As pathway analysis of genomic data has exploded in use, its methods have matured, its results are beginning to meet its potential, and points of consensus are emerging for its continued application and future development. In the coming years, we anticipate that pathways and networks will assume a farther-reaching role in view of the need to integrate multi-omics data through systems biology approaches [81, 82]. A variety of large-scale strategies are being used to study complex diseases, including genomic, transcriptomic, proteomic, and metabolomic approaches, and data from all of these sources can be analyzed through pathways and networks representing coordinated functions and relationships. Importantly, while gene associations do not always indicate therapeutic targets [83], pathways and networks implicated by analyses at multiple levels would be prime targets for therapies. Integrating large-scale data assayed through diverse strategies related to structure and function would provide a fertile process for exploring connections between replicable, statistical association and meaningful biology. As such, the role of pathways and networks as the hub for this integration will be vital in the years to come.
