A multi-objective evolutionary approach ...
Document type :
Rapport de recherche: Autre communication scientifique (congrès sans actes - poster - séminaire...)
Title :
A multi-objective evolutionary approach to phylogenetic inference problems: Initial experiences porting PhyloMOEA to ParadisEO framework
Author(s) :
Cancino Ticona, Waldo Gonzalo [Auteur correspondant]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Jourdan, Laetitia [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Jourdan, Laetitia [Auteur]
![refId](/themes/Mirage2//images/idref.png)
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]
![refId](/themes/Mirage2//images/idref.png)
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Institution :
INRIA
Publication date :
2009
HAL domain(s) :
Informatique [cs]/Bio-informatique [q-bio.QM]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
Sciences du Vivant [q-bio]/Bio-Informatique, Biologie Systémique [q-bio.QM]
English abstract : [en]
Several phylogenetic reconstruction methods have been proposed in order to find the best tree that represents the evolutionary history of species analyzed. Most of these methods define an optimality criterion for the ...
Show more >Several phylogenetic reconstruction methods have been proposed in order to find the best tree that represents the evolutionary history of species analyzed. Most of these methods define an optimality criterion for the evaluation of possible solutions. However, different criteria may lead to dissimilar phylogenies, which often conflict with each other. In this context, a multi-objective approach can be useful since it could produce a set of optimal trees according to multiple criteria. PhyloMOEA proposes a multi objective approach to phylogenetic inference using maximum parsimony and maximum likelihood criteria. However, in many aspects, PhyloMOEA is a very basic tool with limited expandability. The availability of metaheuristic and bioinformatics reusable frameworks provides an excellent opportunity to increase PhyloMOEA capabilities. In this report we describe the development of a new parallel PhyloMOEA version using the ParadisEO framework.Show less >
Show more >Several phylogenetic reconstruction methods have been proposed in order to find the best tree that represents the evolutionary history of species analyzed. Most of these methods define an optimality criterion for the evaluation of possible solutions. However, different criteria may lead to dissimilar phylogenies, which often conflict with each other. In this context, a multi-objective approach can be useful since it could produce a set of optimal trees according to multiple criteria. PhyloMOEA proposes a multi objective approach to phylogenetic inference using maximum parsimony and maximum likelihood criteria. However, in many aspects, PhyloMOEA is a very basic tool with limited expandability. The availability of metaheuristic and bioinformatics reusable frameworks provides an excellent opportunity to increase PhyloMOEA capabilities. In this report we describe the development of a new parallel PhyloMOEA version using the ParadisEO framework.Show less >
Language :
Anglais
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