John Li

5.8k citations
83 papers · 4.1k · h-index 31

Impact in

Papers in

John Li

81 papers receiving 4.0k citations

Peers

John Li
Comparison fields: 5 of 114
  • Biochemistry 928
  • Epidemiology 1.5k
  • Endocrinology, Diabetes and Metabolism 648
  • Cell Biology 550
  • Rheumatology 432
Replace Harold F. Sims with:
Harold F. Sims United States
J.E.M. Groener Netherlands
Sophie Vaulont France
Donald K. Scott United States
Yael Pewzner‐Jung Israel
Kook Hwan Kim South Korea
Nuria Martínez-López United States
Yup Kang South Korea
Hueng-Sik Choi South Korea
Katherine T. Landschulz United States
John Li relative to Harold F. Sims United States Harold F. Sims's profile →
Citations per field
00.5×12×
Harold F. Sims · 1×
Citations per year

Countries citing papers authored by John Li

Since Specialization
Citations

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

Fields of papers citing papers by John Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside John 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 John Li Line = papers co-authored together John Li 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 2009469
2 2010309
3 2014279
4 2012228
5 2008220
6 2009201
7 2010194
8 2015175
9 2007152
10 2008138
11 2017100
12 201695
13 201692
14 200881
15 201573
16 202366
17 201262
18 201160
19 201857
20 199653

About John Li

John Li is a scholar working on Molecular Biology, Biochemistry, Epidemiology, Rheumatology and Oncology, having authored 83 papers that have together received 4.1k indexed citations. Recurring topics across this work include Lipid metabolism and biosynthesis (13 papers), Heterotopic Ossification and Related Conditions (10 papers), Adipose Tissue and Metabolism (9 papers), Liver Disease Diagnosis and Treatment (7 papers), Cancer-related molecular mechanisms research (5 papers), Metabolism, Diabetes, and Cancer (4 papers), HER2/EGFR in Cancer Research (4 papers) and Lipid metabolism and disorders (4 papers). The work is most often cited by research in Biochemistry (928 citations), Epidemiology (1.5k citations), Endocrinology, Diabetes and Metabolism (648 citations), Cell Biology (550 citations) and Rheumatology (432 citations). John Li has collaborated with scholars based in United States, China and Hong Kong. Frequent co-authors include Helen H. Hobbs, Jonathan C. Cohen, Yongcheng Huang, Shaoqing He, Peng Li, Christopher McPhaul, Nick V. Grishin, Rita Garuti, Lisa N. Kinch and Jing Ye. Their work appears in journals such as Diabetes, Journal of Biological Chemistry, American Journal Of Pathology, Proceedings of the National Academy of Sciences and The EMBO Journal.

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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