title: Fast selection of miRNA candidates based on large-scale pre-computed MFE sets of randomized sequences.
abstract: BACKGROUND
  Small RNAs are important regulators of genome function, yet their prediction in genomes is still a major computational challenge. Statistical analyses of pre-miRNA sequences indicated that their 2D structure tends to have a minimal free energy (MFE) significantly lower than MFE values of equivalently randomized sequences with the same nucleotide composition, in contrast to other classes of non-coding RNA. The computation of many MFEs is, however, too intensive to allow for genome-wide screenings.
  
  
  RESULTS
  Using a local grid infrastructure, MFE distributions of random sequences were pre-calculated on a large scale. These distributions follow a normal distribution and can be used to determine the MFE distribution for any given sequence composition by interpolation. It allows on-the-fly calculation of the normal distribution for any candidate sequence composition.
  
  
  CONCLUSIONS
  The speedup achieved makes genome-wide screening with this characteristic of a pre-miRNA sequence practical. Although this particular property alone will not be able to distinguish miRNAs from other sequences sufficiently discriminative, the MFE-based P-value should be added to the parameters of choice to be included in the selection of potential miRNA candidates for experimental verification.
authors.forename: Sven
authors.initials: S
authors.lastname: Warris
authors.forename: Sander
authors.initials: S
authors.lastname: Boymans
authors.forename: Iwe
authors.initials: I
authors.lastname: Muiser
authors.forename: Michiel
authors.initials: M
authors.lastname: Noback
authors.forename: Wim
authors.initials: W
authors.lastname: Krijnen
authors.affiliation: Expertise Centre ALIFE, Institute for Life Science & Technology, Hanze University of Applied Sciences, Groningen, The Netherlands. j.p.h.nap@pl.hanze.nl.
authors.forename: Jan-Peter
authors.initials: JP
authors.lastname: Nap
mesh_terms: D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D019277:Entropy; D004854:Herpesvirus 4, Human / Q000235:genetics; D055029:Inverted Repeat Sequences; D035683:MicroRNAs / Q000737:chemistry / Q000235:genetics*; D008969:Molecular Sequence Data; D016011:Normal Distribution; D009690:Nucleic Acid Conformation
chemical_list: D035683:MicroRNAs