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.
Highlights
Aging is the inescapable consequence of life that is common to all
The Collective Irregular Dynamics (CID) is a dynamic phenomenon known from dynamic system theory and we propose to transfer the concept to spontaneous background activities observed in the brain
The rapid development of artificial intelligence will lead to a new generation of personalized patient tools
Summary
Aging is the inescapable consequence of life that is common to all. the impact of aging on individuals can be very different, where some people live to a high age whilst maintaining excellent physical/mental health yet others may accumulate detrimental symptoms of aging relatively young. Several epigenetic clocks, differing in during cell divisions (Jones and Liang, 2009) Besides being both the included CpG sites and the human tissues on which relatively stable from a biological point of view, DNA they have been validated, have been proposed Availability of several approaches to measure DNA methylation these clocks have been comprehensively shown to detect age at a gene-targeted, genome-wide, and whole-genome level, acceleration effects associated to different age-related conditions, makes this epigenetic modification an ideal candidate to spanning from neurodegenerative diseases to cancer and identify longevity biomarkers. Different types of changes to DNA methylation occurs based on directional changes in DNA methylation, during aging: and on the other aspects of age-related DNA methylation remodeling (hypomethylation of repetitive elements, increase in variability and epimutations), improving the performance of predictors and broadening the spectra of age-related diseases that could benefit from early diagnosis
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
