As part of the International Open Access week, we would like to talk about another one of our open access network visualization and analysis tool – the Reactome FIViz app.

In order to improve our understanding of disease mechanisms and develop better personalized precision therapies for patients, many biological and clinical studies employ high-throughput techniques that generate large-scale data sets. Typically, these data sets are gene- or protein-based, and to better understand the relationships among interesting genes or proteins, researchers usually have to project them onto biological network contexts to provide holistic visualization and analysis platform for reducing the dimensionality of data using network modules.

To assist our users who would like to perform network-based analysis, we have constructed the Reactome Functional Interaction (FI) network which, covers 60% of the total human protein-coding genes, and was created by extracting interactions from manually curated pathways and predicting interactions based on a machine learning technique. We have developed the Cytoscape application (or app), called the “ReactomeFIViz” that uses this highly reliable FI network to support network-based data visualization and analysis. Users of our app can construct an FI subnetwork for a list of genes, perform network clustering to find network modules, annotate the subnetwork and modules, and perform survival analysis for network modules. Furthermore, the app can also perform pathway enrichment analysis using a gene score file, and pathway mathematical modeling based on probabilistic graphical models and Boolean networks. More documentation about the ReactomeFIViz app is available through our User Guide and the Cytoscape App Store.