Jochen Sieg
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Enzyme Catalysis and Immobilization
- Plant biochemistry and biosynthesis
Papers in
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- Computational Drug Discovery Methods 5
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- Protein Structure and Dynamics 5
- Co-authors
- Matthias Rarey (6 shared papers)Florian Flachsenberg (3 shared papers)Christiane Ehrt (1 shared paper)Konrad Diedrich (1 shared paper)Annett Ungethüm (1 shared paper)Joel Graef (1 shared paper)Katrin Stierand (1 shared paper)Patrick Penner (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (4 papers)Nucleic Acids Research (1 paper)Proteins Structure Function and Bioinformatics (1 paper)Briefings in Bioinformatics (1 paper)Faraday Discussions (1 paper)
- Partner nations
- GermanyUnited States
In The Last Decade
Jochen Sieg
8 papers receiving 434 citations
Jochen Sieg's Hit Papers
Peers
Comparison fields: 5 of 75
- Computational Theory and Mathematics 292
- Molecular Biology 68
- Sensory Systems 5
- Health Informatics 2
- Materials Chemistry 30
Countries citing papers authored by Jochen Sieg
This map shows the geographic impact of Jochen Sieg'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 Jochen Sieg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jochen Sieg more than expected).
Fields of papers citing papers by Jochen Sieg
This network shows the impact of papers produced by Jochen Sieg. 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 Jochen Sieg. The network helps show where Jochen Sieg may publish in the future.
Co-authors
The 19 scholars most cited alongside Jochen Sieg, 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 | In Need of Bias Control: Evaluating Chemical Data for Machine Learning in Structure-Based Virtual Screening Hit paper breakdown → | 2019 | 238 |
| 2 | ProteinsPlus: a comprehensive collection of web-based molecular modeling tools Hit paper breakdown → | 2022 | 155 |
| 3 | 2024 | 30 | |
| 4 | 2018 | 6 | |
| 5 | 2024 | 5 | |
| 6 | 2023 | 4 | |
| 7 | 2022 | 3 | |
| 8 | 2023 | 3 | |
| 9 | 2026 | 0 |
About Jochen Sieg
Jochen Sieg is a scholar working on Computational Theory and Mathematics, Molecular Biology, Materials Chemistry, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 9 papers that have together received 444 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Computational Drug Discovery Methods (5 papers) and Enzyme Structure and Function (2 papers). The work is most often cited by research in Computational Theory and Mathematics (292 citations), Molecular Biology (68 citations), Sensory Systems (5 citations), Health Informatics (2 citations) and Materials Chemistry (30 citations). Jochen Sieg has collaborated with scholars based in Germany and United States. Frequent co-authors include Matthias Rarey, Florian Flachsenberg, Christiane Ehrt, Konrad Diedrich, Annett Ungethüm, Joel Graef, Katrin Stierand, Patrick Penner, Miriam Mathea and Andrea Volkamer. Their work appears in journals such as Journal of Chemical Information and Modeling, Nucleic Acids Research, Proteins Structure Function and Bioinformatics, Briefings in Bioinformatics and Faraday Discussions.
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.