Clustering of the structures by using “snakes-&-dragons” approach, or correlation matrix as a signal

Biological, ecological, social, and technological systems are complex
structures with multiple interacting parts, often represented by networks.
Correlation matrices describing interdependency of the variables in such
structures provide key information for comparison and classification of
such systems. Classification based on correlation matrices could
supplement or improve classification based on variable values, since the
former reveals similarities in system structures, while the latter relies
on the similarities in system states. Importantly, this approach of
clustering correlation matrices is different from clustering elements of
the correlation matrices, because our goal is to compare and cluster
multiple networks – not the nodes within the networks. A novel approach
for clustering correlation matrices, named “snakes-&-dragons,” is
introduced and illustrated by examples from neuroscience, human
microbiome, and macroeconomics.