Nobuyoshi Suto

35 total papers · 999 total citations
20 papers, 773 citations indexed

About

Nobuyoshi Suto is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Nobuyoshi Suto has authored 20 papers receiving a total of 773 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cellular and Molecular Neuroscience, 14 papers in Molecular Biology and 5 papers in Cognitive Neuroscience. Recurrent topics in Nobuyoshi Suto's work include Neurotransmitter Receptor Influence on Behavior (16 papers), Receptor Mechanisms and Signaling (13 papers) and Neuroscience and Neuropharmacology Research (11 papers). Nobuyoshi Suto is often cited by papers focused on Neurotransmitter Receptor Influence on Behavior (16 papers), Receptor Mechanisms and Signaling (13 papers) and Neuroscience and Neuropharmacology Research (11 papers). Nobuyoshi Suto collaborates with scholars based in United States, United Kingdom and Japan. Nobuyoshi Suto's co-authors include Paul Vezina, Jennifer D. Austin, Roy A. Wise, Daniel S. Lorrain, Lauren M. Tanabe, Laurel E. Ecke, Zhi‐Bing You, Bruce T. Hope, Gregory I. Elmer and Tony M. Kerr and has published in prestigious journals such as Nature Communications, Journal of Neuroscience and SHILAP Revista de lepidopterología.

In The Last Decade

Nobuyoshi Suto

17 papers receiving 762 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Nobuyoshi Suto 681 390 193 129 87 20 773
P. Soubri� 592 0.9× 266 0.7× 198 1.0× 97 0.8× 97 1.1× 16 783
Shinshu Nakajima 565 0.8× 249 0.6× 262 1.4× 126 1.0× 84 1.0× 32 757
Daniel Benjamin 688 1.0× 280 0.7× 223 1.2× 141 1.1× 152 1.7× 22 902
Ernest N. Damianopoulos 609 0.9× 228 0.6× 234 1.2× 109 0.8× 66 0.8× 40 711
Harinder Aujla 511 0.8× 282 0.7× 199 1.0× 106 0.8× 102 1.2× 21 700
J. D. Belluzzi 556 0.8× 357 0.9× 127 0.7× 139 1.1× 79 0.9× 13 792
Rebecca J. Ralph 516 0.8× 354 0.9× 141 0.7× 110 0.9× 102 1.2× 11 786
Gerald A. Deehan 534 0.8× 260 0.7× 155 0.8× 80 0.6× 97 1.1× 31 681
Andrew McGeehan 443 0.7× 297 0.8× 109 0.6× 117 0.9× 111 1.3× 13 639
Gary Vickers 607 0.9× 299 0.8× 128 0.7× 100 0.8× 49 0.6× 10 679

Countries citing papers authored by Nobuyoshi Suto

Since Specialization
Citations

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

Fields of papers citing papers by Nobuyoshi Suto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nobuyoshi Suto

This figure shows the co-authorship network connecting the top 25 collaborators of Nobuyoshi Suto. A scholar is included among the top collaborators of Nobuyoshi Suto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Nobuyoshi Suto. Nobuyoshi Suto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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