RNA MODELING BY COMBINING STOCHASTIC CONTEXT-FREE GRAMMARS AND n-GRAM MODELS

Abstract

The RNA sentences present structured regions caused by pairwise correlations, and nonstructured regions where any global relation can be found. In this paper, we present a combination of stochastic context-free grammars (SCFG) and bigram models. The SCFGs are used to represent the long-term relations of the structured part of RNA sequences, while the bigram models are used to capture the local relations of the nonstructured part. A stochastic version of Sakakibara's algorithm is used to study the SCFGs. Finally, experiments to evaluate the behavior of this proposal were carried out.