Correlation networks are increasingly being used in biology to analyze large, high-dimensional data sets. Correlation networks are constructed on the basis of correlations between quantitative measurements that can be described by an n × m matrix X = [xil] where the row indices correspond to network nodes (i = 1, . . ., n) and the column indices (l = 1, . . ., m) correspond to sample measurements:
