Keying Li

1.0k citations
35 papers · 800 · h-index 18

Impact in

Papers in

    • ATP Synthase and ATPases Research 3
    • Bone Metabolism and Diseases 3
    • Cancer-related gene regulation 3
    • Gut microbiota and health 2
    • Complement system in diseases 8

Keying Li

30 papers receiving 796 citations

Peers

Keying Li
Comparison fields: 5 of 92
  • Immunology 243
  • Hematology 86
  • Nephrology 45
  • Molecular Biology 367
  • Biological Psychiatry 12
Replace Ge Shi with:
Ge Shi China
Syed S. Asghar Netherlands
Kenji Daigo Japan
Nannan Zhou China
Yvonne Bordon United States
Justyna Rybka Poland
Timothy P. LaBranche United States
Yanan Xu China
Louis Hollingsworth United States
Mingfu Tian China
Keying Li relative to Ge Shi China Ge Shi's profile →
Citations per field
00.5×3.2×
Ge Shi · 1×
Citations per year

Countries citing papers authored by Keying Li

Since Specialization
Citations

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

Fields of papers citing papers by Keying Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 35 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202091
2 200384
3 201167
4 200757
5 201054
6 201242
7 201440
8 200938
9 202036
10 202333
11 200830
12 201027
13 201127
14 201224
15 201023
16 200322
17 202219
18 200918
19 201617
20 202211

About Keying Li

Keying Li is a scholar working on Molecular Biology, Immunology, Hematology, Physiology and Pediatrics, Perinatology and Child Health, having authored 35 papers that have together received 800 indexed citations. Recurring topics across this work include Complement system in diseases (8 papers), Blood groups and transfusion (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), ATP Synthase and ATPases Research (3 papers), Bone Metabolism and Diseases (3 papers), Erythrocyte Function and Pathophysiology (3 papers), Cancer-related gene regulation (3 papers) and Gut microbiota and health (2 papers). The work is most often cited by research in Immunology (243 citations), Hematology (86 citations), Nephrology (45 citations), Molecular Biology (367 citations) and Biological Psychiatry (12 citations). Keying Li has collaborated with scholars based in China, United Kingdom and United States. Frequent co-authors include Stephen J. Perkins, Ruodan Nan, Morris F. Manolson, Yeqi Yao, Sanaullah Khan, Johan N.M. Heersche, Jayesh Gor, Zhenhua Hao, Azubuike I. Okemefuna and Ami Miller. Their work appears in journals such as Journal of Molecular Biology, Journal of Biological Chemistry, Journal of Cellular Biochemistry, Genes and Acta Pharmaceutica Sinica B.

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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