Jin Pan

708 citations
37 papers · 503 · h-index 14

Impact in

Papers in

Jin Pan

34 papers receiving 495 citations

Peers

Jin Pan
Comparison fields: 5 of 83
  • Endocrinology, Diabetes and Metabolism 94
  • Cancer Research 40
  • Cardiology and Cardiovascular Medicine 50
  • Public Health, Environmental and Occupational Health 58
  • Physiology 39
Replace See Kwok with:
See Kwok United Kingdom
Tsogzolmaa Dorjgochoo United States
Hongzhi Wang China
Łukasz Szczerbiński Poland
Claire L. Le Guen United States
Zsigmond Kósa Hungary
Clicerio González United States
Ahmad Reza Soroush Iran
Walter Willet United States
Carla Márcia Moreira Lanna Brazil
Jin Pan relative to See Kwok United Kingdom See Kwok's profile →
Citations per field
00.5×1.5×
See Kwok · 1×
Citations per year

Countries citing papers authored by Jin Pan

Since Specialization
Citations

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

Fields of papers citing papers by Jin Pan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201369
2 201556
3 201641
4 201938
5 201435
6 201727
7 201922
8 202021
9 201917
10 201115
11 201514
12 201014
13 201713
14 201913
15 201612
16 202012
17 201911
18 202111
19 201911
20 20218

About Jin Pan

Jin Pan is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology, Cardiology and Cardiovascular Medicine, Physiology and Clinical Psychology, having authored 37 papers that have together received 503 indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (6 papers), Metabolism, Diabetes, and Cancer (3 papers), Smoking Behavior and Cessation (3 papers), Nutritional Studies and Diet (2 papers), Cardiovascular Health and Risk Factors (2 papers), Banking stability, regulation, efficiency (1 paper), Obesity, Physical Activity, Diet (1 paper) and Gestational Diabetes Research and Management (1 paper). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (94 citations), Cancer Research (40 citations), Cardiology and Cardiovascular Medicine (50 citations), Public Health, Environmental and Occupational Health (58 citations) and Physiology (39 citations). Jin Pan has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Weiwei Gong, Min Yu, Ruying Hu, Ruying Hu, Qingfang He, Hao Wang, Haibin Wu, Danting Su, Lixin Wang and Zhen Ye. Their work appears in journals such as Journal of Diabetes Investigation, PLoS ONE, Frontiers in Public Health, Journal of Clinical Laboratory Analysis and Tobacco Induced Diseases.

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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