RNAG: a new Gibbs sampler for predicting RNA secondary structure for unaligned sequences.

ABSTRACT:

Motivation

RNA secondary structure plays an important role in the function of many RNAs, and structural features are often key to their interaction with other cellular components. Thus, there has been considerable interest in the prediction of secondary structures for RNA families. In this article, we present a new global structural alignment algorithm, RNAG, to predict consensus secondary structures for unaligned sequences. It uses a blocked Gibbs sampling algorithm, which has a theoretical advantage in convergence time. This algorithm iteratively samples from the conditional probability distributions P(Structure | Alignment) and P(Alignment | Structure). Not surprisingly, there is considerable uncertainly in the high-dimensional space of this difficult problem, which has so far r

SUBMITTER: Wei D 

PROVIDER: S-EPMC3167047 | biostudies-literature | 2011 Sep

REPOSITORIES: biostudies-literature