Modeling the classification of Amino acids with Colored Petri Nets

In molecular biology, Amino acids play important roles both as building blocks of proteins and as intermediates in metabolism. Depending on the polarity and charge type of the side chain (R group), 20 essential amino acids are usually classified into four categories: non-polar amino acids, polar and neutral amino acids, acidic amino acids and basic amino acids. It is a significant study to predict the proteins spatial structure if we can determine the different types of amino acids along the polypeptide chain. As a mature mathematical tool for process analysis, Colored Petri Net (CPN) provides an effective theoretical method for studying the biological systems. Based on the table of genetic code, CPN is applied to discriminate the type of amino acids. In this paper, a model of the classification of amino acids is proposed. Examples show that this model can quickly and accurately determine the type of a given amino acid.