Ning Kon

10.4k total citations · 7 hit papers
53 papers, 8.3k citations indexed

About

Ning Kon is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Ning Kon has authored 53 papers receiving a total of 8.3k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Molecular Biology, 19 papers in Oncology and 11 papers in Cancer Research. Recurrent topics in Ning Kon's work include Cancer-related Molecular Pathways (18 papers), Epigenetics and DNA Methylation (15 papers) and Ubiquitin and proteasome pathways (14 papers). Ning Kon is often cited by papers focused on Cancer-related Molecular Pathways (18 papers), Epigenetics and DNA Methylation (15 papers) and Ubiquitin and proteasome pathways (14 papers). Ning Kon collaborates with scholars based in United States, China and Germany. Ning Kon's co-authors include Wei Gu, Le Jiang, Tongyuan Li, Richard Baer, Shang-Jui Wang, Hanina Hibshoosh, Tao Su, Muyang Li, Delin Chen and Christopher Brooks and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Ning Kon

52 papers receiving 8.2k citations

Hit Papers

Ferroptosis as a p53-mediated activity duri... 2004 2026 2011 2018 2015 2012 2019 2012 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
Ning Kon United States 32 5.6k 2.9k 2.8k 2.0k 984 53 8.3k
Nathalie M. Mazure France 39 5.5k 1.0× 637 0.2× 4.1k 1.5× 1.0k 0.5× 659 0.7× 87 8.4k
Maofu Fu United States 34 4.1k 0.7× 711 0.2× 942 0.3× 1.7k 0.9× 531 0.5× 44 5.8k
Dejuan Kong United States 50 6.2k 1.1× 771 0.3× 3.6k 1.3× 3.1k 1.6× 193 0.2× 100 9.0k
Jiajun Zhu United States 17 3.7k 0.7× 1.9k 0.7× 2.3k 0.8× 786 0.4× 373 0.4× 30 5.7k
Brandon Faubert United States 23 4.3k 0.8× 475 0.2× 2.9k 1.0× 1.3k 0.7× 555 0.6× 33 7.2k
Frédéric Bost France 37 4.8k 0.8× 343 0.1× 1.5k 0.5× 1.5k 0.8× 989 1.0× 95 6.7k
Li Li China 43 3.9k 0.7× 1.5k 0.5× 1.7k 0.6× 1.2k 0.6× 275 0.3× 262 6.3k
David R. Plas United States 35 5.6k 1.0× 358 0.1× 3.0k 1.1× 1.7k 0.9× 719 0.7× 64 8.9k
Matilde E. Lleonart Spain 38 3.7k 0.7× 461 0.2× 1.8k 0.6× 1.3k 0.7× 487 0.5× 86 5.6k
Elisabetta Mueller United States 31 6.1k 1.1× 426 0.1× 2.4k 0.9× 1.3k 0.7× 1.4k 1.4× 51 8.5k

Countries citing papers authored by Ning Kon

Since Specialization
Citations

This map shows the geographic impact of Ning Kon'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 Ning Kon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ning Kon more than expected).

Fields of papers citing papers by Ning Kon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ning Kon. 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 Ning Kon. The network helps show where Ning Kon may publish in the future.

Co-authorship network of co-authors of Ning Kon

This figure shows the co-authorship network connecting the top 25 collaborators of Ning Kon. A scholar is included among the top collaborators of Ning Kon 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 Ning Kon. Ning Kon 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.
Xia, Zhangchuan, Ning Kon, Zhenyi Su, et al.. (2025). The PURB–HOTAIR complex regulates p53-dependent promoter-specific transcriptional activation. Nature Structural & Molecular Biology. 32(9). 1669–1682.
2.
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
3.
Yang, Xin, Zhe Wang, Fereshteh Zandkarimi, et al.. (2023). Regulation of VKORC1L1 is critical for p53-mediated tumor suppression through vitamin K metabolism. Cell Metabolism. 35(8). 1474–1490.e8. 80 indexed citations
4.
Su, Zhenyi, Ning Kon, Bo Chu, et al.. (2023). ALOX5-mediated ferroptosis acts as a distinct cell death pathway upon oxidative stress in Huntington's disease. Genes & Development. 37(5-6). 204–217. 65 indexed citations
5.
Yang, Xin, Shoufu Duan, Zhiming Li, et al.. (2023). Protocol of CRISPR-Cas9 knockout screens for identifying ferroptosis regulators. STAR Protocols. 4(4). 102762–102762. 4 indexed citations
6.
Chen, Delin, Bo Chu, Xin Yang, et al.. (2021). iPLA2β-mediated lipid detoxification controls p53-driven ferroptosis independent of GPX4. Nature Communications. 12(1). 3644–3644. 259 indexed citations breakdown →
7.
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
8.
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
9.
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
10.
Sun, Qianqian, K. Liu, Ling Zhang, et al.. (2020). OTUD5 cooperates with TRIM25 in transcriptional regulation and tumor progression via deubiquitination activity. Nature Communications. 11(1). 4184–4184. 36 indexed citations
11.
Kon, Ning, Donglai Wang, & Wei Gu. (2019). Loss of SET reveals both the p53-dependent and the p53-independent functions in vivo. Cell Death and Disease. 10(3). 237–237. 15 indexed citations
12.
Wang, Donglai, Ning Kon, Omid Tavana, & Wei Gu. (2017). The “readers” of unacetylated p53 represent a new class of acidic domain proteins. Nucleus. 8(4). 360–369. 13 indexed citations
13.
Jiang, Le, Ning Kon, Tongyuan Li, et al.. (2015). Ferroptosis as a p53-mediated activity during tumour suppression. Nature. 520(7545). 57–62. 2549 indexed citations breakdown →
14.
Qiang, Li, Ning Kon, Wenhui Zhao, et al.. (2015). Hepatic SirT1-Dependent Gain of Function of Stearoyl-CoA Desaturase-1 Conveys Dysmetabolic and Tumor Progression Functions. Cell Reports. 11(11). 1797–1808. 21 indexed citations
15.
Kon, Ning, et al.. (2011). Inactivation of arf-bp1 Induces p53 Activation and Diabetic Phenotypes in Mice. Journal of Biological Chemistry. 287(7). 5102–5111. 46 indexed citations
16.
Valenti, Luca, et al.. (2011). Glucagon-Like Peptide 1 Inhibits the Sirtuin Deacetylase SirT1 to Stimulate Pancreatic β-Cell Mass Expansion. Diabetes. 60(12). 3217–3222. 45 indexed citations
17.
Kon, Ning, Y. Kobayashi, M Li, et al.. (2009). Inactivation of HAUSP in vivo modulates p53 function. Oncogene. 29(9). 1270–1279. 149 indexed citations
18.
Banks, Alexander S., Ning Kon, Colette M. Knight, et al.. (2008). SirT1 Gain of Function Increases Energy Efficiency and Prevents Diabetes in Mice. Cell Metabolism. 8(4). 333–341. 526 indexed citations breakdown →
19.
Li, Muyang, Christopher Brooks, Ning Kon, & Wei Gu. (2004). A Dynamic Role of HAUSP in the p53-Mdm2 Pathway. Molecular Cell. 13(6). 879–886. 527 indexed citations breakdown →
20.
Suhadolnik, Robert J., Terence J. O’Brien, Paul R. Cheney, et al.. (1997). Biochemical Evidence for a Novel Low Molecular Weight 2-5A-Dependent RNase L in Chronic Fatigue Syndrome. Journal of Interferon & Cytokine Research. 17(7). 377–385. 85 indexed citations

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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