Paper Info
Title
Applying a multiobjective gravitational search algorithm (MO-GSA) to discover motifs
Abstract
Currently there are a large number of Bioinformatics problems that are tackled using computational techniques. The problems discussed range from small molecules to complex systems where many organisms coexist. Among all these issues, we can highlight genomics: it studies the genomes of microorganisms, plants and animals. To discover common patterns, motifs, in a set of deoxyribonucleic acid (DNA) sequences is one of the important sequence analysis problems and it is known as Motif Discovery Problem (MDP). In this work we propose the use of computational Swarm Intelligence for solving the MDP. A new heuristic based on the law of gravity and the notion of mass interactions, the Gravitational Search Algorithm (GSA), is chosen for this purpose, but adapted to a multiobjective context (MO-GSA). To test the performance of the MO-GSA, we have used twelve real data sets corresponding to alive beings. After performing several comparisons with other approaches published in the literature, we conclude that this algorithm outperforms the results obtained by others.
Year
DOI
Venue
2011
10.1007/978-3-642-21498-1_47
IWANN (2)
Keywords
Field
DocType
multiobjective optimization,dna,swarm intelligence
Complex system,Data set,Heuristic,Computer science,Swarm intelligence,Multi-objective optimization,Genomics,Artificial intelligence,Gravitational search algorithm,Machine learning
Conference
Volume
ISSN
Citations 
6692
0302-9743
5
PageRank 
References 
Authors
0.39
9
4
Name
Order
Citations
PageRank
David L. González-Álvarez110712.72
Miguel A. Vega-Rodríguez2741113.05
Juan A. Gómez-Pulido320221.36
Juan Manuel Sánchez-Pérez427830.84