Derek van Tilborg
Impact in
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- Computational Drug Discovery Methods
Papers in
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- Protein Structure and Dynamics 1
- Metabolomics and Mass Spectrometry Studies 1
- Gene expression and cancer classification 1
- vaccines and immunoinformatics approaches 1
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- Computational Drug Discovery Methods 4
- Co-authors
- Francesca Grisoni (5 shared papers)José Jiménez-Luna (1 shared paper)Roy van der Meel (1 shared paper)Lorenzo Albertazzi (1 shared paper)Li C. Xue (1 shared paper)Nicolas Renaud (1 shared paper)Peter A.C. ’t Hoen (1 shared paper)Edoardo Saccenti (1 shared paper)
- Journals
- Journal of Chemical Information and Modeling (1 paper)Current Opinion in Structural Biology (1 paper)Cancers (1 paper)Nature Computational Science (1 paper)ChemBioChem (1 paper)
- Partner nations
- NetherlandsIranUnited Kingdom
In The Last Decade
Derek van Tilborg
7 papers receiving 329 citations
Derek van Tilborg's Hit Papers
Peers
Comparison fields: 5 of 78
- Computational Theory and Mathematics 166
- Health Informatics 6
- Materials Chemistry 116
- Biophysics 13
- Molecular Biology 145
Countries citing papers authored by Derek van Tilborg
This map shows the geographic impact of Derek van Tilborg'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 Derek van Tilborg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Derek van Tilborg more than expected).
Fields of papers citing papers by Derek van Tilborg
This network shows the impact of papers produced by Derek van Tilborg. 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 Derek van Tilborg. The network helps show where Derek van Tilborg may publish in the future.
Co-authors
The 8 scholars most cited alongside Derek van Tilborg, 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 | Exposing the Limitations of Molecular Machine Learning with Activity Cliffs Hit paper breakdown → | 2022 | 155 |
| 2 | 2024 | 52 | |
| 3 | 2023 | 45 | |
| 4 | 2024 | 33 | |
| 5 | 2022 | 25 | |
| 6 | 2024 | 18 | |
| 7 | 2021 | 3 |
About Derek van Tilborg
Derek van Tilborg is a scholar working on Molecular Biology, Computational Theory and Mathematics, Biophysics, Materials Chemistry and Pharmacology, having authored 7 papers that have together received 331 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Machine Learning in Materials Science (3 papers), Cell Image Analysis Techniques (3 papers), Protein Structure and Dynamics (1 paper), Metabolomics and Mass Spectrometry Studies (1 paper), Immunotherapy and Immune Responses (1 paper), Gene expression and cancer classification (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Computational Theory and Mathematics (166 citations), Health Informatics (6 citations), Materials Chemistry (116 citations), Biophysics (13 citations) and Molecular Biology (145 citations). Derek van Tilborg has collaborated with scholars based in Netherlands, Iran and United Kingdom. Frequent co-authors include Francesca Grisoni, José Jiménez-Luna, Roy van der Meel, Lorenzo Albertazzi, Li C. Xue, Nicolas Renaud, Peter A.C. ’t Hoen and Edoardo Saccenti. Their work appears in journals such as Journal of Chemical Information and Modeling, Current Opinion in Structural Biology, Cancers, Nature Computational Science and ChemBioChem.
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.