Fast and accurate search for non-coding RNA pseudoknot structures in genomes
Author(s) -
Zhibin Huang,
Yong Wu,
Joseph Robertson,
Liang Feng,
Russell L. Malmberg,
Liming Cai
Publication year - 2008
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btn393
Subject(s) - pseudoknot , computer science , preprocessor , algorithm , heuristics , theoretical computer science , nucleic acid structure , graph , non coding rna , nucleic acid secondary structure , coding (social sciences) , rna , computational biology , mathematics , artificial intelligence , biology , genetics , gene , operating system , statistics
Searching genomes for non-coding RNAs (ncRNAs) by their secondary structure has become an important goal for bioinformatics. For pseudoknot-free structures, ncRNA search can be effective based on the covariance model and CYK-type dynamic programming. However, the computational difficulty in aligning an RNA sequence to a pseudoknot has prohibited fast and accurate search of arbitrary RNA structures. Our previous work introduced a graph model for RNA pseudoknots and proposed to solve the structure-sequence alignment by graph optimization. Given k candidate regions in the target sequence for each of the n stems in the structure, we could compute a best alignment in time O(k(t)n) based upon a tree width t decomposition of the structure graph. However, to implement this method to programs that can routinely perform fast yet accurate RNA pseudoknot searches, we need novel heuristics to ensure that, without degrading the accuracy, only a small number of stem candidates need to be examined and a tree decomposition of a small tree width can always be found for the structure graph.
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