Josep Arús‐Pous
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 17
- Materials Chemistry top 5%
- Machine Learning in Materials Science 7
- Molecular Biology top 10%
- Chemical Synthesis and Analysis 5
- Protein Structure and Dynamics 4
- Cancer therapeutics and mechanisms 2
- Machine Learning in Bioinformatics 1
- Biophysics top 10%
- Environmental Chemistry top 10%
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- Analytical Chemistry and Chromatography 3
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- Microbial Natural Products and Biosynthesis 3
Josep Arús‐Pous
17 papers receiving 1.3k citations
Hit Papers
Peers
Comparison fields: 5 of 104
- Computational Theory and Mathematics 1.0k
- Materials Chemistry 741
- Molecular Biology 776
- Biophysics 43
- Environmental Chemistry 65
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
The 24 scholars most cited alongside Josep Arús‐Pous, 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 | 2025 | 6 | |
| 2 | 2020 | 131 | |
| 3 | 2020 | 15 | |
| 4 | 2020 | 14 | |
| 5 | 2020 | 1 | |
| 6 | REINVENT 2.0: An AI Tool for De Novo Drug Designbreakdown → | 2020 | 263 |
| 7 | 2020 | 159 | |
| 8 | 2019 | 257 | |
| 9 | 2019 | 23 | |
| 10 | 2019 | 225 | |
| 11 | 2019 | 121 | |
| 12 | 2019 | 34 | |
| 13 | 2019 | 1 | |
| 14 | 2019 | 3 | |
| 15 | 2018 | 5 | |
| 16 | 2017 | 41 | |
| 17 | 2017 | 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), Chemical Synthesis and Analysis (5 papers), Protein Structure and Dynamics (4 papers), Analytical Chemistry and Chromatography (3 papers), Microbial Natural Products and Biosynthesis (3 papers), Cancer therapeutics and mechanisms (2 papers) and Machine Learning in Bioinformatics (1 paper). 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.
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.