2003
DOI: 10.1093/bioinformatics/btg294
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Electrophoretic data classification for phylogenetics and biostatistics

Abstract: ClassMaker is freely available from http://www.agr.unipg.it/cardinali/index.html, where a list of the URLs from which programs of image analysis, statistics and phylogenetics can be freely downloaded.

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Cited by 6 publications
(3 citation statements)
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“…However, problems may arise when combining different types of data (Cardinali et al 2002) and efficient algorithms are needed for nonsubjective classification of continuous data (e.g. the molecular weights of the RAPD bands) in binary matrices (Cardinali and Martini 1999;Rementeria et al 2001Rementeria et al , 2004Cardinali et al 2003). The results presented in this study show that increasing the number of descriptors improves the discrimination of strains with a clear effect of saturation because discrimination of the most similar strains requires many more descriptors than the differentiation of the least similar strains.…”
Section: Discussionmentioning
confidence: 99%
“…However, problems may arise when combining different types of data (Cardinali et al 2002) and efficient algorithms are needed for nonsubjective classification of continuous data (e.g. the molecular weights of the RAPD bands) in binary matrices (Cardinali and Martini 1999;Rementeria et al 2001Rementeria et al , 2004Cardinali et al 2003). The results presented in this study show that increasing the number of descriptors improves the discrimination of strains with a clear effect of saturation because discrimination of the most similar strains requires many more descriptors than the differentiation of the least similar strains.…”
Section: Discussionmentioning
confidence: 99%
“…(GACA) 4 i-SSR and RAPD profiles were converted in binary (0/1) matrixes with the ClassMaker 1.27 software (Cardinali et al, 2003), following the procedures described in the paper and with an additional check that similar bands were included in the same band class. Euclidean distances among the strains were calculated from the binary matrices and used to build the DIANA tree with the Cluster Package (Kaufman and Rousseeuw, 1990) in the R statistical environment.…”
Section: I-ssr (Gaca) 4 and Rapd Analysismentioning
confidence: 99%
“…In order to test the proposed methods in a real situation, we considered a binary matrix with 13 descriptors obtained applying a previously published classification method (Cardinali Bioinformatics 2003) [8] to RAPD profiles of 26 yeast isolates ( Table 3).…”
Section: A Real-world Validationmentioning
confidence: 99%