An Entropy-Based Technique for Classifying Bacterial Chromosomes According to Synonymous Codon Usage

We present a framework based on conditional entropy and the Dirichlet distribution for classifying chromosomes based on the degree to which they use synonymous codons uniformly or preferentially, that is, whether or not codons that code for an amino acid appear with the same relative frequency. Applying the approach to a large collection of annotated bacterial chromosomes reveals three distinct groups of bacteria.