Quantitative Deciphering of pre-mature and pattern recognition of mature miRNAs using some Statistical Parameters

Abstract

Today the DNA and RNA structures and their underlying functions have a very significant role in every aspect of human life. Properly inferring on the gene functions leads us to be more affirmative about the functional system of every organism and thus to take necessary actions in recuperation from diseases. To understand the functional property of any gene sequence it is necessary to study the sequence structure. In the present work the authors have tried to assess the miRNA sequence structures using some mathematical and statistical parameters like calculating the range of hurst exponent or autocorrelation values of each miRNA string sequence, depicting the frequency distribution of each nucleotide in graphical pattern. The authors have also calculated the variance range of each miRNA string sequence. The last two decades the researchers are doing extensive work on quantitative estimation of miRNA. The miRNAs are non-coding short ribonucleic acid (RNA) molecules, approximately ~25 nucleotides long. MiRNAs help in understanding the entire scope of post-transcriptional gene regulation. MiRNAs regulate numerous cellular processes and have roles in cardiac activities, neural functions, psychological functions and lots more. The present work the authors tried to explore the quantification and classification based on statistical results on nucleotide strings of pre-mature miRNAs of the three organisms Homo sapiens (hsa), Gorilla gorilla (ggo) and Pongo pygmaeus (ppy). The present work is also extended to mature miRNAs of species like Pan troglodytes (ptr) to check the effect of linear binary rules on each of the miRNA sequence.