Makoto Kinouchi
- Molecular Biology top 10%
- Genomics and Phylogenetic Studies 13
- RNA and protein synthesis mechanisms 10
- Machine Learning in Bioinformatics 9
- Fractal and DNA sequence analysis 6
- RNA modifications and cancer 6
- Oncology top 10%
- Colorectal Cancer Treatments and Studies 7
- Gastroenterology top 10%
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- Gastric Cancer Management and Outcomes 9
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- Neural Networks and Applications 7
- Co-authors
- Shigehiko KanayaToshimichi IkemuraTakashi AbeYoshihiro KudoYuko YamadaIwao SasakiKoh MiuraChikashi Shibata
- Cited by
- Molecular BiologyOncologyImmunology
- Journals
- Nucleic Acids Research (2 papers)Journal of Clinical Oncology (1 paper)Gastroenterology (1 paper)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Makoto Kinouchi
68 papers receiving 1.8k citations
Peers
Comparison fields: 5 of 131
- Molecular Biology 1.1k
- Oncology 379
- Immunology 196
- Cancer Research 134
- Gastroenterology 47
Countries citing papers authored by Makoto Kinouchi
This map shows the geographic impact of Makoto Kinouchi'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 Makoto Kinouchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Makoto Kinouchi more than expected).
Fields of papers citing papers by Makoto Kinouchi
This network shows the impact of papers produced by Makoto Kinouchi. 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 Makoto Kinouchi. The network helps show where Makoto Kinouchi may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Makoto Kinouchi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2012 | 19 | |
| 2 | 2012 | 9 | |
| 3 | 2011 | 1 | |
| 4 | 2011 | 0 | |
| 5 | 2011 | 0 | |
| 6 | 2010 | 20 | |
| 7 | 2009 | 2 | |
| 8 | 2009 | 1 | |
| 9 | 2009 | 15 | |
| 10 | 2008 | 1 | |
| 11 | 2008 | 1 | |
| 12 | 2007 | 1 | |
| 13 | 2007 | 0 | |
| 14 | A novel bioinformatics strategy for phylogenetic study of genomic sequence fragments: Self-organizing map (SOM) of oligonucleotide frequencies | 2005 | 2 |
| 15 | 2005 | 87 | |
| 16 | 2005 | 2 | |
| 17 | 2004 | 1 | |
| 18 | 2001 | 139 | |
| 19 | 2001 | 1 | |
| 20 | 2000 | 11 |
About Makoto Kinouchi
Makoto Kinouchi is a scholar working on Gastroenterology, Oncology and Otorhinolaryngology, having authored 77 papers that have together received 1.9k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (13 papers), RNA and protein synthesis mechanisms (10 papers), Machine Learning in Bioinformatics (9 papers), Gastric Cancer Management and Outcomes (9 papers), Colorectal Cancer Treatments and Studies (7 papers), Neural Networks and Applications (7 papers), Fractal and DNA sequence analysis (6 papers) and RNA modifications and cancer (6 papers). The work is most often cited by research in Molecular Biology (1.1k citations), Oncology (379 citations) and Immunology (196 citations). Makoto Kinouchi has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Shigehiko Kanaya, Toshimichi Ikemura, Takashi Abe, Yoshihiro Kudo, Yuko Yamada, Iwao Sasaki, Koh Miura, Chikashi Shibata, Takayuki Mizoi and Wataru Fujibuchi. Their work appears in journals such as Nucleic Acids Research, Journal of Clinical Oncology and Gastroenterology.
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.