Josep Arús‐Pous

2.5k total citations · 1 hit paper
17 papers, 1.3k citations indexed

About

Josep Arús‐Pous is a scholar working on Computational Theory and Mathematics, Molecular Biology and Materials Chemistry. According to data from OpenAlex, Josep Arús‐Pous has authored 17 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computational Theory and Mathematics, 11 papers in Molecular Biology and 7 papers in Materials Chemistry. Recurrent topics in Josep Arús‐Pous's work include Computational Drug Discovery Methods (17 papers), Machine Learning in Materials Science (7 papers) and Chemical Synthesis and Analysis (5 papers). Josep Arús‐Pous is often cited by papers focused on Computational Drug Discovery Methods (17 papers), Machine Learning in Materials Science (7 papers) and Chemical Synthesis and Analysis (5 papers). Josep Arús‐Pous collaborates with scholars based in Switzerland, Sweden and Germany. Josep Arús‐Pous's 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 and has published in prestigious journals such as Angewandte Chemie International Edition, Journal of Medicinal Chemistry and Frontiers in Pharmacology.

In The Last Decade

Josep Arús‐Pous

17 papers receiving 1.3k citations

Hit Papers

REINVENT 2.0: An AI Tool for De Novo Drug Design 2020 2026 2022 2024 2020 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. REINVENT 2.0: An AI Tool for De Novo Drug Design
    2020 263 citations Thomas Blaschke, Josep Arús‐Pous et al. Journal of Chemical Information and Modeling profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Josep Arús‐Pous Switzerland 12 1.0k 776 741 119 98 17 1.3k
Feisheng Zhong China 13 1.1k 1.1× 952 1.2× 671 0.9× 157 1.3× 111 1.1× 18 1.7k
Xutong Li China 20 1.2k 1.1× 1.1k 1.4× 715 1.0× 113 0.9× 111 1.1× 67 2.0k
Jike Wang China 18 753 0.7× 660 0.9× 458 0.6× 79 0.7× 77 0.8× 52 1.1k
Timur Madzhidov Russia 18 818 0.8× 524 0.7× 662 0.9× 147 1.2× 54 0.6× 60 1.2k
Timothy Hirzel United States 4 795 0.8× 550 0.7× 797 1.1× 102 0.9× 54 0.6× 6 1.3k
Philipp Eiden Germany 8 895 0.9× 537 0.7× 788 1.1× 69 0.6× 46 0.5× 9 1.2k
Lars Ruddigkeit Switzerland 8 942 0.9× 751 1.0× 703 0.9× 99 0.8× 113 1.2× 8 1.6k
Zhaoping Xiong China 13 1.1k 1.0× 828 1.1× 647 0.9× 61 0.5× 121 1.2× 22 1.6k
Esben Jannik Bjerrum Sweden 21 1.6k 1.5× 1.2k 1.5× 1.3k 1.8× 214 1.8× 140 1.4× 39 2.2k
Steven Kearnes United States 8 1.1k 1.0× 723 0.9× 1.2k 1.6× 145 1.2× 38 0.4× 17 1.8k

Countries citing papers authored by Josep Arús‐Pous

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

17 of 17 papers shown
1.
Reynoso-Moreno, Inés, et al.. (2025). Exploring Simple Drug Scaffolds from the Generated Database Chemical Space Reveals a Chiral Bicyclic Azepane with Potent Neuropharmacology. Journal of Medicinal Chemistry. 68(9). 9176–9201. 6 indexed citations
2.
Arús‐Pous, Josep, Atanas Patronov, Esben Jannik Bjerrum, et al.. (2020). SMILES-based deep generative scaffold decorator for de-novo drug design. Journal of Cheminformatics. 12(1). 38–38. 131 indexed citations
3.
Arús‐Pous, Josep, et al.. (2020). The Generated Databases (GDBs) as a Source of 3D-shaped Building Blocks for Use in Medicinal Chemistry and Drug Discovery. CHIMIA International Journal for Chemistry. 74(4). 241–241. 15 indexed citations
4.
Arús‐Pous, Josep, et al.. (2020). A Potent and Selective Janus Kinase Inhibitor with a Chiral 3D‐Shaped Triquinazine Ring System from Chemical Space. Angewandte Chemie International Edition. 60(4). 2074–2077. 14 indexed citations
5.
Arús‐Pous, Josep, et al.. (2020). A Potent and Selective Janus Kinase Inhibitor with a Chiral 3D‐Shaped Triquinazine Ring System from Chemical Space. Angewandte Chemie. 133(4). 2102–2105. 1 indexed citations
6.
Blaschke, Thomas, Josep Arús‐Pous, Hongming Chen, et al.. (2020). REINVENT 2.0: An AI Tool for De Novo Drug Design. Journal of Chemical Information and Modeling. 60(12). 5918–5922. 263 indexed citations breakdown →
7.
Kotsias, Panagiotis-Christos, Josep Arús‐Pous, Hongming Chen, et al.. (2020). Direct steering of de novo molecular generation with descriptor conditional recurrent neural networks. Nature Machine Intelligence. 2(5). 254–265. 159 indexed citations
8.
Prykhodko, Oleksii, Simon Johansson, Panagiotis-Christos Kotsias, et al.. (2019). A de novo molecular generation method using latent vector based generative adversarial network. Journal of Cheminformatics. 11(1). 74–74. 257 indexed citations
9.
Arús‐Pous, Josep, Mahendra Awale, Daniel Probst, & Jean‐Louis Reymond. (2019). Exploring Chemical Space with Machine Learning. CHIMIA International Journal for Chemistry. 73(12). 1018–1018. 23 indexed citations
10.
Arús‐Pous, Josep, Simon Johansson, Oleksii Prykhodko, et al.. (2019). Randomized SMILES strings improve the quality of molecular generative models. Journal of Cheminformatics. 11(1). 71–71. 225 indexed citations
11.
Arús‐Pous, Josep, et al.. (2019). Exploring the GDB-13 chemical space using deep generative models. Journal of Cheminformatics. 11(1). 20–20. 121 indexed citations
12.
Arús‐Pous, Josep, Johan Karlsson, Ola Engkvist, et al.. (2019). Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research. Frontiers in Pharmacology. 10. 1303–1303. 34 indexed citations
13.
Arús‐Pous, Josep, Johan Karlsson, Ola Engkvist, et al.. (2019). Applications of Deep-Learning in Exploiting Large-Scale and Heterogeneous Compound Data in Industrial Pharmaceutical Research. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
14.
Kotsias, Panagiotis-Christos, Josep Arús‐Pous, Hongming Chen, et al.. (2019). Direct Steering of de novo Molecular Generation using Descriptor Conditional Recurrent Neural Networks (cRNNs). ChemRxiv. 3 indexed citations
15.
Arús‐Pous, Josep, Daniel Probst, & Jean‐Louis Reymond. (2018). Deep Learning Invades Drug Design and Synthesis. CHIMIA International Journal for Chemistry. 72(1-2). 70–70. 5 indexed citations
16.
Awale, Mahendra, Ricardo Visini, Daniel Probst, Josep Arús‐Pous, & Jean‐Louis Reymond. (2017). Chemical Space: Big Data Challenge for Molecular Diversity. CHIMIA International Journal for Chemistry. 71(10). 661–661. 41 indexed citations
17.
Visini, Ricardo, Josep Arús‐Pous, Mahendra Awale, & Jean‐Louis Reymond. (2017). Virtual Exploration of the Ring Systems Chemical Universe. Journal of Chemical Information and Modeling. 57(11). 2707–2718. 33 indexed citations

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.

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