ReactomeFIViz: a Cytoscape app for pathway and network-based data analysis
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Updated: Apr 22, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
Published on: February 8, 2017
Guanming Wu1, Eric Dawson2, Adrian Duong3
1Ontario Institute for Cancer Research, Toronto, Ontario M5G 0A3, Canada ; DMICE, Oregon Health & Science University, Portland, Oregon 97239, USA.
Abstract:
High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called "ReactomeFIViz", which utilizes a highly reliable gene functional interaction network combined with human curated pathways derived from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.
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