Fachada, NunoFigueiredo, Mário A.T.Lopes, Vitor V.Martins, Rui C.Rosa, Agostinho2015-03-192015-03-192014Fachada, N.; Figueiredo, Mário A.T.; Lopes, Vitor V.; Martins, Rui C.; Rosa, A.C. - Spectrometric differentiation of yeast strains using minimum volume increase and minimum direction change clustering criteria. In: attern Recognition Letters, 2014, Vol. 45, p. 55-610167-8655http://hdl.handle.net/10400.9/2651This paper proposes new clustering criteria for distinguishing Saccharomyces cerevisiae (yeast) strains using their spectrometric signature. These criteria are introduced in an agglomerative hierarchical clustering context, and consist of: (a) minimizing the total volume of clusters, as given by their respective convex hulls; and, (b) minimizing the global variance in cluster directionality. The method is deterministic and produces dendrograms, which are important features for microbiologists. A set of experiments, performed on yeast spectrometric data and on synthetic data, show the new approach outperforms several well-known clustering algorithms, including techniques commonly used for microorganism differentiation.engSpectroscopyYeastsSaccharomyces cerevisiaeClusteringjournal article