Masaki Saito
- Molecular Biology top 2%
- Immunology top 2%
- Cell Biology top 1%
- Oncology top 5%
- Genetics top 5%
- Co-authors
- Seiichi KitagawaMasatsugu OhtaYasusada MiuraJulian N. KanferFumimaro TakakuYoshitaka NagaiYusuke FurukawaAkira Yuo
- Topics
- Glycosylation and Glycoproteins Research (40 papers)Liver Disease Diagnosis and Treatment (27 papers)Monoclonal and Polyclonal Antibodies Research (20 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryJournal of Clinical Investigation
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Masaki Saito
266 papers receiving 6.0k citations
Peers
Comparison fields: 5 of 153
- Molecular Biology 3.1k
- Immunology 1.2k
- Cell Biology 882
- Oncology 749
- Genetics 675
Countries citing papers authored by Masaki Saito
This map shows the geographic impact of Masaki Saito'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 Masaki Saito with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masaki Saito more than expected).
Fields of papers citing papers by Masaki Saito
This network shows the impact of papers produced by Masaki Saito. 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 Masaki Saito. The network helps show where Masaki Saito may publish in the future.
Co-authorship network of co-authors of Masaki Saito
This figure shows the co-authorship network connecting the top 25 collaborators of Masaki Saito. A scholar is included among the top collaborators of Masaki Saito 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 Masaki Saito. Masaki Saito is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 12 | |
| 5 | Normal Estimation for Accurate 3D Mesh Reconstruction with Point Cloud Model Incorporating Spatial Structure | 15 |
| 6 | 17 | |
| 7 | 10 | |
| 8 | 27 | |
| 9 | 35 | |
| 10 | 32 | |
| 11 | 181 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 8 | |
| 15 | 3 | |
| 16 | 80 | |
| 17 | 48 | |
| 18 | 3 | |
| 19 | 2 | |
| 20 | Autoxidation of α-fenchene and bornene. | 0 |
About Masaki Saito
Masaki Saito is a scholar working on Hepatology, Immunology and Immunology and Allergy, having authored 274 papers that have together received 6.3k indexed citations. Recurring topics across this work include Glycosylation and Glycoproteins Research (40 papers), Liver Disease Diagnosis and Treatment (27 papers) and Monoclonal and Polyclonal Antibodies Research (20 papers). The work is most often cited by research in Immunology and Allergy (384 citations), Hepatology (448 citations) and Immunology (1.2k citations). Masaki Saito has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Seiichi Kitagawa, Masatsugu Ohta, Yasusada Miura, Julian N. Kanfer, Fumimaro Takaku, Yoshitaka Nagai, Yusuke Furukawa, Akira Yuo, Takao Sakai and Jin‐ichi Inokuchi. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.
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.