Tatsuya Akutsu

13.9k citations
378 papers · 9.2k indexed · 1 hit paper · h-index 48
Topics
Gene Regulatory Network Analysis (90 papers)Bioinformatics and Genomic Networks (89 papers)Machine Learning in Bioinformatics (75 papers)
Journals
Nucleic Acids ResearchNature CommunicationsSHILAP Revista de lepidopterología
Partner nations
JapanChinaAustralia

In The Last Decade

Tatsuya Akutsu

362 papers receiving 8.9k citations

Hit Papers

iLearn: an integrated platform and meta-learner for featu...20192026202120232019100200300

Peers

Tatsuya Akutsu
Comparison fields: 5 of 186
  • Molecular Biology 7.4k
  • Computational Theory and Mathematics 1.4k
  • Artificial Intelligence 884
  • Genetics 483
  • Cancer Research 390
Replace Jinbo Xu with:
Jinbo Xu United States
Reinhard Schneider Germany
Dong Xu United States
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Charles DeLisi United States
Jean‐Philippe Vert France
Michal Linial Israel
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Haiyuan Yu United States
Tatsuya Akutsu relative to Jinbo Xu United States Jinbo Xu's profile →
Citations per field
00.5×1.5×1.9×
Jinbo Xu · 1×
Citations per year

Countries citing papers authored by Tatsuya Akutsu

Since Specialization
Citations

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

Fields of papers citing papers by Tatsuya Akutsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tatsuya Akutsu

This figure shows the co-authorship network connecting the top 25 collaborators of Tatsuya Akutsu. A scholar is included among the top collaborators of Tatsuya Akutsu 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 Tatsuya Akutsu. Tatsuya Akutsu 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 0
2 1
3 1
4 2
5 5
6 27
7 1
8 5
9 8
10 0
11 74
12 15
13 3
14 9
15 16
16 69
17 2
18 3
19
Comparison and Enumeration of Chemical Graphs
0
20 462

About Tatsuya Akutsu

Tatsuya Akutsu is a scholar working on Computational Theory and Mathematics, Molecular Biology and Artificial Intelligence, having authored 378 papers that have together received 9.2k indexed citations. Recurring topics across this work include Gene Regulatory Network Analysis (90 papers), Bioinformatics and Genomic Networks (89 papers) and Machine Learning in Bioinformatics (75 papers). The work is most often cited by research in Molecular Biology (7.4k citations), Computational Theory and Mathematics (1.4k citations) and Microbiology (246 citations). Tatsuya Akutsu has collaborated with scholars based in Japan, China and Australia. Frequent co-authors include Jiangning Song, Satoru Miyano, Satoru Kuhara, Morihiro Hayashida, Jose C. Nacher, Geoffrey I. Webb, Fuyi Li, Wai‐Ki Ching, Michael K. Ng and Nobuhisa Ueda. Their work appears in journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

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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