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Computing the family-free DCJ similarity.


ABSTRACT: BACKGROUND:The genomic similarity is a large-scale measure for comparing two given genomes. In this work we study the (NP-hard) problem of computing the genomic similarity under the DCJ model in a setting that does not assume that the genes of the compared genomes are grouped into gene families. This problem is called family-free DCJ similarity. RESULTS:We propose an exact ILP algorithm to solve the family-free DCJ similarity problem, then we show its APX-hardness and present four combinatorial heuristics with computational experiments comparing their results to the ILP. CONCLUSIONS:We show that the family-free DCJ similarity can be computed in reasonable time, although for larger genomes it is necessary to resort to heuristics. This provides a basis for further studies on the applicability and model refinement of family-free whole genome similarity measures.

SUBMITTER: Rubert DP 

PROVIDER: S-EPMC5998916 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Computing the family-free DCJ similarity.

Rubert Diego P DP   Hoshino Edna A EA   Braga Marília D V MDV   Stoye Jens J   Martinez Fábio V FV  

BMC bioinformatics 20180508 Suppl 6


<h4>Background</h4>The genomic similarity is a large-scale measure for comparing two given genomes. In this work we study the (NP-hard) problem of computing the genomic similarity under the DCJ model in a setting that does not assume that the genes of the compared genomes are grouped into gene families. This problem is called family-free DCJ similarity.<h4>Results</h4>We propose an exact ILP algorithm to solve the family-free DCJ similarity problem, then we show its APX-hardness and present four  ...[more]

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