Abstract
We analyse sequence and structural features of protein-RNA interfaces using RB-147, a non-redundant dataset of protein-RNA complexes extracted from the PDB. We train classifiers using machine learning algorithms to predict protein-RNA interfaces from sequence and structure-derived features of proteins. Our experiments show that Struct-NB, a Naïve Bayes classifier that exploits structural features, outperforms its counterparts that use only sequence features to predict protein-RNA binding residues.
Original language | English (US) |
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Pages (from-to) | 21-43 |
Number of pages | 23 |
Journal | International Journal of Data Mining and Bioinformatics |
Volume | 4 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2010 |
All Science Journal Classification (ASJC) codes
- Information Systems
- General Biochemistry, Genetics and Molecular Biology
- Library and Information Sciences