Kentaro Ito

1.8k citations
27 papers · 1.3k indexed · 1 hit paper · h-index 12
Topics
Slime Mold and Myxomycetes Research (9 papers)Plant and Biological Electrophysiology Studies (6 papers)Biocrusts and Microbial Ecology (6 papers)
Partner nations
JapanAustraliaSweden

In The Last Decade

Kentaro Ito

27 papers receiving 1.2k citations

Hit Papers

Rules for Biologically Inspired Adaptive Network Design20102026201520202010100200300400500

Peers

Kentaro Ito
Comparison fields: 5 of 127
  • Biomedical Engineering 537
  • Ecology, Evolution, Behavior and Systematics 333
  • Plant Science 233
  • Electronic, Optical and Magnetic Materials 188
  • Condensed Matter Physics 157
Replace Takeshi Inoue with:
Takeshi Inoue Japan
Saurabh A. Chandorkar United States
Eldwin J. Ng United States
Chae Hyuck Ahn United States
Vu A. Hong United States
Derek E. Moulton United Kingdom
Shirin Ghaffari United States
David Armitage United States
Nicholas W. Roberts United Kingdom
Michael Leitner Austria
Kentaro Ito relative to Takeshi Inoue Japan Takeshi Inoue's profile →
Citations per field
00.5×3.2×
Takeshi Inoue · 1×
Citations per year

Countries citing papers authored by Kentaro Ito

Since Specialization
Citations

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

Fields of papers citing papers by Kentaro Ito

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kentaro Ito

This figure shows the co-authorship network connecting the top 25 collaborators of Kentaro Ito. A scholar is included among the top collaborators of Kentaro Ito 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 Kentaro Ito. Kentaro Ito 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
#WorkIndexed citations
1 8
2 12
3 38
4 4
5 60
6 1
7 10
8 9
9 28
10 14
11 6
12 86
13 1
14 59
15
Rules for Biologically Inspired Adaptive Network Designbreakdown →
557
16 10
17 9
18 10
19 3
20 77

About Kentaro Ito

Kentaro Ito is a scholar working on Developmental Biology, Ecology, Evolution, Behavior and Systematics and Paleontology, having authored 27 papers that have together received 1.3k indexed citations. Recurring topics across this work include Slime Mold and Myxomycetes Research (9 papers), Plant and Biological Electrophysiology Studies (6 papers) and Biocrusts and Microbial Ecology (6 papers). The work is most often cited by research in Ecology, Evolution, Behavior and Systematics (333 citations), Condensed Matter Physics (157 citations) and Biomedical Engineering (537 citations). Kentaro Ito has collaborated with scholars based in Japan, Australia and Sweden. Frequent co-authors include Toshiyuki Nakagaki, Ryo Kobayashi, Tetsu Saigusa, Mark D. Fricker, Daniel P. Bebber, Atsushi Tero, Seiji Takagi, Yukio Hinatsu, Makoto Wakeshima and Yoshihiro Doi. Their work appears in journals such as Science, The Journal of Physical Chemistry B and Scientific Reports.

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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