Name
Abstract | ||
|---|---|---|
RNAs are functionally important in many biological processes. Predicting secondary structures of RNAs can help understanding 3D structures and functions of RNAs. However, RNA secondary structure prediction with pseudoknots is NP-complete. Predicting whether the RNAs contain pseudoknots in advance can save computation time as secondary structure prediction without pseudoknots is much faster. In this paper, we use k-mer occurrences as attributes to predict whether the RNAs have pseudoknots in the secondary structure. The results show two classifiers can predict 90% of the instance correctly. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/BIBE.2013.6701575 | BIBE |
Keywords | Field | DocType |
k-mer occurrence,rna secondary structure,molecular biophysics,molecular configurations,biological processes,pseudoknots,3d structures,rna functions,np-complete,rna,rna classification | RNA,Computer science,Rna secondary structure prediction,Molecular biophysics,Artificial intelligence,Bioinformatics,Protein secondary structure,k-mer,Machine learning,Computation | Conference |
ISSN | Citations | PageRank |
2471-7819 | 1 | 0.38 |
References | Authors | |
3 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kwan-Yau Cheung | 1 | 7 | 2.59 |
| Kwok-Kit Tong | 2 | 7 | 1.92 |
| Kin-Hong Lee | 3 | 257 | 26.27 |
| Kwong-Sak Leung | 4 | 1887 | 205.58 |