Kunio Takishima

75 total papers · 2.2k total citations
61 papers, 1.8k citations indexed

About

Kunio Takishima is a scholar working on Molecular Biology, Oncology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Kunio Takishima has authored 61 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 11 papers in Oncology and 9 papers in Cellular and Molecular Neuroscience. Recurrent topics in Kunio Takishima's work include Neurogenesis and neuroplasticity mechanisms (8 papers), Protein Kinase Regulation and GTPase Signaling (7 papers) and Enzyme Production and Characterization (6 papers). Kunio Takishima is often cited by papers focused on Neurogenesis and neuroplasticity mechanisms (8 papers), Protein Kinase Regulation and GTPase Signaling (7 papers) and Enzyme Production and Characterization (6 papers). Kunio Takishima collaborates with scholars based in Japan, United States and Mexico. Kunio Takishima's co-authors include Gunji Mamiya, Yasushi Satoh, Tatsuko Suga, Masataka Ito, Marsha Rich Rosner, Junko Imaki, Hideki Miyao, Maiko Satomoto, Osamu Imamura and Mitsuhiro Yamada and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Neuroscience.

In The Last Decade

Kunio Takishima

61 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
Kunio Takishima 803 516 336 278 205 61 1.8k
Kuanyu Li 950 1.2× 139 0.3× 142 0.4× 34 0.1× 52 0.3× 63 1.8k
Sabera Ruždijić 835 1.0× 371 0.7× 223 0.7× 179 0.6× 244 1.2× 93 1.8k
Jun Young Heo 829 1.0× 157 0.3× 123 0.4× 90 0.3× 136 0.7× 103 2.1k
Clarissa von Haefen 736 0.9× 204 0.4× 153 0.5× 80 0.3× 267 1.3× 48 1.4k
Jing Wu 1.1k 1.4× 198 0.4× 161 0.5× 54 0.2× 176 0.9× 96 2.2k
Thomas E. Nelson 1.1k 1.4× 60 0.1× 98 0.3× 146 0.5× 102 0.5× 76 2.0k
Haixia Lü 834 1.0× 316 0.6× 66 0.2× 42 0.2× 192 0.9× 81 1.9k
Nikola Tanić 859 1.1× 130 0.3× 82 0.2× 67 0.2× 354 1.7× 67 1.5k
Dayun Feng 763 1.0× 111 0.2× 35 0.1× 18 0.1× 93 0.5× 76 1.8k
Sufang Liu 680 0.8× 47 0.1× 34 0.1× 32 0.1× 286 1.4× 90 1.6k

Countries citing papers authored by Kunio Takishima

Since Specialization
Citations

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

Fields of papers citing papers by Kunio Takishima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kunio Takishima

This figure shows the co-authorship network connecting the top 25 collaborators of Kunio Takishima. A scholar is included among the top collaborators of Kunio Takishima 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 Kunio Takishima. Kunio Takishima 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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2026