Weijun Jin

37 papers receiving 2.4k citations

Peers

Weijun Jin
Comparison fields: 5 of 89
  • Endocrinology, Diabetes and Metabolism 602
  • Cardiology and Cardiovascular Medicine 604
  • Cancer Research 372
  • Surgery 1.1k
  • Biochemistry 148
Replace Sumeet A. Khetarpal with:
Sumeet A. Khetarpal United States
Allen D. Cooper United States
Joseph C. Obunike United States
Sally P.A. McCormick New Zealand
J M Hoeg United States
Patrizia Tarugi Italy
Ilia V. Fuki United States
Ruud Out Netherlands
Fumihiko Matsuura Japan
Ginny Kellner-Weibel United States
Weijun Jin relative to Sumeet A. Khetarpal United States Sumeet A. Khetarpal's profile →
Citations per field
00.5×1.5×2×2.3×
Sumeet A. Khetarpal · 1×
Citations per year

Countries citing papers authored by Weijun Jin

Since Specialization
Citations

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

Fields of papers citing papers by Weijun Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004554
2 2008353
3 2003189
4 2011120
5 2007114
6 2003106
7 2003101
8 200699
9 201099
10 200588
11 200271
12 200463
13 200447
14 201247
15 201146
16 200542
17 200240
18 200537
19 201235
20 201131

About Weijun Jin

Weijun Jin is a scholar working on Endocrinology, Diabetes and Metabolism, Biochemistry, Cardiology and Cardiovascular Medicine, Surgery and Cancer Research, having authored 38 papers that have together received 2.5k indexed citations. Recurring topics across this work include Diabetes, Cardiovascular Risks, and Lipoproteins (16 papers), Lipid metabolism and disorders (15 papers), Lipid metabolism and biosynthesis (10 papers), Lipoproteins and Cardiovascular Health (4 papers), Cholesterol and Lipid Metabolism (3 papers), Pancreatic function and diabetes (3 papers), Diet, Metabolism, and Disease (2 papers) and Metabolism, Diabetes, and Cancer (2 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (602 citations), Cardiology and Cardiovascular Medicine (604 citations), Cancer Research (372 citations), Surgery (1.1k citations) and Biochemistry (148 citations). Weijun Jin has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Daniel James Rader, Jane M. Glick, John S. Millar, Uli C. Broedl, Nabil Georges Seidah, Dawn H.L. Marchadier, Rachid Essalmani, Annik Prat, Josée Hamelin and Suzanne Benjannet. Their work appears in journals such as Journal of Biological Chemistry, Journal of Clinical Investigation, Circulation Research, Journal of Lipid Research and Arteriosclerosis Thrombosis and Vascular Biology.

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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