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.

Saved in:
Bibliographic Details
Main Authors: Adell, J. C., Dopazo, J.
Format: artículo biblioteca
Language:English
Published: Springer Nature 1994
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
Tags: Add Tag
No Tags, Be the first to tag this record!
id dig-inia-es-10261-291189
record_format koha
spelling 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
institution INIA ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-inia-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del INIA España
language English
topic 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
spellingShingle 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