Pair Stochastic Tree Adjoining Grammars for Aligning and Predicting Pseudoknot RNA Structures

Motivation: Since the whole genome sequences for many species are currently available, computational predictions of RNA secondary structures and computational identifications of those non-coding RNA regions by comparative genomics become important, and require more advanced alignment methods. Recently, an approach of structural alignments for RNA sequences has been introduced to solve these problems. By structural alignments, we mean a pairwise alignment to align an unfolded RNA sequence into a folded RNA sequence of known secondary structure. Pair HMMs on tree structures (PHMMTSs) proposed by Sakakibara are efficient automata-theoretic models for structural alignments of RNA secondary structures, but are incapable of handling pseudoknots. On the other hand, tree adjoining grammars (TAGs) is a subclass of context-sensitive grammar, which is suitable for modeling pseudoknots. Our goal is to extend PHMMTSs by incorporating TAGs to be able to handle pseudoknots. Results: We propose the p...

• Type: Conference
• Year: 2004
• Where: CSB
• Authors: Hiroshi Matsui, Kengo Sato, Yasubumi Sakakibara
• Keywords: Bioinformatics, CSB 2004, RNA Secondary Structures, Rna Sequence, Structural Alignment