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CONTRIBUTORS:
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PROCEEDINGS TITLE:
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YEAR:
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2007
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PUB TYPE:
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Conference Paper in Proceedings
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PAGES:
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1 -
16
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SUBJECT(S):
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correlation; data representation; gradient-based optimization; clustering; neural gas; visualization; multi-dimensional scaling
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DISCIPLINE:
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Mathematics
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HTTP:
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http://lori.academicdirect.org/cites/200705.pdf
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LANGUAGE:
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English
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PUB ID:
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103-437-772
(Last edited on
2009/11/09 07:28:58 US/Mountain)
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SPONSOR(S):
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ABSTRACT:
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.
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STATISTICS
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