Pattern matching in RNA structures

Authors:
Kejie Li;Reazur Rahman;Aditi Gupta;Prasad Siddavatam;Michael Gribskov
Affiliations:
Department of Biological Sciences, Purdue University, West Lafayette, IN;Department of Biological Sciences, Purdue University, West Lafayette, IN;Department of Biological Sciences, Purdue University, West Lafayette, IN;Department of Biological Sciences, Purdue University, West Lafayette, IN;Department of Biological Sciences, Purdue University, West Lafayette, IN
Venue:
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Year:
2008

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Abstract

RNA plays key roles in many biological processes, and its functiondepends largely on its three-dimensional structure. We describe a comparativeapproach to learning biologically important RNA structures, including thosethat are not the predicted minimum free energy (MFE) structure. Our approachidentifies the greatest conserved structure(s) in a set of RNA sequences, even inthe presence of sequences that have no conserved features. We convert RNAstructures to a graph representation (XIOS RNA graph) that includes pseudoknots,and mutually exclusive structures, thereby simultaneously representingensembles of RNA structures. By modifying existing algorithms for maximalsubgraph isomorphism, we can identify the similar portions of the graphs andintegrate this with MFE structure prediction tools to identify biologically relevantnear-MFE conserved structures.