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The Interpretation of Analytical Data by the Use of Cluster Analysis Wiley New York . [7]. W. Vogt
? In addressing this research question, we used a mixed-methods approach to increase transferability. In “Methods” section, we introduce two studies: clustering analysis and focus group interview . The “Results” section reports on the usage types
Fourteen isolates of tomato powdery mildew (Oidium neolycopersici) and one isolate of the following species: Podosphaera fusca (= Sphaerotheca fusca), Erysiphe orontii (cucumber powdery mildews), Erysiphe cichoracearum (lettuce powdery mildew) and Erysiphe aquilegiae var. ranunculi (Ranunculus lingua powdery mildew) were used for comparative morphological studies. Basic characteristics of the anamorphs, including outer conidial wall patterns, were compared using light and scanning electron microscopy (SEM). In main morphological features, O. neolycopersici was strongly differentiated from E. cichoracearum, E. orontii and P. fusca. However, based on morphological features (e.g. germination type; appressorium shape; morphology of conidiophores) O. neolycopersici was close to E. aquilegiae var. ranunculi (both belong to Oidium subgen. Pseudoidium) and it probably could be placed to Erysiphe sect. Erysiphe (= Erysiphe s. str.)
Breckenridge, J. N. (1989): Replicating cluster-analysis — methods, consistency, and validity. — Multivar. Behavioral. Res. 24 : 147–161. Breckenridge J. N
. 1976. Correlation between single ecological variables and vegetation by means of cluster analysis. Not. Fitosoc , 12: 77–82. Feoli E. Correlation between single ecological variables
142 388 396 L. Kaufman and P.J. Rousseeuw Finding groups in data; An introduction to cluster analysis, John Wiley & Sons, New York, 1990
Summary
Chemometrics involves strategies to analyse multivariate data using interdisciplinary approaches aiming to extract relevant information from complex data. Chemometric strategies comprise both the pre-processing of the data, where the choice of methodology is domain-specific, and analysis of the resulting data after preprocessing using multivariate methodology. Although use of multivariate data analysis for gel electrophoresis images has increased substantially in the last decade, its use is still much less frequent than use of univariate approaches. Considering the complexity of the electrophoresis gel images and the multivariate nature of the proteome, applying multivariate data analysis for gel electrophoresis images gives information which is otherwise lost. This paper is written as a review and guideline of chemometric strategies used for analysis of gel electrophoresis images. The multivariate data analyses described are, however, also relevant for other proteome data, for example mass spectrometry, and for functional genomics in general.
16 Artis, M. - Zhang, W. (2002): Membership of EMU: A Fuzzy Clustering Analysis of Alternative Criteria. Journal of Economic Integration, 17: 54
shells preparations. The chemical fingerprints of Moringa seed shells from various regions were established and investigated by similarity analysis (SA), principal component analysis (PCA) and hierarchical clustering analysis (HCA). The combination of
program. For each sample five spectra were collected. Chemometrics Similarities between FT-Raman spectra were studied using Hierarchical Cluster Analysis (program Opus/Bruker package 5.1). The spectra were not baseline