Interval Based Similarity for Function Classification of RNA Pseudoknots

Abstract

Many raw biological sequence data have been generated by the human genome project and related efforts. The understanding of structural information encoded by biological sequences is important to acquire knowledge of their biochemical functions in varied pathways but remains a fundamental challenge. Recent interest in RNA regulation has resulted in a rapid growth of deposited RNA secondary structures in varied databases. However, a functional classification and characterization of the RNA structure have only been partially addressed. Chapter 7 proposes methods for modelling conserved structure patterns of ncRNAs, whereas does not provide a intuitive way to evaluate structure similarity. This chapter aims to introduce a novel interval-based distance metric for structure-based RNA function assignment. The characterization of RNA structures relies on distance vectors learned froma collection of predicted structures. The distance measure considers the intersected, disjoint and inclusion between intervals. A set of RNA pseudoknotted structures with known function are applied and the function of the query structure is determined by measuring structure similarity. This not only offers sequence distance criteria to measure the similarity of secondary structures and aids the functional classification of RNA structures with pesudoknots.