Masayuki Kanki

23 total papers · 450 total citations
15 papers, 363 citations indexed

About

Masayuki Kanki is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Masayuki Kanki has authored 15 papers receiving a total of 363 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Cancer Research and 3 papers in Genetics. Recurrent topics in Masayuki Kanki's work include MicroRNA in disease regulation (4 papers), Carcinogens and Genotoxicity Assessment (3 papers) and Genomics, phytochemicals, and oxidative stress (2 papers). Masayuki Kanki is often cited by papers focused on MicroRNA in disease regulation (4 papers), Carcinogens and Genotoxicity Assessment (3 papers) and Genomics, phytochemicals, and oxidative stress (2 papers). Masayuki Kanki collaborates with scholars based in Japan and Netherlands. Masayuki Kanki's co-authors include Akira Unami, Hajime Tsujimoto, Munekazu NAKAICHI, Yasuyuki Momoi, Sanenori NAKAMA, Daisuke Sasaki, Atsushi Yamada, Akira Moriguchi, Kunitoshi Mitsumori and Yuji Oishi and has published in prestigious journals such as Toxicological Sciences, Toxicology and Toxicology Letters.

In The Last Decade

Masayuki Kanki

15 papers receiving 361 citations

Author Peers

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

Author Last Decade Papers Cites
Masayuki Kanki 208 136 48 45 43 15 363
Hanqing Guo 169 0.8× 94 0.7× 44 0.9× 27 0.6× 20 0.5× 17 311
Jing Yang 178 0.9× 69 0.5× 49 1.0× 90 2.0× 36 0.8× 15 364
Sang Hyun Song 242 1.2× 58 0.4× 82 1.7× 30 0.7× 55 1.3× 22 394
Xingdong Cai 163 0.8× 76 0.6× 74 1.5× 55 1.2× 19 0.4× 23 324
Hongyan Chen 163 0.8× 69 0.5× 99 2.1× 53 1.2× 25 0.6× 22 353
Toshinori Oinuma 172 0.8× 46 0.3× 36 0.8× 28 0.6× 55 1.3× 22 341
Qingyuan Zhang 271 1.3× 57 0.4× 52 1.1× 66 1.5× 12 0.3× 19 365
Hong Liu 224 1.1× 74 0.5× 48 1.0× 31 0.7× 22 0.5× 19 386
Juchao Ren 220 1.1× 106 0.8× 59 1.2× 43 1.0× 16 0.4× 25 365
Zhaohu Xie 192 0.9× 62 0.5× 20 0.4× 30 0.7× 26 0.6× 17 321

Countries citing papers authored by Masayuki Kanki

Since Specialization
Citations

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

Fields of papers citing papers by Masayuki Kanki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Masayuki Kanki

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