The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging - Whitwell, Harry J.; Bacalini, Maria Giulia; Blyuss, Oleg; Chen, Shangbin; Garagnani, Paolo; Gordleeva, Susan Yu; Jalan, Sarika; Ivanchenko, Mikhail; Kanakov, Oleg; Kustikova, Valentina; Mariño, Ines P.; Meyerov, Iosif; et al. (Frontiers in Aging Neuroscience, 2020)
Biological aging is a complex process involving multiple biological processes. These can be understood theoretically though considering them as individual networks – e.g. epigenetic networks, cell-cell networks (such as astro-glial networks) and population genetics. Mathematical modelling allows the combination of such networks so that they may be studied in unison, to better understand how the so called “seven pillars of aging” combine and to generate hypothesis for treating aging as a condition at relatively early biological ages. In this review, we consider how recent progression in mathematical modelling can be utilised to investigate aging, particular in, but not exclusive to, the context of degenerative neuronal disease. We also consider how the latest techniques for generating biomarker models for disease prediction, such as longitudinal analysis and parenclitic analysis can be applied to as both biomarker platforms for aging, as well as to better understand the inescapable condition. This review is written by a highly diverse and multi-disciplinary team of scientists from across the globe and calls for greater collaboration between diverse fields of research.