Hsi‐Yuan Huang

MetExPred predicts drug metabolism and excretion by integrating molecular and protein representations, achieving strong performance across multiple endpoints.

MIRCID improves drug mechanism modeling by integrating inferred hub miRNAs with gene expression and TF activity, showing better performance than TF activity alone.

The paper develops an AI-driven platform to analyze RRBE's photoprotective mechanisms, identifying key bioactive compounds and their targets through computational and experimental validation.

The paper evaluates imputation performance in East and Southeast Asian populations, showing that recent selection affects variant detection and polygenic risk score estimation.

DeepADR predicts adverse drug reaction frequency using early-stage data by integrating chemical, biological, and semantic information with a Kolmogorov-Arnold Network.

This study shows that oxidative stress modifies miR-483 to 8OH-G miR-483, leading to endothelial dysfunction and increased atherosclerosis risk through altered targetomes.