Author

Wen Gao

Peking UniversityORCID 0000-0002-8070-802XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:virus· 2 Approach:deep learning· 1 Assay:protein sequence· 1 Research Focus:sequence-to-function modeling· 1 Approach:statistical model· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Fan XuiD· 2 shared Guoli SongiD· 2 shared Jie CheniD· 2 shared Yonghong TianiD· 2 shared Yu WangiD· 2 shared Zhiwei NieiD· 2 shared Bin ZhouiD· 1 shared Bing ZhengiD· 1 shared

Activity by Year

2023-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Fan XuORCID

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2 papers

Recent·Most cited

E2VD: a unified evolution-driven framework for virus variation drivers prediction

Zhiwei Nie, Xudong Liu, Jie Chen, Zhennan Wang, Yutian Liu, Hao-Rui Si, Tianyi Dong, Fan Xu, Guoli Song, Yu Wang, Peng Zhou, Wen Gao, Yonghong Tian

E2VD predicts virus variation drivers using an evolution-driven framework, outperforming existing methods and identifying critical mutations for viral survival and risk.

bioRxiv · Nov 27, 2023 · PreprintBioinformatics

Running ahead of evolution - AI based simulation for predicting future high-risk SARS-CoV-2 variants

Jie Chen, Zhiwei Nie, Yu Wang, Kai Wang, Fan Xu, Zhiheng Hu, Bing Zheng, Zhennan Wang, Guoli Song, Jingyi Zhang, Jie Fu, Xiansong Huang, Zhongqi Wang, Zhixiang Ren, Qiankun Wang, , Wen Gao

This paper develops an AI-based simulation method to predict future high-risk SARS-CoV-2 variants by simulating RBD mutations and screening potential variants efficiently.

The International Journal of High Performance Computing Applications · Jul 29, 2023Peer-reviewedBioinformatics