A Complex Heterogeneous Network Model of Disease Regulated by Noncoding RNAs: A Case Study of Unstable Angina Pectoris

Table 1

Comparison of the three network analysis methods.

		WGCNA	SimCluster	WGCNA & SimCluster
Data	Data sources	miRNA expression data	MTP network	Data used in the WGCNA method and SimCluster method
	Constructed matrices	Correlation matrix and the topological overlap matrix	First-order similarity matrix or the second-order similarity matrix
Methods	Core principles	Pearson’s correlation of miRNA expression data	Jaccard similarity of miRNAs at the target gene level or pathway level	Intersection of the results of the WGCNA method and the SimCluster method
	Parameters of scale-free networks	Soft threshold	Similarity threshold
		R ^2 greater than 0.9	Both R^2 and the correlation coefficient should be greater than 0.9
	Module generation	Hierarchical clustering	Network clustering
Results	Number of hub miRNAs	40	63	11
	Mean AUC values for the new dataset	0.5191	0.5319	0.6292
	Mean AUPR values for the new dataset	0.6019	0.6069	0.6773

Note. In this table, the results of the SimCluster method and the WGCNA & SimCluster method are calculated based on first-order similarity.