Shinya Ikematsu

58 total papers · 2.3k total citations
43 papers, 1.9k citations indexed

About

Shinya Ikematsu is a scholar working on Molecular Biology, Cell Biology and Immunology and Allergy. According to data from OpenAlex, Shinya Ikematsu has authored 43 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 26 papers in Cell Biology and 8 papers in Immunology and Allergy. Recurrent topics in Shinya Ikematsu's work include Proteoglycans and glycosaminoglycans research (24 papers), Glycosylation and Glycoproteins Research (19 papers) and Fibroblast Growth Factor Research (9 papers). Shinya Ikematsu is often cited by papers focused on Proteoglycans and glycosaminoglycans research (24 papers), Glycosylation and Glycoproteins Research (19 papers) and Fibroblast Growth Factor Research (9 papers). Shinya Ikematsu collaborates with scholars based in Japan, China and United States. Shinya Ikematsu's co-authors include Sadatoshi Sakuma, Kenji Kadomatsu, Takashi Muramatsu, Hisako Muramatsu, Masaharu Noda, T. Muramatsu, Takashi Muramatsu, Kun Zou, Nahoko Sakaguchi and Keiko Ichihara-Tanaka and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Cancer.

In The Last Decade

Shinya Ikematsu

43 papers receiving 1.8k citations

Author Peers

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

Author Last Decade Papers Cites
Shinya Ikematsu 1.1k 945 297 249 194 43 1.9k
Aikaterini Berdiaki 869 0.8× 723 0.8× 315 1.1× 296 1.2× 145 0.7× 55 1.6k
Nikolaos A. Afratis 1.0k 1.0× 816 0.9× 366 1.2× 391 1.6× 149 0.8× 27 2.1k
Vicente A. Torres 1.4k 1.3× 882 0.9× 238 0.8× 325 1.3× 190 1.0× 61 2.1k
Sanna Oikari 889 0.8× 606 0.6× 266 0.9× 282 1.1× 268 1.4× 47 1.5k
Toshiyuki Murai 1.1k 1.0× 527 0.6× 213 0.7× 385 1.5× 144 0.7× 52 1.9k
Enzo Calautti 1.5k 1.4× 683 0.7× 616 2.1× 230 0.9× 307 1.6× 38 2.3k
Manuel A. Pallero 917 0.8× 524 0.6× 202 0.7× 240 1.0× 296 1.5× 28 1.7k
Munenori Takaoka 1.3k 1.2× 636 0.7× 464 1.6× 356 1.4× 161 0.8× 80 2.0k
Paola Moretto 818 0.8× 762 0.8× 121 0.4× 278 1.1× 126 0.6× 39 1.5k
Patricia Abbe 942 0.9× 1.1k 1.2× 316 1.1× 178 0.7× 310 1.6× 23 1.9k

Countries citing papers authored by Shinya Ikematsu

Since Specialization
Citations

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

Fields of papers citing papers by Shinya Ikematsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shinya Ikematsu

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