Author

Dongliang Xu

Shanghai University of Traditional Chinese MedicineORCID 0000-0002-6908-253XUnclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Cancer Biology· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Approach:deep learning· 2 Research Focus:drug response / drug discovery· 2 Organism:human· 2 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Kaixuan DiaoiD· 2 shared Xiaopeng XiongiD· 2 shared Xinxiang LiiD· 2 shared Xuesong LiuiD· 2 shared Chao XuiD· 1 shared Die Qiu· 1 shared Fang BaiiD· 1 shared Gaofeng FaniD· 1 shared

Activity by Year

2025-2025 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 40 mutual co-author links

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2 shared papersCancer Biology

Kaixuan DiaoORCID

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2 papers

Recent·Most cited

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

Tumor hypoxia adaptation depends on FLAD1 mediated mitochondrial metabolic reprogramming

Xiangyu Zhao, Tao Wu, Sanan Wu, Yujin Chen, Yu Zhang, Jing Chen, Kaixuan Diao, Zaoke He, Jiawei Yan, Tianzhu Lu, Chao Xu, Lu Liu, Gaofeng Fan, Dongliang Xu, Xinxiang Li, , Xuesong Liu

The paper identifies FLAD1 as a key gene for hypoxia adaptation in tumors and develops a deep learning model to predict hypoxia-dependent metabolic genes.

bioRxiv · Mar 5, 2025 · PreprintCancer Biology