Estimating Genome Reversal Distance by Genetic Algorithm

TL;DR

This paper introduces a genetic algorithm approach to estimate the reversal distance for unsigned genomes by transforming the problem into a signed permutation search, outperforming existing approximation algorithms.

Contribution

The paper presents a novel method using genetic algorithms to estimate genome reversal distance by converting unsigned to signed permutations, improving accuracy over prior approximation algorithms.

Findings

Genetic algorithm outperforms 3/2-approximation algorithm

Transforming unsigned to signed permutations aids in estimation

Method demonstrates improved accuracy in experiments

Abstract

Sorting by reversals is an important problem in inferring the evolutionary relationship between two genomes. The problem of sorting unsigned permutation has been proven to be NP-hard. The best guaranteed error bounded is the 3/2- approximation algorithm. However, the problem of sorting signed permutation can be solved easily. Fast algorithms have been developed both for finding the sorting sequence and finding the reversal distance of signed permutation. In this paper, we present a way to view the problem of sorting unsigned permutation as signed permutation. And the problem can then be seen as searching an optimal signed permutation in all n2 corresponding signed permutations. We use genetic algorithm to conduct the search. Our experimental result shows that the proposed method outperform the 3/2-approximation algorithm.