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Table 1 clusterMaker algorithm implementation notes

From: clusterMaker: a multi-algorithm clustering plugin for Cytoscape

Algorithm Description Source Details
Hierarchical Standard hierarchical clustering as implemented by Eisen[1] Cluster 3.0 package from Michiel de Hoon of the University of Tokyo Ported by clusterMaker authors from C to Java
k-means Standard k-means clustering as implemented by Eisen[1] with the addition of silhouette estimation of k Cluster 3.0 package from Michiel de Hoon of the University of Tokyo Ported by clusterMaker authors from C to Java. Silhouette implemented by clusterMaker authors.
k-medoid Modification of k-means from above to use medoid rather than means   Implemented by clusterMaker authors. Silhouette implemented by clusterMaker authors.
AutoSOME The AutoSOME cluster algorithm [34] The distributed AutoSOME implementation Ported directly to clusterMaker by AutoSOME author
Affinity Propagation The message passing-based approach to clustering by Frey and Dueck[27] Implemented from the algorithm description in the original reference Implemented by clusterMaker authors
Connected Components Simple division based on connectivity   Implemented by clusterMaker authors
Community (GLay) Newman-Girvan[32] community clustering as implemented by Su, et al.[33] The original GLay plugin for Cytoscape Ported by clusterMaker authors
MCODE Bader and Hogue[4] algorithm for finding modules in PPI networks The MCODE Cytoscape plugin Ported by clusterMaker authors
MCL Markov clustering algorithm from van Dongen[8, 28] that uses random walks to simulate flow Implemented from original thesis with reference to C implementation for validation of results. Implemented by clusterMaker authors as a parallel algorithm to take advantage of multiple CPU cores.
SCPS Spectral clustering algorithm for BLAST similarity networks[24] Implemented from the algorithm description in the original reference using the authors' implementation to validate results Implemented by clusterMaker authors
Transitivity Clustering Transitivity based clustering approach from Wittkop, et al.[25] Ported from Cytoscape TransClust plugin Ported by original TransClust authors