Kiichiro Tomoda
- Molecular Biology top 0.1%
- Surgery top 0.5%
- Biomedical Engineering top 0.5%
- Cellular and Molecular Neuroscience top 0.5%
- Physiology top 1%
- Co-authors
- Shinya YamanakaMegumi NaritaKazutoshi TakahashiTomoko IchisakaKoji TanabeMari OhnukiJun‐ya KatoNoriko Yoneda‐Kato
- Topics
- Pluripotent Stem Cells Research (11 papers)Ubiquitin and proteasome pathways (9 papers)Cancer-related Molecular Pathways (8 papers)
- Partner nations
- JapanUnited StatesRussia
In The Last Decade
Kiichiro Tomoda
30 papers receiving 16.5k citations
Hit Papers
Peers
Comparison fields: 5 of 159
- Molecular Biology 14.0k
- Surgery 3.3k
- Biomedical Engineering 2.7k
- Cellular and Molecular Neuroscience 2.0k
- Physiology 1.7k
Countries citing papers authored by Kiichiro Tomoda
This map shows the geographic impact of Kiichiro Tomoda'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 Kiichiro Tomoda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kiichiro Tomoda more than expected).
Fields of papers citing papers by Kiichiro Tomoda
This network shows the impact of papers produced by Kiichiro Tomoda. 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 Kiichiro Tomoda. The network helps show where Kiichiro Tomoda may publish in the future.
Co-authorship network of co-authors of Kiichiro Tomoda
This figure shows the co-authorship network connecting the top 25 collaborators of Kiichiro Tomoda. A scholar is included among the top collaborators of Kiichiro Tomoda based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Kiichiro Tomoda. Kiichiro Tomoda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 13 | |
| 2 | 5 | |
| 3 | 7 | |
| 4 | 22 | |
| 5 | 1 | |
| 6 | 11 | |
| 7 | 63 | |
| 8 | 10 | |
| 9 | 88 | |
| 10 | 24 | |
| 11 | Induction of Pluripotent Stem Cells from Adult Human Fibroblasts by Defined Factorsbreakdown → | 14494 |
| 12 | 9 | |
| 13 | 28 | |
| 14 | 85 | |
| 15 | 133 | |
| 16 | 62 | |
| 17 | 57 | |
| 18 | 243 | |
| 19 | 31 | |
| 20 | Degradation of the cyclin-dependent-kinase inhibitor p27Kip1 is instigated by Jab1breakdown → | 544 |
About Kiichiro Tomoda
Kiichiro Tomoda is a scholar working on Molecular Biology, Oncology and Sensory Systems, having authored 30 papers that have together received 16.9k indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (11 papers), Ubiquitin and proteasome pathways (9 papers) and Cancer-related Molecular Pathways (8 papers). The work is most often cited by research in Developmental Neuroscience (858 citations), Molecular Biology (14.0k citations) and Genetics (1.6k citations). Kiichiro Tomoda has collaborated with scholars based in Japan, United States and Russia. Frequent co-authors include Shinya Yamanaka, Megumi Narita, Kazutoshi Takahashi, Tomoko Ichisaka, Koji Tanabe, Mari Ohnuki, Jun‐ya Kato, Noriko Yoneda‐Kato, Yukinobu Arata and Akihisa Fukumoto. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.