Pei‐Chi Yang

This paper develops a computational model linking mitochondrial ROS, calcium, and electrophysiology in human ventricular myocytes, showing how ROS and calcium interact to influence cardiac function and arrhythmia risk.

This paper develops a new methodology to model phosphoinositide signaling dynamics, showing that basal PI(4)P levels determine cell-specific responses to genetic perturbations.

The paper uses synthetic data to create digital twins of human cardiomyocytes, enabling precise modeling of electrophysiological properties from experimental recordings.

This paper uses AlphaFold to predict discrete conformational states of hERG channels, revealing structural features and drug interactions that improve drug safety screening.

This paper develops a deep learning model to classify and predict electrophysiological responses in cardiac cells across developmental stages using simulated and experimental data.

This paper develops a multiscale computational model to predict cardiotoxicity from drug chemistry to cardiac rhythm, validated using clinical data and showing high predictive accuracy for arrhythmia vulnerability.

This paper develops a computational framework to distinguish safe and unsafe hERG blockers by modeling atomic interactions and simulating drug-channel dynamics.