Classification of lncRNA and mRNA of Eukaryotic model organism using physicochemical properties and composition of dineuclotides and trineuclotides

Abstract

Unveiling lncRNA and mRNA gene differences at the sequence level is one of the important challenges in molecular and disease biology. In the context of DNA sequence, this difference in a physicochemical signature parameter is very important. In this study, we have proposed a machine learning-based computational approach for the classification of these genomic features. we have considered three important physicochemical properties,solvation energy, hydrogen bonding ensrgy and stacking energy of dinucleotide and trinucleotide of lncRNA and mRNA sequence as well as dinucleotide and trinucleotide composition in their sequences.We have considered lncRNA and mRNA sequences from seven model organisms namely Arabidopsis thliana, C.elegans, Chicken, Chimpanzee, Cow, Platypus, and Zebrafish.