Using the developments of the cutting edge of mathematical physics, we study the aging of various organisms, analyzing it as the dynamics of a complex network system
Mathematical Physics for Discoveries in Aging
To achieve a radical human lifespan extension, it is necessary to find an answer to the following questions in the framework of network theory:
The human body is a complex network of networks.
Conceptually, a human (or any other) organism can be considered as an evolving complex network.
In such a network, or a graph, vertices represent distinct physiological units (PUs) - for instance, genes, proteins, methylation sites, etc. Edges represent time-dependent interactions between PUs. For each vertex there is a degree of freedom - a value that changes specifically to given network due to interaction with other vertices.
The regulation of gene expression involves a complex network of interacting elements. Expression profiles of different tissues and cells can be a powerful tool in aging research in the context of the dynamics of the gene regulatory network. In such a graph, the determining participants are complexes of various transcription factors that regulate gene expression.
Gene network
The dynamics of a gene-regulatory network means the change with time of it's degrees of freedom and of the connections between the vertices.
The topology of the gene regulatory network is the structure of connections between genes.
Gene expression profiles in various tissues are changing with age. This process can be considered as the dynamics of the movement of a point in the space of transcriptomes, where the coordinates on axes correspond to gene expressions of the organism.
The gene-regulatory network operates in a near-critical mode, which is incredibly important for further research.

A gene regulatory network is a complex system with many internal interactions. However, the property of near-criticality allows us to expect that there is a quantity (generally speaking, there may be several) that describes the evolution of the network over time. Such values can be biomarkers of aging, and they are determined by the structure of the network.

There can be more than one independent quantities that unambiguously determine the state of the system at a certain time. This plays a crucial role in the design of clinical trials of anti-aging therapies and the identification of factors affecting the aging process.

More details about the near-critical mode are explained in the "Theory" section.
The most important property of gene regulatory network
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