Mami Kishima
Impact in
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- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
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- Epigenetics and DNA Methylation
- RNA modifications and cancer
- Pluripotent Stem Cells Research
- RNA regulation and disease
- CRISPR and Genetic Engineering
Papers in
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- Pluripotent Stem Cells Research 7
- Epigenetics and DNA Methylation 5
- CRISPR and Genetic Engineering 4
- Single-cell and spatial transcriptomics 2
- Bacillus and Francisella bacterial research 1
- Surgery 3
- Tissue Engineering and Regenerative Medicine 2
- Co-authors
- Harukazu Suzuki (10 shared papers)Takahiro Suzuki (9 shared papers)Hajime Nishimura (7 shared papers)Shiori Maeda (6 shared papers)Yuri Shimizu (3 shared papers)Erina Furuhata (5 shared papers)Haruka Yabukami (2 shared papers)Takuya Imamura (1 shared paper)
- Journals
- Communications Biology (1 paper)PLoS ONE (1 paper)Nucleic Acids Research (1 paper)Genome Research (1 paper)Scientific Reports (1 paper)
- Partner nations
- JapanUnited KingdomSwitzerland
In The Last Decade
Mami Kishima
13 papers receiving 400 citations
Peers
Comparison fields: 5 of 65
- Cancer Research 87
- Molecular Biology 295
- Reproductive Medicine 33
- Aging 6
- Public Health, Environmental and Occupational Health 72
Countries citing papers authored by Mami Kishima
This map shows the geographic impact of Mami Kishima'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 Mami Kishima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mami Kishima more than expected).
Fields of papers citing papers by Mami Kishima
This network shows the impact of papers produced by Mami Kishima. 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 Mami Kishima. The network helps show where Mami Kishima may publish in the future.
Co-authors
The 25 scholars most cited alongside Mami Kishima, 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 | 2021 | 121 | |
| 2 | 2010 | 110 | |
| 3 | 2017 | 61 | |
| 4 | 2017 | 35 | |
| 5 | 2019 | 29 | |
| 6 | 2021 | 9 | |
| 7 | 2012 | 9 | |
| 8 | 2022 | 8 | |
| 9 | 2005 | 8 | |
| 10 | 2017 | 6 | |
| 11 | 2022 | 5 | |
| 12 | 2023 | 3 | |
| 13 | 2016 | 3 | |
| 14 | 2019 | 0 |
About Mami Kishima
Mami Kishima is a scholar working on Molecular Biology, Surgery, Cancer Research, Biomedical Engineering and Genetics, having authored 14 papers that have together received 407 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (7 papers), Epigenetics and DNA Methylation (5 papers), CRISPR and Genetic Engineering (4 papers), Single-cell and spatial transcriptomics (2 papers), Tissue Engineering and Regenerative Medicine (2 papers), 3D Printing in Biomedical Research (2 papers), Bacillus and Francisella bacterial research (1 paper) and Genetics and Neurodevelopmental Disorders (1 paper). The work is most often cited by research in Cancer Research (87 citations), Molecular Biology (295 citations), Reproductive Medicine (33 citations), Aging (6 citations) and Public Health, Environmental and Occupational Health (72 citations). Mami Kishima has collaborated with scholars based in Japan, United Kingdom and Switzerland. Frequent co-authors include Harukazu Suzuki, Takahiro Suzuki, Hajime Nishimura, Shiori Maeda, Yuri Shimizu, Erina Furuhata, Haruka Yabukami, Takuya Imamura, Yoshihide Hayashizaki and Makoto Tachibana. Their work appears in journals such as Communications Biology, PLoS ONE, Nucleic Acids Research, Genome Research and Scientific Reports.
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.