iCTNet: A Cytoscape plugin to produce and analyze integrative complex traits networks
1 School of Computing, Queen's University. 25 Union Street, Goodwin Hall, Queen's University. Kingston, Ontario K7L 3N6, Canada
2 Department of Neurology, University of California San Francisco. 513 Parnassus Ave. Room S-256. San Francisco, CA, 94143. USA
BMC Bioinformatics 2011, 12:380 doi:10.1186/1471-2105-12-380Published: 26 September 2011
The speed at which biological datasets are being accumulated stands in contrast to our ability to integrate them meaningfully. Large-scale biological databases containing datasets of genes, proteins, cells, organs, and diseases are being created but they are not connected. Integration of these vast but heterogeneous sources of information will allow the systematic and comprehensive analysis of molecular and clinical datasets, spanning hundreds of dimensions and thousands of individuals. This integration is essential to capitalize on the value of current and future molecular- and cellular-level data on humans to gain novel insights about health and disease.
We describe a new open-source Cytoscape plugin named iCTNet (
iCTNet provides a user-friendly interface to search, integrate, visualize, and analyze genome-scale biological networks for human complex traits. We argue this tool is a key instrument that facilitates systematic integration of disparate large-scale data through network visualization, ultimately allowing the identification of disease similarities and the design of novel therapeutic approaches.