Jun Dai

33 papers receiving 816 citations

Peers

Jun Dai
Comparison fields: 5 of 106
  • Biological Psychiatry 81
  • Behavioral Neuroscience 51
  • Public Health, Environmental and Occupational Health 220
  • Nutrition and Dietetics 84
  • Physiology 132
Replace Beom Seuk Hwang with:
Beom Seuk Hwang South Korea
Huaixing Li China
Jialin Fu China
Bo Xie China
Khalid K. Abdul‐Razzak Jordan
Jaana Leiviskä Finland
Anthony Villani Australia
Georgios Valsamakis Greece
Pei-an Betty Shih United States
Sharmin Hossain United States
Jun Dai relative to Beom Seuk Hwang South Korea Beom Seuk Hwang's profile →
Citations per field
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Beom Seuk Hwang · 1×
Citations per year

Countries citing papers authored by Jun Dai

Since Specialization
Citations

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

Fields of papers citing papers by Jun Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 36 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008212
2 2008124
3 2007123
4 200747
5 200844
6 201337
7 200837
8 201736
9 201035
10 201525
11
The relationship between media exposure and mental health problems during COVID-19 outbreak
202016
12 200112
13 201612
14
[Impact of cytochrome P450 2C19 polymorphisms on outcome of cardiovascular events in clopidogrel-treated Chinese patients after percutaneous coronary intervention].
201111
15 201410
16 201310
17 20109
18 20099
19 20148
20 20136

About Jun Dai

Jun Dai is a scholar working on Public Health, Environmental and Occupational Health, Molecular Biology, Epidemiology, Cardiology and Cardiovascular Medicine and General Health Professions, having authored 36 papers that have together received 847 indexed citations. Recurring topics across this work include Obesity, Physical Activity, Diet (4 papers), Nutritional Studies and Diet (4 papers), Epigenetics and DNA Methylation (3 papers), Healthcare professionals’ stress and burnout (3 papers), Fatty Acid Research and Health (2 papers), Rheumatoid Arthritis Research and Therapies (2 papers), Employment and Welfare Studies (2 papers) and Workplace Health and Well-being (2 papers). The work is most often cited by research in Biological Psychiatry (81 citations), Behavioral Neuroscience (51 citations), Public Health, Environmental and Occupational Health (220 citations), Nutrition and Dietetics (84 citations) and Physiology (132 citations). Jun Dai has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Viola Vaccarino, Jack Goldberg, Linda Jones, Peter W.F. Wilson, Lucy Shallenberger, Thomas R. Ziegler, Andrew H. Miller, J. Douglas Bremner, Nancy Murrah and Dean P. Jones. Their work appears in journals such as American Journal of Clinical Nutrition, Metabolism, Journal of Nutrition, Annals of Human Genetics and Circulation.

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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