title: Prediction of microRNA targets.
abstract: I describe the use of RNAhybrid, a program that predicts multiple potential binding sites of microRNAs (miRNAs) in large target RNAs. The core algorithm finds the energetically most favorable hybridization sites of a miRNA in a large potential target RNA. Intramolecular hybridizations, i.e., base pairings between target nucleotides or between miRNA nucleotides are, not allowed. For large targets, the time complexity of the algorithm is linear in the target length, allowing many long targets to be searched in a short time. Starting from the observation that the binding energies are results from an optimization procedure, we can model them as following an extreme value distribution. From this, we can calculate the statistical significance of individual binding sites, of multiple binding sites in a single target sequence, and of binding sites in comparative analyses of orthologous sequences across species. The latter involves the calculation of the effective number of orthologous sequences, which can be considerably smaller than the actual number, reflecting the statistical dependence of evolutionarily related sequences.
authors.affiliation: Bielefeld University, CeBiTec, Junior Research Group Bioinformatics of Regulation, Bielefeld, Germany.
authors.forename: Marc
authors.initials: M
authors.lastname: Rehmsmeier
mesh_terms: D000465:Algorithms; D000818:Animals; D001665:Binding Sites; D003196:Computer Graphics; D006801:Humans; D020407:Internet; D035683:MicroRNAs / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism*; D008957:Models, Genetic; D009690:Nucleic Acid Conformation; D012984:Software; D013816:Thermodynamics; D014584:User-Computer Interface
chemical_list: D035683:MicroRNAs