Who is Who in Phylogenetic Networks

Publications related to 'recombination detection'   Order by:   Type | Year

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evaluation explicit-network from-sequences heuristic parsimony phylogenetic-network phylogeny Program-RecPars Program-Sliding-MinPD recombination recombination-detection serial-evolutionary-networks software survey

2007

1 Patricia Buendia and Giri Narasimhan. Searching for Recombinant Donors in a Phylogenetic Network of Serial Samples. In ISBRA07, Vol. 4463:109-120 of LNCS, springer, 2007. Keywords: evaluation, phylogenetic network, phylogeny, recombination, recombination detection. Note: http://dx.doi.org/10.1007/978-3-540-72031-7_10.         2 Patricia Buendia and Giri Narasimhan. Sliding MinPD: Building evolutionary networks of serial samples via an automated recombination detection approach. In BIO, Vol. 23(22):2993-3000, 2007. Keywords: from sequences, phylogenetic network, phylogeny, Program Sliding MinPD, recombination, recombination detection, serial evolutionary networks, software. Note: http://dx.doi.org/10.1093/bioinformatics/btm413.         Toggle abstract "Motivation: Traditional phylogenetic methods assume tree-like evolutionary models and are likely to perform poorly when provided with sequence data from fast-evolving, recombining viruses. Furthermore, these methods assume that all the sequence data are from contemporaneous taxa, which is not valid for serially-sampled data. A more general approach is proposed here, referred to as the Sliding MinPD method, that reconstructs evolutionary networks for serially-sampled sequences in the presence of recombination. Results: Sliding MinPD combines distance-based phylogenetic methods with automated recombination detection based on the best-known sliding window approaches to reconstruct serial evolutionary networks. Its performance was evaluated through comprehensive simulation studies and was also applied to a set of serially-sampled HIV sequences from a single patient. The resulting network organizations reveal unique patterns of viral evolution and may help explain the emergence of disease-associated mutants and drug-resistant strains with implications for patient prognosis and treatment strategies. © The Author 2007. Published by Oxford University Press. All rights reserved."

2002

3 David Posada, Keith A. Crandall and Edward C. Holmes. Recombination in Evolutionary Genomics. In ARG, Vol. 36:75-97, 2002. Keywords: phylogenetic network, phylogeny, recombination, recombination detection, survey. Note: http://dx.doi.org/10.1146/annurev.genet.36.040202.111115.         Toggle abstract "Recombination can be a dominant force in shaping genomes and associated phenotypes. To better understand the impact of recombination on genomic evolution, we need to be able to identify recombination in aligned sequences. We review bioinformatic approaches for detecting recombination and measuring recombination rates. We also examine the impact of recombination on the reconstruction of evolutionary histories and the estimation of population genetic parameters. Finally, we review the role of recombination in the evolutionary history of bacteria, viruses, and human mitochondria. We conclude by highlighting a number of areas for future development of tools to help quantify the role of recombination in genomic evolution."

1993

4 Jotun Hein. A heuristic method to reconstruct the history of sequences subject to recombination. In JME, Vol. 36(4):396-405, 1993. Keywords: explicit network, from sequences, heuristic, parsimony, phylogenetic network, phylogeny, Program RecPars, recombination, recombination detection, software. Note: http://dx.doi.org/10.1007/BF00182187.