Author

Qiang Shawn Cheng

University of KentuckyORCID 0000-0002-3596-2838Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Approach:deep learning· 3 Research Focus:drug response / drug discovery· 3 Research Focus:benchmarking· 2 Assay:bulk RNA-seq· 2 Organism:human· 2 Assay:scRNA-seq· 2 Research Focus:cell type annotation· 1

Frequent Co-Authors

Shuang GeiD· 4 shared Zhixiang ReniD· 4 shared Huan XuiD· 2 shared Mingqing WangiD· 2 shared Shuqing SuniD· 2 shared Yaxin XuiD· 2 shared Fengwei AniD· 1 shared Haomin WuiD· 1 shared

Activity by Year

2024-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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4 shared papersBioinformatics

Shuang GeORCID

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4 papers

Recent·Most cited

PROTOTYPE-BASED CONTINUAL CELL-TYPE ANNOTATION REVEALS CELLULAR STATE TRANSITIONS IN EXPANDING SINGLE-CELL ATLASES

Shuang Ge, Qiming He, Yi Ren, Yaxin Xu, Mingqing Wang, Zhiwei Nie, Huan Xu, Qiang Shawn Cheng, Shuqing Sun, Zhixiang Ren

scEvolver enables continual cell-type annotation across expanding single-cell atlases, revealing cellular state transitions in disease contexts.

bioRxiv · Jul 26, 2026 · PreprintBioinformatics

Phenotype-driven de novo molecular design from gene expression signatures

Yaxin Xu, Taojie Kuang, Shuang Ge, Haomin Wu, Mingqing Wang, HJ Xu, Fengwei An, Z Z Ma, Qiang Shawn Cheng, Zhixiang Ren

This paper introduces Tx2Mol, a framework that translates gene-expression signatures into candidate molecules, outperforming baselines in chemical plausibility and phenotypic preservation.

bioRxiv · Jul 25, 2026 · PreprintBioinformatics

A Multi-Modal Genomic Knowledge Distillation Framework for Drug Response Prediction

Shuang Ge, Shuqing Sun, Huan Xu, Qiang Shawn Cheng, Zhixiang Ren

This paper proposes a framework that transfers knowledge from multi-modal genomic data to gene expression-only models to improve drug response prediction.

Applied Intelligence · Jul 22, 2025Peer-reviewedBioinformatics

SCREP: Towards Single-Cell Drug Response Prediction by Pharmacogenomic Embedding Enhanced Meta-Pretraining and Few-Shot Transfer Learning

Shuang Ge, Shuqing Sun, Yiming Ren, Huan Yan Xu, Qiang Shawn Cheng, Zhixiang Ren

This paper develops a framework for predicting single-cell drug responses using pharmacogenomic embeddings and few-shot transfer learning, showing improved accuracy and generalization.

bioRxiv · Apr 25, 2024 · PreprintBioinformatics