Biocybernetics and Biomedical Engineering 2000, Volume 20, Nlrmber 2, pp. 5-16 JACEK MI ĘDZoBRoDzKl* , ToMAsZ PANZ--, ANDRZEJ KASPROWI CZ* * *, RYSZARD TADEUSI EWI CZ* * * * Remarks on Using Pattern Recognition Methods in Biology This paper makes an attempt to present new possibilities for biology, and especially for microbiology, which derive from applying the procedure used in a pattern recognition. There are straightforward advantages to this approach when compared to using standard statistical methods. Firstly, the amount of data needed for the pattern recognition procedure is much smaller, and, moreover, pattern recognition algorithms can deal with incomplete and even erroneous data. Secondly, pattern recognition method leads directly from raw data to strong and easy-to-interpret results that allow definitive statements on the results to be made as "the drug is effective" or "such a way of drug administration is more promising". The classic statistical methods usually provide only numeric data, forc- ing further speculations and interpretation or demanding further tests, often failing because of insufficient amounts of data. This paper introduces the logic behind pattern recognition and explains the usefulness of this method in mathematical analysis and interpretation of biological experiments, especially in microbiology. Keywords: data analysis, microbiology, pattern recognition 1. Introduction Statistical description of biological experiments and clinical observations is an inherent element of scientific papers. This fact is not in proportion to the amount of methodological papers explaining mathematical theory that ale potentially useful for biology or medical computing [1]. Closer analysis of the published papers shows how the interests of math- ematicians, programmers and biologists develop in parallel with almost no overlapping areas. The result is a growth of both general mathematical and biological knowledge but there exists minimal inspiration and minimal dif- fusion of ideas. 2. Mathematicians and Biology Frequently, mathematicians take their inspiration from biology and create models and mathematical descriptions for which biology is merely a starting