Author

Guoli Song

Peng Cheng LaboratoryORCID 0000-0002-5452-3697Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:virus· 2 Research Focus:benchmarking· 1 Assay:DNA methylation· 1 Research Focus:gene regulatory network inference· 1 Assay:long-read sequencing· 1 Research Focus:protein design· 1 Assay:protein sequence· 1

Frequent Co-Authors

Yonghong TianiD· 3 shared Fan XuiD· 2 shared Jie CheniD· 2 shared Wen GaoiD· 2 shared Xiansong Huang· 2 shared Yu WangiD· 2 shared Zhiwei NieiD· 2 shared Bin ZhouiD· 1 shared

Activity by Year

2023-2023 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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3 shared papersBioinformatics

Yonghong TianORCID

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Author profile →

3 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

Multiple sequence-alignment-based RNA language model and its application to structural inference

Yikun Zhang, Mei Lang, Jiuhong Jiang, Zhiqiang Gao, Fan Xu, Thomas Litfin, Ke Chen, Jaswinder Singh, Xiansong Huang, Guoli Song, Yonghong Tian, Jian Zhan, Jie Chen, Yaoqi Zhou

This paper introduces an RNA language model based on multiple sequence alignment, showing it can accurately predict RNA structure from sequence data.

Nucleic Acids Research · Oct 21, 2023Peer-reviewedBioinformatics

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