A Local Structural Prediction Algorithm for RNA Triple Helix Structure

Abstract

Abstract. Secondary structure prediction (with or without pseudoknots) of an RNA molecule is a well-known problem in computational biology. Most of the existing algorithms have an assumption that each nucleotide can interact with at most one other nucleotide. This assumption is not valid for triple helix structure (a pseudoknotted structure with tertiary interactions). As these structures are found to be important in many biological processes, it is desirable to develop a prediction tool for these structures. We provide the first structural prediction algorithm to handle triple helix structures. Our algorithm runs in O(n 3 ) time where n is the length of input RNA sequence. The accuracy of the prediction is reasonably high, with average sensitivity and specificity over 80% for base pairs, and over 70% for tertiary interactions.

A Survey on Syntactic Pattern Recognition Methods in Bioinformatics

“…The generating of RNA secondary structure including pseudoknots with the help of extended simple linear Tree Adjoining Grammars (ESL-TAG) was presented in [106]. This class of TAGs was used to construct an algorithm for tertiary interactions over pseudoknots for the predicting of RNA secondary structures in [91]. Pair stochastic Tree Adjoining Grammars (PSTAG) were used for a pseudoknot RNA structure prediction in [139].…”