RNA Secondary Structure Prediction with Simple Pseudoknots

Pseudoknots are widely occurring structural motifs in RNA. Pseudoknots have been shown to be functionally important in different RNAs which play regulatory, catalytic, or structural roles in cells. Current biophysical methods to identify the presence of pseudoknots are extremely time consuming and expensive. Therefore, bioinformatics approaches to accurately predict such structures are highly desirable. Most methods for RNA folding with pseudoknots adopt different heuristics such as quasi-Monte Carlo search, genetic algorithms, stochastic context-free grammars, and the Hopfield networks, and techniques like dynamic programming (DP). These approaches, however, have limitations. The DP algorithm has worst case time and space complexities of O(n6.8 ) and O(n4 ), respectively. The algorithm is not practical for sequences longer than 100 nucleotides. In this paper, we present a dynamic programming algorithm for prediction of simple pseudoknots in optimal secondary structure of a single RNA...

• Type: Conference
• Year: 2004
• Where: APBC
• Authors: Jitender S. Deogun, Ruben Donts, Olga Komina, Fangrui Ma
• Keywords: Algorithm, APBC 2004, APBC 2007, Single Rna Sequence, Worst Case Time