Author

Tao Ren

Chinese Academy of SciencesORCID 0000-0002-6486-7338Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:batch correction / integration· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Organism:human· 1 Approach:large language model· 1 Approach:machine learning (classical)· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Gordon Brent MillsiD· 2 shared Zheng XiaiD· 2 shared Adel KardoshiD· 1 shared Alexey Valeryevich DaniloviD· 1 shared Andrew AdeyiD· 1 shared Baiyi Li· 1 shared Canping CheniD· 1 shared Chengyun TangiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 30 mutual co-author links

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2 shared papersBioinformatics

Gordon Brent MillsORCID

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2 papers

Recent·Most cited

ACCREDIT: A Quality-Aware Agentic Engine for Cell-resolved Cross-modal Image Registration with Dynamic Iterative Tuning

Le Zhou, Faming Zhao, Tao Ren, Shaun M. Goodyear, Chengyun Tang, Baiyi Li, Tingting Zhang, Yabing Chen, Rosalie C. Sears, Gordon Brent Mills, Adel Kardosh, Zheng Xia

ACCREDIT improves cross-modal image registration by detecting failures and automatically recovering alignments, outperforming existing methods in accuracy and robustness.

bioRxiv · Aug 18, 2026 · PreprintBioinformatics

Supervised learning of high-confidence phenotypic subpopulations from single-cell data

Tao Ren, Canping Chen, Alexey Valeryevich Danilov, Susan Liu, Xiangnan Guan, Shunyi Du, Xiwei Wu, Mara H. Sherman, Paul T. Spellman, Lisa M. Coussens, Andrew Adey, Gordon Brent Mills, Ling‐Yun Wu, Zheng Xia

PENCIL identifies phenotype-relevant cell subpopulations from single-cell data using a supervised learning framework with feature selection and trajectory prediction capabilities.

Nature Machine Intelligence · May 8, 2023Peer-reviewedBioinformatics