Network propagation algorithm aids in inferring the altered sub-networks or signaling pathways in the given condition. The algorithm was originally developed by Vanunu et al, 2010. We have noticed that standard network propagation suffered from gene-specific biases created by the connections in the network (‘topology bias’). For example, genes with many neighbors will generally tend to accumulate higher scores independent of the gene expression data. Therefore, we devised an improved network propagation method that corrects for this topology bias.
R-package: BioNetSmooth1.0.0
Related Publications
Vanunu et al.
A propagation based algorithm for inferring gene-disease associations.
German Conference on Bioinformatics 2008. pp. 54-62.
Vanunu et al.
Associating Genes and Protein Complexes with Disease via Network Propagation
PLoS Comput Biol 2010. 6(1):e1000641.
Hofree et al.
Network-based stratification of tumor mutations
Nature Methods 2013. 10,1108–1115
Tain et al.
A proteomic atlas of insulin signalling reveals tissue-specific mechanisms of longevity assurance
Molecular Systems Biology 2017.. 13(9), September