Abstract:
:RNA pseudoknots are functional structure elements with key roles in viral and cellular processes. Prediction of a pseudoknotted minimum free energy structure is an NP-complete problem. Practical algorithms for RNA structure prediction including restricted classes of pseudoknots suffer from high runtime and poor accuracy for longer sequences. A heuristic approach is to search for promising pseudoknot candidates in a sequence and verify those. Afterwards, the detected pseudoknots can be further analysed using bioinformatics or laboratory techniques. We present a novel pseudoknot detection method called DotKnot that extracts stem regions from the secondary structure probability dot plot and assembles pseudoknot candidates in a constructive fashion. We evaluate pseudoknot free energies using novel parameters, which have recently become available. We show that the conventional probability dot plot makes a wide class of pseudoknots including those with bulged stems manageable in an explicit fashion. The energy parameters now become the limiting factor in pseudoknot prediction. DotKnot is an efficient method for long sequences, which finds pseudoknots with higher accuracy compared to other known prediction algorithms. DotKnot is accessible as a web server at http://dotknot.csse.uwa.edu.au.
journal_name
Nucleic Acids Resjournal_title
Nucleic acids researchauthors
Sperschneider J,Datta Adoi
10.1093/nar/gkq021subject
Has Abstractpub_date
2010-04-01 00:00:00pages
e103issue
7eissn
0305-1048issn
1362-4962pii
gkq021journal_volume
38pub_type
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