Jérôme Eberhardt
Impact in
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods
- Toxicology top 2%
Papers in
-
- Protein Structure and Dynamics 9
- Ubiquitin and proteasome pathways 1
-
- Computational Drug Discovery Methods 10
- Co-authors
- Stefano Forli (12 shared papers)Diogo Santos‐Martins (6 shared papers)Andreas F. Tillack (3 shared papers)Xavier Robin (4 shared papers)Janani Durairaj (4 shared papers)Annick Dejaegere (3 shared papers)Torsten Schwede (3 shared papers)Leonardo Solis-Vasquez (3 shared papers)
- Journals
- Proteins Structure Function and Bioinformatics (4 papers)Journal of Chemical Information and Modeling (3 papers)Journal of Medicinal Chemistry (2 papers)ACS Chemical Biology (2 papers)Journal of Computer-Aided Molecular Design (2 papers)
- Partner nations
- United StatesSwitzerlandGermany
In The Last Decade
Jérôme Eberhardt
19 papers receiving 4.3k citations
Jérôme Eberhardt's Hit Papers
Peers
Comparison fields: 5 of 145
- Computational Theory and Mathematics 856
- Toxicology 104
- Molecular Biology 2.0k
- Pharmacology 245
- Organic Chemistry 764
Countries citing papers authored by Jérôme Eberhardt
This map shows the geographic impact of Jérôme Eberhardt'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 Jérôme Eberhardt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jérôme Eberhardt more than expected).
Fields of papers citing papers by Jérôme Eberhardt
This network shows the impact of papers produced by Jérôme Eberhardt. 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 Jérôme Eberhardt. The network helps show where Jérôme Eberhardt may publish in the future.
Co-authors
The 25 scholars most cited alongside Jérôme Eberhardt, 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 | AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings Hit paper breakdown → | 2021 | 4068 |
| 2 | 2019 | 55 | |
| 3 | 2020 | 43 | |
| 4 | 2023 | 39 | |
| 5 | 2014 | 38 | |
| 6 | 2019 | 30 | |
| 7 | 2023 | 28 | |
| 8 | 2019 | 14 | |
| 9 | 2018 | 13 | |
| 10 | 2019 | 13 | |
| 11 | 2023 | 13 | |
| 12 | 2020 | 9 | |
| 13 | 2020 | 6 | |
| 14 | 2023 | 4 | |
| 15 | 2025 | 3 | |
| 16 | 2025 | 3 | |
| 17 | 2018 | 2 | |
| 18 | 2025 | 1 | |
| 19 | 2024 | 1 |
About Jérôme Eberhardt
Jérôme Eberhardt is a scholar working on Molecular Biology, Computational Theory and Mathematics, Materials Chemistry, Pharmacology and Oncology, having authored 19 papers that have together received 4.4k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (10 papers), Protein Structure and Dynamics (9 papers), Enzyme Structure and Function (4 papers), Machine Learning in Materials Science (3 papers), Drug Transport and Resistance Mechanisms (2 papers), Estrogen and related hormone effects (2 papers), Click Chemistry and Applications (1 paper) and Ubiquitin and proteasome pathways (1 paper). The work is most often cited by research in Computational Theory and Mathematics (856 citations), Toxicology (104 citations), Molecular Biology (2.0k citations), Pharmacology (245 citations) and Organic Chemistry (764 citations). Jérôme Eberhardt has collaborated with scholars based in United States, Switzerland and Germany. Frequent co-authors include Stefano Forli, Diogo Santos‐Martins, Andreas F. Tillack, Xavier Robin, Janani Durairaj, Annick Dejaegere, Torsten Schwede, Leonardo Solis-Vasquez, Andreas Koch and Francesca Alessandra Ambrosio. Their work appears in journals such as Proteins Structure Function and Bioinformatics, Journal of Chemical Information and Modeling, Journal of Medicinal Chemistry, ACS Chemical Biology and Journal of Computer-Aided Molecular Design.
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.