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

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@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