Author

Yuan Yao

University of MichiganORCID 0000-0003-0502-3714Unclaimed ORCID profile · follow to get notified of new preprints

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Yuan Yao4 papers · University of Oklahoma

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:ChIP-seq· 2 Approach:deep learning· 2 Research Focus:gene regulatory network inference· 2 Assay:Hi-C· 2 Organism:human· 2 Research Focus:benchmarking· 1 Research Focus:differential expression· 1 Approach:graph neural network· 1

Frequent Co-Authors

Fan FengiD· 2 shared Jie LiuiD· 2 shared Xiaotian ZhangiD· 1 shared Xue Qing David WangiD· 1 shared Zhenhao ZhangiD· 1 shared

Activity by Year

2022-2022 · peak 2/yr

Co-Author Collaboration Network

5 top collaborators · 8 mutual co-author links

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2 shared papersBioinformatics

Fan FengORCID

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2 papers

Recent·Most cited

BioinformaticsPLoS Computational BiologyPeer-reviewedJun 6, 2022

Characterizing collaborative transcription regulation with a graph-based deep learning approach

Zhenhao Zhang, Fan Feng, Yuan Yao, Jie Liu

The paper introduces ECHO, a graph-based deep learning model that predicts chromatin features using 3D chromatin organization, showing improved performance over sequence-based models.

3 citations

𝕏 PostBluesky

BioinformaticsNature CommunicationsPeer-reviewedApr 19, 2022

Connecting high-resolution 3D chromatin organization with epigenomics

Fan Feng, Yuan Yao, Xue Qing David Wang…·Jie Liu

The paper develops a deep learning model, CAESAR, to predict high-resolution 3D chromatin structures from epigenomic data and validates its accuracy across 91 human tissues and cell lines.

27 citations

𝕏 PostBluesky