David Ramírez
Impact in
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- Computational Drug Discovery Methods
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
Papers in
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- Ion channel regulation and function 18
- Nicotinic Acetylcholine Receptors Study 7
- Receptor Mechanisms and Signaling 4
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- Computational Drug Discovery Methods 18
- Co-authors
- Julio Caballero (6 shared papers)Ana Martı́nez (11 shared papers)Wendy González (19 shared papers)Carmen Gil (8 shared papers)Vanesa Nozal (5 shared papers)Nuria E. Campillo (2 shared papers)Tiziana Ginex (2 shared papers)Inés Maestro (2 shared papers)
In The Last Decade
David Ramírez
69 papers receiving 1.9k citations
David Ramírez's Hit Papers
Peers
Comparison fields: 5 of 132
- Computational Theory and Mathematics 492
- Infectious Diseases 271
- Molecular Biology 877
- Pharmacology 104
- Drug Discovery 2
Countries citing papers authored by David Ramírez
This map shows the geographic impact of David Ramírez'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 David Ramírez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Ramírez more than expected).
Fields of papers citing papers by David Ramírez
This network shows the impact of papers produced by David Ramírez. 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 David Ramírez. The network helps show where David Ramírez may publish in the future.
Co-authors
The 25 scholars most cited alongside David Ramírez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Is It Reliable to Take the Molecular Docking Top Scoring Position as the Best Solution without Considering Available Structural Data? Hit paper breakdown → | 2018 | 394 |
| 2 | 2020 | 332 | |
| 3 | 2016 | 133 | |
| 4 | 2017 | 90 | |
| 5 | 2016 | 55 | |
| 6 | 2017 | 48 | |
| 7 | 2018 | 48 | |
| 8 | 2014 | 47 | |
| 9 | 2016 | 46 | |
| 10 | 2020 | 37 | |
| 11 | 2016 | 34 | |
| 12 | 2017 | 34 | |
| 13 | 2017 | 34 | |
| 14 | 2018 | 31 | |
| 15 | 2023 | 29 | |
| 16 | 2019 | 29 | |
| 17 | 2006 | 29 | |
| 18 | 2022 | 28 | |
| 19 | 1999 | 26 | |
| 20 | 2021 | 23 |
About David Ramírez
David Ramírez is a scholar working on Molecular Biology, Computational Theory and Mathematics, Organic Chemistry, Genetics and Pharmacology, having authored 76 papers that have together received 1.9k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (18 papers), Ion channel regulation and function (18 papers), Nicotinic Acetylcholine Receptors Study (7 papers), Cholinesterase and Neurodegenerative Diseases (7 papers), Click Chemistry and Applications (6 papers), Cardiac electrophysiology and arrhythmias (5 papers), Receptor Mechanisms and Signaling (4 papers) and Neuroscience and Neuropharmacology Research (4 papers). The work is most often cited by research in Computational Theory and Mathematics (492 citations), Infectious Diseases (271 citations), Molecular Biology (877 citations), Pharmacology (104 citations) and Drug Discovery (2 citations). David Ramírez has collaborated with scholars based in Chile, Colombia and Spain. Frequent co-authors include Julio Caballero, Ana Martı́nez, Wendy González, Carmen Gil, Vanesa Nozal, Nuria E. Campillo, Tiziana Ginex, Inés Maestro, Jesús Urquiza and Miguel Ángel Cuesta-Geijo. Their work appears in journals such as International Journal of Molecular Sciences, Molecules, Scientific Reports, Journal of Medicinal Chemistry and Pharmaceuticals.
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.