Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches

Created by W.Langdon from gp-bibliography.bib Revision:1.3963

@Article{Vanneschi:2013:GPEM,
  author =       "Leonardo Vanneschi and Matteo Mondini and 
                 Martino Bertoni and Alberto Ronchi and Mattia Stefano",
  title =        "Gene regulatory networks reconstruction from time
                 series datasets using genetic programming: a comparison
                 between tree-based and graph-based approaches",
  journal =      "Genetic Programming and Evolvable Machines",
  year =         "2013",
  volume =       "14",
  number =       "4",
  pages =        "431--455",
  month =        dec,
  keywords =     "genetic algorithms, genetic programming, Gene
                 regulatory networks, Tree-based GP, Graph-based GP",
  ISSN =         "1389-2576",
  DOI =          "doi:10.1007/s10710-013-9183-z",
  size =         "25 pages",
  abstract =     "Genetic programming researchers have shown a growing
                 interest in the study of gene regulatory networks in
                 the last few years. Our team has also contributed to
                 the field, by defining two systems for the automatic
                 reverse engineering of gene regulatory networks called
                 GRNGen and GeNet. In this paper, we revise this work by
                 describing in detail the two approaches and empirically
                 comparing them. The results we report, and in
                 particular the fact that GeNet can be used on large
                 networks while GRNGen cannot, encourage us to pursue
                 the study of GeNet in the future. We conclude the paper
                 by discussing the main research directions that we are
                 planning to investigate to improve GeNet.",
}

Genetic Programming entries for Leonardo Vanneschi Matteo Mondini Martino Bertoni Alberto Ronchi Mattia Stefano

Citations