Mining characteristic relations bind to RNA secondary structures

Authors:
Qingfeng Chen;Yi-Ping Phoebe Chen
Affiliations:
Faculty of Science and Technology, Deakin University, Melbourne, Vic., Australia and School of Computer, Electronic and Information, Guangxi University, Nanning, China;Faculty of Science and Technology, Deakin University, Melbourne, Vic., Australia and ARC Centre of Excellence in Bioinformatics, Institute for Molecular Bioscience, The University of Queensland, B ...
Venue:
IEEE Transactions on Information Technology in Biomedicine
Year:
2010

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Abstract

The identification of RNA secondary structures has been among the most exciting recent developments in biology and medical science. It has been recognized that there is an abundance of functional structures with frameshifting, regulation of translation, and splicing functions. However, the inherent signal for secondary structures is weak and generally not straightforward due to complex interleaving substrings. This makes it difficult to explore their potential functions from various structure data. Our approach, based on a collection of predicted RNA secondary structures, allows us to efficiently capture interesting characteristic relations in RNA and bring out the top-ranked rules for specified association groups.Our results not only point to a number of interesting associations and include a brief biological interpretation to them. It assists biologists in sorting out the most significant characteristic structure patterns and predicting structure-function relationships in RNA.