Jun Cheng

1.1k citations
36 papers · 855 · h-index 16

Impact in

Papers in

Jun Cheng

34 papers receiving 834 citations

Peers

Jun Cheng
Comparison fields: 5 of 109
  • Cardiology and Cardiovascular Medicine 290
  • Complementary and alternative medicine 77
  • Endocrinology, Diabetes and Metabolism 94
  • Molecular Biology 284
  • Cancer Research 62
Replace Corey E. Tabit with:
Corey E. Tabit United States
Ren Luo China
Guanchang Cheng China
Danny J. Eapen United States
Sergey Bolevich Russia
Guogang Zhang China
Wenjing Zhao China
Xiaowei Zheng China
Xinwen Min China
Xiao‐Cheng Liu China
Jun Cheng relative to Corey E. Tabit United States Corey E. Tabit's profile →
Citations per field
00.5×1.5×2.0×
Corey E. Tabit · 1×
Citations per year

Countries citing papers authored by Jun Cheng

Since Specialization
Citations

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

Fields of papers citing papers by Jun Cheng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jun Cheng, 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 Cheng Line = papers co-authored together Jun Cheng 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 2010326
2 201277
3 201153
4 202035
5 200934
6 201728
7 202127
8 201824
9 201322
10 201121
11 201821
12 202316
13 201916
14 201816
15 199116
16 201316
17 201814
18 201913
19 200413
20 202312

About Jun Cheng

Jun Cheng is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Surgery, Oncology and Cellular and Molecular Neuroscience, having authored 36 papers that have together received 855 indexed citations. Recurring topics across this work include Traditional Chinese Medicine Analysis (5 papers), Single-cell and spatial transcriptomics (4 papers), Nitric Oxide and Endothelin Effects (3 papers), Neuroscience and Neuropharmacology Research (3 papers), Peptidase Inhibition and Analysis (3 papers), Hormonal Regulation and Hypertension (3 papers), Ion channel regulation and function (3 papers) and Angiogenesis and VEGF in Cancer (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (290 citations), Complementary and alternative medicine (77 citations), Endocrinology, Diabetes and Metabolism (94 citations), Molecular Biology (284 citations) and Cancer Research (62 citations). Jun Cheng has collaborated with scholars based in China, United Kingdom and Saint Kitts and Nevis. Frequent co-authors include Pengyun Li, Yan Yang, Jing Liu, Dong Zhao, Pamela G. Coxson, Yuming Shen, Kirsten Bibbins‐Domingo, Y. Claire Wang, Dongfeng Gu and Lee Goldman. Their work appears in journals such as Hypertension, European Journal of Pharmacology, Journal of Molecular and Cellular Cardiology, The Journals of Gerontology Series A and Frontiers in Pharmacology.

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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