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The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging

Whitwell, HJ; Bacalini, MG; Blyuss, O; Chen, S; Garagnani, P; Gordleeva, SY; Jalan, S; ... Zaikin, A; + view all (2020) The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging. Frontiers in Aging Neuroscience , 12 , Article 136. 10.3389/fnagi.2020.00136. Green open access

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Abstract

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 astroglial networks), and population genetics. Mathematical modeling 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 modeling can be utilized to investigate aging, particularly 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.

Type: Article
Title: The Human Body as a Super Network: Digital Methods to Analyze the Propagation of Aging
Location: Switzerland
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fnagi.2020.00136
Publisher version: https://doi.org/10.3389/fnagi.2020.00136
Language: English
Additional information: Copyright © 2020 Whitwell, Bacalini, Blyuss, Chen, Garagnani, Gordleeva, Jalan, Ivanchenko, Kanakov, Kustikova, Mariño, Meyerov, Ullner, Franceschi and Zaikin. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (http://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: propagation of aging, network analysis, digital medicine, aging, inflammaging
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL EGA Institute for Womens Health > Womens Cancer
URI: https://discovery.ucl.ac.uk/id/eprint/10101769
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