Mai Sakai

51 total papers · 675 total citations
35 papers, 461 citations indexed

About

Mai Sakai is a scholar working on Neurology, Molecular Biology and Clinical Psychology. According to data from OpenAlex, Mai Sakai has authored 35 papers receiving a total of 461 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Neurology, 9 papers in Molecular Biology and 8 papers in Clinical Psychology. Recurrent topics in Mai Sakai's work include Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Tryptophan and brain disorders (8 papers) and COVID-19 and Mental Health (5 papers). Mai Sakai is often cited by papers focused on Neuroinflammation and Neurodegeneration Mechanisms (10 papers), Tryptophan and brain disorders (8 papers) and COVID-19 and Mental Health (5 papers). Mai Sakai collaborates with scholars based in Japan, Canada and United Kingdom. Mai Sakai's co-authors include Hiroaki Tomita, Zhiqian Yu, Yuta Takahashi, Seii Ohka, Miharu Nakanishi, Akio Nomoto, Hiroko Igarashi, Zhiqian Yu, Satoshi Sasaki and Yoshie Kikuchi and has published in prestigious journals such as Journal of Virology, International Journal of Molecular Sciences and European Journal of Neuroscience.

In The Last Decade

Mai Sakai

31 papers receiving 446 citations

Author Peers

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

Author Last Decade Papers Cites
Mai Sakai 121 83 80 64 58 35 461
Adonis Sfera 147 1.2× 72 0.9× 54 0.7× 19 0.3× 35 0.6× 44 445
Yan Lan 42 0.3× 82 1.0× 44 0.6× 33 0.5× 109 1.9× 41 535
Michael D. Kritzer 314 2.6× 45 0.5× 91 1.1× 106 1.7× 67 1.2× 25 548
Carolina Osorio 151 1.2× 59 0.7× 43 0.5× 13 0.2× 27 0.5× 22 460
Xiaoyun Guo 170 1.4× 40 0.5× 55 0.7× 12 0.2× 30 0.5× 49 475
Youbin Kang 83 0.7× 28 0.3× 75 0.9× 18 0.3× 36 0.6× 32 432
Graham Blackman 47 0.4× 36 0.4× 132 1.6× 22 0.3× 97 1.7× 37 548
Tamy Colonetti 33 0.3× 37 0.4× 40 0.5× 26 0.4× 23 0.4× 39 440
Mayra Pérez-Tapia 103 0.9× 27 0.3× 86 1.1× 6 0.1× 49 0.8× 21 533
Teja W. Grömer 183 1.5× 42 0.5× 78 1.0× 14 0.2× 24 0.4× 17 513

Countries citing papers authored by Mai Sakai

Since Specialization
Citations

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

Fields of papers citing papers by Mai Sakai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mai Sakai

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