Sayaka Nagata

1.3k citations
49 papers · 1.0k indexed · h-index 16

Sayaka Nagata

46 papers receiving 994 citations

Peers

Sayaka Nagata
Comparison fields: 5 of 88
  • Cardiology and Cardiovascular Medicine 566
  • Endocrinology, Diabetes and Metabolism 315
  • Cellular and Molecular Neuroscience 256
  • Genetics 139
  • Molecular Biology 440
Replace Wolf‐Eberhard Siems with:
Wolf‐Eberhard Siems Germany
Eriko Takimoto Japan
Xiemin Cao Canada
Melissa Barber Australia
Mona Oppermann Germany
Yasmin Shakur United States
Barbara A. Weaver United States
Anne-Marie Houot France
Marko Bertog Germany
Moni Nader Canada
Sayaka Nagata relative to Wolf‐Eberhard Siems Germany Wolf‐Eberhard Siems's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sayaka Nagata

Since Specialization
Citations

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

Fields of papers citing papers by Sayaka Nagata

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20238
2 20230
3 20220
4 20214
5 202113
6 20204
7 20208
8 20201
9 20206
10 201919
11 201811
12 201496
13 201319
14 201246
15 201021
16 201023
17 200910
18 20088
19 2006144
20 19923

About Sayaka Nagata

Sayaka Nagata is a scholar working on Cellular and Molecular Neuroscience, Endocrinology, Diabetes and Metabolism and Cardiology and Cardiovascular Medicine, having authored 49 papers that have together received 1.0k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (26 papers), Neuropeptides and Animal Physiology (25 papers), Renin-Angiotensin System Studies (15 papers), Hormonal Regulation and Hypertension (15 papers), Peptidase Inhibition and Analysis (8 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (5 papers), Mast cells and histamine (4 papers) and Cardiovascular, Neuropeptides, and Oxidative Stress Research (3 papers). The work is most often cited by research in Cardiology and Cardiovascular Medicine (566 citations), Endocrinology, Diabetes and Metabolism (315 citations) and Cellular and Molecular Neuroscience (256 citations). Sayaka Nagata has collaborated with scholars based in Japan, United States and Bangladesh. Frequent co-authors include Kazuo Kitamura, Johji Kato, Carlos M. Ferrario, Jasmina Varagić, Sarfaraz Ahmad, Kenji Kuwasako, Naoto Minamino, Tanenao Eto, Kazuki Sasaki and Neal D. Kon. Their work appears in journals such as SHILAP Revista de lepidopterología, Biochemical and Biophysical Research Communications 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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