Title
Structure-based RNA Function Prediction Using Elastic Shape Analysis
Abstract
In recent years, RNAs have been found to have diverse functions beyond being a messenger in gene transcription. The functions of non-coding RNAs are determined by their structures. Structure comparison/alignment of RNAs provides an effective means to predict their functions. Despite many previous studies on RNA structure alignment, it is still a challenging problem to predict the function of RNA molecules based on their structure information. In this study, we developed a new RNA structure alignment method based on elastic shape analysis (ESA). ESA treats RNA structures as three dimensional curves and performs flexible alignment between two RNA molecules by bending and stretching one of the molecules to match the other. The amount of bending and stretching is quantified by a formal distance, geodesic distance. Based on ESA, a rigorous mathematical framework can be built for RNA structure comparison. Means and covariances can be computed and probability distributions can be constructed for a group of RNA structures. We further applied the method to predict functions of RNA molecules. Our method achieved good performance when tested on benchmark datasets.
Year
DOI
Venue
2011
10.1109/BIBM.2011.119
BIBM
Keywords
Field
DocType
rna structure,flexible alignment,structure information,structure comparison,elastic shape analysis,structure-based rna function prediction,rna molecule,non-coding rnas,formal distance,new rna structure alignment,rna structure comparison,rna structure alignment,biomechanics,molecular biophysics,genetics,gene transcription,three dimensional,shape analysis,probability distribution,bending,rna,non coding rna,geodesic distance,elasticity
RNA,Structural alignment,Transcription (biology),Nucleic acid structure,Computer science,Probability distribution,Molecular biophysics,Bioinformatics,Geodesic,Shape analysis (digital geometry)
Conference
ISSN
Citations 
PageRank 
2156-1125
3
0.50
References 
Authors
13
3
Name
Order
Citations
PageRank
Jose Laborde171.25
Anuj Srivastava22853199.47
Jinfeng Zhang38610.11