NetDecoder is a 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. Please, go to our website http://netdecoder.org to obtain more information about NetDecoder. NetDecoder was developed in the Hu Li lab (http://www.hulilab.org) at Mayo Clinic.