Diego Darriba
- Ecology top 1%
- Endocrinology top 2%
- Plant Science top 1%
- Chromosomal and Genetic Variations 3
- Molecular Biology top 2%
- Genomics and Phylogenetic Studies 10
- RNA and protein synthesis mechanisms 2
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- Genetic diversity and population structure 5
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- Algorithms and Data Compression 4
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- Evolution and Paleontology Studies 3
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- Amphibian and Reptile Biology 2
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- Species Distribution and Climate Change 2
Diego Darriba
15 papers receiving 6.6k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Ecology 1.6k
- Ecology, Evolution, Behavior and Systematics 1.0k
- Endocrinology 260
- Plant Science 1.8k
- Molecular Biology 3.2k
Countries citing papers authored by Diego Darriba
This map shows the geographic impact of Diego Darriba'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 Diego Darriba with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Darriba more than expected).
Fields of papers citing papers by Diego Darriba
This network shows the impact of papers produced by Diego Darriba. 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 Diego Darriba. The network helps show where Diego Darriba may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Diego Darriba, 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 | 2021 | 6 | |
| 2 | ModelTest-NG: A New and Scalable Tool for the Selection of DNA and Protein Evolutionary Modelsbreakdown → | 2019 | 1226 |
| 3 | RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inferencebreakdown → | 2019 | 2509 |
| 4 | 2018 | 34 | |
| 5 | EPA-ng: Massively Parallel Evolutionary Placement of Genetic Sequencesbreakdown → | 2018 | 398 |
| 6 | 2018 | 26 | |
| 7 | 2016 | 17 | |
| 8 | 2016 | 28 | |
| 9 | 2014 | 70 | |
| 10 | 2014 | 0 | |
| 11 | 2014 | 131 | |
| 12 | 2013 | 4 | |
| 13 | 2013 | 8 | |
| 14 | jModelTest2:より多くのモデル,新規発見的方法と並列演算 | 2012 | 5 |
| 15 | 2011 | 3 | |
| 16 | ProtTest 3: fast selection of best-fit models of protein evolutionbreakdown → | 2011 | 2139 |
About Diego Darriba
Diego Darriba is a scholar working on Ecological Modeling, Paleontology, Genetics, Molecular Biology and Artificial Intelligence, having authored 16 papers that have together received 6.6k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (10 papers), Genetic diversity and population structure (5 papers), Algorithms and Data Compression (4 papers), Chromosomal and Genetic Variations (3 papers), Evolution and Paleontology Studies (3 papers), Amphibian and Reptile Biology (2 papers), Species Distribution and Climate Change (2 papers) and RNA and protein synthesis mechanisms (2 papers). The work is most often cited by research in Ecology (1.6k citations), Ecology, Evolution, Behavior and Systematics (1.0k citations), Endocrinology (260 citations), Plant Science (1.8k citations) and Molecular Biology (3.2k citations). Diego Darriba has collaborated with scholars based in Germany, Spain and Greece. Frequent co-authors include Alexandros Stamatakis, Tomáš Flouri, Alexey M. Kozlov, Benoît Morel, David Posada, Guillermo L. Taboada, Ramón Doallo, Pierre Barbera, Lucas Czech and Fernando Izquierdo-Carrasco. Their work appears in journals such as Bioinformatics, Molecular Biology and Evolution, Molecular Phylogenetics and Evolution, Systematic Biology and Nature Methods.
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.