Iván Pulido
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Materials Science
- Enzyme Structure and Function
- Photochromic and Fluorescence Chemistry
Papers in
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- Protein Structure and Dynamics 5
- Metabolomics and Mass Spectrometry Studies 1
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- Machine Learning in Materials Science 3
- Enzyme Structure and Function 2
- Co-authors
- John D. Chodera (5 shared papers)Yuanqing Wang (3 shared papers)Michael M. Henry (3 shared papers)Benjamin Kaminow (2 shared papers)Ivy Zhang (2 shared papers)Dominic A. Rufa (2 shared papers)Josh Fass (1 shared paper)Hannah E. Bruce Macdonald (1 shared paper)
- Journals
- Chemical Science (2 papers)The Journal of Physical Chemistry A (1 paper)Biophysical Journal (1 paper)Journal of Chemical Theory and Computation (1 paper)PhotonicsViews (1 paper)
- Partner nations
- United StatesJapanUnited Kingdom
In The Last Decade
Iván Pulido
6 papers receiving 110 citations
Peers
Comparison fields: 5 of 38
- Computational Theory and Mathematics 41
- Materials Chemistry 60
- Molecular Biology 61
- Physical and Theoretical Chemistry 7
- Sensory Systems 3
Countries citing papers authored by Iván Pulido
This map shows the geographic impact of Iván Pulido'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 Iván Pulido with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Iván Pulido more than expected).
Fields of papers citing papers by Iván Pulido
This network shows the impact of papers produced by Iván Pulido. 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 Iván Pulido. The network helps show where Iván Pulido may publish in the future.
Co-authors
The 25 scholars most cited alongside Iván Pulido, 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 | 2022 | 50 | |
| 2 | 2024 | 25 | |
| 3 | 2024 | 20 | |
| 4 | 2023 | 13 | |
| 5 | 2019 | 1 | |
| 6 | 2023 | 1 | |
| 7 | 2016 | 0 |
About Iván Pulido
Iván Pulido is a scholar working on Molecular Biology, Materials Chemistry, Atomic and Molecular Physics, and Optics, Computational Theory and Mathematics and Media Technology, having authored 7 papers that have together received 110 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (5 papers), Machine Learning in Materials Science (3 papers), Computational Drug Discovery Methods (2 papers), Enzyme Structure and Function (2 papers), Advanced Optical Imaging Technologies (2 papers), Photorefractive and Nonlinear Optics (1 paper), Crystallography and molecular interactions (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). The work is most often cited by research in Computational Theory and Mathematics (41 citations), Materials Chemistry (60 citations), Molecular Biology (61 citations), Physical and Theoretical Chemistry (7 citations) and Sensory Systems (3 citations). Iván Pulido has collaborated with scholars based in United States, Japan and United Kingdom. Frequent co-authors include John D. Chodera, Yuanqing Wang, Michael M. Henry, Benjamin Kaminow, Ivy Zhang, Dominic A. Rufa, Josh Fass, Hannah E. Bruce Macdonald, Jenke Scheen and Hugo MacDermott-Opeskin. Their work appears in journals such as Chemical Science, The Journal of Physical Chemistry A, Biophysical Journal, Journal of Chemical Theory and Computation and PhotonicsViews.
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.