The MetScape 3 App for Cytoscape provides a bioinformatics framework for the visualization and interpretation of metabolomic and expression profiling data in the context of human metabolism. It allows users to build and analyze networks of genes and compounds, identify enriched pathways from expression profiling data, and visualize changes in metabolite data. MetScape uses an internal relational database that integrates data from KEGG and EHMN databases. Starting with version 3.1, MetScape also provides the ability to build, visualize and explore correlation networks, where nodes are metabolites and edges are the correlations between them. Correlation networks can include both known and unknown metabolites.
MetScape is developed by The Karnosky Lab in the Department of Computational Medicine & Bioinformatics and The Michigan Regional Comprehensive Metabolomics Resource Core (MRC2).
Metscape Development team (past and present): William Duren, Terry Weymouth, Tim Hull, Glenn Tarcea.
Support for MetScape was provided by NIH grants U24 DK097153 and P30 DK089503.