Omics and Clinical Data Integration

Many high-throughput post-genomics (-omics) technologies have been developed to unravel cellular complexity and to investigate biological systems. Each -omics technology (such as genomics, transcriptomics, proteomics, or metabolomics) deals with a different layer of cellular or tissue functioning. The integration of two or more -omics connects these different layers, allowing to extract information that would otherwise remain latent if each dataset was considered alone. This approach paves the way to the identification of functional emergent properties and their design principles at both the cellular and organismal levels. Many diseases are multifactorial in nature and are affected by the alteration of a large number of gene products whose interaction may profoundly modify the penetrance of the disease and the efficacy of a given therapeutic approach. Ultimately, integration of the knowledge of functional emergent properties will merge with personalized -omics data to generate and constrain mathematical models of the diseased functions, allowing to develop personalized medical treatment of multifactorial diseases.