David Asturiol
Impact in
- Dermatology top 5%
- Contact Dermatitis and Allergies
- Chemical Health and Safety top 10%
Papers in
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- Animal testing and alternatives 10
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- Computational Drug Discovery Methods 6
- Co-authors
- Andrew Worth (15 shared papers)Lara Lamon (8 shared papers)Karin Aschberger (5 shared papers)Silvana Casati (1 shared paper)Pilar Prieto (3 shared papers)Rabea Graepel (4 shared papers)Elisabeth Joossens (3 shared papers)Silvia Casati (2 shared papers)
In The Last Decade
David Asturiol
19 papers receiving 446 citations
Peers
Comparison fields: 5 of 85
- Dermatology 103
- Chemical Health and Safety 8
- Small Animals 83
- Health, Toxicology and Mutagenesis 109
- Computational Theory and Mathematics 101
Countries citing papers authored by David Asturiol
This map shows the geographic impact of David Asturiol'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 David Asturiol with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Asturiol more than expected).
Fields of papers citing papers by David Asturiol
This network shows the impact of papers produced by David Asturiol. 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 David Asturiol. The network helps show where David Asturiol may publish in the future.
Co-authors
The 25 scholars most cited alongside David Asturiol, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 56 | |
| 2 | 2016 | 46 | |
| 3 | 2016 | 45 | |
| 4 | 2018 | 43 | |
| 5 | 2019 | 40 | |
| 6 | 2015 | 36 | |
| 7 | 2018 | 32 | |
| 8 | 2021 | 28 | |
| 9 | 2020 | 26 | |
| 10 | 2018 | 19 | |
| 11 | 2018 | 18 | |
| 12 | 2018 | 17 | |
| 13 | 2017 | 14 | |
| 14 | 2017 | 9 | |
| 15 | 2022 | 8 | |
| 16 | 2011 | 8 | |
| 17 | 2023 | 7 | |
| 18 | 2016 | 4 | |
| 19 | Computational models for the safety assessment of nanomaterials | 2017 | 1 |
| 20 | 2025 | 0 |
About David Asturiol
David Asturiol is a scholar working on Small Animals, Computational Theory and Mathematics, Materials Chemistry, Health, Toxicology and Mutagenesis and Dermatology, having authored 21 papers that have together received 457 indexed citations. Recurring topics across this work include Animal testing and alternatives (10 papers), Nanoparticles: synthesis and applications (6 papers), Computational Drug Discovery Methods (6 papers), Contact Dermatitis and Allergies (4 papers), Pesticide Exposure and Toxicity (4 papers), Effects and risks of endocrine disrupting chemicals (3 papers), Microplastics and Plastic Pollution (2 papers) and Occupational exposure and asthma (2 papers). The work is most often cited by research in Dermatology (103 citations), Chemical Health and Safety (8 citations), Small Animals (83 citations), Health, Toxicology and Mutagenesis (109 citations) and Computational Theory and Mathematics (101 citations). David Asturiol has collaborated with scholars based in Italy, France and Belgium. Frequent co-authors include Andrew Worth, Lara Lamon, Karin Aschberger, Silvana Casati, Pilar Prieto, Rabea Graepel, Elisabeth Joossens, Silvia Casati, Joan Cabellos and Alejandro Vílchez. Their work appears in journals such as Toxicology in Vitro, Regulatory Toxicology and Pharmacology, Nanotoxicology, Alternatives to Laboratory Animals and Particle and Fibre Toxicology.
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.