an objective filter for rank-ordering genes based on connectivity or other network features, (4) defining dynamic changes and corresponding causal regulators of the altered network structure associated with disease condition, (5) identifying modules and pathways causally related to disease, and (6) revealing tissue-to-tissue interactions that can aid in the identification of key target tissues for disease (Dobrin et al., 2009). The present study utilizes many of these network advantages to highlight and prioritize pathways and gene targets causally related to LOAD.
