Ming Tan

30.3k total citations · 5 hit papers
243 papers, 13.9k citations indexed

About

Ming Tan is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Ming Tan has authored 243 papers receiving a total of 13.9k indexed citations (citations by other indexed papers that have themselves been cited), including 124 papers in Molecular Biology, 59 papers in Oncology and 57 papers in Cancer Research. Recurrent topics in Ming Tan's work include Cancer, Hypoxia, and Metabolism (22 papers), MicroRNA in disease regulation (21 papers) and Cancer-related molecular mechanisms research (18 papers). Ming Tan is often cited by papers focused on Cancer, Hypoxia, and Metabolism (22 papers), MicroRNA in disease regulation (21 papers) and Cancer-related molecular mechanisms research (18 papers). Ming Tan collaborates with scholars based in United States, China and Malaysia. Ming Tan's co-authors include Dihua Yu, Jianrong Lu, Ethan B. Butler, Yinglan Zhao, Mien‐Chie Hung, Qingsong Cai, Øystein Fodstad, Xiaoyan Zhou, Kristine S. Klos and Keng‐Hsueh Lan and has published in prestigious journals such as New England Journal of Medicine, Journal of Biological Chemistry and Angewandte Chemie International Edition.

In The Last Decade

Ming Tan

229 papers receiving 13.6k citations

Hit Papers

PTEN activation contributes to tumor inhibition by trastu... 2004 2026 2011 2018 2004 2013 2014 2023 2023 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Tan United States 58 7.5k 4.3k 4.3k 1.5k 1.2k 243 13.9k
Beth Y. Karlan United States 69 8.0k 1.1× 6.4k 1.5× 3.9k 0.9× 1.2k 0.8× 651 0.5× 336 18.9k
Douglas Yee United States 69 9.9k 1.3× 6.1k 1.4× 4.1k 1.0× 788 0.5× 1.4k 1.2× 279 17.4k
Emile E. Voest Netherlands 70 7.3k 1.0× 8.5k 2.0× 4.9k 1.1× 1.9k 1.3× 1.0k 0.9× 370 18.8k
Massimo Libra Italy 68 8.5k 1.1× 4.4k 1.0× 3.2k 0.7× 1.8k 1.2× 415 0.3× 290 15.9k
Douglas M. Noonan Italy 66 6.0k 0.8× 3.3k 0.8× 2.1k 0.5× 3.0k 2.0× 484 0.4× 245 13.7k
Shuang Huang China 60 7.5k 1.0× 2.4k 0.6× 2.7k 0.6× 1.4k 0.9× 351 0.3× 308 12.9k
Xin Chen China 58 6.6k 0.9× 2.2k 0.5× 3.2k 0.7× 1.0k 0.7× 502 0.4× 382 11.7k
Yiling Lu United States 64 11.6k 1.5× 3.5k 0.8× 2.9k 0.7× 1.4k 0.9× 594 0.5× 209 15.6k
Bryan T. Hennessy Ireland 59 9.7k 1.3× 9.0k 2.1× 6.4k 1.5× 1.3k 0.9× 1.6k 1.3× 266 19.8k
Alice P. Chen United States 50 4.7k 0.6× 4.4k 1.0× 2.8k 0.7× 1.2k 0.8× 615 0.5× 310 11.2k

