A cluster algorithm for graphs

By Stijn van Dongen. 2000

465 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0d7677864d23801ab3923ac09b0a6eb5428e4b99

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Citations in the corpus

A Survey of Clustering Data Mining Techniques (2006, methodology): “A specific Markov Cluster Algorithm based on the simulation of (stochastic) flow is described in [213].”
Bacterial insertion sequences: their genomic impact and diversity (2014, methodology): “In a second step, we use the Markov cluster algorithm (MCL) (http://micans.org/mcl/) (Van Dongen, 2000; Enright et al., 2002) to weigh the relationships between clusters of ISs and to validate prior ISfinder classification of ISs into families and subgroups (Siguier et al., 2009).”
Estimating the tempo and mode of gene family evolution from comparative genomic data. (2005, methodology): “We then clustered genes using the TRIBE-MCL algorithm (Van Dongen 2000; En-right et al. 2002), and counted the number of genes in each family that came from each species.”
clusterMaker: a multi-algorithm clustering plugin for Cytoscape (2011, methodology): “There are many approaches to this classification, including machine learning [11-13] (see [11] for a good overview) as well as clustering large groups of proteins based on either sequence or structural similarity metrics [7,8,14-28].”
Using MCL to extract clusters from networks. (2012, methodology): “mcl was first published as [1, 2] and then applied to protein sequence networks [4, 5].”
Plasmodium falciparum Erythrocyte Membrane Protein 1 Diversity in Seven Genomes – Divide and Conquer (2010, methodology): “genes were analyzed by two different methods: Markov clustering (MCL)”
Detecting highly overlapping community structure by greedy clique expansion (2010, methodology): “[27], the EM method of Newman and Leicht [28], the Markov clustering algorithm (MCL) of Van Dongen [29], an information theoretic approach by Rosvall and Bergstrom [30], and a spectral algorithm by Donetti and Munoz [31].”
Discovering Corpus-Specific Word Senses (2003, methodology): “We use the same data for both recognising and resolving ambiguity.”