Sorting by Weighted Reversals, Transpositions, and Inverted Transpositions

Bader, Martin; Ohlebusch, Enno

doi:10.1007/11732990_46

Cited by 14 publications

(15 citation statements)

References 22 publications

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“…For example, frameworks such as De Bruijn graphs have aided the assembly of genomes (Pevzner 2000;Zerbino and Birney 2008), and breakpoint graphs have had success in constructing rearrangement phylogeny across species, pioneered with several contributions from Sankoff and Pevzner (Sankoff and Blanchette 1999;Pevzner 2000;Bader and Ohlebusch 2007;Bader et al 2008;Alekseyev and Pevzner 2009;Warren and Sankoff 2009a,b). These methods have also been adapted to genomes containing duplications (Alekseyev and Pevzner 2007) and cancer (Raphael et al 2003;Raphael and Pevzner 2004;Ozery-Flato and Shamir 2009).…”

mentioning

confidence: 99%

Estimation of rearrangement phylogeny for cancer genomes

Greenman¹,

Pleasance²,

Newman³

et al. 2011

Genome Res.

111

135

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Cancer genomes are complex, carrying thousands of somatic mutations including base substitutions, insertions and deletions, rearrangements, and copy number changes that have been acquired over decades. Recently, technologies have been introduced that allow generation of high-resolution, comprehensive catalogs of somatic alterations in cancer genomes. However, analyses of these data sets generally do not indicate the order in which mutations have occurred, or the resulting karyotype. Here, we introduce a mathematical framework that begins to address this problem. By using samples with accurate data sets, we can reconstruct relatively complex temporal sequences of rearrangements and provide an assembly of genomic segments into digital karyotypes. For cancer genes mutated in rearranged regions, this information can provide a chronological examination of the selective events that have taken place.[Supplemental material is available for this article.]

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mentioning

confidence: 99%

Estimation of rearrangement phylogeny for cancer genomes

Greenman¹,

Pleasance²,

Newman³

et al. 2011

Genome Res.

111

135

View full text Add to dashboard Cite

show abstract

“…and Ohlebusch, 2006). Despite many studies, the complexity of sorting by transpositions remains unknown (Bafna and Pevzner, 1998;Christie, 1999;Walter et al, 2003;Hartman, 2003;Elias and Hartman, 2005).…”

Section: Multi-break Distance Between Circular Genomesmentioning

confidence: 99%

Multi-Break Rearrangements and Breakpoint Re-Uses: From Circular to Linear Genomes

Alekseyev

2008

Journal of Computational Biology

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Multi-break rearrangements break a genome into multiple fragments and further glue them together in a new order. While 2-break rearrangements represent standard reversals, fusions, fissions, and translocations, 3-break rearrangements represent a natural generalization of transpositions. Pevzner (2007a, 2008a) studied multi-break rearrangements in circular genomes and further applied them to the analysis of chromosomal evolution in mammalian genomes. In this paper, we extend these results to the more difficult case of linear genomes. In particular, we give lower bounds for the rearrangement distance between linear genomes and for the breakpoint re-use rate as functions of the number and proportion of transpositions. We further use these results to analyze comparative genomic architecture of mammalian genomes.

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“…He designed a (1 + ε)-approximation algorithm for this weighted sorting problem on signed permutations. Later, Bader et al gave a 1.5-approximation algorithm for any weight proportion between 1 : 1 and 1 : 2 on signed permutations [23] .…”

Section: Introductionmentioning

confidence: 99%

Sorting Unsigned Permutations by Weighted Reversals, Transpositions, and Transreversals

Lou

Zhu

2010

J. Comput. Sci. Technol.

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Reversals, transpositions and transreversals are common events in genome rearrangement. The genome rearrangement sorting problem is to transform one genome into another using the minimum number of given rearrangement operations. An integer permutation is used to represent a genome in many cases. It can be divided into disjoint strips with each strip denoting a block of consecutive integers. A singleton is a strip of one integer. And the genome rearrangement problem turns into the problem of sorting a permutation into the identity permutation equivalently. Hannenhalli and Pevzner designed a polynomial time algorithm for the unsigned reversal sorting problem on those permutations with O(log n) singletons. In this paper, first we describe one case in which Hannenhalli and Pevzner's algorithm may fail and propose a corrected approach. In addition, we propose a (1 + ε)-approximation algorithm for sorting unsigned permutations with O(log n) singletons by reversals of weight 1 and transpositions/transreversals of weight 2.

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Sorting by Weighted Reversals, Transpositions, and Inverted Transpositions

Cited by 14 publications

References 22 publications

Estimation of rearrangement phylogeny for cancer genomes

Estimation of rearrangement phylogeny for cancer genomes

Multi-Break Rearrangements and Breakpoint Re-Uses: From Circular to Linear Genomes

Sorting Unsigned Permutations by Weighted Reversals, Transpositions, and Transreversals

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