Kohonen’s self-organizing maps as applied to graphical visualization of some yeast DNA data
نویسندگان
چکیده
We analyze a set of data describing N=3300 yeast genes, each gene characterized by d=13 variables (traits). First we performed an explorative data analysis and stated a high multivariate kurtosis. Next we clustered the data and visualized them using Kohonen’s self-organizing maps. This permitted us to get an idea how the data are distributed in the multivariate space.
منابع مشابه
Kohonen’s self-organizing maps as applied to graphical visualization of some yeast DNA data – Supplement: PLOTS
Figure 1 Spider plot for the yeast gene YBL008w (HIR1); position 1 the walker visits every first nucleotide of codons and moves a unit up if the nucleotide is G, down if it is C, right if it is A and left if it is T; position 2 the walker visits every second nucleotide of codons, and proceeds the same way; position 3 the walker visits every third nucleotide of codons, and proceeds the same way ...
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