ABSTRACT
The network would show the pairwise correlations between the percentage changes in the biomarker variables. Network or graphs provide a very useful mathematical representation of complex biological systems or therapeutics effects on such systems. A network of nodes and their interconnectedness is represented by an adjacency matrix. Statistical summaries like correlations or P values can be represented as edges of the network graph and the nodes or vertices would be random variables. The whole network then would be a summary of the interconnectedness among the variables. A network of nodes and their interconnectedness is represented by an adjacency matrix. The adjacency matrix is a square matrix p p, where there are p biomarkers in the data set, for example. Of course, additional variables can be added, including but not limited to continuous variables, into the analysis.
