ABSTRACT
Network analysis of Protein-Protein Interaction (PPI) maps is valuable for identifying key regulators of cellular processes such as cancer-related signaling pathways. Previous studies have used the Minimum Connected Dominating Set (MCDS) to identify such key proteins. However, these studies did not account for directionality and regulatory effects. In this study, a directed MCDS algorithm was developed and tested on a human PPI network simulating HER2-positive breast cancer using regulation and expression data. The biological significance of the directed MCDS was examined using pathway enrichment analysis. The directed MCDS was found to be significantly smaller (333 nodes) than the undirected MCDS (811 nodes) of the same network, with 68 uniquely identified nodes involved in cancer. This suggests that the directed MCDS identifies a more specialized set of critical proteins under given biological conditions. The performance of the directed MCDS under conditions other than breast cancer is recommended for future analysis.
