bioRxiv

On the Aging and Reproductive Consequences of Biological Complexity

Preprint: computational studyMechanisms
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Abstract

Abstract Modeling the dynamics of aging often involves attempting to identify a handful of causal factors and correlating it to some ordered and/or disordered evolution. However, this approach may completely overlook the reality of aging as a distributed and complex evolution. Additionally, the theory driving aging should not just be about the how, but also the why, in that there should be motivated objectives and principles behind growth, decay and alternative routes like reproduction. All of these features are incorporated into a new, theoretical model for the aging process proposed herein. It incorporates a number of techniques from other fields that regularly characterize and predict complex systems dynamics.

The paper

Stanford University

bioRxiv, Sep 15, 2022, Open access, Preprint, not peer-reviewed

doi.org/10.1101/2022.09.14.505979