A new method for classifying bacteria is presented and applied to a large set of biochemical data for the 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.

Department of Mathematics Royal Institute of Technology 10044 Stockholm Sweden

Department of Mathematics University of Turku 20014 Turku Finland

Department of Medical Microbiology 3 Medical Faculty Charles University Srobarova 50 Prague 10 Czech Republic

Faculty of Technical Mathematics and Informatics Delft University of Technology 2600 GA Delft The Netherlands

Institute of Biotechnology University of Helsinki 00014 Helsinki Finland

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