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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23084
Ver los metadatos del registro completo
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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 Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/23084 |
url |
http://sedici.unlp.edu.ar/handle/10915/23084 |
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) |
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openAccess |
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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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application/pdf 1359-1371 |
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