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A simpler and faster 1.5-approximation algorithm for sorting by transpositions

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TLDR
All algorithms for sorting linear permutations by transpositions can be used to sort circular permutations, and a new O(n 3/2 log n) 1.5-approximation algorithm is observed, which is considerably simpler than previously reported.
Abstract
An important problem in genome rearrangements is sorting permutations by transpositions. The complexity of the problem is still open, and two rather complicated 1.5-approximation algorithms for sorting linear permutations are known (Bafna and Pevzner, 98 and Christie, 99). The fastest known algorithm is the quadratic algorithm of Bafna and Pevzner. In this paper, we observe that the problem of sorting circular permutations by transpositions is equivalent to the problem of sorting linear permutations by transpositions. Hence, all algorithms for sorting linear permutations by transpositions can be used to sort circular permutations. Our main result is a new O(n3/2√log n) 1.5-approximation algorithm, which is considerably simpler than the previous ones, and whose analysis is significantly less involved.

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Citations
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Journal ArticleDOI

A 1.375-Approximation Algorithm for Sorting by Transpositions

TL;DR: A 1.375-approximation algorithm for sorting by transpositions is provided based on a new upper bound on the diameter of 3-permutations and some new results regarding the transposition diameter are presented.
Journal ArticleDOI

A review of metrics on permutations for search landscape analysis

TL;DR: Algorithms for computing distances on permutations for the most widely applied operators are reviewed and simulation results that compare the exact distances to commonly used approximations are presented.
Journal ArticleDOI

Sorting by Transpositions is Difficult

TL;DR: The transposition distance between two genomes, that is, the minimum number of transpositions needed to transform a genome into another, is a relevant evolutionary distance, and it is proved that the Sorting by Transpositions problem is solved.
Journal ArticleDOI

Sorting by weighted reversals, transpositions, and inverted transpositions.

TL;DR: This paper provides a 1.5-approximation algorithm for sorting by weighted reversals, transpositions and inverted transposition for biologically realistic weights in order to reconstruct ancient events in the evolutionary history of organisms.
Book ChapterDOI

A 2-approximation algorithm for sorting by prefix reversals

TL;DR: This work presents the first polynomial-time 2-approximation algorithm to solve the problem of sorting by Prefix Reversals, where the only allowed operations are reversals of a prefix of the permutation.
References
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Journal ArticleDOI

Self-adjusting binary search trees

TL;DR: The splay tree, a self-adjusting form of binary search tree, is developed and analyzed and is found to be as efficient as balanced trees when total running time is the measure of interest.
BookDOI

Introduction to computational biology

TL;DR: Introduction to computational biology, Introduction to computational Biology, مرکز فناوری اطلاعات و اصاع رسانی, کδاوρزی.
Proceedings ArticleDOI

Transforming cabbage into turnip: polynomial algorithm for sorting signed permutations by reversals

TL;DR: A duality theorem is proved explaining this intriguing performance and it is shown that there exists a “hidden” parameter that allows one to compute the reversal distance between signed permutations in polynomial time.
Journal ArticleDOI

Transforming cabbage into turnip: polynomial algorithm for sorting signed permutations by reversals

TL;DR: Sorting of signed permutations by reversals is studied, a problem that adequately models rearrangements in a small genomes like chloroplast or mitochondrial DNA and proves a duality theorem explaining this intriguing performance.
BookDOI

Computational molecular biology : an algorithmic approach

TL;DR: In one of the first major texts in the emerging field of computational molecular biology, Pavel Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they are connected to molecular biology and to biotechnology.