Clustering and Graphs from steady-states correlation matrix #105
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Aim of this PR is to provide functions to dingo/utils.py and dingo/illustrations.py for clustering and graphs analysis of a steady-states correlation matrix alongside visualizations.
Reactions that belong to the same clusters, tend to appear in the same connected subgraphs.
If the given as input correlation matrix is strictly filtered (with a pearson cutoff of ~ 0.9999), then each subgraph created corresponds to a metabolic pathway in a metabolic model (A metabolic pathway is a group of reactions that are either near each other (connected) in the topology of a metabolic network or share metabolites).