METHOD TO DETERMINE CAUSAL RELATIONSHIPS IN COMPLEX NETWORKS

Elucidating causal relationships between the components within complex networks has impact in commercial and research applications.  For example, the ability to understand causal relationships of the components that determine stock prices can predict how the stock market will behave.  In biomedical research, knowing the relationships between the genes within complex biological pathways can lead to fundamental understanding of the mechanisms of diseases such as cancer and Alzheimer’s disease and generate in-silico predictions on phenotypes which facilitates drug discovery.  The current methods to analyze complex networks require the data of each