Use of Intelligent Evolutionary Agents in the Analysis of Genomic Signals

Surprising regularities in the distribution of nucleotides and pairs of nucleotides along the genomes of both prokaryotes and eukaryotes become evident when converting nucleotide sequences from symbolic to digital form. These regularities make the structure of a genome be less like that of a "plain text", which simply conveys a semantics in accordance to a grammar, and more like that of a "poem", which obeys additional structural rules that give "rhythm" and "rhyme". Direct applications of the rules satisfied by nucleotide sequences are (1) objective evaluation of sequencing process quality, (2) prediction of nucleotides sequences similarly to time series, (3) revealing of genome ancestral structure, (4) analysis of pathogen variability. Intelligent Evolutionary Agents can be used to track pathogen variability, specifically to identify drug resistance mutations, without the need of the conventional lengthily and expensive phenotypic clinical studies that request pathogen culture. Key-Words: Evolutionary Intelligent Agents, Genomic Signals, Mutation Analysis, Pathogen Variability, Drug Resistance