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Inferring horizontal transfers in the presence of rearrangements by the minimum evolution criterion
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
2008 (English)In: Bioinformatics, ISSN 1367-4803, Vol. 24, no 6, 826-832 p.Article in journal (Refereed) Published
Abstract [en]

Motivation: The evolution of viruses is very rapid and in addition to local point mutations (insertion, deletion, substitution) it also includes frequent recombinations, genome rearrangements and horizontal transfer of genetic materials (HGTS). Evolutionary analysis of viral sequences is therefore a complicated matter for two main reasons: First, due to HGTs and recombinations, the right model of evolution is a network and not a tree. Second, due to genome rearrangements, an alignment of the input sequences is not guaranteed. These facts encourage developing methods for inferring phylogenetic networks that do not require aligned sequences as input. Results: In this work, we present the first computational approach which deals with both genome rearrangements and horizontal gene transfers and does not require a multiple alignment as input. We formalize a new set of computational problems which involve analyzing such complex models of evolution. We investigate their computational complexity, and devise algorithms for solving them. Moreover, we demonstrate the viability of our methods on several synthetic datasets as well as four biological datasets.

Place, publisher, year, edition, pages
2008. Vol. 24, no 6, 826-832 p.
Keyword [en]
algorithm, article, controlled study, Cyanobacterium, evolution, gene deletion, gene duplication, gene insertion, gene rearrangement, genetic recombination, horizontal gene transfer, molecular phylogeny, nonhuman, plant, plastid, point mutation, priority journal, Proteobacteria, sequence alignment, simulation, Algorithms, Bacterial Proteins, Base Sequence, Chromosome Mapping, Computer Simulation, DNA Mutational Analysis, Evolution, Molecular, Gene Rearrangement, T-Lymphocyte, Gene Transfer, Horizontal, Models, Genetic, Molecular Sequence Data, Plant Proteins, Sequence Analysis, DNA, Variation (Genetics)
National Category
Bioinformatics (Computational Biology)
URN: urn:nbn:se:kth:diva-154876DOI: 10.1093/bioinformatics/btn024ISI: 000254010400012ScopusID: 2-s2.0-40749139524OAI: diva2:759227

QC 20141029

Available from: 2014-10-29 Created: 2014-10-28 Last updated: 2015-10-12Bibliographically approved

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Elias, Isaac
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Computational Biology, CB
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