Jin Yan

1.2k citations
34 papers · 968 · h-index 16

Impact in

  • Aging top 10%
  • Physiology top 10%
    • Calcium signaling and nucleotide metabolism

Papers in

    • Signaling Pathways in Disease 4
    • FOXO transcription factor regulation 3
    • Atherosclerosis and Cardiovascular Diseases 4
    • Reproductive System and Pregnancy 4
    • Immune cells in cancer 3

Jin Yan

34 papers receiving 958 citations

Peers

Jin Yan
Comparison fields: 5 of 91
  • Aging 27
  • Physiology 50
  • Cancer Research 163
  • Epidemiology 319
  • Cell Biology 135
Replace Raffaella Iurlaro with:
Raffaella Iurlaro Spain
My Chouinard United States
Jian Fang China
Sarbari Saha India
Yanjiao Wang China
Saori Morino‐Koga Japan
Luciano Galdieri United States
Xu Zhao China
Jin Yan relative to Raffaella Iurlaro Spain Raffaella Iurlaro's profile →
Citations per field
00.5×1.5×1.8×
Raffaella Iurlaro · 1×
Citations per year

Countries citing papers authored by Jin Yan

Since Specialization
Citations

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

Fields of papers citing papers by Jin Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998113
2 2017100
3 2000100
4 200694
5 199887
6 199974
7 201952
8 200841
9 200532
10 200631
11 201829
12 201129
13 202026
14 202025
15 202019
16 201816
17 201713
18 200812
19 201011
20
STAT5 inhibitor attenuates atherosclerosis via inhibition of inflammation: the role of STAT5 in atherosclerosis.
202111

About Jin Yan

Jin Yan is a scholar working on Molecular Biology, Immunology, Cancer Research, Cellular and Molecular Neuroscience and Public Health, Environmental and Occupational Health, having authored 34 papers that have together received 968 indexed citations. Recurring topics across this work include Signaling Pathways in Disease (4 papers), Atherosclerosis and Cardiovascular Diseases (4 papers), MicroRNA in disease regulation (4 papers), Reproductive System and Pregnancy (4 papers), Cell Adhesion Molecules Research (3 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), FOXO transcription factor regulation (3 papers) and Immune cells in cancer (3 papers). The work is most often cited by research in Aging (27 citations), Physiology (50 citations), Cancer Research (163 citations), Epidemiology (319 citations) and Cell Biology (135 citations). Jin Yan has collaborated with scholars based in China, Canada and Japan. Frequent co-authors include Barbara F. Hales, Hidehito Kuroyanagi, Takuji Shirasawa, Boyang Yu, Masa-aki Muramatsu, Yoichi Matsuda, Asato Kuroiwa, Junping Kou, Noriko Okazaki and Yasuhiko Masuho. Their work appears in journals such as Biomedicine & Pharmacotherapy, Journal of Pharmacology and Experimental Therapeutics, Toxicological Sciences, Pesticide Biochemistry and Physiology and Bioscience Reports.

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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