Identification of atherosclerosis-related prioritizing metabolites based on a multi-omics composite network.

Metabolites are the final products of cellular regulation processes, their level is the ultimate response of biological systems to environmental and genetic changes. Therefore, the identification of key metabolites is required for the diagnosis and therapy of diseases. In this study, atherosclerosis-related gene expression profile information was extracted from ArrayExpress database (GEOD-57691), and analyzed with limma package.