By integrating genomic, metagenomic, transcriptomic, proteomic, metabolomic, and miRNome analyses, we apply a holistic approach to the study of biological systems. This facilitates the understanding of their dynamic interactions, both at the level of cellular function under physiological conditions and in response to environmental factors, treatments, or disease. Omics studies provide crucial information for applications in the agri-food, nutraceutical, pharmaceutical, and environmental sectors.
Furthermore, the analysis of complex datasets derived from omics studies is performed using advanced bioinformatics approaches. These include correlation networks between genes, metabolites, and phenotypes, gene co-expression analyses as well as protein–protein and protein–ligand interaction analyses. These approaches enable the integration and interpretation of the large-scale datasets generated by multi-level analyses, allowing the identification of functional modules (subsystems of molecular networks) and metabolic or gene pathways correlated with traits of interest. This enhances our understanding of the regulatory mechanisms of biological systems and accelerates optimization and selection processes in plant species, while also supporting the development of novel preventive and therapeutic strategies.