Author

Renyu Zhang

Toyota Technological Institute at ChicagoORCID 0000-0002-7750-9353Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:contrastive learning· 1 Approach:deep learning· 1 Organism:human· 1 Assay:protein structure· 1 Research Focus:protein structure prediction· 1 Research Focus:spatial domain detection· 1 Assay:spatial transcriptomics· 1

Frequent Co-Authors

Aly Azeem KhaniD· 1 shared Andrey Kuznetsov· 1 shared Christopher R. WeberiD· 1 shared Emaan Mohsin· 1 shared Jinbo XuiD· 1 shared Le SheniD· 1 shared Robert L. GrossmaniD· 1 shared Sheng WangiD· 1 shared

Activity by Year

2017-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Aly Azeem KhanORCID

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2 papers

Recent·Most cited

ATAT: Automated Tissue Alignment and Traversal in Spatial Transcriptomics with Self-Supervised Learning

Steven Song, Emaan Mohsin, Renyu Zhang, Andrey Kuznetsov, Le Shen, Robert L. Grossman, Christopher R. Weber, Aly Azeem Khan

ATAT automates spatial transcriptomics analysis by aligning and traversing tissue samples using self-supervised learning, improving gene expression modeling without manual annotation.

bioRxiv · Dec 8, 2023 · PreprintBioinformatics

Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model

Sheng Wang, Siqi Sun, Zhen Li, Renyu Zhang, Jinbo Xu

This paper introduces a deep learning method for predicting protein contact maps, achieving higher accuracy than existing methods, especially for proteins with few sequence homologs.

PLoS Computational Biology · Jan 5, 2017Peer-reviewedBioinformatics