Heuristics based on Adjacency Graph Packing for DCJ Distance Considering Intergenic Regions

Fuente: arXiv
Guardado en:
Detalles Bibliográficos
Autores principales: Siqueira, Gabriel, Alexandrino, Alexsandro Oliveira, Oliveira, Andre Rodrigues, Dias, Zanoni
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866915102015356928
author Siqueira, Gabriel
Alexandrino, Alexsandro Oliveira
Oliveira, Andre Rodrigues
Dias, Zanoni
author_facet Siqueira, Gabriel
Alexandrino, Alexsandro Oliveira
Oliveira, Andre Rodrigues
Dias, Zanoni
contents In this work, we explore heuristics for the Adjacency Graph Packing problem, which can be applied to the Double Cut and Join (DCJ) Distance Problem. The DCJ is a rearrangement operation and the distance problem considering it is a well established method for genome comparison. Our heuristics will use the structure called adjacency graph adapted to include information about intergenic regions, multiple copies of genes in the genomes, and multiple circular or linear chromosomes. The only required property from the genomes is that it must be possible to turn one into the other with DCJ operations. We propose one greedy heuristic and one heuristic based on Genetic Algorithms. Our experimental tests in artificial genomes show that the use of heuristics is capable of finding good results that are superior to a simpler random strategy.
format Preprint
id arxiv_https___arxiv_org_abs_2501_07606
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Heuristics based on Adjacency Graph Packing for DCJ Distance Considering Intergenic Regions
Siqueira, Gabriel
Alexandrino, Alexsandro Oliveira
Oliveira, Andre Rodrigues
Dias, Zanoni
Quantitative Methods
In this work, we explore heuristics for the Adjacency Graph Packing problem, which can be applied to the Double Cut and Join (DCJ) Distance Problem. The DCJ is a rearrangement operation and the distance problem considering it is a well established method for genome comparison. Our heuristics will use the structure called adjacency graph adapted to include information about intergenic regions, multiple copies of genes in the genomes, and multiple circular or linear chromosomes. The only required property from the genomes is that it must be possible to turn one into the other with DCJ operations. We propose one greedy heuristic and one heuristic based on Genetic Algorithms. Our experimental tests in artificial genomes show that the use of heuristics is capable of finding good results that are superior to a simpler random strategy.
title Heuristics based on Adjacency Graph Packing for DCJ Distance Considering Intergenic Regions
topic Quantitative Methods
url https://arxiv.org/abs/2501.07606