Run Li

919 citations
47 papers · 585 · h-index 13

Impact in

Papers in

    • Transplantation: Methods and Outcomes 5
    • Trauma Management and Diagnosis 2
    • Physiological and biochemical adaptations 2

Run Li

44 papers receiving 578 citations

Peers

Run Li
Comparison fields: 5 of 127
  • Sensory Systems 42
  • Obstetrics and Gynecology 49
  • Transplantation 11
  • Complementary and alternative medicine 34
  • Neurology 32
Replace Nishant Sharma with:
Nishant Sharma United States
Wei‐Chuan Liao Taiwan
Hiroyasu Nakamura Japan
Arzu Yay Türkiye
Huijeong Ahn South Korea
Farnaz Farsi Iran
Ning Yu China
Dongxu Fu United States
Hadi Zare Marzouni Iran
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Citations per field
00.5×11×
Nishant Sharma · 1×
Citations per year

Countries citing papers authored by Run Li

Since Specialization
Citations

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

Fields of papers citing papers by Run Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Run 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 Run Li Line = papers co-authored together Run Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020129
2 201948
3 202341
4 202041
5 201932
6 202129
7 202320
8 201919
9 202318
10 202015
11 202313
12 202313
13 202112
14 202211
15 20209
16
[Evaluation of the dietary quality by diet balance index for pregnancy among pregnant women].
20169
17 20139
18 20238
19 20218
20 20167

About Run Li

Run Li is a scholar working on Surgery, Ecology, Obstetrics and Gynecology, Pharmacology and Neurology, having authored 47 papers that have together received 585 indexed citations. Recurring topics across this work include Transplantation: Methods and Outcomes (5 papers), Gestational Diabetes Research and Management (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (4 papers), Polyomavirus and related diseases (2 papers), Trauma Management and Diagnosis (2 papers), Physiological and biochemical adaptations (2 papers), Biological and pharmacological studies of plants (2 papers) and Viral-associated cancers and disorders (2 papers). The work is most often cited by research in Sensory Systems (42 citations), Obstetrics and Gynecology (49 citations), Transplantation (11 citations), Complementary and alternative medicine (34 citations) and Neurology (32 citations). Run Li has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Chi‐Tang Ho, Muwen Lu, Jie Xiao, Qingrong Huang, Yong Cao, Yaqi Lan, Junqing Huang, Chengyu Chen, Xiangmei Chen and Lianmei Zhong. Their work appears in journals such as Animals, BMC Pregnancy and Childbirth, Food & Function, Computers in Biology and Medicine and Pharmaceutics.

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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