Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology

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

@InProceedings{Widera:2010:geccocomp,
  author =       "Pawel Widera and Jaume Bacardit and 
                 Natalio Krasnogor and Carlos Garcia-Martinez and Manuel Lozano",
  title =        "Evolutionary symbolic discovery for bioinformatics,
                 systems and synthetic biology",
  booktitle =    "GECCO 2010 Symbolic regression workshop",
  year =         "2010",
  editor =       "Steven Gustafson and Mark Kotanchek",
  isbn13 =       "978-1-4503-0073-5",
  keywords =     "genetic algorithms, genetic programming",
  pages =        "1991--1998",
  month =        "7-11 " # jul,
  organisation = "SIGEVO",
  address =      "Portland, Oregon, USA",
  DOI =          "doi:10.1145/1830761.1830842",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  abstract =     "Symbolic regression and modelling are tightly linked
                 in many Bioinformatics, Systems and Synthetic Biology
                 problems. In this paper we briefly overview two
                 problems, and the approaches we have use to tackle
                 them, that can be deemed to represent this entwining of
                 regression and modeling, namely, the evolutionary
                 discovery of (1) effective energy functions for protein
                 structure prediction and (2) models that capture
                 biological behaviour at the gene, signalling and
                 metabolic networks level. These problems are not,
                 strictly speaking, {"}regression problems{"} but they
                 do share several characteristics with the latter,
                 namely, a symbolic representation of a solution is
                 sought, this symbolic representation must be human
                 understandable and the results obtained by the symbolic
                 and human interpretable solution must fit the available
                 data without over-learning.",
  notes =        "Also known as \cite{1830842} Distributed on CD-ROM at
                 GECCO-2010.

                 ACM Order Number 910102.",
}

Genetic Programming entries for Pawel Widera Jaume Bacardit Natalio Krasnogor Carlos Garcia-Martinez Manuel Lozano

Citations