MicroRNAfold: Pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy

Dianwei Han, Jun Zhang, Guiliang Tang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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.

Original languageEnglish
Pages (from-to)272-291
Number of pages20
JournalInternational Journal of Data Mining and Bioinformatics
Volume6
Issue number3
DOIs
StatePublished - Sep 2012

Keywords

  • Bottom-up local optimal solutions
  • Pre-microRNA secondary structure prediction
  • RNA folding
  • Thermodynamics-based scoring function

ASJC Scopus subject areas

  • Information Systems
  • General Biochemistry, Genetics and Molecular Biology
  • Library and Information Sciences

Fingerprint

Dive into the research topics of 'MicroRNAfold: Pre-microRNA secondary structure prediction based on modified NCM model with thermodynamics-based scoring strategy'. Together they form a unique fingerprint.

Cite this