K Segawa
- Molecular Biology top 10%
- Oncology top 5%
- Genetics top 10%
- Cell Biology top 10%
- Immunology
- Co-authors
- Yoichi TayaIkuko Suzuki‐TakahashiHideaki HigashiSusumu NishimuraMasatoshi KitagawaKatsuyuki TamaiHai Kwan JungEisaku Yoshida
- Topics
- Virus-based gene therapy research (9 papers)Polyomavirus and related diseases (8 papers)Bacteriophages and microbial interactions (6 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyThe EMBO Journal
- Partner nations
- JapanUnited StatesAustralia
In The Last Decade
K Segawa
27 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Molecular Biology 810
- Oncology 640
- Genetics 198
- Cell Biology 193
- Immunology 180
Countries citing papers authored by K Segawa
This map shows the geographic impact of K Segawa'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 K Segawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K Segawa more than expected).
Fields of papers citing papers by K Segawa
This network shows the impact of papers produced by K Segawa. 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 K Segawa. The network helps show where K Segawa may publish in the future.
Co-authorship network of co-authors of K Segawa
This figure shows the co-authorship network connecting the top 25 collaborators of K Segawa. A scholar is included among the top collaborators of K Segawa 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 K Segawa. K Segawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 16 | |
| 6 | 45 | |
| 7 | Increased expression of highly branched N-glycans at cell surface is correlated with the malignant phenotypes of mouse tumor cells. | 87 |
| 8 | The 273rd codon mutants of p53 show growth modulation activities not correlated with p53-specific transactivation activity. | 25 |
| 9 | 26 | |
| 10 | Phosphorylation of E2F-1 by cyclin A-cdk2. | 87 |
| 11 | 26 | |
| 12 | 11 | |
| 13 | 10 | |
| 14 | 7 | |
| 15 | 21 | |
| 16 | Oncogene and its production of an avian sarcoma virus Y73. | 1 |
| 17 | 9 | |
| 18 | 50 | |
| 19 | 162 | |
| 20 | Antisera from mice and rats incubated with syngeneic Rous sarcoma cells. | 3 |
About K Segawa
K Segawa is a scholar working on Oncology, Genetics and Ecology, having authored 28 papers that have together received 1.2k indexed citations. Recurring topics across this work include Virus-based gene therapy research (9 papers), Polyomavirus and related diseases (8 papers) and Bacteriophages and microbial interactions (6 papers). The work is most often cited by research in Oncology (640 citations), Cell Biology (193 citations) and Molecular Biology (810 citations). K Segawa has collaborated with scholars based in Japan, United States and Australia. Frequent co-authors include Yoichi Taya, Ikuko Suzuki‐Takahashi, Hideaki Higashi, Susumu Nishimura, Masatoshi Kitagawa, Katsuyuki Tamai, Hai Kwan Jung, Eisaku Yoshida, M. Ikeda and Jun‐ya Kato. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and The EMBO Journal.
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.