Countries citing papers authored by Ming Tan

Since Specialization
Citations

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

Fields of papers citing papers by Ming Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Tan. A scholar is included among the top collaborators of Ming Tan 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 Ming Tan. Ming Tan 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.
Jiang, Niu, et al.. (2025). Three-dimensional shading models for estimating global radiation on photovoltaic module. Renewable Energy. 242. 122333–122333. 1 indexed citations
2.
Li, Xingguang, Ran Yan, Ming Tan, et al.. (2025). Facile Access to Piezoelectric Polyamides by Polyamidation of Carboxylic Acids and Ynamides for Potent Tumor Immunotherapy. Angewandte Chemie International Edition. 64(21). e202424923–e202424923. 1 indexed citations
3.
Zhou, Qing, Ying Liu, Yijun Liu, et al.. (2024). PLUNC inhibits invasion and metastasis in nasopharyngeal carcinoma by inhibiting NLRP3 inflammasome activation. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1870(7). 167352–167352. 1 indexed citations
4.
Hamid, Shahrul Bariyah Sahul, et al.. (2024). The regulatory effects of mitragynine on P-glycoprotein transporter. Journal of Pharmacy and Pharmacology. 77(2). 321–334. 1 indexed citations
5.
Dai, Chun, et al.. (2023). A LoC-SERS platform based on triple signal amplification for highly sensitive detection of colorectal cancer miRNAs. Analytical Methods. 15(33). 4194–4203. 2 indexed citations
6.
Yaacob, Nik Soriani, et al.. (2022). Optimization of the CYP inhibition assay using LC-MS/MS. MethodsX. 9. 101827–101827.
7.
Sulaiman, Shaida Fariza, et al.. (2022). The Effects of Deoxyelephantopin on the Akt/mTOR/P70S6K Signaling Pathway in MCF-7 Breast Carcinoma Cells In Vitro. Journal of Pharmacology and Pharmacotherapeutics. 13(2). 148–159. 1 indexed citations
8.
Mohtar, Noratiqah, Thaigarajan Parumasivam, Amirah Mohd Gazzali, et al.. (2021). Advanced Nanoparticle-Based Drug Delivery Systems and Their Cellular Evaluation for Non-Small Cell Lung Cancer Treatment. Cancers. 13(14). 3539–3539. 27 indexed citations
9.
Lim, Sangbin, Joshua B. Phillips, Luciana Madeira da Silva, et al.. (2017). Interplay between Immune Checkpoint Proteins and Cellular Metabolism. Cancer Research. 77(6). 1245–1249. 82 indexed citations
10.
Adenan, Mohd Ilham, et al.. (2017). The effects of deoxyelephantopin on the cardiac delayed rectifier potassium channel current (IKr) and human ether-a-go-go-related gene (hERG) expression. Food and Chemical Toxicology. 107(Pt A). 293–301. 3 indexed citations
11.
Yuzefovych, Larysa V., Andrea G. Kahn, Lars Eide, et al.. (2016). Mitochondrial DNA Repair through OGG1 Activity Attenuates Breast Cancer Progression and Metastasis. Cancer Research. 76(1). 30–34. 37 indexed citations
12.
Lim, Sangbin, Hao Liu, Luciana Madeira da Silva, et al.. (2016). Immunoregulatory Protein B7-H3 Reprograms Glucose Metabolism in Cancer Cells by ROS-Mediated Stabilization of HIF1α. Cancer Research. 76(8). 2231–2242. 127 indexed citations
13.
Luo, Xiaomei, et al.. (2015). Effect of exogenous hydrogen sulfide on hippocampal neuronal damage induced by epilepsy. Chinese Journal of Neuromedicine. 14(8). 805–809. 1 indexed citations
15.
Butler, Ethan B., Yuhua Zhao, Cristina Muñoz‐Pinedo, Jianrong Lu, & Ming Tan. (2013). Stalling the Engine of Resistance: Targeting Cancer Metabolism to Overcome Therapeutic Resistance. Cancer Research. 73(9). 2709–2717. 103 indexed citations
16.
Tekle, Christina, Alexandr Kristian, Yuhua Zhao, et al.. (2011). B7-H3 Silencing Increases Paclitaxel Sensitivity by Abrogating Jak2/Stat3 Phosphorylation. Molecular Cancer Therapeutics. 10(6). 960–971. 128 indexed citations
17.
Zhao, Yuhua, Hao Liu, Zixing Liu, et al.. (2011). Overcoming Trastuzumab Resistance in Breast Cancer by Targeting Dysregulated Glucose Metabolism. Cancer Research. 71(13). 4585–4597. 240 indexed citations
18.
Zhu, Pengcheng, Ming Tan, Chek Kun Tan, et al.. (2011). Angiopoietin-like 4 Protein Elevates the Prosurvival Intracellular O2−:H2O2 Ratio and Confers Anoikis Resistance to Tumors. Cancer Cell. 19(3). 401–415. 222 indexed citations
19.
Shiozawa, Ken, Takeo Nakanishi, Ming Tan, et al.. (2009). Preclinical Studies of Vorinostat (Suberoylanilide Hydroxamic Acid) Combined with Cytosine Arabinoside and Etoposide for Treatment of Acute Leukemias. Clinical Cancer Research. 15(5). 1698–1707. 54 indexed citations
20.

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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