Wei Gu

49.0k total citations · 35 hit papers
188 papers, 35.2k citations indexed

About

Wei Gu is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Wei Gu has authored 188 papers receiving a total of 35.2k indexed citations (citations by other indexed papers that have themselves been cited), including 146 papers in Molecular Biology, 83 papers in Oncology and 47 papers in Cancer Research. Recurrent topics in Wei Gu's work include Cancer-related Molecular Pathways (72 papers), Ubiquitin and proteasome pathways (60 papers) and Epigenetics and DNA Methylation (42 papers). Wei Gu is often cited by papers focused on Cancer-related Molecular Pathways (72 papers), Ubiquitin and proteasome pathways (60 papers) and Epigenetics and DNA Methylation (42 papers). Wei Gu collaborates with scholars based in United States, China and Canada. Wei Gu's co-authors include Christopher Brooks, Delin Chen, Ning Kon, Muyang Li, Le Jiang, Richard Baer, Shang-Jui Wang, Tongyuan Li, Yingming Zhao and Anatoly Nikolaev and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Wei Gu

184 papers receiving 34.8k citations

Hit Papers

Ferroptosis as a p53-mediated activi... 2000 2026 2008 2017 2015 2001 2019 2009 2004 500 1000 1.5k 2.0k 2.5k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Wei Gu United States 81 24.1k 10.1k 8.6k 7.6k 5.7k 188 35.2k
Marcia C. Haigis United States 65 13.7k 0.6× 3.5k 0.3× 5.7k 0.7× 1.2k 0.2× 6.6k 1.2× 128 24.7k
Reuben J. Shaw United States 53 20.6k 0.9× 3.2k 0.3× 5.3k 0.6× 1.4k 0.2× 1.3k 0.2× 85 30.3k
Simone Fulda Germany 82 20.4k 0.8× 5.6k 0.6× 4.8k 0.6× 1.8k 0.2× 722 0.1× 395 27.4k
Eric W.‐F. Lam United Kingdom 87 15.3k 0.6× 5.4k 0.5× 4.0k 0.5× 1.3k 0.2× 1.0k 0.2× 298 23.1k
Brendan D. Manning United States 62 22.0k 0.9× 3.9k 0.4× 4.9k 0.6× 2.0k 0.3× 452 0.1× 118 30.9k
Nissim Hay United States 75 20.2k 0.8× 4.9k 0.5× 6.5k 0.8× 1.7k 0.2× 338 0.1× 160 27.9k
Xuejun Jiang United States 64 18.6k 0.8× 3.3k 0.3× 9.0k 1.0× 11.2k 1.5× 279 0.0× 171 28.7k
Mikhail V. Blagosklonny United States 81 12.7k 0.5× 5.6k 0.6× 3.3k 0.4× 1.1k 0.1× 592 0.1× 243 19.8k
Jan M. van Deursen United States 60 13.3k 0.6× 4.1k 0.4× 2.8k 0.3× 1.1k 0.1× 720 0.1× 116 26.1k
Boudewijn Burgering Netherlands 64 17.6k 0.7× 3.9k 0.4× 2.7k 0.3× 557 0.1× 1.3k 0.2× 155 22.7k

Countries citing papers authored by Wei Gu

Since Specialization
Citations

This map shows the geographic impact of Wei Gu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Wei Gu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Gu more than expected).

Fields of papers citing papers by Wei Gu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei Gu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Wei Gu. The network helps show where Wei Gu may publish in the future.

