Evolving DNA motifs to Predict GeneChip Probe Performance

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "W. B. Langdon and A. P. Harrison",
  title =        "Evolving {DNA} motifs to Predict {GeneChip} Probe
  journal =      "Algorithms in Molecular Biology",
  year =         "2009",
  volume =       "4",
  number =       "6",
  month =        "19 " # mar,
  keywords =     "genetic algorithms, genetic programming,
                 Bioinformatics, Affymetrix GeneChip, strongly typed
                 genetic programming, grammars, regular expressions",
  ISSN =         "1748-7188",
  URL =          "http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/langdon_amb.pdf",
  URL =          "http://www.almob.org/content/4/1/6",
  DOI =          "doi:10.1186/1748-7188-4-6",
  size =         "16 pages",
  abstract =     "Background:

                 Affymetrix High Density Oligonuclotide Arrays (HDONA)
                 simultaneously measure expression of thousands of genes
                 using millions of probes. We use correlations between
                 measurements for the same gene across 6685 human tissue
                 samples from NCBI's GEO database to indicated the
                 quality of individual HG-U133A probes. Low correlation
                 indicates a poor probe.


                 Regular expressions can be automatically created from a
                 Backus-Naur form (BNF) context-free grammar using
                 strongly typed genetic programming.


                 The automatically produced motif is better at
                 predicting poor DNA sequences than an existing human
                 generated RE, suggesting runs of Cytosine and Guanine
                 and mixtures should all be avoided.",
  notes =        "Based on \cite{langdon:2008:PPSN}. PMID: 19298675
                 PMCID: PMC2679018",

Genetic Programming entries for William B Langdon Andrew P Harrison