Ming‐Qing Li

12.9k citations
308 papers · 7.7k indexed · 1 hit paper · h-index 49

Impact in

Papers in

Ming‐Qing Li

294 papers receiving 7.6k citations

Hit Papers

Generative artificial intelligence and its applications in materials science: Current situation and future perspectives 2023 · 164 citations
164202320262024202550100150

Peers

Ming‐Qing Li
Comparison fields: 5 of 171
  • Obstetrics and Gynecology 2.3k
  • Reproductive Medicine 2.3k
  • Immunology 3.5k
  • Cancer Research 866
  • Cell Biology 615
Replace Mohammad Nouri with:
Mohammad Nouri Iran
Farhad Jadidi‐Niaragh Iran
Fang Fang China
Xia Zhao China
Majid Ahmadi Iran
Ying Liu China
Michael C. Ostrowski United States
Jing Dai China
Yoshihiro Komohara Japan
Lin Wang China
Ming‐Qing Li relative to Mohammad Nouri Iran Mohammad Nouri's profile →
Citations per field
00.5×3.7×
Mohammad Nouri · 1×
Citations per year

Countries citing papers authored by Ming‐Qing Li

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Qing Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ming‐Qing Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ming‐Qing Li Line = papers co-authored together Ming‐Qing Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20252
3 20250
4 20243
5 20242
6 20242
7 20241
8 20236
9 20234
10 20236
11
Generative artificial intelligence and its applications in materials science: Current situation and future perspectives
Hit paper breakdown →
2023164
12 20238
13 20232
14 20234
15 20232
16 2022118
17 2021117
18 20213
19 202011
20 201765

About Ming‐Qing Li

Ming‐Qing Li is a scholar working on Obstetrics and Gynecology, Reproductive Medicine, Immunology, Cancer Research and Biological Psychiatry, having authored 308 papers that have together received 7.7k indexed citations. Recurring topics across this work include Reproductive System and Pregnancy (157 papers), Endometriosis Research and Treatment (105 papers), Pregnancy and preeclampsia studies (56 papers), Endometrial and Cervical Cancer Treatments (27 papers), Uterine Myomas and Treatments (25 papers), Pregnancy and Medication Impact (18 papers), Cancer, Hypoxia, and Metabolism (12 papers) and Preterm Birth and Chorioamnionitis (10 papers). The work is most often cited by research in Obstetrics and Gynecology (2.3k citations), Reproductive Medicine (2.3k citations), Immunology (3.5k citations), Cancer Research (866 citations) and Cell Biology (615 citations). Ming‐Qing Li has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Da‐Jin Li, Jie Mei, Hui‐Li Yang, Wen‐Jie Zhou, Kai‐Kai Chang, Liping Jin, Xiao‐Yong Zhu, Jun Shao, Feng Xie and Huaping Li. Their work appears in journals such as American Journal of Reproductive Immunology, Reproduction, Journal of Reproductive Immunology, International Journal of Biological Sciences and Biomolecules.

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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