Evaluating the quality of SHAPE data simulated by k-mers for RNA structure prediction

Abstract

Finding an effective measure to predict a more accurate RNA secondary structure is a challenging problem. In the last decade, an experimental method, known as selective -hydroxyl acylation analyzed by primer extension (SHAPE), was proposed to measure the tendency of forming a base pair for almost all nucleotides in an RNA sequence. These SHAPE reactivities are then utilized to improve the accuracy of RNA structure prediction. Due to a significant impact of SHAPE reactivity and in order to reduce the experimental costs, we propose a new model called HL-k-mer. This model simulates the SHAPE reactivity for each nucleotide in an RNA sequence. This is done by fetching the SHAPE reactivities for all sub-sequences of length k (k-mers) appearing in helix and loop regions. For evaluating the quality of simulated SHAPE data, ESD-Fold method is used based on the SHAPE data simulated by the HL-k-mer model …

Fatemeh Zare

Associate Professor

My research interests include bioinformatics, computational biology and artificial intelligence.