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Correlation-based Data Representation Strickert, Marc Seiffert, Udo Correlation data representation gradient-based optimization clustering neural gas The Dagstuhl Seminar 'Similarity-based Clustering and its Application to Medicine and Biology' (07131) held in March 25--30, 2007, provided an excellent atmosphere for in-depth discussions about the research frontier of computational methods for relevant applications of biomedical clustering and beyond. We address some highlighted issues about correlation-based data analysis in this seminar postribution. First, some prominent correlation measures are briefly revisited. Then, a focus is put on Pearson correlation, because of its widespread use in biomedical sciences and because of its analytic accessibility. A connection to Euclidean distance of z-score transformed data outlined. Cost function optimization of correlation-based data representation is discussed for which, finally, applications to visualization and clustering of gene expression data are given. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Marc Strickert and Udo Seiffert 2007 Is Part Of Dagstuhl Seminar Proceedings, Volume 7131, Similarity-based Clustering and its Application to Medicine and Biology (2007) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.07131.4 urn:nbn:de:0030-drops-11347 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07131.4 eng https://creativecommons.org/licenses/by/4.0/legalcode