Takeshi Hashitani

42 total papers · 429 total citations
26 papers, 363 citations indexed

About

Takeshi Hashitani is a scholar working on Cellular and Molecular Neuroscience, Neurology and Developmental Neuroscience. According to data from OpenAlex, Takeshi Hashitani has authored 26 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cellular and Molecular Neuroscience, 5 papers in Neurology and 5 papers in Developmental Neuroscience. Recurrent topics in Takeshi Hashitani's work include Nerve injury and regeneration (9 papers), Neurotransmitter Receptor Influence on Behavior (6 papers) and Neuroscience and Neuropharmacology Research (6 papers). Takeshi Hashitani is often cited by papers focused on Nerve injury and regeneration (9 papers), Neurotransmitter Receptor Influence on Behavior (6 papers) and Neuroscience and Neuropharmacology Research (6 papers). Takeshi Hashitani collaborates with scholars based in Japan, Hungary and United States. Takeshi Hashitani's co-authors include Hitoo Nishino, Michiko Kumazaki, Hideki Hida, Hitoo Nishino, Yoshiaki Isobe, Hitoe Nishino, Fujiya Furuyama, Haruhiko Sato, Yasunobu Shimano and András Czurkó and has published in prestigious journals such as Brain Research, Progress in brain research and Brain Research Bulletin.

In The Last Decade

Takeshi Hashitani

26 papers receiving 358 citations

Author Peers

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

Author Last Decade Papers Cites
Takeshi Hashitani 249 101 93 93 87 26 363
Kyohei Kin 142 0.6× 69 0.7× 105 1.1× 111 1.2× 106 1.2× 27 390
Charlotte M. Ermine 127 0.5× 59 0.6× 146 1.6× 58 0.6× 58 0.7× 20 327
Xiaoqi Hong 119 0.5× 71 0.7× 116 1.2× 72 0.8× 94 1.1× 14 330
Kumiko Yokouchi 211 0.8× 147 1.5× 40 0.4× 44 0.5× 73 0.8× 37 386
Juliann D. Jaumotte 162 0.7× 50 0.5× 143 1.5× 109 1.2× 53 0.6× 15 350
David J. Marmion 195 0.8× 47 0.5× 192 2.1× 192 2.1× 91 1.0× 14 396
Sachiyo Misumi 91 0.4× 97 1.0× 102 1.1× 88 0.9× 65 0.7× 17 363
Shuhua Mu 190 0.8× 38 0.4× 122 1.3× 76 0.8× 54 0.6× 26 377
Joan Carreres Polo 91 0.4× 42 0.4× 76 0.8× 74 0.8× 59 0.7× 32 390
Kozo Saito 149 0.6× 35 0.3× 135 1.5× 48 0.5× 167 1.9× 23 368

Countries citing papers authored by Takeshi Hashitani

Since Specialization
Citations

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

Fields of papers citing papers by Takeshi Hashitani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Takeshi Hashitani

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