Kaoru Akita
- Molecular Biology
- Immunology top 10%
- Oncology
- Cell Biology top 10%
- Organic Chemistry
- Co-authors
- Hiroshi NakadaMunetoyo TodaMizue InoueAkiko IshidaAlexander von HolstAndréas FaissnerTakeomi MurataKosei Hirakawa
- Topics
- Glycosylation and Glycoproteins Research (19 papers)Galectins and Cancer Biology (10 papers)Proteoglycans and glycosaminoglycans research (5 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryBiochemical Journal
- Partner nations
- JapanGermanyUnited States
In The Last Decade
Kaoru Akita
26 papers receiving 891 citations
Peers
Comparison fields: 5 of 77
- Molecular Biology 639
- Immunology 369
- Oncology 163
- Cell Biology 162
- Organic Chemistry 78
Countries citing papers authored by Kaoru Akita
This map shows the geographic impact of Kaoru Akita'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 Kaoru Akita with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaoru Akita more than expected).
Fields of papers citing papers by Kaoru Akita
This network shows the impact of papers produced by Kaoru Akita. 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 Kaoru Akita. The network helps show where Kaoru Akita may publish in the future.
Co-authorship network of co-authors of Kaoru Akita
This figure shows the co-authorship network connecting the top 25 collaborators of Kaoru Akita. A scholar is included among the top collaborators of Kaoru Akita 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 Kaoru Akita. Kaoru Akita is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 28 | |
| 2 | 50 | |
| 3 | 21 | |
| 4 | 33 | |
| 5 | 17 | |
| 6 | 33 | |
| 7 | 37 | |
| 8 | 25 | |
| 9 | 26 | |
| 10 | 45 | |
| 11 | 28 | |
| 12 | Mechanisms for Cancer Metastasis in the Formation of Trimeric Tn Antigen Modified by pp-GalNAc-T13 Gene | 1 |
| 13 | 70 | |
| 14 | 34 | |
| 15 | 9 | |
| 16 | 36 | |
| 17 | 35 | |
| 18 | 62 | |
| 19 | 13 | |
| 20 | Phosphorylation of retinoid X receptor alpha at serine 260 impairs its metabolism and function in human hepatocellular carcinoma. | 109 |
About Kaoru Akita
Kaoru Akita is a scholar working on Immunology, Cell Biology and Immunology and Allergy, having authored 26 papers that have together received 900 indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (19 papers), Galectins and Cancer Biology (10 papers) and Proteoglycans and glycosaminoglycans research (5 papers). The work is most often cited by research in Immunology (369 citations), Cell Biology (162 citations) and Molecular Biology (639 citations). Kaoru Akita has collaborated with scholars based in Japan, Germany and United States. Frequent co-authors include Hiroshi Nakada, Munetoyo Toda, Mizue Inoue, Akiko Ishida, Alexander von Holst, Andréas Faissner, Takeomi Murata, Kosei Hirakawa, Masakazu Yashiro and Yoko Furukawa. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Biochemical 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.