Jenke Scheen
Impact in
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- Computational Drug Discovery Methods
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- Protein Structure and Dynamics
- RNA and protein synthesis mechanisms
- Microbial Metabolic Engineering and Bioproduction
Papers in
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- Protein Structure and Dynamics 6
- Melanoma and MAPK Pathways 1
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- Machine Learning in Materials Science 4
- Enzyme Structure and Function 2
- Co-authors
- Julien Michel (5 shared papers)Antonia S. J. S. Mey (4 shared papers)John D. Chodera (4 shared papers)Andrea Rizzi (2 shared papers)Michael R. Shirts (2 shared papers)Gary Tresadern (2 shared papers)David L. Mobley (3 shared papers)Bryce K. Allen (2 shared papers)
- Journals
- The Journal of Physical Chemistry B (2 papers)Journal of Chemical Information and Modeling (1 paper)The Journal of Physical Chemistry A (1 paper)eScholarship (California Digital Library) (1 paper)Digital Discovery (1 paper)
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Jenke Scheen
7 papers receiving 267 citations
Peers
Comparison fields: 5 of 63
- Computational Theory and Mathematics 130
- Molecular Biology 216
- Materials Chemistry 107
- Physical and Theoretical Chemistry 14
- Spectroscopy 23
Countries citing papers authored by Jenke Scheen
This map shows the geographic impact of Jenke Scheen'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 Jenke Scheen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jenke Scheen more than expected).
Fields of papers citing papers by Jenke Scheen
This network shows the impact of papers produced by Jenke Scheen. 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 Jenke Scheen. The network helps show where Jenke Scheen may publish in the future.
Co-authors
The 25 scholars most cited alongside Jenke Scheen, 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 | Best Practices for Alchemical Free Energy Calculations [Article v1.0]. | 2020 | 184 |
| 2 | 2020 | 40 | |
| 3 | 2024 | 20 | |
| 4 | 2023 | 9 | |
| 5 | 2019 | 8 | |
| 6 | 2022 | 8 | |
| 7 | 2025 | 5 | |
| 8 | 2025 | 0 |
About Jenke Scheen
Jenke Scheen is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Computer Networks and Communications and Information Systems and Management, having authored 8 papers that have together received 274 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (4 papers), Enzyme Structure and Function (2 papers), Molecular Junctions and Nanostructures (1 paper), Scientific Computing and Data Management (1 paper), Distributed and Parallel Computing Systems (1 paper) and Melanoma and MAPK Pathways (1 paper). The work is most often cited by research in Computational Theory and Mathematics (130 citations), Molecular Biology (216 citations), Materials Chemistry (107 citations), Physical and Theoretical Chemistry (14 citations) and Spectroscopy (23 citations). Jenke Scheen has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Julien Michel, Antonia S. J. S. Mey, John D. Chodera, Andrea Rizzi, Michael R. Shirts, Gary Tresadern, David L. Mobley, Bryce K. Allen, Samarjeet Prasad and Levi N. Naden. Their work appears in journals such as The Journal of Physical Chemistry B, Journal of Chemical Information and Modeling, The Journal of Physical Chemistry A, eScholarship (California Digital Library) and Digital Discovery.
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.