A chaotic study on pandemic and classical (H1N1) using EIIP sequence indicators

A novel influenza A (H1N1) virus of swine origin emerged in the spring of 2009 and spread very rapidly among people. The severity of the disease and the number of deaths caused by a pandemic virus varies greatly and can change over time. For these reasons it becomes a challenge to study the genomic features that characterize this new virus. At the same time, the theory and methods of signal processing are becoming increasingly important in molecular biology, especially in the analysis of genomic sequences. Throughout this work we have characterized these sequences according to their chaotic features such as moment invariants, correlation dimension, and largest Lyapunov exponent estimates. We have applied our method to a number of sequences encoded into a time series using EIIP sequence indicators. In order to extract genomic features that can distinguish the new swine flu from the classical H1N1 existed before using sequences from segment 8 which encodes two important proteins for immune system attack (NS1 and NS2). Our results indicate that this study have yielded a significant differences between the two types of influenza H1N1 (Pandemic and classical).