoes dynamic changes in molecular composition, phenotypic expression, and morphological intricacies orchestrated by time.1,2,3 Various methods have been employed to pinpoint cellular age and its associated health, ranging from the traditional,...