Ricardo Macarrón
Impact in
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- Computational Drug Discovery Methods
- Molecular Biology top 5%
- Histone Deacetylase Inhibitors Research
- Protein Degradation and Inhibitors
- Chemical Synthesis and Analysis
Papers in
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- Enzyme Production and Characterization 5
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- Computational Drug Discovery Methods 9
- Co-authors
- Robert HertzbergDarren V. S. GreenMartyn BanksDragan A. CirovicDejan BojanicG. Sitta SittampalamJeff W. PaslayWilliam P. Janzen
- Journals
- SLAS DISCOVERY (4 papers)Blood (3 papers)Biochemical Journal (3 papers)Journal of Pharmacology and Experimental Therapeutics (1 paper)FEBS Letters (1 paper)
- Partner nations
- United StatesUnited KingdomSpain
In The Last Decade
Ricardo Macarrón
26 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Computational Theory and Mathematics 582
- Molecular Biology 1.3k
- Biophysics 102
- Biotechnology 153
- Pharmacology 208
Countries citing papers authored by Ricardo Macarrón
This map shows the geographic impact of Ricardo Macarrón'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 Ricardo Macarrón with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ricardo Macarrón more than expected).
Fields of papers citing papers by Ricardo Macarrón
This network shows the impact of papers produced by Ricardo Macarrón. 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 Ricardo Macarrón. The network helps show where Ricardo Macarrón may publish in the future.
Co-authors
The 25 scholars most cited alongside Ricardo Macarrón, 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 | 2023 | 2 | |
| 2 | 2020 | 15 | |
| 3 | 2018 | 43 | |
| 4 | 2017 | 12 | |
| 5 | 2016 | 6 | |
| 6 | Impact of high-throughput screening in biomedical research Hit paper breakdown → | 2011 | 920 |
| 7 | 2010 | 112 | |
| 8 | 2010 | 67 | |
| 9 | 2009 | 27 | |
| 10 | 2009 | 47 | |
| 11 | 2006 | 165 | |
| 12 | 2003 | 300 | |
| 13 | 2003 | 11 | |
| 14 | 2003 | 19 | |
| 15 | 2002 | 29 | |
| 16 | 2002 | 41 | |
| 17 | 2000 | 31 | |
| 18 | 1993 | 46 | |
| 19 | 1993 | 17 | |
| 20 | Xylanase and β-xylosidase isolation from cultures of trichoderma reesei QM 9414. | 1990 | 2 |
About Ricardo Macarrón
Ricardo Macarrón is a scholar working on Biotechnology, Computational Theory and Mathematics, Biophysics, Genetics and Molecular Biology, having authored 26 papers that have together received 2.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (9 papers), Biofuel production and bioconversion (7 papers), Enzyme Production and Characterization (5 papers), Protein Degradation and Inhibitors (3 papers), Enzyme Catalysis and Immobilization (3 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (3 papers), Biosimilars and Bioanalytical Methods (3 papers) and Cell Image Analysis Techniques (3 papers). The work is most often cited by research in Computational Theory and Mathematics (582 citations), Molecular Biology (1.3k citations), Biophysics (102 citations), Biotechnology (153 citations) and Pharmacology (208 citations). Ricardo Macarrón has collaborated with scholars based in United States, United Kingdom and Spain. Frequent co-authors include Robert Hertzberg, Darren V. S. Green, Martyn Banks, Dragan A. Cirovic, Dejan Bojanic, G. Sitta Sittampalam, Jeff W. Paslay, William P. Janzen, Tina Garyantes and David Burns. Their work appears in journals such as SLAS DISCOVERY, Blood, Biochemical Journal, Journal of Pharmacology and Experimental Therapeutics and FEBS Letters.
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.