Ming Xu

3.6k total citations · 1 hit paper
124 papers, 2.7k citations indexed

About

Ming Xu is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Ming Xu has authored 124 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Molecular Biology, 35 papers in Cardiology and Cardiovascular Medicine and 19 papers in Surgery. Recurrent topics in Ming Xu's work include RNA Interference and Gene Delivery (13 papers), DNA and Nucleic Acid Chemistry (11 papers) and Receptor Mechanisms and Signaling (11 papers). Ming Xu is often cited by papers focused on RNA Interference and Gene Delivery (13 papers), DNA and Nucleic Acid Chemistry (11 papers) and Receptor Mechanisms and Signaling (11 papers). Ming Xu collaborates with scholars based in China, United States and Romania. Ming Xu's co-authors include Youyi Zhang, Han Xiao, Xiaowei Ma, Gu Yuan, Zhizhen Lv, Zhizhen Lü, Yi Zhu, Yongnan Fu, Zijian Li and Jiang Zhou and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Ming Xu

116 papers receiving 2.7k citations

Hit Papers

Inhibition of fatty acid uptake by TGR5 prevents diabetic... 2024 2026 2025 2024 10 20 30 40

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Xu China 28 1.5k 639 321 295 294 124 2.7k
Zhongyi Chen China 23 1.1k 0.7× 359 0.6× 201 0.6× 246 0.8× 597 2.0× 62 2.4k
Patrick Münzer Germany 25 1.3k 0.9× 551 0.9× 112 0.3× 367 1.2× 248 0.8× 50 3.3k
Huimin Yu China 28 962 0.6× 423 0.7× 254 0.8× 156 0.5× 154 0.5× 89 2.1k
Simon C. Johnson United States 23 2.0k 1.4× 298 0.5× 139 0.4× 847 2.9× 179 0.6× 42 3.5k
Gary F. Merrill United States 33 2.3k 1.5× 376 0.6× 134 0.4× 670 2.3× 482 1.6× 113 3.6k
Gillian Hughes New Zealand 23 1.9k 1.3× 157 0.2× 140 0.4× 481 1.6× 354 1.2× 41 3.0k
Andrey Sorokin United States 35 2.0k 1.4× 337 0.5× 75 0.2× 477 1.6× 154 0.5× 94 3.5k
Chiara Bolego Italy 31 810 0.5× 307 0.5× 70 0.2× 368 1.2× 315 1.1× 83 2.9k
Qiong Zhou China 27 1.4k 1.0× 313 0.5× 63 0.2× 512 1.7× 324 1.1× 106 2.8k
Qing Liu China 30 1.8k 1.2× 181 0.3× 120 0.4× 268 0.9× 537 1.8× 120 3.5k

Countries citing papers authored by Ming Xu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Xu. A scholar is included among the top collaborators of Ming Xu 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 Xu. Ming Xu 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.
Yang, Shao H., Sikandar Amanullah, Yu Amanda Guo, et al.. (2024). Fine genetic mapping and transcriptomic analysis revealed major gene modulating the clear stripe margin pattern of watermelon peel. Frontiers in Plant Science. 15. 1462141–1462141. 2 indexed citations
2.
Fan, Chenyu, Huiying Liu, Hui Li, et al.. (2024). Inhibition of fatty acid uptake by TGR5 prevents diabetic cardiomyopathy. Nature Metabolism. 6(6). 1161–1177. 49 indexed citations breakdown →
3.
Yu, Haiyi, et al.. (2024). Spatiotemporal analysis of the effects of exercise on the hemodynamics of the aorta in hypertensive rats using fluid-structure interaction simulation. Journal of Translational Internal Medicine. 12(1). 64–77. 2 indexed citations
4.
Zhou, Shuduo, Yan Zhang, Na Li, et al.. (2024). Regional variations in management and outcomes of patients with acute coronary syndrome in China: Evidence from the National Chest Pain Center Program. Science Bulletin. 69(9). 1302–1312. 3 indexed citations
5.
Xu, Ming, Meiling Gao, Sikandar Amanullah, et al.. (2023). Fine genetic mapping confers a major gene controlling leaf shape variation in watermelon. Euphytica. 219(9). 5 indexed citations
6.
Tan, Xu, Jiaxing Wang, Rui Xiang, et al.. (2023). FAM3A Deficiency − Induced Mitochondrial Dysfunction Underlies Post-Infarct Mortality and Heart Failure. Journal of Cardiovascular Translational Research. 17(1). 104–120. 2 indexed citations
7.
Xu, Jie, Mingming Zhao, Anxin Wang, et al.. (2021). Association Between Plasma Trimethyllysine and Prognosis of Patients With Ischemic Stroke. Journal of the American Heart Association. 10(23). e020979–e020979. 14 indexed citations
8.
Guan, Zhiyuan, Xiaoqing Guan, Kaiyun Gu, et al.. (2020). Short-term outcomes of on- vs off-pump coronary artery bypass grafting in patients with left ventricular dysfunction: a systematic review and meta-analysis. Journal of Cardiothoracic Surgery. 15(1). 84–84. 14 indexed citations
9.
Gao, Juan, et al.. (2018). Cardiac Hypertrophy is Positively Regulated by MicroRNA-24 in Rats. Chinese Medical Journal. 131(11). 1333–1341. 13 indexed citations
10.
Tan, Wei, Jiang Zhou, Jiangyong Gu, et al.. (2016). Probing the G‑quadruplex from hsa-miR-3620-5p and inhibition of its interaction with the target sequence. Talanta. 154. 560–566. 28 indexed citations
11.
Zhang, Yuan, et al.. (2014). β2-Adrenoceptor Involved in Smoking-Induced Airway Mucus Hypersecretion through β-Arrestin-Dependent Signaling. PLoS ONE. 9(6). e97788–e97788. 22 indexed citations
12.
Zhao, Na, Haiyi Yu, Haitao Yu, et al.. (2013). miRNA-711-SP1-collagen-I pathway is involved in the anti-fibrotic effect of pioglitazone in myocardial infarction. Science China Life Sciences. 56(5). 431–439. 23 indexed citations
13.
Xu, Ming, et al.. (2012). Study on preparation of velvet antlers polypeptide by enzymatic hydrolysis. Science and Technology of Food Industry. 205–207. 1 indexed citations
14.
Xu, Ming. (2011). Establishment of primary core collection of Chinese plum(Prunus salicina) by improved least distance stepwise sampling strategy. Guoshu xuebao.
15.
Xu, Ming. (2011). Genetic Diversity Analysis of Morphological and Agronomic Characters of Chinese plum(Prunus salicina Lindl.)Germplasm. Zhiwu yichuan ziyuan xuebao. 2 indexed citations
16.
Liu, Xuehui, Fei Liu, Wei Gao, et al.. (2010). Trimetazidine inhibits pressure overload-induced cardiac fibrosis through NADPH oxidase–ROS–CTGF pathway. Cardiovascular Research. 88(1). 150–158. 69 indexed citations
17.
Zhang, Qiuping, et al.. (2009). Establishment and evaluation of primary core collection of apricot (Armeniaca vulgaris) germplasm.. Guoshu xuebao. 26(6). 819–825. 4 indexed citations
19.
Xia, Yi, Kaizheng Gong, Ming Xu, et al.. (2009). Regulation of gap-junction protein connexin 43 by β-adrenergic receptor stimulation in rat cardiomyocytes. Acta Pharmacologica Sinica. 30(7). 928–934. 26 indexed citations
20.
Ingvardsen, Christina Rønn, et al.. (2005). Molecular analysis of Sugarcane mosaic virus resistance in maize. 1 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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