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BEAST: Bayesian evolutionary analysis by sampling trees
Open accessAbstract
BACKGROUND: The evolutionary analysis of molecular sequence variation is a statistical enterprise. This is reflected in the increased use of probabilistic models for phylogenetic inference, multiple sequence alignment, and molecular population genetics. Here we present BEAST: a fast, flexible software architecture for Bayesian analysis of molecular sequences related by an evolutionary tree. A large number of popular stochastic models of sequence evolution are provided and tree-based models suitable for both within- and between-species sequence data are implemented. RESULTS: BEAST version 1.4.6 consists of 81000 lines of Java source code, 779 classes and 81 packages. It provides models for DNA and protein sequence evolution, highly parametric coalescent analysis, relaxed clock phylogenetics, non-contemporaneous sequence data, statistical alignment and a wide range of options for prior distributions. BEAST source code is object-oriented, modular in design and freely available at http://beast-mcmc.googlecode.com/ under the GNU LGPL license. CONCLUSION: BEAST is a powerful and flexible evolutionary analysis package for molecular sequence variation. It also provides a resource for the further development of new models and statistical methods of evolutionary analysis.
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Torriani, S. F. F., Penselin, D., Knogge, W., Felder, M., Taudien, S., Platzer, M., McDonald, B. A., & Brunner, P. C. (2014) · Fungal Genetics and Biology · doi:10.1016/j.fgb.2013.11.001 · Cited by 63
The Effect of Ancient DNA Damage on Inferences of Demographic Histories
Axelsson, E., Willerslev, E., Gilbert, M. T. P., & Nielsen, R. (2008) · Molecular Biology and Evolution · doi:10.1093/molbev/msn163 · Cited by 62
Hooper, D. M., & Price, T. D. (2015) · Evolution · doi:10.1111/evo.12633 · Cited by 62
Teacher, A. G., Thomas, J. A., & Barnes, I. (2011) · BMC Evolutionary Biology · doi:10.1186/1471-2148-11-214 · Cited by 60
Forrestel, E. J., Donoghue, M. J., & Smith, M. D. (2014) · New Phytologist · doi:10.1111/nph.12846 · Cited by 58
An ordination of life histories using morphological proxies: capital vs. income breeding in insects
Davis, R. B., Javoiš, J., Kaasik, A., Õunap, E., & Tammaru, T. (2016) · Ecology · doi:10.1002/ecy.1435 · Cited by 57
A distinct CDV genotype causing a major epidemic in Alpine wildlife
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Edwards, C. J., Soulsbury, C. D., Statham, M. J., Ho, S. Y. W., Wall, D., Dolf, G., Iossa, G., Baker, P. J., Harris, S., Sacks, B. N., et al. (2012) · Quaternary Science Reviews · doi:10.1016/j.quascirev.2012.10.010 · Cited by 48
The State of Software for Evolutionary Biology
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Maltsev, Y., Krivova, Z., Maltseva, S., Maltseva, K., Gorshkova, E., & Kulikovskiy, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-99376-9 · Cited by 40
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Metadata
- Authors
- Drummond, A. J., & Rambaut, A.
- Venue
- BMC Evolutionary Biology
- Published
- 2007
- Volume
- 7
- Issue
- 1
- Pages
- 214
- ISSN
- 1471-2148 (ISSN-L)
- OpenAlex
- W2110835349
- Cited by
- 12,919
- References
- 16
- FWCI
- 162.59
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.