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 |
|---|---|
| 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
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