Masato Kobori
- Reproductive Medicine top 5%
- Molecular Biology top 5%
- Receptor Mechanisms and Signaling 4
- Protein Structure and Dynamics 3
- RNA and protein synthesis mechanisms 3
- Chemical Synthesis and Analysis 3
- Glycosylation and Glycoproteins Research 2
- Nephrology top 5%
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- Enzyme Structure and Function 4
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- Computational Drug Discovery Methods 4
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- Monoclonal and Polyclonal Antibodies Research 3
- Co-authors
- Jun TakasakiHiroki ShiraiTetsu SaitoShun‐ichiro MatsumotoJunn YanagisawaShigeaki KatoSachiko KitanakaKen‐ichi Takeyama
- Journals
- Biochemical and Biophysical Research Communications (5 papers)The Journal of Antibiotics (4 papers)Journal of Chemical Information and Modeling (3 papers)
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Masato Kobori
32 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 105
- Pathology and Forensic Medicine 404
- Reproductive Medicine 176
- Endocrinology, Diabetes and Metabolism 342
- Molecular Biology 1.4k
- Nephrology 137
Countries citing papers authored by Masato Kobori
This map shows the geographic impact of Masato Kobori'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 Masato Kobori with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masato Kobori more than expected).
Fields of papers citing papers by Masato Kobori
This network shows the impact of papers produced by Masato Kobori. 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 Masato Kobori. The network helps show where Masato Kobori may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masato Kobori, 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 | 2012 | 62 | |
| 2 | 2010 | 35 | |
| 3 | 2008 | 51 | |
| 4 | 2008 | 49 | |
| 5 | 2008 | 97 | |
| 6 | 2006 | 216 | |
| 7 | 2006 | 15 | |
| 8 | 2005 | 58 | |
| 9 | 2005 | 87 | |
| 10 | 2005 | 53 | |
| 11 | 2005 | 28 | |
| 12 | 2004 | 329 | |
| 13 | 2004 | 286 | |
| 14 | 2002 | 20 | |
| 15 | 1998 | 136 | |
| 16 | 1998 | 175 | |
| 17 | 1993 | 29 | |
| 18 | 1990 | 1 | |
| 19 | 1989 | 32 | |
| 20 | 1989 | 102 |
About Masato Kobori
Masato Kobori is a scholar working on Molecular Biology, Biotechnology and Cancer Research, having authored 33 papers that have together received 2.6k indexed citations. Recurring topics across this work include Enzyme Structure and Function (4 papers), Computational Drug Discovery Methods (4 papers), Receptor Mechanisms and Signaling (4 papers), Protein Structure and Dynamics (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), RNA and protein synthesis mechanisms (3 papers), Chemical Synthesis and Analysis (3 papers) and Glycosylation and Glycoproteins Research (2 papers). The work is most often cited by research in Pathology and Forensic Medicine (404 citations), Reproductive Medicine (176 citations) and Endocrinology, Diabetes and Metabolism (342 citations). Masato Kobori has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Jun Takasaki, Hiroki Shirai, Tetsu Saito, Shun‐ichiro Matsumoto, Junn Yanagisawa, Shigeaki Kato, Sachiko Kitanaka, Ken‐ichi Takeyama, Takashi Sato and Shinji Soga. Their work appears in journals such as Biochemical and Biophysical Research Communications, The Journal of Antibiotics, Journal of Chemical Information and Modeling, Proteins Structure Function and Bioinformatics 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.