• Medientyp: E-Artikel; Elektronischer Konferenzbericht; Sonstige Veröffentlichung
  • Titel: Correlation-based Data Representation
  • Beteiligte: Strickert, Marc [VerfasserIn]; Seiffert, Udo [VerfasserIn]
  • Erschienen: Schloss Dagstuhl – Leibniz-Zentrum für Informatik, 2007
  • Sprache: Englisch
  • DOI: https://doi.org/10.4230/DagSemProc.07131.4
  • Schlagwörter: neural gas ; clustering ; data representation ; gradient-based optimization ; Correlation
  • Entstehung:
  • Anmerkungen: Diese Datenquelle enthält auch Bestandsnachweise, die nicht zu einem Volltext führen.
  • Beschreibung: 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.
  • Zugangsstatus: Freier Zugang