Gert‐Jan Bekker
- Molecular Biology
- Materials Chemistry
- Pollution top 10%
- Radiology, Nuclear Medicine and Imaging top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- Narutoshi KamiyaHaruki NakamuraAkira R. KinjoTakeshi KawabataВ. Б. АникинN. A. FilatovaPhilippe BuletSergey Chernysh
- Topics
- Protein Structure and Dynamics (20 papers)Enzyme Structure and Function (14 papers)Computational Drug Discovery Methods (7 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyNucleic Acids Research
- Partner nations
- JapanUnited StatesRussia
In The Last Decade
Gert‐Jan Bekker
39 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 106
- Molecular Biology 678
- Materials Chemistry 182
- Pollution 125
- Radiology, Nuclear Medicine and Imaging 121
- Computational Theory and Mathematics 114
Countries citing papers authored by Gert‐Jan Bekker
This map shows the geographic impact of Gert‐Jan Bekker'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 Gert‐Jan Bekker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gert‐Jan Bekker more than expected).
Fields of papers citing papers by Gert‐Jan Bekker
This network shows the impact of papers produced by Gert‐Jan Bekker. 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 Gert‐Jan Bekker. The network helps show where Gert‐Jan Bekker may publish in the future.
Co-authorship network of co-authors of Gert‐Jan Bekker
This figure shows the co-authorship network connecting the top 25 collaborators of Gert‐Jan Bekker. A scholar is included among the top collaborators of Gert‐Jan Bekker 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 Gert‐Jan Bekker. Gert‐Jan Bekker is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 10 | |
| 9 | 8 | |
| 10 | 16 | |
| 11 | 3 | |
| 12 | 13 | |
| 13 | 15 | |
| 14 | 8 | |
| 15 | 16 | |
| 16 | 53 | |
| 17 | 65 | |
| 18 | 41 | |
| 19 | 61 | |
| 20 | 92 |
About Gert‐Jan Bekker
Gert‐Jan Bekker is a scholar working on Pollution, Molecular Biology and Computational Theory and Mathematics, having authored 42 papers that have together received 1.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (20 papers), Enzyme Structure and Function (14 papers) and Computational Drug Discovery Methods (7 papers). The work is most often cited by research in Microbiology (93 citations), Pollution (125 citations) and Molecular Biology (678 citations). Gert‐Jan Bekker has collaborated with scholars based in Japan, United States and Russia. Frequent co-authors include Narutoshi Kamiya, Haruki Nakamura, Akira R. Kinjo, Takeshi Kawabata, В. Б. Аникин, N. A. Filatova, Philippe Bulet, Sergey Chernysh, Yasushi Okuno and Mitsugu Araki. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.
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.