Jochen Sieg
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- Bioinformatics and Genomic Networks
- Genetics, Bioinformatics, and Biomedical Research
- Chemical Synthesis and Analysis
- vaccines and immunoinformatics approaches
Papers in
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- Enzyme Structure and Function 5
- Machine Learning in Materials Science 4
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- Protein Structure and Dynamics 6
- Genetics, Bioinformatics, and Biomedical Research 1
- Microbial Metabolic Engineering and Bioproduction 1
- RNA and protein synthesis mechanisms 1
- Co-authors
- Matthias Rarey (6 shared papers)Florian Flachsenberg (3 shared papers)Patrick Penner (1 shared paper)Christiane Ehrt (1 shared paper)Konrad Diedrich (1 shared paper)Katrin Stierand (1 shared paper)Miriam Mathea (3 shared papers)Andrea Volkamer (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (4 papers)Briefings in Bioinformatics (1 paper)Bioinformatics (1 paper)Nucleic Acids Research (1 paper)Proteins Structure Function and Bioinformatics (1 paper)
- Partner nations
- Germany
In The Last Decade
Jochen Sieg
9 papers receiving 355 citations
Peers
Comparison fields: 5 of 88
- Computational Theory and Mathematics 207
- Molecular Biology 227
- Materials Chemistry 128
- Pharmacology 35
- Toxicology 4
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 | 2019 | 205 | |
| 2 | 2022 | 112 | |
| 3 | 2024 | 15 | |
| 4 | 2024 | 10 | |
| 5 | 2018 | 6 | |
| 6 | 2023 | 5 | |
| 7 | 2022 | 3 | |
| 8 | 2023 | 3 | |
| 9 | 2024 | 1 |
About Jochen Sieg
Jochen Sieg is a scholar working on Materials Chemistry, Molecular Biology, Computational Theory and Mathematics, Control and Systems Engineering and Artificial Intelligence, having authored 9 papers that have together received 360 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Enzyme Structure and Function (5 papers), Computational Drug Discovery Methods (4 papers), Machine Learning in Materials Science (4 papers), Genetics, Bioinformatics, and Biomedical Research (1 paper), Microbial Metabolic Engineering and Bioproduction (1 paper), Mass Spectrometry Techniques and Applications (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Computational Theory and Mathematics (207 citations), Molecular Biology (227 citations), Materials Chemistry (128 citations), Pharmacology (35 citations) and Toxicology (4 citations). Jochen Sieg has collaborated with scholars based in Germany. Frequent co-authors include Matthias Rarey, Florian Flachsenberg, Patrick Penner, Christiane Ehrt, Konrad Diedrich, Katrin Stierand, Miriam Mathea, Andrea Volkamer, Christian Feldmann and Conrad Stork. Their work appears in journals such as Journal of Chemical Information and Modeling, Briefings in Bioinformatics, Bioinformatics, Nucleic Acids Research and Proteins Structure Function and Bioinformatics.
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.