Pascal Heitel
Impact in
- Biochemistry top 10%
- Eicosanoids and Hypertension Pharmacology
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- Computational Drug Discovery Methods
Papers in
- Oncology 7
- Drug Transport and Resistance Mechanisms 5
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- Inflammatory mediators and NSAID effects 3
- Co-authors
- Daniel J. Merk (15 shared papers)Ewgenij Proschak (9 shared papers)Astrid Kaiser (9 shared papers)Jan Heering (6 shared papers)Manfred Schubert‐Zsilavecz (5 shared papers)Jurema Schmidt (4 shared papers)Mario Wurglics (3 shared papers)Apirat Chaikuad (4 shared papers)
- Journals
- Journal of Medicinal Chemistry (7 papers)ACS Medicinal Chemistry Letters (2 papers)Scientific Reports (2 papers)Journal of the American Chemical Society (1 paper)ChemMedChem (1 paper)
- Partner nations
- GermanyUnited KingdomItaly
In The Last Decade
Pascal Heitel
18 papers receiving 497 citations
Peers
Comparison fields: 5 of 70
- Biochemistry 50
- Biochemistry 29
- Computational Theory and Mathematics 77
- Pharmacology 34
- Cellular and Molecular Neuroscience 72
Countries citing papers authored by Pascal Heitel
This map shows the geographic impact of Pascal Heitel'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 Pascal Heitel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Heitel more than expected).
Fields of papers citing papers by Pascal Heitel
This network shows the impact of papers produced by Pascal Heitel. 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 Pascal Heitel. The network helps show where Pascal Heitel may publish in the future.
Co-authors
The 25 scholars most cited alongside Pascal Heitel, 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 | 2017 | 80 | |
| 2 | 2017 | 78 | |
| 3 | 2020 | 47 | |
| 4 | 2017 | 44 | |
| 5 | 2019 | 39 | |
| 6 | 2018 | 32 | |
| 7 | 2023 | 30 | |
| 8 | 2020 | 25 | |
| 9 | 2021 | 17 | |
| 10 | 2023 | 17 | |
| 11 | 2019 | 16 | |
| 12 | 2019 | 15 | |
| 13 | 2018 | 15 | |
| 14 | 2020 | 15 | |
| 15 | 2021 | 13 | |
| 16 | 2022 | 11 | |
| 17 | 2014 | 7 | |
| 18 | 2024 | 1 | |
| 19 | 2025 | 0 | |
| 20 | 2026 | 0 |
About Pascal Heitel
Pascal Heitel is a scholar working on Oncology, Pharmacology, Biochemistry, Molecular Biology and Computational Theory and Mathematics, having authored 20 papers that have together received 502 indexed citations. Recurring topics across this work include Peroxisome Proliferator-Activated Receptors (6 papers), Drug Transport and Resistance Mechanisms (5 papers), Estrogen and related hormone effects (3 papers), Retinoids in leukemia and cellular processes (3 papers), Computational Drug Discovery Methods (3 papers), Inflammatory mediators and NSAID effects (3 papers), Cholesterol and Lipid Metabolism (2 papers) and Protein Degradation and Inhibitors (2 papers). The work is most often cited by research in Biochemistry (50 citations), Biochemistry (29 citations), Computational Theory and Mathematics (77 citations), Pharmacology (34 citations) and Cellular and Molecular Neuroscience (72 citations). Pascal Heitel has collaborated with scholars based in Germany, United Kingdom and Italy. Frequent co-authors include Daniel J. Merk, Ewgenij Proschak, Astrid Kaiser, Jan Heering, Manfred Schubert‐Zsilavecz, Jurema Schmidt, Mario Wurglics, Apirat Chaikuad, Stefan Knapp and Sabine Willems. Their work appears in journals such as Journal of Medicinal Chemistry, ACS Medicinal Chemistry Letters, Scientific Reports, Journal of the American Chemical Society and ChemMedChem.
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.