A Modified Algorithm for Quantifying of Pre-mature MiRNAs using Some Fractal Parameters

The prime research area now is to understand microRNA (miRNA) in a quantitative manner. The miRNAs are non-coding short ribonucleic acid (RNA) molecules, approximately ~25 nucleotides long. MicroRNAs have emerged as powerful regulators of diverse cellular processes with important roles in tissue remodeling. The scientists across the globe are working on quantitative estimation of microRNA (miRNA) from different angles. The authors in their earlier paper have already made a new addition in the present scenario. In the present paper the authors are appending few more fractal parameters to strengthen the algorithm. In the previous work the authors deciphered the inherent statistical behavior in pre-mature miRNA strings through few statistical parameters namely: Hurst Exponent values, Variance, Poly-String Mean and Poly-String Standard Deviation. Now, in the present work the authors have to tried to explore the quantification of the same miRNA dataset based on fractal and statistical parameters namely: (i) Fractal Dimension (FD) of 4 binary indicator matrices, (ii) FD of the DNA walk and (iii) Complexity of the miRNA strings, of the three organisms Homo sapiens (hsa), Macaca mulatta (mml) and Pan troglodytes (ptr).