Author

Yuanmei Wang

Chinese Academy of SciencesORCID 0000-0002-5628-2276Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 1 Evolutionary Biology· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Organism:human· 2 Organism:mouse· 2 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:drug response / drug discovery· 1 Approach:experimental assay· 1

Frequent Co-Authors

Huanming YangiD· 3 shared Can HuiD· 1 shared Chun XuiD· 1 shared Duoyuan CheniD· 1 shared Fubaoqian HuangiD· 1 shared Gang CaoiD· 1 shared Hong WangiD· 1 shared Jian Wang· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 31 mutual co-author links

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3 shared papersGenetics

Huanming YangORCID

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3 papers

Recent·Most cited

Chromatin state shapes site-specific A-to-I RNA editing

Peng Cai, Xing Chen, Jun Guo, Yuanmei Wang, Huanming Yang, Li Lin, Yi Zhang

The paper identifies chromatin state regulators that influence A-to-I RNA editing frequency across species and tissues.

bioRxiv · Jul 27, 2026 · PreprintGenetics

Genomic evolution reshapes cell type diversification in the amniote brain

Duoyuan Chen, Zhenkun Zhuang, Maolin Huang, Yunqi Huang, Yuting Yan, Yanru Zhang, Youning Lin, Xiaoying Jin, Yuanmei Wang, Jinfeng Huang, Wenbo Xu, Jingfang Pan, Hong Wang, Fubaoqian Huang, Kuo Liao, , Shiping Liu

The paper creates a single-cell atlas of amniote brains to study cell type diversification and identifies species-specific gene expression patterns and novel cell subtypes.

Developmental Cell · May 13, 2025Peer-reviewedEvolutionary Biology

An interpretable integration model improving disease-free survival prediction for gastric cancer based on CT images and clinical parameters

Xiaoping Cen, Can Hu, Yuan Li, Xiangdong Cheng, Wei Dong, Run Zhou, Yuanmei Wang, Jiansheng Zou, Tianyu Lu, Huanming Yang, Yahan Tong

This paper proposes a model integrating deep features, radiomics features, and clinical parameters to improve gastric cancer disease-free survival prediction, achieving a 3%-5% C-index and 10% AUC improvement.

bioRxiv · Apr 1, 2024 · PreprintCancer Biology