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Networks of Networks: An Essay on Multi-Level Biological Organization

Authors
  • Uversky, Vladimir N.1
  • Giuliani, Alessandro2
  • 1 Department of Molecular Medicine, Byrd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL , (United States)
  • 2 Department of Environment and Health, Istituto Superiore di Sanità, Rome , (Italy)
Type
Published Article
Journal
Frontiers in Genetics
Publisher
Frontiers Media SA
Publication Date
Jun 21, 2021
Volume
12
Identifiers
DOI: 10.3389/fgene.2021.706260
Source
Frontiers
Keywords
Disciplines
  • Genetics
  • Review
License
Green

Abstract

The multi-level organization of nature is self-evident: proteins do interact among them to give rise to an organized metabolism, while in the same time each protein (a single node of such interaction network) is itself a network of interacting amino-acid residues allowing coordinated motion of the macromolecule and systemic effect as allosteric behavior. Similar pictures can be drawn for structure and function of cells, organs, tissues, and ecological systems. The majority of biologists are used to think that causally relevant events originate from the lower level (the molecular one) in the form of perturbations, that “climb up” the hierarchy reaching the ultimate layer of macroscopic behavior (e.g., causing a specific disease). Such causative model, stemming from the usual genotype-phenotype distinction, is not the only one. As a matter of fact, one can observe top-down, bottom-up, as well as middle-out perturbation/control trajectories. The recent complex network studies allow to go further the pure qualitative observation of the existence of both non-linear and non-bottom-up processes and to uncover the deep nature of multi-level organization. Here, taking as paradigm protein structural and interaction networks, we review some of the most relevant results dealing with between networks communication shedding light on the basic principles of complex system control and dynamics and offering a more realistic frame of causation in biology.

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