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Simultaneous Clustering of Multiple Gene Expression and Physical Interaction Datasets
2010
PLoS Computational Biology
Many genome-wide datasets are routinely generated to study different aspects of biological systems, but integrating them to obtain a coherent view of the underlying biology remains a challenge. We propose simultaneous clustering of multiple networks as a framework to integrate large-scale datasets on the interactions among and activities of cellular components. Specifically, we develop an algorithm JointCluster that finds sets of genes that cluster well in multiple networks of interest, such as
doi:10.1371/journal.pcbi.1000742
pmid:20419151
pmcid:PMC2855327
fatcat:2e6eimejmvhwvomzuwx7qijznu