IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source

5. Common Code: A Further Report of Reliable, Invariant Occasions

Jordan, Ferenc, et al. A Hierarchy of Networks Spanning from Individual Organisms to Ecological Landscapes. Estrada, Ernesto, et al, eds. Network Science: Complexity in Nature and Technology. London, Springer, 2010. Jordan, with Federica Ciocchetta, Centre for Computational and Systems Biology, University of Trento, and Gabriella Baranyi, Institute of Environmental Studies, Eotvos University, in this volume about this natural phenomena from common principles, and instantiation from protein to financial webs, provide a cogent paper over this ubiquity. As the quotes convey, a nested net repetition or iteration is the evident case, as informed by convergent statistical physics and systems ecology approaches.

Living systems are hierarchically organised. A number of components are linked by the multiplicity of interactions at each level (from organisms to species to ecosystems). This kind of compositional and hierarchical complexity is a computational and conceptual challenge. We need new approaches to determine the key components of large interaction networks and we need to better understand how they influence the system dynamics horizontally (at the same level) and vertically (between organisational levels). We provide examples for various interaction networks (animal social group, food web, landscape) and discuss how to dynamically link them. (Abstract, 165)

Biological systems are composed of a large number of various components, like millions of molecules in a cell, thousands of cells in an organism, hundreds of individuals in a population and dozens of species in an ecological system. Yet, biosystems are complex not primarily because of the number of components but rather because of composition: the multiplicity of interactions among similar components and the hierarchical, nested nature of different kinds of components at several organizational levels. These components are composed of subsystems as well as compose larger systems, and all layers have been coevolved in evolution. (165)

Kaschube, Matthias, et al. Universality in the Evolution of Orientation Columns in the Visual Cortex. Science. 330/1113, 2010. German and American neurogeneticists first report a specific instance of how dynamic nonlinearites are found to guide the formation and acuity of optical shapes, and go on, re the second quote, to advise that their common prevalence across living systems would attest to a generative spontaneity on a par with genetic and behavioral influences. For our nascent 2010 revolution, here is tangible evidence of an innately creative complexity that is manifest in a similar fashion everywhere. This implicate independence can then be realized to take on a genomic identity, so as to grace, propel, and ascend through, a natural genesis.

The brain’s visual cortex processes information concerning form, pattern, and motion within functional maps that reflect the layout of neuronal circuits. We analyzed functional maps of orientation preference in the ferret, tree shrew, and galago—three species separated since the basal radiation of placental mammals more than 65 million years ago—and found a common organizing principle. A symmetry-based class of models for the self-organization of cortical networks predicts all essential features of the layout of these neuronal circuits, but only if suppressive long-range interactions dominate development. We show mathematically that orientation-selective long-range connectivity can mediate the required interactions. Our results suggest that self-organization has canalized the evolution of the neuronal circuitry underlying orientation preference maps into a single common design. (Abstract, 1113)

We conclude that wherever such complex biological systems unfold, especially in the mammalian brain where they are likely to abound, the principles of dynamical network self-organization may design and constrain system behavior as powerfully as an organisms genetic endowment or early life experiences. (1116)

Kashtan, Padav and Uri Alon. Spontaneous Evolution of Modularity and Network Motifs. Proceedings of the National Academy of Sciences. 102/13773, 2005. Another example of how new understandings of evolution by way of complexity theory can identify a universally emergent structure and dynamics.

Biological networks have an inherent simplicity: they are modular with a design that can be separated into units that perform almost independently. Furthermore, they show reuse of recurring patterns termed network motifs. (13773)

Keil, Petr, et al. Macroecological and Macroevolutionary Patterns Emerge in the Universe of GNU/Linux Operating Systems. Ecography. 41/11, 2018. When we first posted this section in the early 2000s, any notice of environmental regularities was sparsely evident. In these later 2010s, eight European theoretical ecologists based at the German Centre for Intergrative Biodiversity Research, Leipzig not only aver their wide, constant presence, indeed an untangled bank, but go on to find a cross-affinity with computer software. A true universality across nature’s diversities is becoming patently apparent. See also Evolution in the Debian GNU/Linux Software Network: Analogies and Differences with Gene Regulatory Networks by Pablo Villegas, et al in the Journal of the Royal Society Interface (February 2020) which cites this paper.

