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 language | English |
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Pages (from-to) | 272-291 |
Number of pages | 20 |
Journal | International Journal of Data Mining and Bioinformatics |
Volume | 6 |
Issue number | 3 |
DOIs | |
State | Published - 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