Who is Who in Phylogenetic Networks

Publications related to 'AIC' : The AIC or Akaike Information Criterion is a criterion for model selection. More information on Wikipedia   Order by:   Type | Year

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Associated keywords

abstract-network AIC BIC branch-length coalescent explicit-network from-rooted-trees from-species-tree heuristic hybridization likelihood lineage-sorting model-selection phylogenetic-network phylogeny reconstruction split split-network statistical-model

Article (Journal)

1 Laura S. Kubatko. Identifying Hybridization Events in the Presence of Coalescence via Model Selection. In Systematic Biology, Vol. 58(5):478-488, 2009. Keywords: AIC, BIC, branch length, coalescent, explicit network, from rooted trees, from species tree, hybridization, lineage sorting, model selection, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1093/sysbio/syp055.         2 Yun Yu, James H. Degnan and Luay Nakhleh. The probability of a gene tree topology within a phylogenetic network with applications to hybridization detection. In PLoS Genetics, Vol. 8(4):e1002660, 2012. Keywords: AIC, BIC, explicit network, hybridization, phylogenetic network, phylogeny, statistical model. Note: http://dx.doi.org/10.1371/journal.pgen.1002660.         Toggle abstract "Gene tree topologies have proven a powerful data source for various tasks, including species tree inference and species delimitation. Consequently, methods for computing probabilities of gene trees within species trees have been developed and widely used in probabilistic inference frameworks. All these methods assume an underlying multispecies coalescent model. However, when reticulate evolutionary events such as hybridization occur, these methods are inadequate, as they do not account for such events. Methods that account for both hybridization and deep coalescence in computing the probability of a gene tree topology currently exist for very limited cases. However, no such methods exist for general cases, owing primarily to the fact that it is currently unknown how to compute the probability of a gene tree topology within the branches of a phylogenetic network. Here we present a novel method for computing the probability of gene tree topologies on phylogenetic networks and demonstrate its application to the inference of hybridization in the presence of incomplete lineage sorting. We reanalyze a Saccharomyces species data set for which multiple analyses had converged on a species tree candidate. Using our method, though, we show that an evolutionary hypothesis involving hybridization in this group has better support than one of strict divergence. A similar reanalysis on a group of three Drosophila species shows that the data is consistent with hybridization. Further, using extensive simulation studies, we demonstrate the power of gene tree topologies at obtaining accurate estimates of branch lengths and hybridization probabilities of a given phylogenetic network. Finally, we discuss identifiability issues with detecting hybridization, particularly in cases that involve extinction or incomplete sampling of taxa. © 2012 Yu et al."

InProceedings

3 Hyun Jung Park and Luay Nakhleh. Inference of reticulate evolutionary histories by maximum likelihood: The performance of information criteria. In RECOMB-CG'12, Vol. 13(suppl 19):S12 of BMCB, 2012. Keywords: AIC, BIC, explicit network, heuristic, likelihood, phylogenetic network, phylogeny, reconstruction, statistical model. Note: http://www.biomedcentral.com/1471-2105/13/S19/S12.

PhdThesis

4 Alethea Rea. Statistical approaches to phylogenetic networks, recombination and testing of incongruence. PhD thesis, The University of Auckland, New Zealand, 2011. Keywords: abstract network, AIC, BIC, phylogenetic network, phylogeny, split, split network, statistical model. Note: https://researchspace.auckland.ac.nz/handle/2292/67624.