Co-authorship network of co-authors of Wei Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Wei Gu. A scholar is included among the top collaborators of Wei Gu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Wei Gu. Wei Gu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Chen, Hao, Cole Ferguson, Dylan C. Mitchell, et al.. (2025). The Hao-Fountain syndrome protein USP7 regulates neuronal connectivity in the brain via a novel p53-independent ubiquitin signaling pathway. Cell Reports. 44(2). 115231–115231. 6 indexed citations
3.
Liu, Yanqing, Zhenyi Su, Omid Tavana, & Wei Gu. (2024). Understanding the complexity of p53 in a new era of tumor suppression. Cancer Cell. 42(6). 946–967. 187 indexed citations breakdown →
4.
Kabir, Md, Xiao Hu, Tiphaine Martin, et al.. (2024). Harnessing the TAF1 Acetyltransferase for Targeted Acetylation of the Tumor Suppressor p53. Advanced Science. 12(7). e2413377–e2413377. 2 indexed citations
5.
Su, Zhenyi, Ning Kon, Jingjie Yi, et al.. (2023). Specific regulation of BACH1 by the hotspot mutant p53R175H reveals a distinct gain-of-function mechanism. Nature Cancer. 4(4). 564–581. 36 indexed citations
6.
Liu, Dong, Chunhui Liang, Bin Huang, et al.. (2023). Tryptophan Metabolism Acts as a New Anti‐Ferroptotic Pathway to Mediate Tumor Growth. Advanced Science. 10(6). e2204006–e2204006. 107 indexed citations breakdown →
7.
Miao, Zong, Wei Tian, Yangfan Ye, et al.. (2022). Hsp90 induces Acsl4-dependent glioma ferroptosis via dephosphorylating Ser637 at Drp1. Cell Death and Disease. 13(6). 548–548. 72 indexed citations
8.
Kon, Ning, Michael Churchill, Huan Li, et al.. (2020). Robust p53 Stabilization Is Dispensable for Its Activation and Tumor Suppressor Function. Cancer Research. 81(4). 935–944. 18 indexed citations
9.
Kon, Ning, Yang Ou, Shang-Jui Wang, et al.. (2020). mTOR inhibition acts as an unexpected checkpoint in p53-mediated tumor suppression. Genes & Development. 35(1-2). 59–64. 41 indexed citations
10.
Kim, Jung‐Min, Kwang Hwan Park, Xianpeng Ge, et al.. (2020). A RUNX2 stabilization pathway mediates physiologic and pathologic bone formation. Nature Communications. 11(1). 2289–2289. 70 indexed citations
11.
Liu, Tong, Le Jiang, Omid Tavana, & Wei Gu. (2019). The Deubiquitylase OTUB1 Mediates Ferroptosis via Stabilization of SLC7A11. Cancer Research. 79(8). 1913–1924. 379 indexed citations breakdown →
12.
Yang, Xin, Zhe Wang, Xin Li, et al.. (2017). SHMT2 Desuccinylation by SIRT5 Drives Cancer Cell Proliferation. Cancer Research. 78(2). 372–386. 162 indexed citations
13.
Gu, Wei, et al.. (2013). Histone Modifications of Notch1 Promoter Affect Lung CD4+ T Cell Differentiation in Asthmatic Rats. International Journal of Immunopathology and Pharmacology. 26(2). 371–381. 21 indexed citations
14.
Chen, Delin, Jing Shan, Wei‐Guo Zhu, Jun Qin, & Wei Gu. (2010). Transcription-independent ARF regulation in oncogenic stress-mediated p53 responses. Nature. 464(7288). 624–627. 127 indexed citations
15.
Gu, Wei, et al.. (2010). Urinary proteomics as a novel tool for biomarker discovery in kidney diseases. Journal of Zhejiang University SCIENCE B. 11(4). 227–237. 52 indexed citations
16.
Lee, Hye-Ra, Zsolt Tóth, Young C. Shin, et al.. (2009). Kaposi's Sarcoma-Associated Herpesvirus Viral Interferon Regulatory Factor 4 Targets MDM2 To Deregulate the p53 Tumor Suppressor Pathway. Journal of Virology. 83(13). 6739–6747. 62 indexed citations
17.
Abida, Wassim & Wei Gu. (2008). p53-Dependent and p53-Independent Activation of Autophagy by ARF. Cancer Research. 68(2). 352–357. 86 indexed citations
18.
Brooks, Christopher, Muyang Li, & Wei Gu. (2007). Mechanistic Studies of MDM2-mediated Ubiquitination in p53 Regulation. Journal of Biological Chemistry. 282(31). 22804–22815. 35 indexed citations
19.
Bouras, Toula, Maofu Fu, Anthony A. Sauve, et al.. (2005). SIRT1 Deacetylation and Repression of p300 Involves Lysine Residues 1020/1024 within the Cell Cycle Regulatory Domain 1. Journal of Biological Chemistry. 280(11). 10264–10276. 283 indexed citations
20.
Luo, Jianyuan, et al.. (2000). Deacetylation of p53 modulates its effect on cell growth and apoptosis. Nature. 408(6810). 377–381. 681 indexed citations breakdown →

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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