Jin Yang

2.4k citations
77 papers · 1.9k · h-index 27

Impact in

Papers in

    • Pancreatic function and diabetes 22
    • Metabolism, Diabetes, and Cancer 7
    • Pluripotent Stem Cells Research 4

Jin Yang

74 papers receiving 1.8k citations

Peers

Jin Yang
Comparison fields: 5 of 102
  • Endocrinology, Diabetes and Metabolism 586
  • Nephrology 173
  • Surgery 456
  • Endocrine and Autonomic Systems 61
  • Physiology 213
Replace Harvest F. Gu with:
Harvest F. Gu China
Yukichi Okuda Japan
Elizabeth A. Kirk United States
Robyn Cunard United States
David R. Powell United States
Hirobumi Tokuyama Japan
Takeshi Kanda Japan
Lakshmi Pulakat United States
Charles W. Heilig United States
Yusaku Mori Japan
Jin Yang relative to Harvest F. Gu China Harvest F. Gu's profile →
Citations per field
00.5×2×3.4×
Harvest F. Gu · 1×
Citations per year

Countries citing papers authored by Jin Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jin Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 77 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017150
2 2016117
3 200790
4 202076
5 201374
6 201466
7 199866
8 201966
9 200258
10 201457
11 201654
12 202045
13 200339
14 200237
15 201936
16 202334
17 200133
18 201733
19 202032
20 201732

About Jin Yang

Jin Yang is a scholar working on Surgery, Molecular Biology, Endocrinology, Diabetes and Metabolism, Physiology and Genetics, having authored 77 papers that have together received 1.9k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (22 papers), Diabetes Treatment and Management (15 papers), Metabolism, Diabetes, and Cancer (7 papers), Parathyroid Disorders and Treatments (6 papers), Nitric Oxide and Endothelin Effects (4 papers), Diabetes and associated disorders (4 papers), Diabetes Management and Research (4 papers) and Pluripotent Stem Cells Research (4 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (586 citations), Nephrology (173 citations), Surgery (456 citations), Endocrine and Autonomic Systems (61 citations) and Physiology (213 citations). Jin Yang has collaborated with scholars based in China, Japan and United States. Frequent co-authors include Tianpei Hong, Rui Wei, Ye Liu, Toshio Ogihara, Kun Yang, Junling Liu, Haining Wang, Qing Tian, Keisuke Fukuo and Jing Ke. Their work appears in journals such as Peptides, Diabetes/Metabolism Research and Reviews, American Journal of Physiology-Endocrinology and Metabolism, PLoS ONE and Acta Diabetologica.

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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