By combining data from different omics layers, researchers can develop more accurate predictive models for disease risk. For instance, integrating genomic data with metabolomic profiles can improve the prediction of chronic diseases like diabetes or cardiovascular conditions. This multi-dimensional data helps in identifying individuals at high risk much earlier than traditional methods.
