Adrià Pérez
Impact in
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- Computational Drug Discovery Methods
- Materials Chemistry top 10%
- Machine Learning in Materials Science
- Block Copolymer Self-Assembly
- Enzyme Structure and Function
- Material Dynamics and Properties
Papers in
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- Protein Structure and Dynamics 9
- RNA and protein synthesis mechanisms 2
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- Machine Learning in Materials Science 5
- Enzyme Structure and Function 4
- Co-authors
- Gianni De Fabritiis (10 shared papers)Frank Noé (4 shared papers)Cecilia Clementi (4 shared papers)Nicholas E. Charron (3 shared papers)Jiang Wang (2 shared papers)Simon Olsson (2 shared papers)Christoph Wehmeyer (1 shared paper)Maciej Majewski (4 shared papers)
- Journals
- Journal of Chemical Information and Modeling (2 papers)Journal of Chemical Theory and Computation (2 papers)Nature Communications (1 paper)Construction and Building Materials (1 paper)Frontiers in Microbiology (1 paper)
- Partner nations
- SpainUnited StatesGermany
In The Last Decade
Adrià Pérez
11 papers receiving 794 citations
Adrià Pérez's Hit Papers
Peers
Comparison fields: 5 of 97
- Computational Theory and Mathematics 203
- Materials Chemistry 511
- Molecular Biology 437
- Structural Biology 5
- Statistical and Nonlinear Physics 35
Countries citing papers authored by Adrià Pérez
This map shows the geographic impact of Adrià Pérez'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 Adrià Pérez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrià Pérez more than expected).
Fields of papers citing papers by Adrià Pérez
This network shows the impact of papers produced by Adrià Pérez. 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 Adrià Pérez. The network helps show where Adrià Pérez may publish in the future.
Co-authors
The 25 scholars most cited alongside Adrià Pérez, 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 | Machine Learning of Coarse-Grained Molecular Dynamics Force Fields Hit paper breakdown → | 2019 | 355 |
| 2 | 2021 | 172 | |
| 3 | 2020 | 122 | |
| 4 | 2023 | 69 | |
| 5 | 2018 | 29 | |
| 6 | 2020 | 18 | |
| 7 | 2023 | 11 | |
| 8 | 2020 | 11 | |
| 9 | 2021 | 8 | |
| 10 | 2024 | 4 | |
| 11 | 2023 | 4 |
About Adrià Pérez
Adrià Pérez is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Civil and Structural Engineering and Atomic and Molecular Physics, and Optics, having authored 11 papers that have together received 803 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (9 papers), Computational Drug Discovery Methods (5 papers), Machine Learning in Materials Science (5 papers), Enzyme Structure and Function (4 papers), RNA and protein synthesis mechanisms (2 papers), Concrete and Cement Materials Research (1 paper), Building materials and conservation (1 paper) and Fire effects on concrete materials (1 paper). The work is most often cited by research in Computational Theory and Mathematics (203 citations), Materials Chemistry (511 citations), Molecular Biology (437 citations), Structural Biology (5 citations) and Statistical and Nonlinear Physics (35 citations). Adrià Pérez has collaborated with scholars based in Spain, United States and Germany. Frequent co-authors include Gianni De Fabritiis, Frank Noé, Cecilia Clementi, Nicholas E. Charron, Jiang Wang, Simon Olsson, Christoph Wehmeyer, Maciej Majewski, Andreas Krämer and Toni Giorgino. Their work appears in journals such as Journal of Chemical Information and Modeling, Journal of Chemical Theory and Computation, Nature Communications, Construction and Building Materials and Frontiers in Microbiology.
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.