Chikako Mitsuoka
- Plant Science top 0.5%
- Molecular Biology top 5%
- Genetics top 2%
- Cell Biology top 2%
- Immunology top 5%
- Co-authors
- Ryohei TerauchiKentaro YoshidaSophien KamounSatoshi NatsumeLiliana M. CanoHiroki TakagiMuluneh TamiruAkira Abe
- Topics
- Glycosylation and Glycoproteins Research (13 papers)Cell Adhesion Molecules Research (11 papers)Monoclonal and Polyclonal Antibodies Research (6 papers)
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Chikako Mitsuoka
34 papers receiving 3.9k citations
Hit Papers
Peers
Comparison fields: 5 of 95
- Plant Science 2.5k
- Molecular Biology 1.9k
- Genetics 903
- Cell Biology 541
- Immunology 443
Countries citing papers authored by Chikako Mitsuoka
This map shows the geographic impact of Chikako Mitsuoka'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 Chikako Mitsuoka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chikako Mitsuoka more than expected).
Fields of papers citing papers by Chikako Mitsuoka
This network shows the impact of papers produced by Chikako Mitsuoka. 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 Chikako Mitsuoka. The network helps show where Chikako Mitsuoka may publish in the future.
Co-authorship network of co-authors of Chikako Mitsuoka
This figure shows the co-authorship network connecting the top 25 collaborators of Chikako Mitsuoka. A scholar is included among the top collaborators of Chikako Mitsuoka 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 Chikako Mitsuoka. Chikako Mitsuoka 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 | 176 | |
| 3 | 122 | |
| 4 | 989 | |
| 5 | 9 | |
| 6 | 230 | |
| 7 | Genome sequencing reveals agronomically important loci in rice using MutMapbreakdown → | 939 |
| 8 | 124 | |
| 9 | 31 | |
| 10 | 5 | |
| 11 | 169 | |
| 12 | 23 | |
| 13 | Expression of sialyl 6-sulfo Lewis X is inversely correlated with conventional sialyl Lewis X expression in human colorectal cancer. | 85 |
| 14 | 39 | |
| 15 | 12 | |
| 16 | 124 | |
| 17 | 34 | |
| 18 | 77 | |
| 19 | 76 | |
| 20 | 9 |
About Chikako Mitsuoka
Chikako Mitsuoka is a scholar working on Immunology and Allergy, Cell Biology and Molecular Biology, having authored 34 papers that have together received 4.0k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (13 papers), Cell Adhesion Molecules Research (11 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). The work is most often cited by research in Horticulture (80 citations), Plant Science (2.5k citations) and Immunology and Allergy (341 citations). Chikako Mitsuoka has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Ryohei Terauchi, Kentaro Yoshida, Sophien Kamoun, Satoshi Natsume, Liliana M. Cano, Hiroki Takagi, Muluneh Tamiru, Akira Abe, Shunichi Kosugi and Hideki Innan. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.
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.