Since the beginning of this century, the emergence of systems biology, driven by technological, informatic, and theoretical advances, has led to an unprecedented generation of data and information about biological systems at multiple levels of organization. We now have access not only to components of living systems but also to some of the underlying principles governing their organization within networks. This review focuses on the systems biology of aging, metabolism, and mitochondria, along with the integration of experimental and computational systems biology approaches as applied to multilayered biological networks, spanning from the molecular–subcellular to the whole organism. Sections 2 and 3 provide an overview of the insights gained from systems biology and multi-omics approaches as applied to aging and metabolism. Using the spatiotemporal dynamics of biological networks as a unifying thread, Sections 4 and 5 explore how systems biology and current methods can leverage the understanding of complex biological phenomena through integrated experimental–computational strategies, utilizing iterative, verification–validation loops between experiments and models. Section 6 concludes by highlighting the autonomously dynamic, self-organizing, and self-regulating integrative nature of living systems and the need to address these properties at the emerging convergence of biology, medicine, physics, and powerful computational technologies that include artificial intelligence.
Aon et al. (Tue,) studied this question.