Bayesian sampling of evolutionarily conserved RNA secondary structures with pseudoknots
Author(s) -
Gero Doose,
Dirk Metzler
Publication year - 2012
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/bts369
Subject(s) - rna , nucleic acid secondary structure , computational biology , nucleic acid structure , computer science , protein secondary structure , biology , set (abstract data type) , bayesian probability , rnase p , software , sequence (biology) , theoretical computer science , genetics , gene , artificial intelligence , programming language , biochemistry
Today many non-coding RNAs are known to play an active role in various important biological processes. Since RNA's functionality is correlated with specific structural motifs that are often conserved in phylogenetically related molecules, computational prediction of RNA structure should ideally be based on a set of homologous primary structures. But many available RNA secondary structure prediction programs that use sequence alignments do not consider pseudoknots or their estimations consist on a single structure without information on uncertainty.
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