Jin Su

1.2k citations
46 papers · 867 · h-index 20

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
  • Nephrology top 10%
    • Acute Kidney Injury Research

Papers in

Jin Su

42 papers receiving 854 citations

Peers

Jin Su
Comparison fields: 5 of 96
  • Cancer Research 161
  • Nephrology 57
  • Cardiology and Cardiovascular Medicine 131
  • Endocrinology, Diabetes and Metabolism 91
  • Virology 26
Replace Mark A. Dominick with:
Mark A. Dominick United States
Stuart Levin United States
Mehdi Rasouli Iran
Jiahua Li China
Surinder Cheema‐Dhadli Canada
Mehmet Köseoğlu Türkiye
Xuguang Li China
Yogesh Saini United States
Aleš Hořínek Czechia
Frank Harris United States
Jin Su relative to Mark A. Dominick United States Mark A. Dominick's profile →
Citations per field
00.5×10×14.2×
Mark A. Dominick · 1×
Citations per year

Countries citing papers authored by Jin Su

Since Specialization
Citations

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

Fields of papers citing papers by Jin Su

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201791
2 200662
3 200258
4 201146
5 201743
6 201641
7 201936
8 201734
9 201633
10 201728
11 200228
12 201327
13 202027
14 200225
15 201923
16 201323
17 201823
18 200420
19 201419
20 200319

About Jin Su

Jin Su is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine, Nutrition and Dietetics, Nephrology and Endocrinology, Diabetes and Metabolism, having authored 46 papers that have together received 867 indexed citations. Recurring topics across this work include Renin-Angiotensin System Studies (5 papers), Fatty Acid Research and Health (5 papers), Acute Kidney Injury Research (4 papers), Chronic Kidney Disease and Diabetes (2 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Receptor Mechanisms and Signaling (2 papers) and Hormonal Regulation and Hypertension (2 papers). The work is most often cited by research in Cancer Research (161 citations), Nephrology (57 citations), Cardiology and Cardiovascular Medicine (131 citations), Endocrinology, Diabetes and Metabolism (91 citations) and Virology (26 citations). Jin Su has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Choon Nam Ong, Katsuo Kanmatsuse, Noboru Fukuda, Rob M. van Dam, Woon‐Puay Koh, Yimu Lai, Yoshiko Tahira, Yukihiro Ikeda, Ryo Suzuki and Zhangli Liu. Their work appears in journals such as Journal of Cardiovascular Pharmacology, Nutrients, Biochemical and Biophysical Research Communications, American Journal of Hypertension and Hypertension.

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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