A detection method for snoRNA modification domain by fully indexable dictionary retrieving
Recently, non-coding RNA which participates with organic activities has been found in non-coding region. Until now, we do not know detailed function of non-coding RNAs very well. To make clear functions of non-coding RNAs, we need to obtain a lot of data about non-coding RNAs and their targets. However, we do not have efficient techniques to analyze relations between non-coding RNAs and their targets. In this paper, we propose a high-speed method that can detect modification domain candidates on the target RNA based on the small nucleolar RNA (snoRNA) sequence. A snoRNA modifies a target RNA by composing complementary base pairs between a part of snoRNA and a part of target RNA. Our method stores the relations between snoRNA sequences and their target in a Fully Indexable Dictionary built by Trie data structure and Level-Order Unary Degree Sequence for high-speed retrieving.
KeywordsLOUDS rRNA snoRNA Succinct data structure Trie
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