Common structural motif identification in genomic sequences

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "V. Preeja and K. A. {Abdul Nazeer} and 
                 S. S. {Vinod Chandra}",
  booktitle =    "Data Science Engineering (ICDSE), 2012 International
                 Conference on",
  title =        "Common structural motif identification in genomic
  year =         "2012",
  pages =        "37--41",
  DOI =          "doi:10.1109/ICDSE.2012.6282301",
  size =         "5 pages",
  abstract =     "Identification of structural and sequence motifs in
                 genomic sequences is gaining much attention now a days.
                 Ribonucleic acid or RNA is one of the important
                 biomolecule whose secondary structure defines its
                 functionality. Soft computing techniques like genetic
                 programming have been used for motif identification. In
                 this paper, we propose a method for identifying common
                 structural motifs in a set of RNA sequences by particle
                 swarm optimisation technique. The common motif
                 identification finds its application in drug design. To
                 prove the correctness of our approach, we tested it on
                 data sets previously used to find common structural
                 motif using genetic programming approaches. Several
                 experiments were conducted using Signal Recognition
                 Particle (SRP), Ferritin Iron Response Element (IRE)
                 and microRNA sequences. Our results are comparable to
                 the latest genetic programming approach. Some of the
                 results indicate that our method out performs to most
                 of the genetic programming approaches.",
  keywords =     "genetic algorithms, genetic programming, RNA, drugs,
                 genomics, particle swarm optimisation, IRE, SRP, common
                 structural motif identification, drug design, ferritin
                 iron response element, genetic programming approach,
                 genomic sequences, microRNA sequences, particle swarm
                 optimisation technique, ribonucleic acid, sequence
                 motif identification, signal recognition particle, soft
                 computing techniques, Iron, Optimisation, Particle
                 swarm optimisation, RNA, Skeleton",
  notes =        "Also known as \cite{6282301}",

Genetic Programming entries for V Preeja K A Abdul Nazeer S S Vinod Chandra