What leads to classically recognized patterns of biodiversity remains an open question. Here, we employ analogies between GNU/Linux operating systems, and biodiversity. We demonstrate that patterns of the Linux universe generally match macroecological patterns. Moreover, the composition of functional traits (software packages) exhibits significant phylogenetic signal. The emergence of macroecological patterns across Linux suggests that the patterns are produced independently of the system identity, which points to the possibility of non‐biological drivers of fundamental biodiversity patterns. (Abstract excerpt)

To explain these patterns, we can invoke uniquely ecological and evolutionary processes: the patterns could be an outcome of assembly rules, natural selection, behavior, species interactions, or interplay between specific functional traits and environments. However, it has been demonstrated that some of the patterns are not unique to ecological and evolutionary systems, and often emerge in other complex systems. Examples are: species‐abundance distributions of music festival setlists, frequency distributions of components of software, latitudinal gradients of language diversity, species–area relationships in corporations, industrial codes, and minerals. However, structural constraints are not the only way that biological and non‐biological systems can resemble one another – similarity may also arise from analogous underlying processes. (2)

Kelso, Scott and David Engstrom. The Complementary Nature. Cambridge: MIT Press, 2006. This unique work is mainly noted in Current Vistas and by an extensive review in Recent Writings. An important, overdue statement of this obvious universal quality which is a main theme of this website.

Khaluf, Yara, et al. Scale Invariance in Natural and Artificial Collective Systems. Journal of the Royal Society Interface. Online November, 2017. From General systems theory in the 1960s and before, the Santa Fe Institute in the 1980s, unto this site going online in 2004, the hope and goal has been a common, code-like, form and flow that recurs in kind everywhere. Here complex bioinformatics theorists Khaluf and Pieter Simoens, Ghent University, Eliseo Ferrante, KU Leuven Belgium and Cristian Huepe, Northwestern University provide a deep and wide affirmation. From physical nature to human cultures and in between, an iconic fractal-like, self-organizing, network dynamics is recurrent effect as an exemplary presence. An aspect is its tendency to reach a critical state between discrete individuals and a communal whole, e.g. biofilms, brains and flocks. The authors then begin to consider ways to apply these findings for a better, viable society and technology. And if to reflect at this late day, here is an epochal, salutary discovery coming together in our midst due to worldwise humankinder. In the long arc of uniVerse to humanVerse evolution, nature’s procreative code may pass to our sentient, palliative and creative, intention.

Self-organized collective coordinated behaviour is an impressive phenomenon, observed in a variety of natural and artificial systems, in which coherent global structures or dynamics emerge from local interactions between individual parts. If the degree of collective integration of a system does not depend on size, its level of robustness and adaptivity is typically increased and we refer to it as scale-invariant. In this review, we first identify three main types of self-organized scale-invariant systems: scale-invariant spatial structures, scale-invariant topologies and scale-invariant dynamics. We then provide examples of scale invariance from different domains in science, describe their origins and main features and discuss potential challenges and approaches for designing and engineering artificial systems with scale-invariant properties. (Abstract)

Khovanov, Igor, et al. Editorial. European Physical Journal Special Topics. 222/10, 2013. An introduction to an issue on Nonlinear Dynamics of Deterministic and Stochastic Systems: Unraveling Complexity. And again a standard format for articles of this kind is held to by first citing how every realm from stellar to snail are now known to exemplify this emergent phenomena. With this place, a revitalized systems physics can be sighted as quite morphing into a true cosmic biology.

