Tries based RNA structure prediction

Abstract

RNA (Ribo Nucleic Acid) is a single strand of nucleotides composed of Adenine (A), Guanine (G), Cytosine(C) and Uracil (U) and it can be fold back on itself to form its secondary structure with base pairs like A'U, G=C and Gi U. Information on the secondary structure of a RNA molecule can be used as a stepping stone to model the full structure of an RNA molecule which in turn can be related to the biological function. The RNA secondary structure is determined by X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy. Genetic algorithm combined with tries is proposed to effectively predict the secondary structure of RNA. This Soft Computing gained importance with the need to get approximate solutions for RNA sequence by considering the issues with kinetic effects, transcriptional folding and estimation of certain energy parameters. Genetic algorithm optimizes the problems according to the fitness function. The pair of chromosomes with good fitness values will produce new chromosomes for the next generation. Based on the selected values, the secondary structure of the RNA is successfully predicted and the experimental results show improved prediction for various RNA's.