Yang-Chi-Dung Lin

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 identifies sRNA-mediated feed-forward loops in E. coli that modulate gene regulation through distinct dose-response profiles, showing how sRNAs enhance regulatory diversity and efficiency.

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

This study identifies a CRP-mediated coherent type-4 feed-forward loop in E. coli that regulates lacI expression in response to glucose, enhancing lactose metabolism efficiency.

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