Paper Info
Title
Finding motifs in DNA sequences applying a multiobjective artificial bee colony (MOABC) algorithm
Abstract
In this work we propose the application of a Swarm Intelligence (SI) algorithm to solve the Motif Discovery Problem (MDP), applied to the specific task of discovering novel Transcription Factor Binding Sites (TFBS) in DNA sequences. In the last years there have appeared many new evolutionary algorithms based on the collective intelligence. Finding TFBS is crucial for understanding the gene regulatory relationship but, motifs are weakly conserved, and motif discovery is an NP-hard problem. Therefore, the use of such algorithms can be a good way to obtain quality results. The chosen algorithm is the Artificial Bee Colony (ABC), it is an optimization algorithm based on the intelligent foraging behaviour of honey bee swarm. To solve the MDP we have applied multiobjective optimization and consequently, we have adapted the ABC to multiobjective problems, defining the Multiobjective Artificial Bee Colony (MOABC) algorithm. New results have been obtained, that significantly improve those published in previous researches.
Year
DOI
Venue
2011
10.1007/978-3-642-20389-3_9
EvoBIO
Keywords
Field
DocType
optimization algorithm,dna sequence,new evolutionary algorithm,artificial bee colony,new result,multiobjective artificial bee colony,motif discovery problem,finding tfbs,multiobjective optimization,chosen algorithm,evolutionary algorithm,swarm intelligence,transcription factor binding site,np hard problem,collective intelligence
Evolutionary algorithm,Computer science,Swarm intelligence,Swarming (honey bee),Multi-objective optimization,Artificial intelligence,DNA sequencing,Artificial bee colony algorithm,DNA binding site,Collective intelligence,Algorithm,Bioinformatics,Machine learning
Conference
Volume
ISSN
Citations 
6623
0302-9743
9
PageRank 
References 
Authors
0.49
15
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