Taichi Kimura
Impact in
- Genetics top 5%
- Glioma Diagnosis and Treatment
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- Cancer-related gene regulation 5
- Oncology 21
- Cancer Cells and Metastasis 8
- Co-authors
- Shinya Tanaka (50 shared papers)Hiroshi Nishihara (42 shared papers)Mishie Tanino (38 shared papers)Masumi Tsuda (21 shared papers)Shinji Kohsaka (8 shared papers)Roshan Mahabir (5 shared papers)Tamio Itoh (3 shared papers)Makoto Ouchi (3 shared papers)
- Journals
- Brain Tumor Pathology (7 papers)Biochemical and Biophysical Research Communications (5 papers)Neuropathology (3 papers)Neuro-Oncology (3 papers)Molecular Cancer (3 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Taichi Kimura
89 papers receiving 2.1k citations
Peers
Comparison fields: 5 of 115
- Genetics 304
- Cancer Research 337
- Oncology 514
- Molecular Biology 1.0k
- Pathology and Forensic Medicine 203
Countries citing papers authored by Taichi Kimura
This map shows the geographic impact of Taichi Kimura'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 Taichi Kimura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Taichi Kimura more than expected).
Fields of papers citing papers by Taichi Kimura
This network shows the impact of papers produced by Taichi Kimura. 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 Taichi Kimura. The network helps show where Taichi Kimura may publish in the future.
Co-authors
The 25 scholars most cited alongside Taichi Kimura, 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 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2016 | 183 | |
| 2 | 2012 | 165 | |
| 3 | 2007 | 163 | |
| 4 | 2013 | 142 | |
| 5 | 2008 | 88 | |
| 6 | 2016 | 64 | |
| 7 | 2010 | 60 | |
| 8 | 2014 | 53 | |
| 9 | 2021 | 49 | |
| 10 | 2014 | 42 | |
| 11 | 2009 | 40 | |
| 12 | 2010 | 39 | |
| 13 | 2014 | 39 | |
| 14 | 2014 | 36 | |
| 15 | 2007 | 36 | |
| 16 | 2016 | 36 | |
| 17 | 2016 | 33 | |
| 18 | 2015 | 32 | |
| 19 | 2023 | 31 | |
| 20 | 2015 | 30 |
About Taichi Kimura
Taichi Kimura is a scholar working on Molecular Biology, Oncology, Genetics, Pulmonary and Respiratory Medicine and Surgery, having authored 90 papers that have together received 2.1k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (16 papers), Cancer Cells and Metastasis (8 papers), Sarcoma Diagnosis and Treatment (6 papers), Cancer-related gene regulation (5 papers), Advanced Polymer Synthesis and Characterization (4 papers), Organ Transplantation Techniques and Outcomes (4 papers), Microtubule and mitosis dynamics (3 papers) and Meningioma and schwannoma management (3 papers). The work is most often cited by research in Genetics (304 citations), Cancer Research (337 citations), Oncology (514 citations), Molecular Biology (1.0k citations) and Pathology and Forensic Medicine (203 citations). Taichi Kimura has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Shinya Tanaka, Hiroshi Nishihara, Mishie Tanino, Masumi Tsuda, Shinji Kohsaka, Roshan Mahabir, Tamio Itoh, Makoto Ouchi, Kouichi Tabu and Keiko Nakayama. Their work appears in journals such as Brain Tumor Pathology, Biochemical and Biophysical Research Communications, Neuropathology, Neuro-Oncology and Molecular Cancer.
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.