Evolutionary Algorithm for RNA Secondary Structure Prediction Based on Simulated SHAPE Data.

ABSTRACT:

Background

Non-coding RNAs perform a wide range of functions inside the living cells that are related to their structures. Several algorithms have been proposed to predict RNA secondary structure based on minimum free energy. Low prediction accuracy of these algorithms indicates that free energy alone is not sufficient to predict the functional secondary structure. Recently, the obtained information from the SHAPE experiment greatly improves the accuracy of RNA secondary structure prediction by adding this information to the thermodynamic free energy as pseudo-free energy.

Method

In this paper, a new method is proposed to predict RNA secondary structure based on both free energy and SHAPE pseudo-free energy. For each RNA sequence, a population of secondary structures is cons

SUBMITTER: Montaseri S 

PROVIDER: S-EPMC5125645 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature