Stuti Kumari

scKNIFE integrates gene expression with functional annotations to identify tumor programs and treatment-related functional variation in breast cancer.

This paper introduces FORGE, a framework that jointly models drug response and gene essentiality to identify treatment groups and predict efficacy using basal gene expression.

RCoxNet improves cancer survival prediction by integrating mutation and clinical data with a deep learning Cox model and random walk algorithm, achieving better performance than existing models.