Ming Lyu

916 total citations · 1 hit paper
23 papers, 693 citations indexed

About

Ming Lyu is a scholar working on Complementary and alternative medicine, Neurology and Molecular Biology. According to data from OpenAlex, Ming Lyu has authored 23 papers receiving a total of 693 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Complementary and alternative medicine, 8 papers in Neurology and 6 papers in Molecular Biology. Recurrent topics in Ming Lyu's work include Traditional Chinese Medicine Analysis (7 papers), Neurological Disease Mechanisms and Treatments (6 papers) and Neuroinflammation and Neurodegeneration Mechanisms (5 papers). Ming Lyu is often cited by papers focused on Traditional Chinese Medicine Analysis (7 papers), Neurological Disease Mechanisms and Treatments (6 papers) and Neuroinflammation and Neurodegeneration Mechanisms (5 papers). Ming Lyu collaborates with scholars based in China, United Kingdom and United States. Ming Lyu's co-authors include Yan Zhu, Guanwei Fan, Xiaoying Wang, Yuefei Wang, Shuang-yong Xu, Guangxu Xiao, Taiyi Wang, Guanwei Fan, Jigang Wang and Yuling Ma and has published in prestigious journals such as Scientific Reports, Frontiers in Immunology and Frontiers in Microbiology.

In The Last Decade

Ming Lyu

21 papers receiving 688 citations

Hit Papers

Traditional Chinese medicine in COVID-19 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Traditional Chinese medicine in COVID-19
    2021 153 citations Ming Lyu, Guanwei Fan et al. Acta Pharmaceutica Sinica B profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Lyu China 13 305 202 144 79 72 23 693
De Jin China 15 347 1.1× 198 1.0× 131 0.9× 63 0.8× 33 0.5× 52 835
Long Cheng China 17 345 1.1× 134 0.7× 56 0.4× 58 0.7× 34 0.5× 41 736
Chi Man Koon Hong Kong 19 324 1.1× 303 1.5× 230 1.6× 104 1.3× 24 0.3× 39 1000
Zezheng Gao China 15 392 1.3× 97 0.5× 101 0.7× 55 0.7× 31 0.4× 30 694
Guanwei Fan China 13 330 1.1× 107 0.5× 101 0.7× 66 0.8× 17 0.2× 31 732
Yun Hee Jeong South Korea 16 315 1.0× 86 0.4× 119 0.8× 75 0.9× 67 0.9× 41 686
Anna Bogacz Poland 15 296 1.0× 161 0.8× 108 0.8× 35 0.4× 19 0.3× 102 919
Zunpeng Shu China 17 362 1.2× 222 1.1× 149 1.0× 58 0.7× 50 0.7× 45 882
Wei Xiao China 17 452 1.5× 113 0.6× 135 0.9× 66 0.8× 47 0.7× 55 777

Countries citing papers authored by Ming Lyu

Since Specialization
Citations

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

Fields of papers citing papers by Ming Lyu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Lyu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming Lyu. A scholar is included among the top collaborators of Ming Lyu 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 Lyu. Ming Lyu 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
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Du, Hongying, Y. Lawrence Yao, Min Zhang, et al.. (2025). Protection against stroke-induced blood-brain barrier disruption by Guanxinning injection and its active-component combination via TLR4/NF-κB/MMP9-mediated neuroinflammation. Phytomedicine. 147. 157162–157162. 2 indexed citations
3.
Chen, Liping, Taiyi Wang, Ming Lyu, et al.. (2025). Identification of salvianolic acid A as an ADP receptor-selective and Gq/IP3 pathway-mediated anti-platelet component in Qishen Yiqi. Chinese Medicine. 20(1). 167–167.
4.
Liu, Jiaxu, et al.. (2024). Heart–brain interaction in cardiogenic dementia: pathophysiology and therapeutic potential. Frontiers in Cardiovascular Medicine. 11. 1304864–1304864. 12 indexed citations
5.
Peng, Zhen, Xiaolong Lv, Xintong Wang, et al.. (2023). ACT001 improved cardiovascular function in septic mice by inhibiting the production of proinflammatory cytokines and the expression of JAK-STAT signaling pathway. Frontiers in Pharmacology. 14. 1265177–1265177. 5 indexed citations
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Xiao, Guangxu, Simeng Wang, Ruijiao Wang, et al.. (2023). “Three medicines and three formulas” in COVID-19: from bench to bedside. 3(4). 309–322. 5 indexed citations
8.
Shang, Ting, Zhisen Zhang, Jing Chang, et al.. (2022). Xuebijing injection inhibited neutrophil extracellular traps to reverse lung injury in sepsis mice via reducing Gasdermin D. Frontiers in Pharmacology. 13. 1054176–1054176. 22 indexed citations
9.
Xiao, Guangxu, Jiaxu Liu, Shuang He, et al.. (2022). CXCR1 and its downstream NF-κB inflammation signaling pathway as a key target of Guanxinning injection for myocardial ischemia/reperfusion injury. Frontiers in Immunology. 13. 1007341–1007341. 13 indexed citations
10.
Liu, Dandan, Qian Zhang, Piao Luo, et al.. (2022). Neuroprotective Effects of Celastrol in Neurodegenerative Diseases-Unscramble Its Major Mechanisms of Action and Targets. Aging and Disease. 13(3). 815–815. 27 indexed citations
11.
Xiao, Guangxu, Ming Lyu, Zhixiong Li, et al.. (2021). Restoration of early deficiency of axonal guidance signaling by guanxinning injection as a novel therapeutic option for acute ischemic stroke. Pharmacological Research. 165. 105460–105460. 11 indexed citations
12.
Lyu, Ming, Guanwei Fan, Guangxu Xiao, et al.. (2021). Traditional Chinese medicine in COVID-19. Acta Pharmaceutica Sinica B. 11(11). 3337–3363. 153 indexed citations breakdown →
13.
Li, Zhixiong, Guangxu Xiao, Ming Lyu, et al.. (2020). Shuxuening injection facilitates neurofunctional recovery via down-regulation of G-CSF-mediated granulocyte adhesion and diapedesis pathway in a subacute stroke mouse model. Biomedicine & Pharmacotherapy. 127. 110213–110213. 23 indexed citations
14.
15.
Wang, Taiyi, et al.. (2019). A Network Pharmacology Study of the Multi-Targeting Profile of an Antiarrhythmic Chinese Medicine Xin Su Ning. Frontiers in Pharmacology. 10. 1138–1138. 11 indexed citations
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Lyu, Ming, Xiaoming Wang, Mei Wang, et al.. (2018). Network Pharmacology-Guided Development of a Novel Integrative Regimen to Prevent Acute Graft-vs.-Host Disease. Frontiers in Pharmacology. 9. 1440–1440. 23 indexed citations
18.
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Lyu, Ming, Haixin Liu, Taiyi Wang, et al.. (2017). Network pharmacology exploration reveals endothelial inflammation as a common mechanism for stroke and coronary artery disease treatment of Danhong injection. Scientific Reports. 7(1). 15427–15427. 80 indexed citations
20.
Lyu, Ming, Yuefei Wang, Guanwei Fan, et al.. (2017). Balancing Herbal Medicine and Functional Food for Prevention and Treatment of Cardiometabolic Diseases through Modulating Gut Microbiota. Frontiers in Microbiology. 8. 2146–2146. 163 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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