Kwong‐Sak Leung

This paper introduces scCaT, a deep learning framework combining capsulating architecture and Transformer for sepsis diagnosis using single-cell RNA sequencing data and transferring to bulk RNA data, achieving high accuracy and explainability.

The paper identifies circular RNA competing endogenous gene pairs (cceGPs) as predictive indicators for serous ovarian cancer using a novel method and validates their predictive capacity in independent cohorts.

The paper identifies and characterizes moonlighting long non-coding RNAs using a statistical algorithm integrating protein interactome and functional data, revealing distinct sequence and localization features.