Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms

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@Article{Saetrom:2005:RNA,
  author =       "Ola Saetrom and Ola {Snove, Jr.} and Pal Saetrom",
  title =        "Weighted sequence motifs as an improved seeding step
                 in microRNA target prediction algorithms",
  journal =      "RNA",
  year =         "2005",
  volume =       "1",
  number =       "7",
  pages =        "995--1003",
  month =        jul,
  keywords =     "genetic algorithms, genetic programming, miRNA target
                 prediction, boosting, machine learning",
  DOI =          "doi:10.1261/rna.7290705",
  abstract =     "We present a new microRNA target prediction algorithm
                 called TargetBoost, and show that the algorithm is
                 stable and identifies more true targets than do
                 existing algorithms. TargetBoost uses machine learning
                 on a set of validated microRNA targets in lower
                 organisms to create weighted sequence motifs that
                 capture the binding characteristics between microRNAs
                 and their targets. Existing algorithms require
                 candidates to have (1) near-perfect complementarity
                 between microRNAs' 5' end and their targets; (2)
                 relatively high thermodynamic duplex stability; (3)
                 multiple target sites in the target's 3' UTR; and (4)
                 evolutionary conservation of the target between
                 species. Most algorithms use one of the two first
                 requirements in a seeding step, and use the three
                 others as filters to improve the method's specificity.
                 The initial seeding step determines an algorithm's
                 sensitivity and also influences its specificity. As all
                 algorithms may add filters to increase the specificity,
                 we propose that methods should be compared before such
                 filtering. We show that TargetBoost's weighted sequence
                 motif approach is favorable to using both the duplex
                 stability and the sequence complementarity steps.
                 (TargetBoost is available as a Web tool from
                 http://www.interagon.com/demo/.)",
  notes =        "PMID:",
}

Genetic Programming entries for Ola Saetrom Ola Snove Jr Pal Saetrom

Citations