From the dynamics of the solar system to the functioning of the nerve cell of a snail, nonlinear phenomena are related to some of the most intriguing features of the world around us. In the form of self-sustained oscillations, synchronization, bifurcations, pattern formation, and chaos, nonlinear dynamic phenomena are manifest in physical, chemical, ecological and biological systems. Life itself is characterized by the large number of mutually interacting rhythmic processes it sustains. Nonlinear dynamic phenomena are also important for many types of engineering systems, and the same type of phenomena may be involved in the generation of complex forms of economic and managerial dynamics. (1)

Investigation of the complex dynamic phenomena that can arise in all of these different circumstances help us to get a deeper understanding of the mechanisms underlying a broad range of important problems that, for lack of a proper theoretical framework, were inaccessible for many years and, hence, considered as irrelevant or poorly posed. At the same time the study of nonlinear dynamic phenomena has proved to challenge several classical concepts in physics and mathematics. (1)

Kim, Hyunju, et al. Universal Scaling Across Biochemical Networks of Earth. Science Advances. 5/eaau0149, 2019. This Arizona State University based team, herein HK, Harrison Smith, Cole Mathis, Jason Raymond and Sara Walker, contribute to a flow of papers which lately seem to be closing on, as the extended quotes say, an ability to discern and quantify a common, iterative recurrence from the physical cosmos to chemistry, biology, psychology, cultures and onto the Earth’s biosphere. A prime feature is the formation of generic network activities, along with scale-invariant phase transitions, autocatalytic processes and hierarchical self-organization. As a result, a specific affinity can be drawn between individuals and ecosystems.

The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes, and 8,658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, and the biosphere as a whole. Taken together our results point to a deeper level of organization in biochemical networks than what has been understood so far. (Abstract excerpt)

There is increasing interest in whether biology is governed by general principles, rather than chemical instantiation or evolutionary contingency. Such principles would be strong candidates for being universal to all life. Universal biology, if it exists, would have important implications for our search for life beyond Earth, for engineering synthetic life in the lab, and for solving the origin of life. So far, systems biology has primarily focused on specific levels of organization within biological hierarchies, such as individual organisms or ecological communities, and is rarely applied to the biosphere as a whole. But, biology exhibits some of its most striking regularities moving up in levels from individuals to ecosystems, and these regularities may ultimately manifest at the level of the biosphere. (1-2)

In order to explore regularities within and between levels of organization, we adopt a network view of biochemistry by constructing reaction networks from genomic and metagenomic data. We show that biochemical networks share universal properties characterized by scaling laws for topology and biochemical diversity. These scaling relations exist independent of evolutionary domain of organization, applying across the nested hierarchy of individuals, ecosystems, and the biosphere. Our results provide a first quantitative application of network theory at a planetary scale that can uncover properties and be predictive of major divisions within a given level. (2)

Koonin, Eugene. Are There Laws of Genome Evolution? PLoS Computational Biology. 7/8, 2011. As now broadly evident, as documented herein, life from cosmos to cities seems to be graced by repetitive, similar nonlinear patterns and processes in manifest effect everywhere. A NIH bioinformatician, geneticist, and author, ponders whether this ubiquitous presence, as apparent in cellular protoplasm, would in fact imply and arise from a realm of independent natural principles. In lieu of more review, the gist of these insights is well conveyed by extended excerpts. See also Koonin’s new book The Logic of Chance: The Nature and Origin of Biological Evolution (Financial Times Press, 2011).

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law–like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics…. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. (Abstract, 1)

The most conspicuous universals include: log-normal distribution of the evolutionary rates between orthologous genes; power law–like distributions of membership in paralogous gene families and node degree in biological ‘‘scale-free’’ networks; negative correlation between a gene’s sequence evolution rate and expression level (or protein abundance); distinct scaling of functional classes of genes with genome size. (1)

