Automated identification of RNA 3D modules with discriminative power in RNA structural alignments.

ABSTRACT: Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and rand

SUBMITTER: Theis C 

PROVIDER: S-EPMC3905863 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature