Igor N. Berezovsky
- Molecular Biology top 2%
- Protein Structure and Dynamics 67
- RNA and protein synthesis mechanisms 34
- Genomics and Phylogenetic Studies 10
- Receptor Mechanisms and Signaling 10
- Microbial Metabolic Engineering and Bioproduction 7
- Machine Learning in Bioinformatics 5
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 17
- Materials Chemistry top 5%
- Enzyme Structure and Function 39
- Spectroscopy top 5%
- Biotechnology top 10%
- Co-authors
- Enrico GuarneraEugene I. ShakhnovichEdward N. TrifonovAlexander GoncearencoWei-Ven TeeKonstantin B. ZeldovichSimon MitternachtZhen Wah Tan
In The Last Decade
Igor N. Berezovsky
88 papers receiving 3.7k citations
Peers
Comparison fields: 5 of 126
- Molecular Biology 3.2k
- Computational Theory and Mathematics 656
- Materials Chemistry 957
- Spectroscopy 244
- Biotechnology 89
Countries citing papers authored by Igor N. Berezovsky
This map shows the geographic impact of Igor N. Berezovsky'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 Igor N. Berezovsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor N. Berezovsky more than expected).
Fields of papers citing papers by Igor N. Berezovsky
This network shows the impact of papers produced by Igor N. Berezovsky. 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 Igor N. Berezovsky. The network helps show where Igor N. Berezovsky may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Igor N. Berezovsky, 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 | 2025 | 0 | |
| 2 | 2024 | 25 | |
| 3 | 2023 | 2 | |
| 4 | 2022 | 27 | |
| 5 | 2021 | 4 | |
| 6 | 2020 | 29 | |
| 7 | 2020 | 1 | |
| 8 | 2019 | 17 | |
| 9 | 2016 | 108 | |
| 10 | 2016 | 39 | |
| 11 | 2015 | 122 | |
| 12 | 2015 | 45 | |
| 13 | 2013 | 88 | |
| 14 | 2008 | 31 | |
| 15 | 2006 | 26 | |
| 16 | 2003 | 19 | |
| 17 | 2002 | 4 | |
| 18 | 2002 | 14 | |
| 19 | 2001 | 32 | |
| 20 | 1999 | 36 |
About Igor N. Berezovsky
Igor N. Berezovsky is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry, having authored 89 papers that have together received 3.8k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (67 papers), Enzyme Structure and Function (39 papers), RNA and protein synthesis mechanisms (34 papers), Computational Drug Discovery Methods (17 papers), Genomics and Phylogenetic Studies (10 papers), Receptor Mechanisms and Signaling (10 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Machine Learning in Bioinformatics (5 papers). The work is most often cited by research in Molecular Biology (3.2k citations), Computational Theory and Mathematics (656 citations) and Materials Chemistry (957 citations). Igor N. Berezovsky has collaborated with scholars based in Singapore, Israel and Norway. Frequent co-authors include Enrico Guarnera, Eugene I. Shakhnovich, Edward N. Trifonov, Alexander Goncearenco, Wei-Ven Tee, Konstantin B. Zeldovich, Simon Mitternacht, Zhen Wah Tan, Igor V. Kurochkin and Dan S. Tawfik. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research 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.