Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates
Monte Carlo simulation has commonly been used in phylogenetic studies to test different tree-reconstruction methods, and consequently, its application for testing evolutionary models can be considered as a natural extension of this usage. Repetitive simulation of a given evolutionary process, under the restrictions imposed by the model to be tested, along a determinate tree topology allow the estimate of probability distributions for the desired parameters. Next, the phylogenetic tree can be reconstructed again without the constraints of the model, and the parameter of interest, derived from this tree, can be compared to the corresponding probability distribution derived from the restricted, simulated trees. As an example we have used Monte Carlo simulation to test the constancy of evolutionary rates in a set of cytochrome-c protein sequences. © 1994, Springer-Verlag New York Inc. All rights reserved.
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Format: | artículo biblioteca |
Language: | English |
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Springer Nature
1994
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Subjects: | Monte Carlo simulation, Parametric bootstrap, Molecular clock, Evolutionary rates, Phylogeny, Least-squares method, Cytochrome-c, |
Online Access: | http://hdl.handle.net/20.500.12792/1518 http://hdl.handle.net/10261/291189 |
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dig-inia-es-10261-2911892023-02-20T07:15:31Z Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates Adell, J. C. Dopazo, J. Monte Carlo simulation Parametric bootstrap Molecular clock Evolutionary rates Phylogeny Least-squares method Cytochrome-c Monte Carlo simulation has commonly been used in phylogenetic studies to test different tree-reconstruction methods, and consequently, its application for testing evolutionary models can be considered as a natural extension of this usage. Repetitive simulation of a given evolutionary process, under the restrictions imposed by the model to be tested, along a determinate tree topology allow the estimate of probability distributions for the desired parameters. Next, the phylogenetic tree can be reconstructed again without the constraints of the model, and the parameter of interest, derived from this tree, can be compared to the corresponding probability distribution derived from the restricted, simulated trees. As an example we have used Monte Carlo simulation to test the constancy of evolutionary rates in a set of cytochrome-c protein sequences. © 1994, Springer-Verlag New York Inc. All rights reserved. 2023-02-20T07:15:31Z 2023-02-20T07:15:31Z 1994 artículo Journal of Molecular Evolution 38: 305-309 (1994) 0022-2844 http://hdl.handle.net/20.500.12792/1518 http://hdl.handle.net/10261/291189 10.1007/BF00176093 1432-1432 en none Springer Nature |
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Monte Carlo simulation Parametric bootstrap Molecular clock Evolutionary rates Phylogeny Least-squares method Cytochrome-c Monte Carlo simulation Parametric bootstrap Molecular clock Evolutionary rates Phylogeny Least-squares method Cytochrome-c |
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Monte Carlo simulation Parametric bootstrap Molecular clock Evolutionary rates Phylogeny Least-squares method Cytochrome-c Monte Carlo simulation Parametric bootstrap Molecular clock Evolutionary rates Phylogeny Least-squares method Cytochrome-c Adell, J. C. Dopazo, J. Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates |
description |
Monte Carlo simulation has commonly been used in phylogenetic studies to test different tree-reconstruction methods, and consequently, its application for testing evolutionary models can be considered as a natural extension of this usage. Repetitive simulation of a given evolutionary process, under the restrictions imposed by the model to be tested, along a determinate tree topology allow the estimate of probability distributions for the desired parameters. Next, the phylogenetic tree can be reconstructed again without the constraints of the model, and the parameter of interest, derived from this tree, can be compared to the corresponding probability distribution derived from the restricted, simulated trees. As an example we have used Monte Carlo simulation to test the constancy of evolutionary rates in a set of cytochrome-c protein sequences. © 1994, Springer-Verlag New York Inc. All rights reserved. |
format |
artículo |
topic_facet |
Monte Carlo simulation Parametric bootstrap Molecular clock Evolutionary rates Phylogeny Least-squares method Cytochrome-c |
author |
Adell, J. C. Dopazo, J. |
author_facet |
Adell, J. C. Dopazo, J. |
author_sort |
Adell, J. C. |
title |
Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates |
title_short |
Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates |
title_full |
Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates |
title_fullStr |
Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates |
title_full_unstemmed |
Monte Carlo simulation in phylogenies An application to test the constancy of evolutionary rates |
title_sort |
monte carlo simulation in phylogenies an application to test the constancy of evolutionary rates |
publisher |
Springer Nature |
publishDate |
1994 |
url |
http://hdl.handle.net/20.500.12792/1518 http://hdl.handle.net/10261/291189 |
work_keys_str_mv |
AT adelljc montecarlosimulationinphylogeniesanapplicationtotesttheconstancyofevolutionaryrates AT dopazoj montecarlosimulationinphylogeniesanapplicationtotesttheconstancyofevolutionaryrates |
_version_ |
1767603184088383488 |