Weikaixin Kong

Paired activity learning supports systematic identification of mutant-selective EGFR inhibitors

The paper develops a computational-experimental framework to identify mutant-selective EGFR inhibitors by leveraging paired activity measurements and structural analysis.

Domain-adversarial learning predicts clinically actionable drug combination synergy in leukemia patients using bulk transcriptomics data

This paper develops a domain-adversarial neural network to predict drug combination synergy in leukemia patients using bulk transcriptomics data, showing improved accuracy over existing methods.

Off-target mapping enhances selectivity of machine learning-predicted CK2 inhibitors

The paper develops an ML-powered drug discovery pipeline to design selective CK2 inhibitors with favorable off-target profiles, achieving a 90% hit-rate.