Jun Agata

1.7k citations
26 papers · 1.4k · h-index 20

Impact in

Papers in

Jun Agata

26 papers receiving 1.3k citations

Peers

Jun Agata
Comparison fields: 5 of 95
  • Genetics 328
  • Endocrine and Autonomic Systems 154
  • Cardiology and Cardiovascular Medicine 319
  • Endocrinology, Diabetes and Metabolism 175
  • Cellular and Molecular Neuroscience 190
Replace Wolfgang Auch–Schwelk with:
Wolfgang Auch–Schwelk Germany
Hans‐Dieter Orzechowski Germany
Katsutoshi Yayama Japan
Jiang Xu United States
Michelle P. Winn United States
Cendrine Cabou France
Vijaya Karoor United States
Anthony J. Arleth United States
Yun-He Liu United States
Shinichi Hirotani Japan
Jun Agata relative to Wolfgang Auch–Schwelk Germany Wolfgang Auch–Schwelk's profile →
Citations per field
00.5×3.8×
Wolfgang Auch–Schwelk · 1×
Citations per year

Countries citing papers authored by Jun Agata

Since Specialization
Citations

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

Fields of papers citing papers by Jun Agata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 26 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1997201
2 2002146
3 2003113
4 2006112
5 200280
6 200276
7 200575
8 200069
9 200567
10 200261
11 200052
12 200252
13 200144
14 200444
15 199529
16 199924
17 200023
18 200422
19 199821
20 200319

About Jun Agata

Jun Agata is a scholar working on Genetics, Molecular Biology, Cardiology and Cardiovascular Medicine, Physiology and Cellular and Molecular Neuroscience, having authored 26 papers that have together received 1.4k indexed citations. Recurring topics across this work include Coagulation, Bradykinin, Polyphosphates, and Angioedema (9 papers), Neuropeptides and Animal Physiology (4 papers), Nitric Oxide and Endothelin Effects (3 papers), Receptor Mechanisms and Signaling (3 papers), Peptidase Inhibition and Analysis (3 papers), Blood Coagulation and Thrombosis Mechanisms (3 papers), Diet and metabolism studies (3 papers) and Adenosine and Purinergic Signaling (2 papers). The work is most often cited by research in Genetics (328 citations), Endocrine and Autonomic Systems (154 citations), Cardiology and Cardiovascular Medicine (319 citations), Endocrinology, Diabetes and Metabolism (175 citations) and Cellular and Molecular Neuroscience (190 citations). Jun Agata has collaborated with scholars based in United States, Japan and Italy. Frequent co-authors include Julie Chao, Lee Chao, Hideaki Yoshida, Qing Miao, Hang Yin, Nobuyuki Ura, Robert S. Smith, Kazuaki Shimamoto, Eric Dobrzynski and Lee Chao. Their work appears in journals such as Hypertension Research, American Journal of Hypertension, Hypertension, Arteriosclerosis Thrombosis and Vascular Biology and Circulation Journal.

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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