Variable neighborhood search for solving the DNA fragment assembly problem

Autores
Minetti, Gabriela F.; Alba Torres, Enrique; Luque, Gabriel
Año de publicación
2007
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
The fragment assembly problem consists in the building of the DNA sequence from several hundreds (or even, thousands) of fragments obtained by biologists in the laboratory. This is an important task in any genome project, since the accuracy of the rest of the phases depends of the result of this stage. In addition, real instances are very large and therefore, the efficiency is also a very important issue in the design of fragment assemblers. In this paper, we propose two Variable Neighborhood Search variants for solving the DNA fragment assembly problem. These algorithms are specifically adapted for the problem being the difference between them the optimization orientation (fitness function). One of them maximizes the Parsons’s fitness function (which only considers the overlapping among the fragments) and the other estimates the variation in the number of contigs during a local search movement, in order to minimize the number of contigs. The results show that doesn’t exist a direct relation between these functions (even in several cases opposite values are generated) although for the tested instances, both variants allow to find similar and very good results but the second option reduces significatively the consumed-time.
VIII Workshop de Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
Informática
DNA fragment assembly problem
variable neighborhood search
2-opt heuristic
ADN
Intelligent agents
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/23084

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network_name_str SEDICI (UNLP)
spelling Variable neighborhood search for solving the DNA fragment assembly problemMinetti, Gabriela F.Alba Torres, EnriqueLuque, GabrielCiencias InformáticasInformáticaDNA fragment assembly problemvariable neighborhood search2-opt heuristicADNIntelligent agentsThe fragment assembly problem consists in the building of the DNA sequence from several hundreds (or even, thousands) of fragments obtained by biologists in the laboratory. This is an important task in any genome project, since the accuracy of the rest of the phases depends of the result of this stage. In addition, real instances are very large and therefore, the efficiency is also a very important issue in the design of fragment assemblers. In this paper, we propose two Variable Neighborhood Search variants for solving the DNA fragment assembly problem. These algorithms are specifically adapted for the problem being the difference between them the optimization orientation (fitness function). One of them maximizes the Parsons’s fitness function (which only considers the overlapping among the fragments) and the other estimates the variation in the number of contigs during a local search movement, in order to minimize the number of contigs. The results show that doesn’t exist a direct relation between these functions (even in several cases opposite values are generated) although for the tested instances, both variants allow to find similar and very good results but the second option reduces significatively the consumed-time.VIII Workshop de Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI)2007-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1359-1371http://sedici.unlp.edu.ar/handle/10915/23084enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T10:55:20Zoai:sedici.unlp.edu.ar:10915/23084Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 10:55:20.915SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Variable neighborhood search for solving the DNA fragment assembly problem
title Variable neighborhood search for solving the DNA fragment assembly problem
spellingShingle Variable neighborhood search for solving the DNA fragment assembly problem
Minetti, Gabriela F.
Ciencias Informáticas
Informática
DNA fragment assembly problem
variable neighborhood search
2-opt heuristic
ADN
Intelligent agents
title_short Variable neighborhood search for solving the DNA fragment assembly problem
title_full Variable neighborhood search for solving the DNA fragment assembly problem
title_fullStr Variable neighborhood search for solving the DNA fragment assembly problem
title_full_unstemmed Variable neighborhood search for solving the DNA fragment assembly problem
title_sort Variable neighborhood search for solving the DNA fragment assembly problem
dc.creator.none.fl_str_mv Minetti, Gabriela F.
Alba Torres, Enrique
Luque, Gabriel
author Minetti, Gabriela F.
author_facet Minetti, Gabriela F.
Alba Torres, Enrique
Luque, Gabriel
author_role author
author2 Alba Torres, Enrique
Luque, Gabriel
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Informática
DNA fragment assembly problem
variable neighborhood search
2-opt heuristic
ADN
Intelligent agents
topic Ciencias Informáticas
Informática
DNA fragment assembly problem
variable neighborhood search
2-opt heuristic
ADN
Intelligent agents
dc.description.none.fl_txt_mv The fragment assembly problem consists in the building of the DNA sequence from several hundreds (or even, thousands) of fragments obtained by biologists in the laboratory. This is an important task in any genome project, since the accuracy of the rest of the phases depends of the result of this stage. In addition, real instances are very large and therefore, the efficiency is also a very important issue in the design of fragment assemblers. In this paper, we propose two Variable Neighborhood Search variants for solving the DNA fragment assembly problem. These algorithms are specifically adapted for the problem being the difference between them the optimization orientation (fitness function). One of them maximizes the Parsons’s fitness function (which only considers the overlapping among the fragments) and the other estimates the variation in the number of contigs during a local search movement, in order to minimize the number of contigs. The results show that doesn’t exist a direct relation between these functions (even in several cases opposite values are generated) although for the tested instances, both variants allow to find similar and very good results but the second option reduces significatively the consumed-time.
VIII Workshop de Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática (RedUNCI)
description The fragment assembly problem consists in the building of the DNA sequence from several hundreds (or even, thousands) of fragments obtained by biologists in the laboratory. This is an important task in any genome project, since the accuracy of the rest of the phases depends of the result of this stage. In addition, real instances are very large and therefore, the efficiency is also a very important issue in the design of fragment assemblers. In this paper, we propose two Variable Neighborhood Search variants for solving the DNA fragment assembly problem. These algorithms are specifically adapted for the problem being the difference between them the optimization orientation (fitness function). One of them maximizes the Parsons’s fitness function (which only considers the overlapping among the fragments) and the other estimates the variation in the number of contigs during a local search movement, in order to minimize the number of contigs. The results show that doesn’t exist a direct relation between these functions (even in several cases opposite values are generated) although for the tested instances, both variants allow to find similar and very good results but the second option reduces significatively the consumed-time.
publishDate 2007
dc.date.none.fl_str_mv 2007-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
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dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/23084
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dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
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1359-1371
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