Conrad Stork
Impact in
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- Computational Drug Discovery Methods
- Pharmacology top 5%
- Pharmacogenetics and Drug Metabolism
- Microbial Natural Products and Biosynthesis
Papers in
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- Computational Drug Discovery Methods 16
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- Metabolomics and Mass Spectrometry Studies 4
- Plant biochemistry and biosynthesis 2
- Protein Structure and Dynamics 2
- Co-authors
- Johannes Kirchmair (17 shared papers)Martin Šícho (7 shared papers)Christina de Bruyn Kops (8 shared papers)Ya Chen (3 shared papers)Daniel Svozil (4 shared papers)Angelica Mazzolari (1 shared paper)Bernard Testa (1 shared paper)Alessandro Pedretti (1 shared paper)
In The Last Decade
Conrad Stork
20 papers receiving 604 citations
Peers
Comparison fields: 5 of 87
- Computational Theory and Mathematics 364
- Pharmacology 130
- Pharmacology 82
- Molecular Biology 331
- Toxicology 14
Countries citing papers authored by Conrad Stork
This map shows the geographic impact of Conrad Stork'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 Conrad Stork with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Conrad Stork more than expected).
Fields of papers citing papers by Conrad Stork
This network shows the impact of papers produced by Conrad Stork. 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 Conrad Stork. The network helps show where Conrad Stork may publish in the future.
Co-authors
The 25 scholars most cited alongside Conrad Stork, 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 | 2019 | 88 | |
| 2 | 2019 | 85 | |
| 3 | 2019 | 69 | |
| 4 | 2019 | 60 | |
| 5 | 2017 | 52 | |
| 6 | 2019 | 48 | |
| 7 | 2021 | 44 | |
| 8 | 2017 | 41 | |
| 9 | 2019 | 22 | |
| 10 | 2020 | 19 | |
| 11 | 2024 | 17 | |
| 12 | 2021 | 17 | |
| 13 | 2024 | 16 | |
| 14 | 2021 | 10 | |
| 15 | 2019 | 9 | |
| 16 | 2021 | 8 | |
| 17 | 2023 | 5 | |
| 18 | 2021 | 4 | |
| 19 | 2017 | 4 | |
| 20 | 2025 | 1 |
About Conrad Stork
Conrad Stork is a scholar working on Computational Theory and Mathematics, Molecular Biology, Materials Chemistry, Pharmacology and Dermatology, having authored 20 papers that have together received 619 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (16 papers), Machine Learning in Materials Science (6 papers), Pharmacogenetics and Drug Metabolism (5 papers), Metabolomics and Mass Spectrometry Studies (4 papers), Contact Dermatitis and Allergies (3 papers), Plant biochemistry and biosynthesis (2 papers), Protein Structure and Dynamics (2 papers) and Analytical Chemistry and Chromatography (2 papers). The work is most often cited by research in Computational Theory and Mathematics (364 citations), Pharmacology (130 citations), Pharmacology (82 citations), Molecular Biology (331 citations) and Toxicology (14 citations). Conrad Stork has collaborated with scholars based in Germany, Norway and Austria. Frequent co-authors include Johannes Kirchmair, Martin Šícho, Christina de Bruyn Kops, Ya Chen, Daniel Svozil, Angelica Mazzolari, Bernard Testa, Alessandro Pedretti, Giulio Vistoli and Nina Jeliazkova. Their work appears in journals such as Journal of Chemical Information and Modeling, International Journal of Molecular Sciences, Bioinformatics, Pharmaceuticals and ChemMedChem.
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.