It is useful to analyze correlation graphs

TL;DR

This paper emphasizes the importance of analyzing correlation graphs in biological systems, integrating concepts like adaptation energy, entropy, and free energy, and reviews recent discussions and developments in this area over 33 years.

Contribution

It provides an analytical overview of recent commentary and advances in correlation graph analysis and adaptive models in biological research.

Findings

Correlation graph analysis is valuable in understanding biological adaptation.

Incorporating thermodynamic concepts enhances adaptive models.

Recent discussions have expanded applications to aging and omics data.

Abstract

In 1987, we analyzed the changes in correlation graphs between various features of the organism during stress and adaptation. After 33 years of research of many authors, discoveries and rediscoveries, we can say with complete confidence: It is useful to analyze correlation graphs. In addition, we should add that the concept of adaptability ('adaptation energy') introduced by Selye is useful, especially if it is supplemented by 'adaptation entropy' and free energy, as well as an analysis of limiting factors. Our review of these topics, Dynamic and Thermodynamic Adaptation Models" (Phys Life Rev, 2021, arXiv:2103.01959 [q-bio.OT]), attracted many comments from leading experts, with new ideas and new problems, from the dynamics of aging and the training of athletes to single-cell omics. Methodological backgrounds, like free energy analysis, were also discussed in depth. In this article, we provide an analytical overview of twelve commenting papers and some related publications.