Markov Cluster Algorithm
Contains the Markov cluster algorithm (MCL) by van Dongen (2000) for identifying clusters in networks and graphs. The algorithm simulates random walks on a (n x n) matrix as the adjacency matrix of a graph. It alternates an expansion step and an inflation step until an equilibrium state is reached.
|License:||GPL-2 | GPL-3 [expanded from: GPL (= 2)]|
The Markov Cluster Algorithm (MCL) is a method to identify clusters in undirected network graphs. It is suitable for high-dimensional data (e.g. gene expression data).
The original MCL uses the adjacency matrix of a graph (propsed by van Dongen (2000)). The function
mcl in this package allows in addition the input of a (n x n) matrix.
We thank Moritz Hanke for his help in realizing this package.
Martin L. Jäger
Maintainer: Ronja Foraita <firstname.lastname@example.org>
Leibniz Institute for Prevention Research and Epidemiology (BIPS)
van Dongen, S.M. (2000) Graph Clustering by Flow Simulation. Ph.D. thesis, Universtiy of Utrecht. Utrecht University Repository: http://dspace.library.uu.nl/handle/1874/848
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