Keiichi Matsuda

54 total papers · 452 total citations
34 papers, 370 citations indexed

About

Keiichi Matsuda is a scholar working on Molecular Biology, Pharmacology and Agronomy and Crop Science. According to data from OpenAlex, Keiichi Matsuda has authored 34 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Pharmacology and 6 papers in Agronomy and Crop Science. Recurrent topics in Keiichi Matsuda's work include Inflammatory mediators and NSAID effects (8 papers), Estrogen and related hormone effects (4 papers) and Protein Kinase Regulation and GTPase Signaling (3 papers). Keiichi Matsuda is often cited by papers focused on Inflammatory mediators and NSAID effects (8 papers), Estrogen and related hormone effects (4 papers) and Protein Kinase Regulation and GTPase Signaling (3 papers). Keiichi Matsuda collaborates with scholars based in Japan, United States and United Kingdom. Keiichi Matsuda's co-authors include Mitsuo Yamazaki, Shigeru Ushiyama, Yorihisa Tanaka, Fumitoshi Asai, Masahiko Sugimoto, Takeshi Oshima, Hideyuki Haruyama, Akira Okuno, K. Ikeda and Seiichi KAWAMURA and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Journal of Medicinal Chemistry and Archives of Biochemistry and Biophysics.

In The Last Decade

Keiichi Matsuda

34 papers receiving 349 citations

Author Peers

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

Author						Papers	Cites
Keiichi Matsuda	141	126	47	47	40	34	370
Minoru Tsuboi	166 1.2×	82 0.7×	26 0.6×	65 1.4×	52 1.3×	36	415
R. K. Banerjee	218 1.5×	38 0.3×	44 0.9×	71 1.5×	58 1.4×	22	423
Peter S. Cammarata	193 1.4×	80 0.6×	24 0.5×	21 0.4×	22 0.6×	15	384
F. von Bruchhausen	145 1.0×	78 0.6×	34 0.7×	26 0.6×	49 1.2×	23	420
Raymond J. Bowers	221 1.6×	93 0.7×	62 1.3×	23 0.5×	28 0.7×	19	383
Takashi Uesugi	119 0.8×	47 0.4×	59 1.3×	56 1.2×	64 1.6×	45	445
Fumie Nakashima	160 1.1×	30 0.2×	31 0.7×	45 1.0×	22 0.6×	23	368
Leonid Kaluzhskiy	147 1.0×	42 0.3×	29 0.6×	19 0.4×	77 1.9×	47	337
Pushkaraj J. Lad	240 1.7×	37 0.3×	62 1.3×	105 2.2×	22 0.6×	23	440
Xin Li	209 1.5×	41 0.3×	18 0.4×	49 1.0×	32 0.8×	24	442

Countries citing papers authored by Keiichi Matsuda

Since Specialization

Citations

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

Fields of papers citing papers by Keiichi Matsuda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keiichi Matsuda

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