BMC Bioinformatics | Abstract | Sensitive detection of pathway perturbations in cancers

Sensitive detection of pathway perturbations in #cancers Differential expression of #pathways (in toto or a sub-part)

** Sensitive detection of pathway perturbations in cancers. Rivera et al. BMC Bioinfo (2014)

In this paper, the authors introduce a new computational method that identifies subsets of pathways that exhibit differential gene expression between cancer and normal tissue. Some previous methods only considered differential expression in sets of genes without considering the structure of interactions between the genes or their protein products. Other previous methods looked at pathway
perturbations, but required all members of a pathway to exhibit differential gene expression in order for the pathway to appear significant. The authors demonstrate the general superiority of their method to these previous methods, as well as the robustness of their method to missing data. The authors also consider future enhancements, such as taking into account the direction of differential expression, using more information on the nature of each gene interaction involved, and using universal protein interaction networks to incorporate data beyond what is found in curated pathway databases.

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