Masahiko Terada

35 total papers · 843 total citations
29 papers, 732 citations indexed

About

Masahiko Terada is a scholar working on Cellular and Molecular Neuroscience, Physiology and Molecular Biology. According to data from OpenAlex, Masahiko Terada has authored 29 papers receiving a total of 732 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Cellular and Molecular Neuroscience, 13 papers in Physiology and 10 papers in Molecular Biology. Recurrent topics in Masahiko Terada's work include Pain Mechanisms and Treatments (11 papers), Nerve injury and regeneration (7 papers) and Botulinum Toxin and Related Neurological Disorders (4 papers). Masahiko Terada is often cited by papers focused on Pain Mechanisms and Treatments (11 papers), Nerve injury and regeneration (7 papers) and Botulinum Toxin and Related Neurological Disorders (4 papers). Masahiko Terada collaborates with scholars based in Japan and United States. Masahiko Terada's co-authors include Hitoshi Yasuda, Ryuichi Kikkawa, Kengo Maeda, Masakazu Haneda, Atsunori Kashiwagi, Mitsuru Sanada, Yukio Shigeta, Ikuo Hatanaka, Masanobu Sonobe and Ryuichi Kikkawa and has published in prestigious journals such as Diabetes, Biochemical and Biophysical Research Communications and Journal of Neurochemistry.

In The Last Decade

Masahiko Terada

29 papers receiving 714 citations

Author Peers

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

Author Last Decade Papers Cites
Masahiko Terada 378 277 192 142 138 29 732
Nádia Pereira Gonçalves 294 0.8× 261 0.9× 202 1.1× 108 0.8× 329 2.4× 26 883
C. G. Rasool 257 0.7× 216 0.8× 251 1.3× 110 0.8× 245 1.8× 26 746
Mette Richner 335 0.9× 402 1.5× 131 0.7× 69 0.5× 276 2.0× 26 885
Mitsuru Sanada 327 0.9× 202 0.7× 214 1.1× 46 0.3× 181 1.3× 43 848
John H. Mayer 397 1.1× 182 0.7× 144 0.8× 277 2.0× 101 0.7× 24 790
Yoshiyuki Mitsui 269 0.7× 247 0.9× 314 1.6× 57 0.4× 121 0.9× 36 757
L.T. Diemel 436 1.2× 451 1.6× 176 0.9× 81 0.6× 145 1.1× 18 868
Andres Deik 223 0.6× 188 0.7× 373 1.9× 85 0.6× 139 1.0× 32 716
Carla Porretta‐Serapiglia 267 0.7× 143 0.5× 197 1.0× 74 0.5× 204 1.5× 17 648
You‐Yong Tian 132 0.3× 195 0.7× 195 1.0× 63 0.4× 240 1.7× 34 746

Countries citing papers authored by Masahiko Terada

Since Specialization
Citations

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

Fields of papers citing papers by Masahiko Terada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masahiko Terada

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