Tim Miyashiro
Impact in
- Endocrinology top 0.5%
- Vibrio bacteria research studies
- Escherichia coli research studies
- Molecular Medicine top 5%
- Antibiotic Resistance in Bacteria
Papers in
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- Vibrio bacteria research studies 22
-
- Bacterial biofilms and quorum sensing 13
- Co-authors
- Edward G. Ruby (5 shared papers)Mark Goulian (4 shared papers)Subhash Verma (4 shared papers)Michael S. Wollenberg (4 shared papers)Xiaodan Cao (3 shared papers)Kirsten R. Guckes (6 shared papers)Mark J. Mandel (4 shared papers)Zhi Liu (1 shared paper)
- Journals
- Molecular Microbiology (6 papers)Proceedings of the National Academy of Sciences (4 papers)Journal of Bacteriology (2 papers)Applied and Environmental Microbiology (2 papers)mBio (2 papers)
- Partner nations
- United StatesChina
In The Last Decade
Tim Miyashiro
30 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 78
- Endocrinology 561
- Molecular Medicine 94
- Genetics 268
- Molecular Biology 638
- Immunology 194
Countries citing papers authored by Tim Miyashiro
This map shows the geographic impact of Tim Miyashiro'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 Tim Miyashiro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tim Miyashiro more than expected).
Fields of papers citing papers by Tim Miyashiro
This network shows the impact of papers produced by Tim Miyashiro. 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 Tim Miyashiro. The network helps show where Tim Miyashiro may publish in the future.
Co-authors
The 25 scholars most cited alongside Tim Miyashiro, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 134 | |
| 2 | 2008 | 134 | |
| 3 | 2012 | 116 | |
| 4 | 2013 | 97 | |
| 5 | 2013 | 69 | |
| 6 | 2010 | 68 | |
| 7 | 2008 | 59 | |
| 8 | 2012 | 55 | |
| 9 | 2011 | 41 | |
| 10 | 2013 | 41 | |
| 11 | 2007 | 41 | |
| 12 | 2016 | 33 | |
| 13 | 2007 | 28 | |
| 14 | 2014 | 22 | |
| 15 | 2018 | 21 | |
| 16 | 2019 | 16 | |
| 17 | 2016 | 12 | |
| 18 | 2015 | 11 | |
| 19 | 2020 | 11 | |
| 20 | 2019 | 10 |
About Tim Miyashiro
Tim Miyashiro is a scholar working on Endocrinology, Molecular Biology, Genetics, Ecology, Evolution, Behavior and Systematics and Immunology, having authored 30 papers that have together received 1.1k indexed citations. Recurring topics across this work include Vibrio bacteria research studies (22 papers), Bacterial biofilms and quorum sensing (13 papers), Cephalopods and Marine Biology (7 papers), Aquaculture disease management and microbiota (6 papers), Yersinia bacterium, plague, ectoparasites research (4 papers), Bacterial Genetics and Biotechnology (4 papers), Microbial Community Ecology and Physiology (3 papers) and Antibiotic Resistance in Bacteria (3 papers). The work is most often cited by research in Endocrinology (561 citations), Molecular Medicine (94 citations), Genetics (268 citations), Molecular Biology (638 citations) and Immunology (194 citations). Tim Miyashiro has collaborated with scholars based in United States and China. Frequent co-authors include Edward G. Ruby, Mark Goulian, Subhash Verma, Michael S. Wollenberg, Xiaodan Cao, Kirsten R. Guckes, Mark J. Mandel, Zhi Liu, Amy M. Tsou and Jun Zhu. Their work appears in journals such as Molecular Microbiology, Proceedings of the National Academy of Sciences, Journal of Bacteriology, Applied and Environmental Microbiology and mBio.
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.