Jun Kanno

12.8k total citations · 3 hit papers
194 papers, 8.5k citations indexed

About

Jun Kanno is a scholar working on Molecular Biology, Health, Toxicology and Mutagenesis and Genetics. According to data from OpenAlex, Jun Kanno has authored 194 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Molecular Biology, 34 papers in Health, Toxicology and Mutagenesis and 29 papers in Genetics. Recurrent topics in Jun Kanno's work include Carcinogens and Genotoxicity Assessment (18 papers), Effects and risks of endocrine disrupting chemicals (18 papers) and Estrogen and related hormone effects (17 papers). Jun Kanno is often cited by papers focused on Carcinogens and Genotoxicity Assessment (18 papers), Effects and risks of endocrine disrupting chemicals (18 papers) and Estrogen and related hormone effects (17 papers). Jun Kanno collaborates with scholars based in Japan, United States and Sri Lanka. Jun Kanno's co-authors include Katsuhide Igarashi, Satoshi Kitajima, Akihiko Hirose, Yumiko Saga, Atsuya Takagi, Tohru Inoue, Fumiaki Ohtake, Yuuki Imai, Benson T. Akingbemi and Cheryl S. Watson and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jun Kanno

191 papers receiving 8.4k citations

Hit Papers

Estrogen Prevents Bone Loss via Estrogen Receptor α and I... 2007 2026 2013 2019 2007 2007 2008 250 500 750

Peers

Jun Kanno
Comparison fields: 5 of 171
  • Molecular Biology 3.6k
  • Health, Toxicology and Mutagenesis 1.9k
  • Genetics 1.3k
  • Oncology 1.0k
  • Cancer Research 947
Replace David Dinsdale with:
David Dinsdale United Kingdom
Jeffrey I. Everitt United States
Pinpin Lin Taiwan
Xinru Wang China
Rodrigo Franco United States
Kyung‐Sun Kang South Korea
Thomas B. Knudsen United States
Kyung‐Chul Choi South Korea
M. Prakash Hande Singapore
Xiaodong Han China
David Dinsdale United Kingdom View profile →
Citations per field, relative to Jun Kanno
Jun Kanno · 1×
Citations per year, relative to Jun Kanno
Jun Kanno · 1×

Countries citing papers authored by Jun Kanno

Since Specialization
Citations

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

Fields of papers citing papers by Jun Kanno

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jun Kanno

This figure shows the co-authorship network connecting the top 25 collaborators of Jun Kanno. A scholar is included among the top collaborators of Jun Kanno 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 Jun Kanno. Jun Kanno is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 10
3 2
4 1
5 6
6 13
7 145
8 25
9 143
10 47
11 25
12 32
13
In vitro molecular mechanisms of bisphenol A action breakdown →
750
14 255
15 32
16 80
17 118
18 1
19 194
20 5

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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