![]() It supports the interpretation and navigation of large-scale datasets by creating focus networks, facilitating mechanistic predictions from –omics studies. Conclusions: The Cytoscape plug-in viPEr integrates –omics data with interactome data. ![]() Moreover, we find an enrichment of metabolic and cancer pathways in the Fox transcriptional network and demonstrate a patient-specific reaction to the drug. Based on our investigations using viPEr and PEANuT, we suggest a role of the FoxA1/A2/A3 transcriptional network in the cellular response to atorvastatin treatment. Using time series expression data of atorvastatin treated primary hepatocytes from six patients, we demonstrate the handling and applicability of viPEr and PEANuT. The pathway enrichment analysis tool PEANuT annotates networks with pathway information from various sources and calculates enriched pathways between a focus and a background network. Numerical values from expression studies assigned to the nodes serve to score identified paths. viPEr calculates all paths between two or more user-selected nodes, or explores the neighborhood of a single selected node. ![]() The virtual pathway explorer viPEr creates so-called focus networks by joining a list of experimentally determined genes with the interactome of a specific organism. Results: We introduce two Cytoscape plug-ins, which support the generation and interpretation of experiment-based interaction networks. Yet, toolboxes for navigating and understanding even small gene or protein networks are poorly developed. Combining expression with physical or genetic interaction data has already been successfully applied to enhance knowledge from all types of high-throughput studies. Background: Interpreting large-scale studies from microarrays or next-generation sequencing for further experimental testing remains one of the major challenges in quantitative biology.
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