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-- DEMO VERSION --


Distance function

Actually six distance metrics are available:

  1. Euclidean (normal)

    2. When you want to look at absolute values.

  2. Euclidean (squared)

    3. When you want to look at absolute values.

  3. Correlation Coefficient (linear)

    4. When you want to look at the shapes of the patterns.

  4. Correlation Coefficient (offset of 0)

    5. When you want to look at the shapes of the patterns, but considering 0 as the refence state.

  5. Correlation Coefficient (Spearman)

    6. When you want to look at the shapes of the patterns in a non-parametric way. This measure is based on the relative order of the data in each pattern.

  6. Correlation Coefficient (jackknifed)

    7. When you want to look at the shapes of the patterns. This is the the linear correlation coefficient but taking off exteme values.
Herrero, J., Valencia, A. and Dopazo, J. (2001) A hierarchical unsupervised growing neural network for clustering gene expression patterns. Bioinformatics. 17:126-136
Use of this program is logged Send comments to the webmaster. Last rev. March 16th, 2001