Evolving better RNAfold structure prediction

Created by W.Langdon from gp-bibliography.bib Revision:1.3989

@InProceedings{langdon:2018:EuroGP,
  author =       "William B. Langdon and Justyna Petke and 
                 Ronny Lorenz",
  title =        "Evolving better {RNAfold} structure prediction",
  booktitle =    "EuroGP 2018: Proceedings of the 21st European
                 Conference on Genetic Programming",
  year =         "2018",
  month =        "4-6 " # apr,
  editor =       "Mauro Castelli and Lukas Sekanina and Mengjie Zhang",
  address =      "Parma, Italy",
  organisation = "EvoStar, Species",
  note =         "accepted",
  keywords =     "genetic algorithms, genetic programming, genetic
                 improvement, GGGP, software~engineering, SBSE,
                 Bioinformatics, local search, genomic and phenotypic
                 Tabu restrictions, genetic repair",
  size =         "16 pages",
  abstract =     "Grow and graft genetic programming (GGGP) evolves more
                 than 50000 parameters in a state-of-the-art C program
                 to make functional source code changes which give more
                 accurate predictions of how RNA molecules fold up.
                 Genetic improvement updates 29percent of the dynamic
                 programming free energy model parameters. In most cases
                 (50.3percent) GI gives better predictions on 4655 known
                 secondary structures from RNA_STRAND (29.0percent are
                 worse and 20.7percent are unchanged, Indeed it also
                 does better than parameters recommended by Andronescu,
                 M., et~al.: Bioinformatics 23(13) (2007) i19--i28",
  notes =        "Part of \cite{Castelli:2018:GP} EuroGP'2018 held in
                 conjunction with EvoCOP2018, EvoMusArt2018 and
                 EvoApplications2018",
}

Genetic Programming entries for William B Langdon Justyna Petke Ronny Lorenz

Citations