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NetDecoder is developed by Hu Li's Lab. It is a novel network biology-based computational platform designed to integrate transcriptomes, interactomes and gene ontologies to identify phenotype-specific subnetworks. NetDecoder is based on network flow algorithm and formulated as a minimum-cost flow optimization problem to identify and prioritize paths and key regulators within disease specific subnetworks. NetDecoder is designed to capture molecular switches and infer disease-specific networks to better understand pathways and identify key regulators that contribute to a disease phenotype. NetDecoder has extensive documentation and tutorial with free software package downloadable for the research communities. You can use NetDecoder on-line by uploading your data here, or you can download and run NetDecoder locally on your computer. NetDecoder is provided under the OSI-approved Artistic License (version 2.0).
NetDecoder takes as input a phenotype-specific edge-weighted interaction network and a list of genes to be used as sources and returns: