Jinyu Cheng

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.

This paper introduces stMLnet, a method for inferring spatial intercellular communication and multilayer signaling regulations using spatial transcriptomics data, showing its effectiveness across multiple datasets and technologies.