Wiktor Beker
Impact in
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- Computational Drug Discovery Methods
- Materials Chemistry top 10%
- Machine Learning in Materials Science
Papers in
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- Computational Drug Discovery Methods 12
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- Machine Learning in Materials Science 11
- Co-authors
- Bartosz A. Grzybowski (18 shared papers)Rafał Roszak (7 shared papers)Agnieszka Wołos (6 shared papers)Sara Szymkuć (8 shared papers)Ewa Gajewska (4 shared papers)Tomasz Badowski (3 shared papers)Nicholas H. Angello (2 shared papers)Martin D. Burke (3 shared papers)
- Journals
- Journal of the American Chemical Society (4 papers)Nature (2 papers)Angewandte Chemie International Edition (2 papers)Journal of Chemical Theory and Computation (2 papers)Science (2 papers)
- Partner nations
- PolandUnited StatesSouth Korea
In The Last Decade
Wiktor Beker
27 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 101
- Computational Theory and Mathematics 388
- Materials Chemistry 623
- Inorganic Chemistry 111
- Organic Chemistry 216
- Catalysis 48
Countries citing papers authored by Wiktor Beker
This map shows the geographic impact of Wiktor Beker'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 Wiktor Beker with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wiktor Beker more than expected).
Fields of papers citing papers by Wiktor Beker
This network shows the impact of papers produced by Wiktor Beker. 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 Wiktor Beker. The network helps show where Wiktor Beker may publish in the future.
Co-authors
The 25 scholars most cited alongside Wiktor Beker, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 203 | |
| 2 | 2022 | 166 | |
| 3 | 2022 | 143 | |
| 4 | 2018 | 128 | |
| 5 | 2020 | 121 | |
| 6 | 2023 | 113 | |
| 7 | 2019 | 79 | |
| 8 | 2020 | 42 | |
| 9 | 2021 | 32 | |
| 10 | 2018 | 22 | |
| 11 | 2021 | 20 | |
| 12 | 2012 | 15 | |
| 13 | 2018 | 14 | |
| 14 | 2013 | 14 | |
| 15 | 2020 | 13 | |
| 16 | 2021 | 13 | |
| 17 | 2020 | 12 | |
| 18 | 2017 | 10 | |
| 19 | 2015 | 10 | |
| 20 | 2014 | 10 |
About Wiktor Beker
Wiktor Beker is a scholar working on Computational Theory and Mathematics, Materials Chemistry, Molecular Biology, Physical and Theoretical Chemistry and Organic Chemistry, having authored 27 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (12 papers), Machine Learning in Materials Science (11 papers), Protein Structure and Dynamics (7 papers), Chemical Synthesis and Analysis (5 papers), Enzyme Catalysis and Immobilization (2 papers), Free Radicals and Antioxidants (2 papers), Plant biochemistry and biosynthesis (2 papers) and Microbial Natural Products and Biosynthesis (2 papers). The work is most often cited by research in Computational Theory and Mathematics (388 citations), Materials Chemistry (623 citations), Inorganic Chemistry (111 citations), Organic Chemistry (216 citations) and Catalysis (48 citations). Wiktor Beker has collaborated with scholars based in Poland, United States and South Korea. Frequent co-authors include Bartosz A. Grzybowski, Rafał Roszak, Agnieszka Wołos, Sara Szymkuć, Ewa Gajewska, Tomasz Badowski, Nicholas H. Angello, Martin D. Burke, Vandana Rathore and Karol Molga. Their work appears in journals such as Journal of the American Chemical Society, Nature, Angewandte Chemie International Edition, Journal of Chemical Theory and Computation and Science.
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.