Koichiro Doi
Impact in
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- Amyotrophic Lateral Sclerosis Research
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- Neurogenetic and Muscular Disorders Research
Papers in
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- Algorithms and Data Compression 3
- Co-authors
- Jun Yoshimura (17 shared papers)Shinichi Morishita (17 shared papers)Hiroyuki Ishiura (16 shared papers)Shoji Tsuji (16 shared papers)Jun Mitsui (16 shared papers)Hiroshi Imai (3 shared papers)Jun Goto (8 shared papers)Yuji Takahashi (6 shared papers)
- Journals
- Journal of the Neurological Sciences (3 papers)Japanese Journal of Applied Physics (2 papers)Bioinformatics (1 paper)The Cerebellum (1 paper)Sensors and Actuators B Chemical (1 paper)
- Partner nations
- JapanUnited States
In The Last Decade
Koichiro Doi
30 papers receiving 433 citations
Peers
Comparison fields: 5 of 68
- Neurology 76
- Genetics 42
- Molecular Biology 266
- Genetics 102
- Cellular and Molecular Neuroscience 56
Countries citing papers authored by Koichiro Doi
This map shows the geographic impact of Koichiro Doi'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 Koichiro Doi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Koichiro Doi more than expected).
Fields of papers citing papers by Koichiro Doi
This network shows the impact of papers produced by Koichiro Doi. 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 Koichiro Doi. The network helps show where Koichiro Doi may publish in the future.
Co-authors
The 25 scholars most cited alongside Koichiro Doi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 71 | |
| 2 | 2013 | 66 | |
| 3 | 2013 | 48 | |
| 4 | 2017 | 39 | |
| 5 | 2018 | 27 | |
| 6 | 2003 | 27 | |
| 7 | 2016 | 20 | |
| 8 | A Greedy Algorithm for Minimizing the Number of Primers in Multiple PCR Experiments. | 1999 | 19 |
| 9 | 2017 | 16 | |
| 10 | 2016 | 13 | |
| 11 | 2020 | 12 | |
| 12 | Greedy Algorithms for Finding a Small Set of Primers Satisfying Cover and Length Resolution Conditions in PCR Experiments. | 1997 | 12 |
| 13 | 2016 | 11 | |
| 14 | 2020 | 10 | |
| 15 | 2017 | 10 | |
| 16 | 2020 | 9 | |
| 17 | 2018 | 7 | |
| 18 | 2019 | 4 | |
| 19 | 2013 | 4 | |
| 20 | Sequencing by hybridization in the presence of hybridization errors. | 2000 | 4 |
About Koichiro Doi
Koichiro Doi is a scholar working on Molecular Biology, Artificial Intelligence, Genetics, Neurology and Aerospace Engineering, having authored 33 papers that have together received 445 indexed citations. Recurring topics across this work include Neurogenetic and Muscular Disorders Research (5 papers), Human auditory perception and evaluation (5 papers), Amyotrophic Lateral Sclerosis Research (4 papers), Rough Sets and Fuzzy Logic (4 papers), Metabolism and Genetic Disorders (3 papers), Data Mining Algorithms and Applications (3 papers), Genetic Neurodegenerative Diseases (3 papers) and Algorithms and Data Compression (3 papers). The work is most often cited by research in Neurology (76 citations), Genetics (42 citations), Molecular Biology (266 citations), Genetics (102 citations) and Cellular and Molecular Neuroscience (56 citations). Koichiro Doi has collaborated with scholars based in Japan and United States. Frequent co-authors include Jun Yoshimura, Shinichi Morishita, Hiroyuki Ishiura, Shoji Tsuji, Jun Mitsui, Hiroshi Imai, Jun Goto, Yuji Takahashi, Takashi Matsukawa and Jing Li. Their work appears in journals such as Journal of the Neurological Sciences, Japanese Journal of Applied Physics, Bioinformatics, The Cerebellum and Sensors and Actuators B Chemical.
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.