Feng‐ao Wang

TSTScope integrates single-cell transcriptomics and T-cell receptor data to identify functional T cell states predictive of immunotherapy response, finding that functional state, not abundance, determines treatment outcomes.

scTFBridge infers gene regulatory networks from single-cell multi-omics data by integrating TF-motif binding knowledge, outperforming baselines in cis- and trans-regulation tasks.

This study introduces XgeneVAE, a deep learning framework that characterizes tumor heterogeneity and fitness effects using multi-omics data, showing its ability to reflect patient survival differences and uncover genomic alterations.