Mako Nakamura

109 total papers · 2.0k total citations
68 papers, 1.6k citations indexed

About

Mako Nakamura is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, Mako Nakamura has authored 68 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 9 papers in Cellular and Molecular Neuroscience and 8 papers in Physiology. Recurrent topics in Mako Nakamura's work include Muscle Physiology and Disorders (22 papers), RNA Research and Splicing (10 papers) and Nerve injury and regeneration (7 papers). Mako Nakamura is often cited by papers focused on Muscle Physiology and Disorders (22 papers), RNA Research and Splicing (10 papers) and Nerve injury and regeneration (7 papers). Mako Nakamura collaborates with scholars based in Japan, United States and Canada. Mako Nakamura's co-authors include Takafumi Nagamine, Yoshimi Benno, Kiyoshi Tajima, Rustam Aminov, Hiroki Matsui, Ryuichi Tatsumi, Wataru Mizunoya, Yoshihide Ikeuchi, Charles G. Sagerström and Yusuke Sato and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Applied and Environmental Microbiology.

In The Last Decade

Mako Nakamura

65 papers receiving 1.6k citations

Hit Papers

Diet-Dependent Shifts in ... 2001 2026 2009 2017 2001 100 200 300 400 500

Author Peers

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

Author Last Decade Papers Cites
Mako Nakamura 841 429 203 196 181 68 1.6k
Michelle A. Lane 1.1k 1.2× 243 0.6× 373 1.8× 135 0.7× 158 0.9× 66 1.9k
Gordon K. Murdoch 529 0.6× 172 0.4× 236 1.2× 251 1.3× 43 0.2× 76 1.6k
G. A. Stewart 705 0.8× 254 0.6× 99 0.5× 231 1.2× 70 0.4× 63 1.7k
Annette Sørensen 873 1.0× 344 0.8× 333 1.6× 191 1.0× 92 0.5× 47 2.3k
Ying Xiong 677 0.8× 110 0.3× 238 1.2× 106 0.5× 88 0.5× 101 2.2k
Karl‐Heinz Wrobel 527 0.6× 240 0.6× 512 2.5× 69 0.4× 136 0.8× 106 1.7k
Ha Thi Thanh Tran 808 1.0× 132 0.3× 193 1.0× 83 0.4× 136 0.8× 51 1.5k
Udaya DeSilva 708 0.8× 755 1.8× 423 2.1× 198 1.0× 43 0.2× 57 2.2k
Jianbin Li 1.0k 1.2× 257 0.6× 644 3.2× 86 0.4× 63 0.3× 120 2.1k
Kate Powell 603 0.7× 88 0.2× 97 0.5× 88 0.4× 121 0.7× 53 1.4k

Countries citing papers authored by Mako Nakamura

Since Specialization
Citations

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

Fields of papers citing papers by Mako Nakamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mako Nakamura

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