A Control Perspective on the Evolution of Biological Modularity

Constantino, Pedro H.; Daoutidis, Pródromos

doi:10.1016/j.ifacol.2019.09.136

Cited by 7 publications

(3 citation statements)

References 32 publications

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“…Once modularity is appraised as a valid mechanism in biological networks, there is no reason to suppose that these in toto segmental exchanges would be random. And further, given that these are en bloc genetic transfers, it follows that there is no requirement that the resulting biological shifts yield merely gradual differential physical expressions [ 125 ].…”

Section: The Role Of Viral Modularitymentioning

confidence: 99%

Cellular and Natural Viral Engineering in Cognition-Based Evolution

Miller

Reber

Marshall³

et al. 2023

Communicative & Integrative Biology

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Neo-Darwinism conceptualizes evolution as the continuous succession of predominately random genetic variations disciplined by natural selection. In that frame, the primary interaction between cells and the virome is relegated to host-parasite dynamics governed by selective influences. Cognition-Based Evolution regards biological and evolutionary development as a reciprocating cognition-based informational interactome for the protection of self-referential cells. To sustain cellular homeorhesis, cognitive cells collaborate to assess the validity of ambiguous biological information. That collective interaction involves coordinate measurement, communication, and active deployment of resources as Natural Cellular Engineering. These coordinated activities drive multicellularity, biological development, and evolutionary change. The virome participates as the vital intercessory among the cellular domains to ensure their shared permanent perpetuation. The interactions between the virome and the cellular domains represent active virocellular cross-communications for the continual exchange of resources. Modular genetic transfers between viruses and cells carry bioactive potentials. Those exchanges are deployed as nonrandom flexible tools among the domains in their continuous confrontation with environmental stresses. This alternative framework fundamentally shifts our perspective on viral-cellular interactions, strengthening established principles of viral symbiogenesis. Pathogenesis can now be properly appraised as one expression of a range of outcomes between cells and viruses within a larger conceptual framework of Natural Viral Engineering as a co-engineering participant with cells. It is proposed that Natural Viral Engineering should be viewed as a co-existent facet of Natural Cellular Engineering within Cognition-Based Evolution.

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Section: The Role Of Viral Modularitymentioning

confidence: 99%

Cellular and Natural Viral Engineering in Cognition-Based Evolution

Miller

Reber

Marshall³

et al. 2023

Communicative & Integrative Biology

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“…This question has been addressed in evolutionary/developmental biology (evo/devo) and in molecular systems biology as a kind of intersection point between both disciplines. It has been argued that there is indeed a relationship between modularity and controllability (Constantino and Daoutidis, 2019 ).…”

Section: Modularity In Biological Systemsmentioning

confidence: 99%

Modularity in Biological Networks

et al. 2021

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Network modeling, from the ecological to the molecular scale has become an essential tool for studying the structure, dynamics and complex behavior of living systems. Graph representations of the relationships between biological components open up a wide variety of methods for discovering the mechanistic and functional properties of biological systems. Many biological networks are organized into a modular structure, so methods to discover such modules are essential if we are to understand the biological system as a whole. However, most of the methods used in biology to this end, have a limited applicability, as they are very specific to the system they were developed for. Conversely, from the statistical physics and network science perspective, graph modularity has been theoretically studied and several methods of a very general nature have been developed. It is our perspective that in particular for the modularity detection problem, biology and theoretical physics/network science are less connected than they should. The central goal of this review is to provide the necessary background and present the most applicable and pertinent methods for community detection in a way that motivates their further usage in biological research.

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“…• In Constantino and Daoutidis, 131 a simulated evolution was performed on a population of random networks using a genetic algorithm, with the total control cost function as the fitness indicator to be optimized. It was observed that random mutations alone are insufficient to result in community structures.…”

Section: Inspirations From Network Structures In Biologymentioning

confidence: 99%