Prediction of Genome Sequences in Terms of Cellular Automata Expansion of Rule Based Logics

Abstract

This paper proposes a novel concept called “Percentage Nucleotide Concentration of genomes” in terms of cellular automata evolutions of adjoints of Adenine, Thymine, Guanine, and Cytosine. The adjoints of the given a genome sequenceare the characteristic binary string sequences. For example, the adjoint of Adenine of a given genome sequence is a binary string consisting of 0’s and 1’s where 1’s corresponds to the presence of Adenine in the genome sequence. So, one can have four adjoint sequences of Adenine, Thymine, Guanine, and Cytosine corresponding to a given genome sequence. One-dimensional three neighborhood binary value cellular automata rules could be applied to an adjoint sequence and the desired number of evolutions obtained.These rules aredefined by linear Boolean functions and one can have 256 such linear Boolean functions. The analysis of genome sequences with predictive analytics gives a scope of getting the inherent properties of the genome. The predictive model suits the Nucleotide concentration and is computed for an adjoint sequence and its variation evaluated for its successive evolutions based on a cellular automaton rule.