Digital coding for amino acid based on cellular automata

With the development of bioinformatics, it is a valuable subject to study the biological sequence on the protein aspect with the computer based on the threshold of encoding 20 kinds of amino acids, because many biological phenotype characters, gene regulating control network are determined by amino acids sequence. It is feasible to analyze genetic signals in amino acid sequences because there are already a lot of mature information process systems. This work makes use of similarity rule, complementary rule, molecular recognition theory, and information theory to set up a model of digital coding for amino acids. The model reflects better amino acid chemical physical properties and degeneracy. It transforms the symbolic DNA sequences into digital genetic signals of amino acids and offers the possibility to utilize cellular automata. Correspondingly, it opens the possibility to apply a whole range of powerful signal processing methods for analysis of amino acids.