CLASSIFICATION OF ENTEROBACTERIACEAE BY MINIMIZATION OF STOCHASTIC COMPLEXITY

A new method for classifying bacteria is presented and applied to a la rge set of biochemical data for the Enterobacteriaceae. The method min imizes the bits needed to encode the classes and the items or, equival ently, maximizes the information content of the classification. The re sulting taxonomy of Enterobacteriaceae corresponds well to the general structure of earlier classifications. Minimization of stochastic comp lexity can be considered as a useful tool to create bacterial classifi cations that are optimal from the point of view of information theory.