Jun Agata

1.7k citations
26 papers · 1.3k indexed · h-index 19

Jun Agata

26 papers receiving 1.3k citations

Peers

Jun Agata
Comparison fields: 5 of 95
  • Genetics 327
  • Endocrine and Autonomic Systems 170
  • Cardiology and Cardiovascular Medicine 377
  • Endocrinology, Diabetes and Metabolism 197
  • Cellular and Molecular Neuroscience 194
Replace Anna Franca Milia with:
Anna Franca Milia Italy
Wolfgang Auch–Schwelk Germany
Jiang Xu United States
Katsutoshi Yayama Japan
Lawrence de Garavilla United States
Cendrine Cabou France
Shinichi Hirotani Japan
Stefan Amisten Sweden
Vijaya Karoor United States
Yun-He Liu United States
Jun Agata relative to Anna Franca Milia Italy Anna Franca Milia's profile →
Citations per field
00.5×5.2×
Anna Franca Milia · 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-authorship network

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
#Work
1 200717
2 2006111
3 200610
4 200570
5 200421
6 200443
7 200318
8 200258
9 2002144
10 200141
11 200062
12 200016
13 200049
14 200021
15 19993
16 199924
17 19986
18 199821
19 1997198
20 199528

About Jun Agata

Jun Agata is a scholar working on Genetics, Physiology, Cardiology and Cardiovascular Medicine, Hematology and Cellular and Molecular Neuroscience, having authored 26 papers that have together received 1.3k indexed citations. Recurring topics across this work include Coagulation, Bradykinin, Polyphosphates, and Angioedema (9 papers), Nitric Oxide and Endothelin Effects (4 papers), Renin-Angiotensin System Studies (4 papers), Neuropeptides and Animal Physiology (4 papers), Diet and metabolism studies (3 papers), Peptidase Inhibition and Analysis (3 papers), Blood Coagulation and Thrombosis Mechanisms (3 papers) and Receptor Mechanisms and Signaling (3 papers). The work is most often cited by research in Genetics (327 citations), Endocrine and Autonomic Systems (170 citations), Cardiology and Cardiovascular Medicine (377 citations), Endocrinology, Diabetes and Metabolism (197 citations) and Cellular and Molecular Neuroscience (194 citations). Jun Agata has collaborated with scholars based in Japan, United States and Italy. Frequent co-authors include Julie Chao, Lee Chao, Hideaki Yoshida, Qing Miao, Hang Yin, Nobuyuki Ura, Kazuaki Shimamoto, Robert S. Smith, Eric Dobrzynski and Kazuo Kato. Their work appears in journals such as Hypertension Research, Hypertension, American Journal of Hypertension, Arteriosclerosis Thrombosis and Vascular Biology and Diabetes.

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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