Variable Genetic Operator Search for the Molecular Docking Problem

Salma Mesmoudi 1 Jorge Tavares 2 Laetitia Jourdan 3 El-Ghazali Talbi 3
1 DECISION
LIP6 - Laboratoire d'Informatique de Paris 6
3 DOLPHIN - Parallel Cooperative Multi-criteria Optimization
LIFL - Laboratoire d'Informatique Fondamentale de Lille, Inria Lille - Nord Europe
Abstract : The aim of this work is to present a new hybrid algorithm for the Molecular Docking problem: Variable Genetic Operator Search (VGOS). The proposed method combines an Evolutionary Algorithm with Variable Neighborhood Search. Experimental results show that the algorithm is able to achieve good results, in terms of energy optimization and RMSD values for several molecules when compared with previous approaches. In addition, when hybridized with the L-BFGS local search method it attains very competitive results.
Type de document :
Communication dans un congrès
EvoBIO 2010 - 8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, Apr 2010, Istanbul, Turkey. Springer, 6023, pp.1-12, 2010, Lecture Notes in Computer Science. 〈10.1007/978-3-642-12211-8_1〉
Liste complète des métadonnées

https://hal.inria.fr/inria-00522636
Contributeur : Laetitia Jourdan <>
Soumis le : vendredi 1 octobre 2010 - 11:29:48
Dernière modification le : vendredi 31 août 2018 - 09:25:55

Identifiants

Citation

Salma Mesmoudi, Jorge Tavares, Laetitia Jourdan, El-Ghazali Talbi. Variable Genetic Operator Search for the Molecular Docking Problem. EvoBIO 2010 - 8th European Conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics, Apr 2010, Istanbul, Turkey. Springer, 6023, pp.1-12, 2010, Lecture Notes in Computer Science. 〈10.1007/978-3-642-12211-8_1〉. 〈inria-00522636〉

Partager

Métriques

Consultations de la notice

331