Identification and classification of ncRNA molecules using graph properties.

ABSTRACT: The study of non-coding RNA genes has received increased attention in recent years fuelled by accumulating evidence that larger portions of genomes than previously acknowledged are transcribed into RNA molecules of mostly unknown function, as well as the discovery of novel non-coding RNA types and functional RNA elements. Here, we demonstrate that specific properties of graphs that represent the predicted RNA secondary structure reflect functional information. We introduce a computational algorithm and an associated web-based tool (GraPPLE) for classifying non-coding RNA molecules as functional and, furthermore, into Rfam families based on their graph properties. Unlike sequence-similarity-based methods and covariance models, GraPPLE is demonstrated to be more robust with regard to increas

SUBMITTER: Childs L 

PROVIDER: S-EPMC2685108 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature