Naoya Ichimura

39 total papers · 1.7k total citations
14 papers, 167 citations indexed

About

Naoya Ichimura is a scholar working on Infectious Diseases, Surgery and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Naoya Ichimura has authored 14 papers receiving a total of 167 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Infectious Diseases, 5 papers in Surgery and 4 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Naoya Ichimura's work include Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers) and SARS-CoV-2 detection and testing (3 papers). Naoya Ichimura is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers) and SARS-CoV-2 detection and testing (3 papers). Naoya Ichimura collaborates with scholars based in Japan. Naoya Ichimura's co-authors include Minoru Tozuka, Ryunosuke Ohkawa, Shuji Tohda, Seiichi Urushiyama, Hiroshi Shibuyà, Junko Hyodo‐Miura, Misato Yamada, Shigeo Okubo, Bisei Ohkawara and Yutaka Yatomi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and BioMed Research International.

In The Last Decade

Naoya Ichimura

14 papers receiving 166 citations

Author Peers

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

Author Last Decade Papers Cites
Naoya Ichimura 60 49 40 29 20 14 167
V. Spagnolo 52 0.9× 54 1.1× 22 0.6× 36 1.2× 5 0.3× 9 245
Tomokazu Nunoue 45 0.8× 122 2.5× 32 0.8× 24 0.8× 22 1.1× 16 273
Virginie Brès 89 1.5× 25 0.5× 39 1.0× 43 1.5× 8 0.4× 11 207
Wen-Sen Lee 58 1.0× 101 2.1× 64 1.6× 46 1.6× 20 1.0× 13 290
Jean‐Baptiste Julla 35 0.6× 33 0.7× 40 1.0× 58 2.0× 7 0.3× 21 173
Sarah Ellul 77 1.3× 21 0.4× 19 0.5× 11 0.4× 7 0.3× 10 140
Manickam Chidambaram 80 1.3× 50 1.0× 20 0.5× 33 1.1× 11 0.6× 11 195
Takami Komatsu 121 2.0× 33 0.7× 72 1.8× 17 0.6× 47 2.4× 17 283
Xing Liu 56 0.9× 18 0.4× 31 0.8× 30 1.0× 21 1.1× 14 165
Maarten Criel 60 1.0× 75 1.5× 24 0.6× 11 0.4× 56 2.8× 16 223

Countries citing papers authored by Naoya Ichimura

Since Specialization
Citations

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

Fields of papers citing papers by Naoya Ichimura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naoya Ichimura

This figure shows the co-authorship network connecting the top 25 collaborators of Naoya Ichimura. A scholar is included among the top collaborators of Naoya Ichimura 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 Naoya Ichimura. Naoya Ichimura 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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