Josep Arús‐Pous
- Computational Theory and Mathematics top 0.5%
- Molecular Biology top 10%
- Materials Chemistry top 5%
- Biomedical Engineering
- Pharmacology top 10%
- Co-authors
- Hongming ChenOla EngkvistEsben Jannik BjerrumChristian TyrchanJean‐Louis ReymondSimon JohanssonOleksii PrykhodkoPanagiotis-Christos Kotsias
- Topics
- Computational Drug Discovery Methods (17 papers)Machine Learning in Materials Science (7 papers)Chemical Synthesis and Analysis (5 papers)
- Journals
- Angewandte Chemie International EditionJournal of Medicinal ChemistryFrontiers in Pharmacology
- Partner nations
- SwitzerlandSwedenGermany
In The Last Decade
Josep Arús‐Pous
17 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Computational Theory and Mathematics 1.0k
- Molecular Biology 776
- Materials Chemistry 741
- Biomedical Engineering 119
- Pharmacology 98
Countries citing papers authored by Josep Arús‐Pous
This map shows the geographic impact of Josep Arús‐Pous'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 Josep Arús‐Pous with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josep Arús‐Pous more than expected).
Fields of papers citing papers by Josep Arús‐Pous
This network shows the impact of papers produced by Josep Arús‐Pous. 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 Josep Arús‐Pous. The network helps show where Josep Arús‐Pous may publish in the future.
Co-authorship network of co-authors of Josep Arús‐Pous
This figure shows the co-authorship network connecting the top 25 collaborators of Josep Arús‐Pous. A scholar is included among the top collaborators of Josep Arús‐Pous based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Josep Arús‐Pous. Josep Arús‐Pous is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 131 | |
| 3 | 15 | |
| 4 | 14 | |
| 5 | 1 | |
| 6 | REINVENT 2.0: An AI Tool for De Novo Drug Designbreakdown → | 263 |
| 7 | 159 | |
| 8 | 257 | |
| 9 | 23 | |
| 10 | 225 | |
| 11 | 121 | |
| 12 | 34 | |
| 13 | 1 | |
| 14 | 3 | |
| 15 | 5 | |
| 16 | 41 | |
| 17 | 33 |
About Josep Arús‐Pous
Josep Arús‐Pous is a scholar working on Computational Theory and Mathematics, Spectroscopy and Pharmacology, having authored 17 papers that have together received 1.3k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (17 papers), Machine Learning in Materials Science (7 papers) and Chemical Synthesis and Analysis (5 papers). The work is most often cited by research in Computational Theory and Mathematics (1.0k citations), Materials Chemistry (741 citations) and Molecular Biology (776 citations). Josep Arús‐Pous has collaborated with scholars based in Switzerland, Sweden and Germany. Frequent co-authors include Hongming Chen, Ola Engkvist, Esben Jannik Bjerrum, Christian Tyrchan, Jean‐Louis Reymond, Simon Johansson, Oleksii Prykhodko, Panagiotis-Christos Kotsias, Thomas Blaschke and Atanas Patronov. Their work appears in journals such as Angewandte Chemie International Edition, Journal of Medicinal Chemistry and Frontiers in Pharmacology.
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.