Paper Info
Title
A Parallel Multi-Core Team of Multiobjective Evolutionary Algorithms to Discover DNA Motifs
Abstract
This paper proposes the use of a parallel multi-core team to exploit the characteristics of several algorithms, when solving one of the best known biological problems, the Motif Discovery Problem (MDP). Often, when we solve an optimization problem, we have to tackle very different scenarios. This complicates finding a single technique or algorithm that will be able to solve all of them adequately. One possible solution to this problem is to combine different algorithms in a team that allows us to solve all scenarios. A parallel methodology is designed in this work, which combines the operation of four multiobjective evolutionary algorithms by using OpenMP to solve different motif discovery scenarios. Our conclusions show that our parallel multi-core team is quite flexible and accurate for this application, and an important tool for discovering relevant DNA motifs.
Year
DOI
Venue
2012
10.1109/HPCC.2012.13
HPCC-ICESS
Keywords
Field
DocType
different algorithm,multiobjective evolutionary algorithm,multiobjective evolutionary algorithms,parallel multi-core team,parallel methodology,motif discovery problem,optimization problem,different scenario,different motif discovery scenario,discover dna motifs,biological problem,important tool,optimization,dna,parallel processing,multiobjective optimization,open systems,evolutionary computation,evolutionary algorithms,statistics,multi core,sociology
Evolutionary algorithm,Computer science,Parallel processing,Evolutionary computation,Multi-objective optimization,Exploit,Theoretical computer science,Artificial intelligence,Open system (systems theory),Multi-core processor,Optimization problem,Machine learning
Conference
ISSN
Citations 
PageRank 
2576-3504
1
0.35
References 
Authors
0
4
Name
Order
Citations
PageRank
David L. González-Alvarez110.35
Miguel A. Vega-Rodriguez214518.81
Juan Antonio Gómez Pulido3465.88
Juan Manuel Sánchez-Pérez427830.84