Chenxin Yi

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.

This study benchmarks deep learning methods for single-cell RNA sequencing integration, identifies limitations in existing metrics, and proposes improvements to better preserve biological signals.

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.