Li Kang

5.8k citations
83 papers · 4.3k · 2 hit papers · h-index 32

Impact in

Papers in

Li Kang

81 papers receiving 4.2k citations

Li Kang's Hit Papers

The membrane receptor CD44: novel insights into metabolism 2022 · 158 citations
1580+5+11Years since publication250500750

Peers

Li Kang
Comparison fields: 5 of 133
  • Physiology 1.5k
  • Geriatrics and Gerontology 87
  • Cell Biology 431
  • Molecular Biology 1.7k
  • Biochemistry 171
Replace José E. Galgani with:
José E. Galgani Chile
Julio Cesar Batista Ferreira Brazil
Annika Höhn Germany
Wenhong Cao China
Yuehua Li China
Goo Taeg Oh South Korea
Marie‐Agnès Chauvin France
Margaret F. Gregor United States
Ryan P. McMillan United States
Jeong‐a Kim United States
Li Kang relative to José E. Galgani Chile José E. Galgani's profile →
Citations per field
00.5×1.5×
José E. Galgani · 1×
Citations per year

Countries citing papers authored by Li Kang

Since Specialization
Citations

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

Fields of papers citing papers by Li Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 83 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mitochondrial H2O2 emission and cellular redox state link excess fat intake to insulin resistance in both rodents and humans
Hit paper breakdown →
2009999
2 2014200
3 2016177
4 2015174
5 2006173
6
The membrane receptor CD44: novel insights into metabolism
Hit paper breakdown →
2022158
7 2007146
8 2011134
9 2021128
10 2015126
11 2010120
12 2013108
13 200794
14 200792
15 201485
16 201378
17 201068
18 201764
19 201459
20 201659

About Li Kang

Li Kang is a scholar working on Molecular Biology, Physiology, Epidemiology, Cell Biology and Immunology, having authored 83 papers that have together received 4.3k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (15 papers), Adipokines, Inflammation, and Metabolic Diseases (11 papers), Metabolism, Diabetes, and Cancer (7 papers), Nutrition and Health in Aging (7 papers), Proteoglycans and glycosaminoglycans research (5 papers), Lipid metabolism and biosynthesis (5 papers), Immune cells in cancer (4 papers) and Pancreatic function and diabetes (4 papers). The work is most often cited by research in Physiology (1.5k citations), Geriatrics and Gerontology (87 citations), Cell Biology (431 citations), Molecular Biology (1.7k citations) and Biochemistry (171 citations). Li Kang has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include David H. Wasserman, P. Darrell Neufer, Chien‐Te Lin, Ethan J. Anderson, Kristen E. Boyle, Hazel H. Szeto, Ronald N. Cortright, Jesse W. Price, Daniel A. Kane and Peter S. Rabinovitch. Their work appears in journals such as Diabetes, PLoS ONE, Diabetologia, Journal of Biological Chemistry and International Journal of Molecular Sciences.

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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