Diyuan Lu

The paper develops a regression framework to identify pan-cancer single-gene biomarkers of drug sensitivity in cell line screens, recovering known markers and identifying new ones for ERK/MAPK inhibitors.

This study uses machine learning to improve metronidazole resistance prediction in Helicobacter pylori using whole-genome sequencing, achieving better accuracy than traditional methods.

The paper develops an interpretable multimodal machine learning framework to predict distal sensorimotor polyneuropathy using clinical and molecular data, identifying key biomarkers and improving prediction accuracy with additional molecular modalities.

This paper introduces GExMix, a data augmentation method for gene expression data, which improves drug response prediction by enhancing representation learning and prioritizing gene-centric information.