Author

Sai Zhang

Beijing University of Chinese Medicine

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

Same name, identified by ORCID

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 2 Approach:benchmark study· 1 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Organism:human· 1

Frequent Co-Authors

Albert Thor ThorhallssoniD· 1 shared Andrew MitchelliD· 1 shared Arthur ComteiD· 1 shared Chong QiniD· 1 shared Emmanuelle Jacquin‐JolyiD· 1 shared Jérémie TopiniD· 1 shared Jérémy GévariD· 1 shared Maxence LalisiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 28 mutual co-author links

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1 shared paperMolecular Biology

Albert Thor ThorhallssonORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Single-point mutation alters odorant receptor sensitivity associated with host plant specialization in Spodoptera moths

Arthur Comte, Maxence Lalis, Sai Zhang, Albert Thor Thorhallsson, Riccardo Moracci, Jérémy Gévar, Nicolas Montagné, Jérémie Topin, Andrew Mitchell, Sébastien Fiorucci, Emmanuelle Jacquin‐Joly

The paper identifies a single amino acid mutation in an odorant receptor that increases sensitivity to host plant volatiles in the lily moth Spodoptera picta.

bioRxiv · Sep 28, 2026 · PreprintMolecular Biology

PSMA-Guided PROTAC Degraders for Tumor-Specific Protein Degradation in Prostate Cancer

Xiao-Lei Meng, Xiaolin Hu, Shan Gao, Wenrui Jia, Sai Zhang, Siqi Zhang, Xiao Wang, Shumin Ma, Chong Qin

This study develops PSMA-guided PROTACs for prostate cancer, showing they selectively degrade target proteins in PSMA-overexpressing cells and improve therapeutic effects in vivo.

Journal of Medicinal Chemistry · May 2, 2025Peer-reviewedCancer Biology

Network Pharmacology and Bioinformatics Methods Reveal the Mechanism of Sishenwan in the Treatment of diabetic nephropathy

Yuanyuan Deng, Yu Ma, Sai Zhang, Mianzhi Zhang

This study uses network pharmacology and bioinformatics to identify the bioactive components and mechanisms of Sishenwan in treating diabetic nephropathy.

bioRxiv · Feb 14, 2023 · PreprintBioinformatics