Wanheng Zhang

PRIORITI uses language models to predict target-indication success in drug discovery, achieving high accuracy and robustness across different benchmarks.

This study shows that a ketogenic diet reduces lung injury and inflammation in a murine model of endotoxin-induced lung injury through the metabolite BHB.

Domain-grounded prompting lets GPT-5 produce genetic evidence for 13,022 drug target-indication pairs that predicts clinical success as well as expert curation, with wider coverage.

The paper constructs a multi-ancestry methylome atlas of purified monocytes, identifies population-specific methylation quantitative trait loci, and performs methylome-wide association studies for 41 traits, revealing novel associations for type 2 diabetes.

This paper introduces an unsupervised deep learning method to derive brain imaging phenotypes from MRI data, identifying new genetic loci associated with these endophenotypes.

The paper introduces iGWAS, a method using self-supervised deep learning to extract phenotypes from medical images for GWAS, finding new genetic loci related to retinal vessel development.