Evidence map›Paper›PMID 39719618›Full record

ArticleAlgorithms for molecular biology : AMB2024

On the parameterized complexity of the median and closest problems under some permutation metrics.

Luís Cunha, Ignasi Sau, Uéverton Souza

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Article in Algorithms for molecular biology : AMB, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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Authors and funding

3 authors.

Luís CunhaInstituto de Computação, Universidade Federal Fluminense, Niterói, Brazil. lfignacio@ic.uff.br.
Ignasi Sau *IMPA, Instituto de Matemática Pura e Aplicada, Rio de Janeiro, Brazil.
Uéverton Souza *Instituto de Computação, Universidade Federal Fluminense, Niterói, Brazil.

Funding

Conselho Nacional de Desenvolvimento Científico e Tecnológico 309832/2020-9Conselho Nacional de Desenvolvimento Científico e Tecnológico Universal - 406173/2021-4Coordenação de Aperfeiçoamento de Pessoal de Nível Superior PRINT, 41/2017, grant 88887.717401/2022-00ELITechGroup ANR-20-CE48-0008-01Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro E-26/201.344/2021Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro E-26/201.372/2022
6 · The paper itself

Abstract

Genome rearrangements are events where large blocks of DNA exchange places during evolution. The analysis of these events is a promising tool for understanding evolutionary genomics, providing data for phylogenetic reconstruction based on genome rearrangement measures. Many pairwise rearrangement distances have been proposed, based on finding the minimum number of rearrangement events to transform one genome into the other, using some predefined operation. When more than two genomes are considered, we have the more challenging problem of rearrangement-based phylogeny reconstruction. Given a set of genomes and a distance notion, there are at least two natural ways to define the "target" genome. On the one hand, finding a genome that minimizes the sum of the distances from this to any other, called the median genome. On the other hand, finding a genome that minimizes the maximum distance to any other, called the closest genome. Considering genomes as permutations of distinct integers, some distance metrics have been extensively studied. We investigate the median and closest problems on permutations over the following metrics: breakpoint distance, swap distance, block-interchange distance, short-block-move distance, and transposition distance. In biological applications some values are usually very small, such as the solution value d or the number k of input permutations. For each of these metrics and parameters d or k, we analyze the closest and the median problems from the viewpoint of parameterized complexity. We obtain the following results: NP-hardness for finding the median/closest permutation regarding some metrics of distance, even for only

Indexed as

Closest problemGenome rearrangementsMedian problemParameterized complexity

Identifiers

PMID39719618
PMCPMC11669244

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