Motoi Ohba
- Molecular Biology top 5%
- Protein Kinase Regulation and GTPase Signaling 31
- Metabolism, Diabetes, and Cancer 12
- PI3K/AKT/mTOR signaling in cancer 9
- Cell death mechanisms and regulation 8
- Signaling Pathways in Disease 8
- Sphingolipid Metabolism and Signaling 5
- Cell Biology top 5%
- Cancer Research top 5%
- Oncology top 5%
- HER2/EGFR in Cancer Research 5
- Immunology top 5%
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- Lung Cancer Treatments and Mutations 8
- Co-authors
- Toshio KurokiToshimitsu YamaokaTohru OhmoriSojiro KusumotoKoichi AndōMariko KashiwagiSatoru EguchiGerald D. Frank
- Journals
- Journal of Biological Chemistry (14 papers)Biochemical and Biophysical Research Communications (5 papers)Molecular and Cellular Biology (4 papers)
- Partner nations
- JapanUnited StatesSouth Korea
In The Last Decade
Motoi Ohba
66 papers receiving 3.3k citations
Peers
Comparison fields: 5 of 112
- Molecular Biology 2.3k
- Cell Biology 421
- Cancer Research 361
- Oncology 601
- Immunology 434
Countries citing papers authored by Motoi Ohba
This map shows the geographic impact of Motoi Ohba'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 Motoi Ohba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Motoi Ohba more than expected).
Fields of papers citing papers by Motoi Ohba
This network shows the impact of papers produced by Motoi Ohba. 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 Motoi Ohba. The network helps show where Motoi Ohba may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Motoi Ohba, 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 | 2018 | 39 | |
| 2 | 2017 | 41 | |
| 3 | 2017 | 4 | |
| 4 | 2016 | 28 | |
| 5 | 2007 | 14 | |
| 6 | 2004 | 44 | |
| 7 | 2003 | 8 | |
| 8 | 2003 | 50 | |
| 9 | 2002 | 6 | |
| 10 | 2002 | 94 | |
| 11 | 2002 | 25 | |
| 12 | 2002 | 86 | |
| 13 | 2002 | 75 | |
| 14 | 2002 | 50 | |
| 15 | 2001 | 67 | |
| 16 | 2000 | 52 | |
| 17 | 2000 | 183 | |
| 18 | 1998 | 178 | |
| 19 | 1998 | 36 | |
| 20 | 1998 | 15 |
About Motoi Ohba
Motoi Ohba is a scholar working on Molecular Biology, Genetics and Cell Biology, having authored 66 papers that have together received 3.3k indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (31 papers), Metabolism, Diabetes, and Cancer (12 papers), PI3K/AKT/mTOR signaling in cancer (9 papers), Cell death mechanisms and regulation (8 papers), Lung Cancer Treatments and Mutations (8 papers), Signaling Pathways in Disease (8 papers), Sphingolipid Metabolism and Signaling (5 papers) and HER2/EGFR in Cancer Research (5 papers). The work is most often cited by research in Molecular Biology (2.3k citations), Cell Biology (421 citations) and Cancer Research (361 citations). Motoi Ohba has collaborated with scholars based in Japan, United States and South Korea. Frequent co-authors include Toshio Kuroki, Toshimitsu Yamaoka, Tohru Ohmori, Sojiro Kusumoto, Koichi Andō, Mariko Kashiwagi, Satoru Eguchi, Gerald D. Frank, Keiko Ishino and Tamar Tennenbaum. Their work appears in journals such as Journal of Biological Chemistry, Biochemical and Biophysical Research Communications, Molecular and Cellular Biology, Journal of Clinical Investigation and Molecular Endocrinology.
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.