Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-15294-8_25
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dc.titleAn efficient method for DNA-based species assignment via gene tree and species tree reconciliation
dc.contributor.authorZhang, L.
dc.contributor.authorCui, Y.
dc.date.accessioned2014-10-28T02:50:30Z
dc.date.available2014-10-28T02:50:30Z
dc.date.issued2010
dc.identifier.citationZhang, L.,Cui, Y. (2010). An efficient method for DNA-based species assignment via gene tree and species tree reconciliation. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6293 LNBI : 300-311. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-15294-8_25" target="_blank">https://doi.org/10.1007/978-3-642-15294-8_25</a>
dc.identifier.isbn3642152937
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104533
dc.description.abstractDNA-based species assignment and delimitation are two important problems in systematic biology. In a recent work of O'Meara, species delimitation is investigated through coupling it with species tree inference in the framework of gene tree and species tree reconciliation. We present a polynomial time algorithm for splitting individuals into species to minimize the deep coalescence cost of the gene tree and species tree reconciliation, a species assignment problem arises from species delimitation via gene tree and species tree reconciliation. How to incorporate this proposed algorithm into the heuristic search strategy of O'Meara for species delimitation is also discussed. The proposed algorithm is implemented in C++. © 2010 Springer-Verlag.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-15294-8_25
dc.sourceScopus
dc.subjectdeep coalescence
dc.subjectdene duplication and loss
dc.subjectDNA barcoding
dc.subjectgene tree and species tree reconciliation
dc.subjectspecies delimitation
dc.typeConference Paper
dc.contributor.departmentMATHEMATICS
dc.description.doi10.1007/978-3-642-15294-8_25
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6293 LNBI
dc.description.page300-311
dc.identifier.isiutNOT_IN_WOS
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