Title
Clustering with overlap for genetic interaction networks via local search optimization
Abstract
Algorithms for detection of modules in genetics interaction networks, while often identifying new models of functional modular organization between genes, have been limited to the output of disjoint, non-overlapping modules, while natural overlapping modules have been observed in biological networks. We present CLOVER, an algorithm for clustering weighted networks into overlapping clusters. We apply this algorithm to the correlation network obtained from a large-scale genetic interaction network of Saccharomyces cerevisiae derived from Synthetic Genetic Arrays (SGA) that covers ∼4,500 nonessential genes. We compare CLOVER to previous clustering methods, and demonstrate that genes assigned by our method to multiple clusters known to link distinct biological processes.
Year
DOI
Venue
2011
10.1007/978-3-642-23038-7_27
WABI
Keywords
Field
DocType
synthetic genetic arrays,local search optimization,weighted network,large-scale genetic interaction network,genetics interaction network,biological network,overlapping cluster,previous clustering method,natural overlapping module,correlation network,distinct biological process,local search,graph clustering
Fuzzy clustering,Combinatorics,Correlation clustering,Biological network,Computer science,Interaction network,Bioinformatics,Local search (optimization),Cluster analysis,Clustering coefficient,Single-linkage clustering
Conference
Citations 
PageRank 
References 
0
0.34
7
Authors
6
Name
Order
Citations
PageRank
Joseph Whitney100.34
J L Koh211014.39
Michael Costanzo3192.50
Grant Brown401.01
Charles Boone5203.57
Michael Brudno626215.80