Author

Xiangyu Zhao

ShanghaiTech University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:bulk RNA-seq· 1 Research Focus:drug response / drug discovery· 1 Organism:human· 1 Research Focus:protein design· 1 Assay:proteomics· 1

Frequent Co-Authors

Die Qiu· 2 shared Kaixuan DiaoiD· 2 shared Dongliang XuiD· 1 shared Haopeng WangiD· 1 shared Jing Chen· 1 shared Tao Wu· 1 shared Tao WuiD· 1 shared W WangiD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 29 mutual co-author links

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2 shared papersBioinformatics

Die Qiu

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2 papers

Recent·Most cited

TcrDesign: De novo design of epitope specific full-length T cell receptors

Kaixuan Diao, Jing Chen, Xiangyu Zhao, Tao Wu, Die Qiu, W Wang, Haopeng Wang, Xue-Song Liu

TcrDesign generates experimentally validated, functional, full-length TCRs using deep learning, achieving state-of-the-art performance in binding prediction and sequence generation.

Science China Life Sciences · Apr 28, 2026Peer-reviewedBioinformatics

Precise metabolic dependencies of cancer through deep learning and validations

Tao Wu, Xiangyu Zhao, Yu Zhang, Die Qiu, Kaixuan Diao, Dongliang Xu, Weiliang Wang, Xiaopeng Xiong, Xinxiang Li, Xuesong Liu

This study uses deep learning to predict metabolic vulnerabilities in cancer cells and validates findings using TCGA data, showing improved clinical responses to targeted therapies.

Cell Reports · Jul 1, 2025Peer-reviewedCancer Biology