Revealing the causes of dynamic change in protein-protein interaction network

Uncovering the dynamic nature of protein-protein interaction networks is important to understand life at the system-level. However, the large-scale protein interaction data sets are static and unable to capture the changes in the profile of protein. In this paper, we focus on the following questions (1) Can we detangle the dynamic features of PPI networks? (2) Can we effectively detect the overlapping dynamic functional modules in PPI networks? (3) What the causes of dynamic changes for the modules in PPI networks? We propose a graph-based analysis approach that integrates protein-protein interactions with time-series gene expression data to reveal dynamic functional modules under different biological states. Experimental results demonstrate that the majority of the identified dynamic modules are functionally homogeneous. More importantly, we build on the idea that the dynamic changes in functional modules are partly caused by interacting with other modules at the same time.