Kenneth Atz
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Materials Science
Papers in
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- Protein Structure and Dynamics 7
- Chemical Synthesis and Analysis 4
- Bioinformatics and Genomic Networks 2
- Pharmacological Receptor Mechanisms and Effects 2
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- Computational Drug Discovery Methods 16
- Co-authors
- Gisbert Schneider (17 shared papers)Clemens Isert (8 shared papers)José Jiménez-Luna (2 shared papers)Michaël Moret (2 shared papers)Francesca Grisoni (2 shared papers)Daniel Merk (2 shared papers)Alexander L. Button (1 shared paper)Leandro Cotos (3 shared papers)
- Journals
- Molecular Informatics (3 papers)RSC Advances (2 papers)Nature Communications (2 papers)Nature Chemistry (1 paper)Journal of Biomolecular NMR (1 paper)
- Partner nations
- SwitzerlandGermanySingapore
In The Last Decade
Kenneth Atz
22 papers receiving 639 citations
Peers
Comparison fields: 5 of 97
- Computational Theory and Mathematics 371
- Materials Chemistry 300
- Molecular Biology 309
- Health Informatics 6
- Organic Chemistry 104
Countries citing papers authored by Kenneth Atz
This map shows the geographic impact of Kenneth Atz'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 Kenneth Atz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kenneth Atz more than expected).
Fields of papers citing papers by Kenneth Atz
This network shows the impact of papers produced by Kenneth Atz. 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 Kenneth Atz. The network helps show where Kenneth Atz may publish in the future.
Co-authors
The 25 scholars most cited alongside Kenneth Atz, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 103 | |
| 2 | 2023 | 95 | |
| 3 | 2022 | 92 | |
| 4 | 2023 | 90 | |
| 5 | 2023 | 50 | |
| 6 | 2019 | 47 | |
| 7 | 2024 | 44 | |
| 8 | 2022 | 42 | |
| 9 | 2019 | 18 | |
| 10 | 2021 | 18 | |
| 11 | 2024 | 11 | |
| 12 | 2023 | 8 | |
| 13 | 2020 | 6 | |
| 14 | 2022 | 6 | |
| 15 | 2024 | 4 | |
| 16 | 2024 | 3 | |
| 17 | 2022 | 3 | |
| 18 | 2023 | 2 | |
| 19 | 2024 | 1 | |
| 20 | 2025 | 1 |
About Kenneth Atz
Kenneth Atz is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Organic Chemistry and Pharmacology, having authored 22 papers that have together received 646 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), Machine Learning in Materials Science (11 papers), Protein Structure and Dynamics (7 papers), Chemical Synthesis and Analysis (4 papers), Cannabis and Cannabinoid Research (3 papers), Free Radicals and Antioxidants (2 papers), Bioinformatics and Genomic Networks (2 papers) and Pharmacological Receptor Mechanisms and Effects (2 papers). The work is most often cited by research in Computational Theory and Mathematics (371 citations), Materials Chemistry (300 citations), Molecular Biology (309 citations), Health Informatics (6 citations) and Organic Chemistry (104 citations). Kenneth Atz has collaborated with scholars based in Switzerland, Germany and Singapore. Frequent co-authors include Gisbert Schneider, Clemens Isert, José Jiménez-Luna, Michaël Moret, Francesca Grisoni, Daniel Merk, Alexander L. Button, Leandro Cotos, Uwe Grether and Martin Baumgartner. Their work appears in journals such as Molecular Informatics, RSC Advances, Nature Communications, Nature Chemistry and Journal of Biomolecular NMR.
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.