Introduction Mathematical Taxonomy
Taxonomy comprises a broad variety of activities related to the construction of classificatory systems. Over the past several years, the development of numerical and mathematical techniques designed to produce more objective results has transformed the field. This text offers students of mathematical biology an introduction to modern methods of taxonomy. Starting with an introduction to the philosophy and aims of numerical taxonomy, the text considers taxonomic characters and the measurement of similarity. An analysis of principal components presents geometric and mathematical interpretations; other chapters explore multidimensional scaling, cluster analysis, identification and assignment techniques, and the construction of evolutionary trees. Each of the eight major sections concludes with a helpful summary of its contents. In addition to its value to undergraduates, this text should also prove practical for postgraduate students and researchers interested in taxonomy and in the use of numerical methods in evolutionary studies. A familiarity with matrix algebra and elementary statistics are the sole prerequisites. Book jacket.
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amino acid antennal segment bacterial binary characters branch lengths canonical variate analysis Cavalli-Sforza chapter character space character values city-block metric classification Clone cluster analysis clustering algorithm clustering methods coding construction cophenetic correlation correlation defined dendrogram described diagnostic key discussed distance measure Euclidean distance evolution evolutionary tree example four OTUs gene given groups homologous hypothetical identification indicate Jaccard's coefficient Jardine & Sibson latent roots latent vectors mean measure of similarity minimum spanning tree monotonic multidimensional scaling NC NC non-metric multidimensional scaling nucleotide number of characters numerical taxonomist observed proximities obtained organisms OTUs pair of OTUs particular partition petals phenetic plot points populations possible principal components analysis principal coordinates analysis problem produce proximity matrix qualitative characters quantitative red campion relationships sequences similarity matrix simple matching coefficient single linkage Sneath & Sokal species specimen spore Taken with permission taxa taxon taxonomy transformation variables variance weight