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Bayesian predictive identification and cumulative classification of bacteria

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Abstract

In this paper we give a mathematically precise formulation of an old idea in bacterial taxonomy, namely cumulative classification, where the taxonomy is continuously updated and possibly augmented as new strains are identified. Our formulation is based on Bayesian predictive probability distributions. The criterion for founding a new taxon is given a firm theoretical foundation based on prediction and it is given a clear-cut interpretation. We formulate an algorithm for cumulative classification and apply it to a large database of bacteria belonging to the family Enterobacteriaceae. The resulting taxonomy makes microbiological sense.

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Authors and Affiliations

  1. Department of Mathematics, University of Turku, 20014, Turku, Finland

    Mats Gyllenberg, Timo Koski & Tatu Lund

  2. Institute of Biotechnology, University of Helsinki, 00014, Helsinki, Finland

    Helge G. Gyllenberg

  3. Department of Mathematics, Royal Institute of Technology, 10044, Stockholm, Sweden

    Timo Koski

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  1. Mats Gyllenberg
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  2. Timo Koski
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  4. Helge G. Gyllenberg
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Correspondence to Mats Gyllenberg.

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Gyllenberg, M., Koski, T., Lund, T. et al. Bayesian predictive identification and cumulative classification of bacteria. Bull. Math. Biol. 61, 85–111 (1999). https://doi.org/10.1006/bulm.1998.0076

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  • DOI: https://doi.org/10.1006/bulm.1998.0076

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