MotifGP: Using multi-objective evolutionary computing for mining network expressions in DNA sequences

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Belmadani:2016:CIBCB,

• author = "Manuel Belmadani and Marcel Turcotte",
• booktitle = "2016 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB)",
• title = "MotifGP: Using multi-objective evolutionary computing for mining network expressions in DNA sequences",
• year = "2016",
• abstract = "This paper describes and evaluates a multi-objective strongly typed genetic programming algorithm for the discovery of network expressions in DNA sequences. Using 13 realistic data sets, we compare the results of our tool, MotifGP, to that of DREME, a state-of-the-art program. MotifGP outperforms DREME when the motifs to be sought are long, and the specificity is distributed over the length of the motif. For shorter motifs, the performance of MotifGP compares favourably with the state-of-the-art method. Finally, we discuss the advantages of multi-objective optimisation in the context of this specific motif discovery problem.",
• keywords = "genetic algorithms, genetic programming",
• DOI = "doi:10.1109/CIBCB.2016.7758133",
• month = oct,
• notes = "Also known as \cite{7758133}",

}

Genetic Programming entries for Manuel Belmadani Marcel Turcotte

Citations