The paper demonstrates how BinoX can be used to find many biologically meaningful pathway annotations for gene sets from cancer and other diseases, which are not found by other methods.
"We believe that our new method will revolutionise the way researchers do pathway analysis and yield many new functional insights. The tools commonly used today are based on the gene overlap method which is very limited and unreliable. It often fails to find activated pathways, yet it often finds incorrect pathways. The reason for this is that it applies a statistical method to very sparse data that violate its statistical assumptions", stated Erik Sonnhammer.
To make BinoX directly usable for other researchers, a public web server (Ogris et al., 2016b) was set up for on-line pathway analysis of single gene sets, which applies the BinoX algorithm to all KEGG pathways and FunCoup networks. The FunCoup network database of functional couplings between genes and gene products was also developed by Erik Sonnhammer's group. It currently contains comprehensive networks for human and 10 model organisms. For instance, the human network consists of over 18,000 genes/proteins connected to each other with over 4 million links.
"BinoX works so well thanks to the high density of the FunCoup networks, which makes it possible to find many functional network links between gene sets, even if they have no shared genes. This gives statistical power and makes it possible to find statistically significant enrichment of crosstalk", stated Erik Sonnhammer.
Ogris C., Guala D., Helleday T. and Sonnhammer E.L.L. are the authors of the paper titled "A Novel Method for Crosstalk Analysis of Biological Networks: Improving accuracy of Pathway Annotation", published in
Ogris C., Helleday T. and Sonnhammer E.L.L. are the authors of the paper titled "PathwAX: a web server for network crosstalk based pathway annotation", published in
More information is available at http://nar.oxfordjournals.org/content/early/2016/09/22/nar.gkw849.full.pdf+html .