Hierarchical analysis of RNA secondary structures with pseudoknots based on sections.

ABSTRACT: Predicting RNA structures containing pseudoknots remains computationally challenging due to high processing costs and complexity. While standard methods for pseudoknot prediction require O(N6) time complexity, we present a hierarchical approach that significantly reduces computational cost while maintaining prediction accuracy. Our method analyzes RNA structures by dividing them into contiguous regions of unpaired bases ("sections") derived from known secondary structures. We examine pseudoknot interactions between sections using a nearest-neighbor energy model with dynamic programming. Our algorithm scales as [Formula: see text], offering substantial computational advantages over existing global prediction methods. Analysis of 726 transfer messenger RNA and 454 Ribonuclease P RNA sequence

SUBMITTER: Masuki R 

PROVIDER: S-EPMC12858078 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature