Name
Title | ||
|---|---|---|
SARNA-ensemble-predict: the effect of different dissimilarity metrics on a novel ensemble-based RNA secondary structure prediction algorithm |
Abstract | ||
|---|---|---|
Recently, there is a resurgence of interest in the RNA secondary structure prediction problem due to the discovery of many new families of non-coding RNAs with a variety of functions. This paper describes and presents a novel algorithm for RNA secondary structure prediction based on an ensemble-based approach. An evaluation of the performance in terms of sensitivity and specificity is made. Experiments were performed on eleven structures from four RNA classes (RNaseP, Group I intron 16S rRNA, Group I intron 23S rRNA and 16S rRNA). Three RNA secondary structure similarity metrics (base pair distance, tree edit distance, and thermodynamic energy distance) and their effects on the clustering algorithm were explored. The significant contribution of this paper is in the examining of the various results from employing different dissimilarity metrics. Overall, the base pair distance dissimilarity metric shows better results with the other two distance metrics (tree edit distance and thermodynamic energy distance). The results presented in this paper demonstrate that SARNA-Ensemble-Predict can give comparable performance to a state-of-the-art algorithm Sfold in terms of sensitivity. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CIBCB.2009.4925701 | Nashville, TN |
Keywords | Field | DocType |
rna secondary structure similarity,base pair distance dissimilarity,rna secondary structure prediction,rna class,distance metrics,base pair distance,clustering algorithm,different dissimilarity metrics,group i intron,thermodynamic energy distance,molecular biophysics,16s rrna,non coding rna,sensitivity,thermodynamics,distance metric,rna,base pair,prediction algorithms,rna secondary structure,clustering algorithms | RNA,23S ribosomal RNA,Computer science,Rna secondary structure prediction,Artificial intelligence,Cluster analysis,Nucleic acid secondary structure,Thermodynamic free energy,Algorithm,Intron,Bioinformatics,Base pair,Machine learning | Conference |
ISBN | Citations | PageRank |
978-1-4244-2756-7 | 1 | 0.36 |
References | Authors | |
21 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Herbert H. Tsang | 1 | 92 | 19.08 |
| Kay C. Wiese | 2 | 164 | 19.10 |