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dc.contributor.authorNakhleh, Luay
dc.date.accessioned 2014-12-15T17:34:21Z
dc.date.available 2014-12-15T17:34:21Z
dc.date.issued 2013
dc.identifier.citation Nakhleh, Luay. "Computational approaches to species phylogeny inference and gene tree reconciliation." Trends in Ecology & Evolution, 28, no. 12 (2013) Elsevier: 719-728. http://dx.doi.org/10.1016/j.tree.2013.09.004.
dc.identifier.urihttps://hdl.handle.net/1911/78742
dc.description.abstract An intricate relationship exists between gene trees and species phylogenies, due to evolutionary processes that act on the genes within and across the branches of the species phylogeny. From an analytical perspective, gene trees serve as character states for inferring accurate species phylogenies, and species phylogenies serve as a backdrop against which gene trees are contrasted for elucidating evolutionary processes and parameters. In a 1997 paper, Maddison discussed this relationship, reviewed the signatures left by three major evolutionary processes on the gene trees, and surveyed parsimony and likelihood criteria for utilizing these signatures to computationally elucidate this relationship. Here, we review progress that has been made on developing computational methods for analyses under these two criteria, and survey remaining challenges.
dc.language.iso eng
dc.publisher Elsevier
dc.rights This is an author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier.
dc.title Computational approaches to species phylogeny inference and gene tree reconciliation
dc.type Journal article
dc.contributor.funder National Science Foundation
dc.contributor.funder National Library of Medicine
dc.citation.journalTitle Trends in Ecology & Evolution
dc.citation.volumeNumber 28
dc.citation.issueNumber 12
dc.type.dcmi Text
dc.identifier.doihttp://dx.doi.org/10.1016/j.tree.2013.09.004
dc.identifier.pmcid PMC3855310
dc.identifier.pmid 24094331
dc.identifier.grantID DBI-1062463 (National Science Foundation)
dc.identifier.grantID CCF-130217 (National Science Foundation)
dc.identifier.grantID R01LM009494 (National Library of Medicine)
dc.type.publication post-print
dc.citation.firstpage 719
dc.citation.lastpage 728


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