Natural computing was recently defined as a novel paradigm for computation where nature is taken as an example to define computational architectures and algorithms capable to solve problems efficiently and while being based on a low complexity description of its structure. A living being can be considered as performing various natural computation tasks. While exhibiting complexity in performing various functional tasks (pattern recognition, decision, orientation, optimization, planning, creative thinking, self-repair and self-reproduction, to name just a few) it is assumed that the entire development of the being is encoded within its genome. Due to recent progress in mapping the entire human genome, it is widely accepted that such a genome contains no more than several megabytes of information stored in the strings of DNA, being even simpler for more primitive species. Thus, in a simplified approach, the entire behavioral complexity of a living being can be regarded as being encoded in a relatively compact information storage structure, the DNA. This is what we will call structural information, i.e. the minimal information required to construct a computational architecture.