Classification of bacteria by stochastic complexity.
Mats Gyllenberg & Timo Koski
Department of Mathematics
University of Turku
20014 Turku, Finland
Abstract
A new method for classifying bacteria is presented and applied to a
large material of Enterobacteriaceae. The method minimizes
the bits needed to encode the classes and the items or, equivalently,
maximizes the information content of the classification. The
resulting taxonomy of Enterobacteriaceae corresponds well to
the general structure of earlier classifications. Minimization of
stochastic complexity can be considered as a useful tool to create
bacterial classifications that are optimal from the point of view of
information theory.