Shuyu Zheng

This study benchmarks single-cell drug response models across 26 datasets, showing performance varies with dataset type, imbalance, and model design, with scDEAL showing competitive results.

This study uses ReSisTrace to identify pre-sensitizing agents for FLT3 inhibitors in FLT3-ITD-positive AML by analyzing transcriptional signatures and validating compounds that enhance treatment efficacy.

The study distinguishes between memory strengthening and generalization, finding that memory generalization, not strengthening, drives depression-like behaviors through mPFC-BNST circuit mechanisms.

This study investigates the role of TIE1 and its interaction with TIE2 in venous development, finding that TIE1 restricts angiogenic sprouting to coordinate vein formation.

This study introduces a gene essentiality signature to predict drug mechanisms of action and target interactions, showing improved accuracy over existing methods.

This study uses multipartite network models to predict effective drug combinations and patient subclasses in acute myeloid leukemia using drug response data.

SynergyFinder Plus improves interpretation and annotation of drug combination screening data through updated methods and a web interface.

This paper develops a drug synergy prediction model using transfer learning to address data scarcity in understudied cancer tissues.