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MODEL SELECTION IN PHYLOGENETICS

Investigation into model selection has a long history in the statistical literature. As model-based approaches begin dominating systematic biology, increased attention has focused on how models should be selected for distance-based, likelihood, and Bayesian phylogenetics. Here, we review issues that... Full description

Journal Title: Annual review of ecology evolution, and systematics, 2005-12-15, Vol.36 (1), p.445-466
Main Author: Sullivan, Jack
Other Authors: Joyce, Paul
Format: Electronic Article Electronic Article
Language: English
Subjects:
AIC
Analysis
Animal and plant ecology
Animal, plant and microbial ecology
BIC
Biological and medical sciences
Biology
Data analysis
Data models
Datasets
Decision theory
Deoxyribonucleic acid
DNA
Evolution
Fundamental and applied biological sciences. Psychology
General aspects
likelihood ratio
Modeling
Nature
Nucleotides
Parametric models
Phylogenetics
Phylogeny
Phylogeny (Botany)
Posadas
Quantitative genetics
Science
statistical phylogenetics
Studies
Taxonomy
Topology
Publisher: Palo Alto, CA: Annual Reviews
ID: ISSN: 1543-592X
Link: http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17350747
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recordid: cdi_proquest_journals_219529996
title: MODEL SELECTION IN PHYLOGENETICS
format: Article
creator:
  • Sullivan, Jack
  • Joyce, Paul
subjects:
  • AIC
  • Analysis
  • Animal and plant ecology
  • Animal, plant and microbial ecology
  • BIC
  • Biological and medical sciences
  • Biology
  • Data analysis
  • Data models
  • Datasets
  • Decision theory
  • Deoxyribonucleic acid
  • DNA
  • Evolution
  • Fundamental and applied biological sciences. Psychology
  • General aspects
  • likelihood ratio
  • Modeling
  • Nature
  • Nucleotides
  • Parametric models
  • Phylogenetics
  • Phylogeny
  • Phylogeny (Botany)
  • Posadas
  • Quantitative genetics
  • Science
  • statistical phylogenetics
  • Studies
  • Taxonomy
  • Topology
ispartof: Annual review of ecology, evolution, and systematics, 2005-12-15, Vol.36 (1), p.445-466
description: Investigation into model selection has a long history in the statistical literature. As model-based approaches begin dominating systematic biology, increased attention has focused on how models should be selected for distance-based, likelihood, and Bayesian phylogenetics. Here, we review issues that render model-based approaches necessary, briefly review nucleotide-based models that attempt to capture relevant features of evolutionary processes, and review methods that have been applied to model selection in phylogenetics: likelihood-ratio tests, AIC, BIC, and performance-based approaches.
language: eng
source:
identifier: ISSN: 1543-592X
fulltext: no_fulltext
issn:
  • 1543-592X
  • 1545-2069
url: Link


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descriptionInvestigation into model selection has a long history in the statistical literature. As model-based approaches begin dominating systematic biology, increased attention has focused on how models should be selected for distance-based, likelihood, and Bayesian phylogenetics. Here, we review issues that render model-based approaches necessary, briefly review nucleotide-based models that attempt to capture relevant features of evolutionary processes, and review methods that have been applied to model selection in phylogenetics: likelihood-ratio tests, AIC, BIC, and performance-based approaches.
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subjectAIC ; Analysis ; Animal and plant ecology ; Animal, plant and microbial ecology ; BIC ; Biological and medical sciences ; Biology ; Data analysis ; Data models ; Datasets ; Decision theory ; Deoxyribonucleic acid ; DNA ; Evolution ; Fundamental and applied biological sciences. Psychology ; General aspects ; likelihood ratio ; Modeling ; Nature ; Nucleotides ; Parametric models ; Phylogenetics ; Phylogeny ; Phylogeny (Botany) ; Posadas ; Quantitative genetics ; Science ; statistical phylogenetics ; Studies ; Taxonomy ; Topology
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issn1543-592X
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abstractInvestigation into model selection has a long history in the statistical literature. As model-based approaches begin dominating systematic biology, increased attention has focused on how models should be selected for distance-based, likelihood, and Bayesian phylogenetics. Here, we review issues that render model-based approaches necessary, briefly review nucleotide-based models that attempt to capture relevant features of evolutionary processes, and review methods that have been applied to model selection in phylogenetics: likelihood-ratio tests, AIC, BIC, and performance-based approaches.
copPalo Alto, CA
pubAnnual Reviews
doi10.1146/annurev.ecolsys.36.102003.152633