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Open Access Database

RAG: An update to the RNA-As-Graphs resource

Joseph A Izzo1, Namhee Kim1, Shereef Elmetwaly1 and Tamar Schlick12*

  • * Corresponding author: Tamar Schlick schlick@nyu.edu

  • † Equal contributors

Author Affiliations

1 Department of Chemistry, New York University, 100 Washington Square East, New York, NY 10003, USA

2 Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY, 10012, USA

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BMC Bioinformatics 2011, 12:219  doi:10.1186/1471-2105-12-219

Published: 31 May 2011

Abstract

Background

In 2004, we presented a web resource for stimulating the search for novel RNAs, RNA-As-Graphs (RAG), which classified, catalogued, and predicted RNA secondary structure motifs using clustering and build-up approaches. With the increased availability of secondary structures in recent years, we update the RAG resource and provide various improvements for analyzing RNA structures.

Description

Our RAG update includes a new supervised clustering algorithm that can suggest RNA motifs that may be "RNA-like". We use this utility to describe RNA motifs as three classes: existing, RNA-like, and non-RNA-like. This produces 126 tree and 16,658 dual graphs as candidate RNA-like topologies using the supervised clustering algorithm with existing RNAs serving as the training data. A comparison of this clustering approach to an earlier method shows considerable improvements. Additional RAG features include greatly expanded search capabilities, an interface to better utilize the benefits of relational database, and improvements to several of the utilities such as directed/labeled graphs and a subgraph search program.

Conclusions

The RAG updates presented here augment the database's intended function - stimulating the search for novel RNA functionality - by classifying available motifs, suggesting new motifs for design, and allowing for more specific searches for specific topologies. The updated RAG web resource offers users a graph-based tool for exploring available RNA motifs and suggesting new RNAs for design.