Probing the linearity and nonlinearity in DNA sequences

In this paper, we apply the principles of information theory that relate to the definition of nonlinear predictability, which is a measure that describes both the linear and nonlinear components of a system. By comparing this measure to a measure of linear predictability, one can assess whether a given system has a strong linear or a strong nonlinear component. This provides insights as to whether the system should be modeled by a nonlinear or a linear model. We apply these ideas to DNA sequences. Our results, which extend previous results on this issue indicate that all DNA sequences (coding and noncoding) exhibit strong nonlinear structure. At the same time the results provide insights to understand DNA structure and possible clues about evolutionary mechanisms.