title: MicroRNAfold: pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy.
abstract: An accurate prediction of the pre-microRNA secondary structure is important in miRNA informatics. Based on a recently proposed model, nucleotide cyclic motifs (NCM), to predict RNA secondary structure, we propose and implement a Modified NCM (MNCM) model with a physics-based scoring strategy to tackle the problem of pre-microRNA folding. Our microRNAfold is implemented using a global optimal algorithm based on the bottom-up local optimal solutions. Our experimental results show that microRNAfold outperforms the current leading prediction tools in terms of True Negative rate, False Negative rate, Specificity, and Matthews coefficient ratio.
authors.affiliation: Department of Computer Science, University of Kentucky, Lexington, KY 40506-0046, USA. dianweih@csr.uky.edu
authors.forename: Dianwei
authors.initials: D
authors.lastname: Han
authors.forename: Jun
authors.initials: J
authors.lastname: Zhang
authors.forename: Guiliang
authors.initials: G
authors.lastname: Tang
mesh_terms: D000465:Algorithms; D035683:MicroRNAs / Q000737:chemistry*; D009690:Nucleic Acid Conformation; D012313:RNA / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D035683:MicroRNAs; D012313:RNA