Mika Suga
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
Papers in
-
- Pluripotent Stem Cells Research 17
- CRISPR and Genetic Engineering 5
- Renal and related cancers 2
- Surgery 6
- Co-authors
- Miho Furue (16 shared papers)Masaki Kinehara (5 shared papers)Kana Yanagihara (7 shared papers)Hiroki Nikawa (6 shared papers)Haruhisa Inoue (9 shared papers)Takayuki Kondo (10 shared papers)Kozue Uchio‐Yamada (2 shared papers)Yasujiro Kiyota (3 shared papers)
- Journals
- Stem Cell Research (5 papers)In Vitro Cellular & Developmental Biology - Animal (4 papers)The International Journal of Developmental Biology (2 papers)Stem Cells and Development (2 papers)Stem Cells Translational Medicine (2 papers)
- Partner nations
- JapanUnited StatesSwitzerland
In The Last Decade
Mika Suga
27 papers receiving 356 citations
Peers
Comparison fields: 5 of 65
- Biophysics 36
- Developmental Neuroscience 18
- Molecular Biology 238
- Biomedical Engineering 105
- Hepatology 14
Countries citing papers authored by Mika Suga
This map shows the geographic impact of Mika Suga'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 Mika Suga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mika Suga more than expected).
Fields of papers citing papers by Mika Suga
This network shows the impact of papers produced by Mika Suga. 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 Mika Suga. The network helps show where Mika Suga may publish in the future.
Co-authors
The 25 scholars most cited alongside Mika Suga, 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 28 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 57 | |
| 2 | 2016 | 56 | |
| 3 | 2016 | 28 | |
| 4 | 2016 | 26 | |
| 5 | 2015 | 23 | |
| 6 | 2019 | 22 | |
| 7 | 2014 | 21 | |
| 8 | 2016 | 21 | |
| 9 | 2018 | 19 | |
| 10 | 2017 | 10 | |
| 11 | 2016 | 9 | |
| 12 | 2015 | 9 | |
| 13 | 2021 | 9 | |
| 14 | 2024 | 8 | |
| 15 | 2016 | 6 | |
| 16 | 2022 | 5 | |
| 17 | 2019 | 4 | |
| 18 | 2021 | 4 | |
| 19 | 2018 | 4 | |
| 20 | 2024 | 3 |
About Mika Suga
Mika Suga is a scholar working on Molecular Biology, Surgery, Genetics, Biomedical Engineering and Cellular and Molecular Neuroscience, having authored 28 papers that have together received 357 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (17 papers), 3D Printing in Biomedical Research (6 papers), CRISPR and Genetic Engineering (5 papers), Liver physiology and pathology (2 papers), Neuroscience and Neuropharmacology Research (2 papers), Renal and related cancers (2 papers), Cleft Lip and Palate Research (2 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Biophysics (36 citations), Developmental Neuroscience (18 citations), Molecular Biology (238 citations), Biomedical Engineering (105 citations) and Hepatology (14 citations). Mika Suga has collaborated with scholars based in Japan, United States and Switzerland. Frequent co-authors include Miho Furue, Masaki Kinehara, Kana Yanagihara, Hiroki Nikawa, Haruhisa Inoue, Takayuki Kondo, Kozue Uchio‐Yamada, Yasujiro Kiyota, Takayuki Fukuda and Daiki Tateyama. Their work appears in journals such as Stem Cell Research, In Vitro Cellular & Developmental Biology - Animal, The International Journal of Developmental Biology, Stem Cells and Development and Stem Cells Translational Medicine.
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.