The universality of these dependencies appears genuinely surprising. For example, the distributions of sequence evolution rate of orthologous genes are virtually indistinguishable in all evolutionary lineages for which genomic data are available, including diverse groups of bacteria, archaea, and eukaryotes. The shape of the distribution did not perceptibly change through about 3.5 billion years of the evolution of life even though the number of genes in the compared organisms differs by more than an order of magnitude, and the repertoires of gene functions are dramatically different as well. The same conundrum pertains to the other universals: despite major biological differences between organisms, these quantitative regularities hold, often to a high precision. What is the nature of the genomic universals? Do they reflect fundamental ‘‘laws’’ of genome evolution or are they ‘‘just’’ pervasive statistical patterns that do not really help us understand biology? (1)

Networks have become ubiquitous images and tools of systems biology. Indeed, any class of interacting objects can be naturally represented by nodes, and the interactions between these objects, regardless of their specific nature, can be represented by edges. (3) These networks are said to be scale-free because the shape of their node degree distribution remains the same regardless of the chosen scale, that is, any subnetwork is topologically similar to the complete network (in other words, scale-free networks display fractal properties). (3) Collectively, the ability of simple models to generate the universals of genome evolution and additional results indicating that the global architecture of biological networks is not a selected feature suggest that all evolutionary universals are not results of adaptive evolution. (3)

Kovacs, Istvan, et al. Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics. PLoS One. 5/9, 2010. In this 100 page entry with bioinformatic programs and references, Semmelweis University, Budapest, living system scientists, including Peter Csermely, parse modular networks to uncover a ubiquitous topological feature. Indeed, nature seems intent on forming communal groupings of an appropriate size and populace at each and every strata and instance. Might one even broach an “ubuntu Universe.”

Background: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics.

Labra, Fabio, et al. Scaling Metabolic Rate Fluctuations. Proceedings of the National Academy of Sciences. 104/10900, 2007. Another example of an international collaboration from Chile and the United States, which again reports general principles and topologies, in this case for metabolism dynamics, that hold across 71 individual types from 25 vertebrate species including reptiles, birds, and mammals. Once more deep in the primary literature, a cerebral humankind goes on to describe and discover an organic natural genesis graced by the same recurrent phenomena at each stage and instance.

Complex ecological and economic systems show fluctuations in macroscopic quantities such as exchange rates, size of companies or populations that follow non-Gaussian tent-shaped probability distributions of growth rates with power-law decay, which suggests that fluctuations in complex systems may be governed by universal mechanisms, independent of particular details and idiosyncrasies. We propose here that metabolic rate with individual organisms may be considered as an example of an emergent property of a complex system and test the hypothesis that the probability distribution of fluctuations in the metabolic rate of individuals has a “universal” form regardless of body size or taxonomic affiliation. (10900)

Laurienti, Paul, et al. Universal Fractal Scaling of Self-Organized Networks. Physica A. 390/20, 2011. After some two decades of complex systems studies from every angle, in disparate fields and terms, on every continent, a maturity is lately being reached so it is possible, for example, for this team of Wake Forest University biomedical researchers to propose a natural “universality” of “node and interaction” dynamic network phenomena. To wit, the same fractal pattern and process faithfully recurs across broad Biological, Information, Social, and Technological domains. These extended quotes might portend, circa 2011, a new animate nature suffused with intrinsic creativities that repeat and reiterate across every regnant realm. At what point, and by what insight, might this realization become a revolution, and its spontaneity be appreciated as genetic in kind?

There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consisting of interconnected nodes, are often self-organized, naturally emerging without any overarching designs on topological structure yet enabling efficient interactions among nodes. Here we show that the number of nodes and the density of connections in such self-organized networks exhibit a power law relationship. We examined the size and connection density of 47 self-organizing networks of various biological, social, and technological origins, and found that the size-density relationship follows a fractal relationship spanning over 6 orders of magnitude. This finding indicates that there is an optimal connection density in self-organized networks following fractal scaling regardless of their sizes. (Abstract, 1)

The findings reported here demonstrate a universal relationship in self-organized networks such that the network size dictates the density. The fractal behavior observed is of particular interest because it indicates that self-organized networks are critically organized. The number of connections within each network is scaled to the size of the network, and this universal behavior likely represents an optimal organization that ensures maximal capacity as a minimal cost. (4-5) We show an important, apparently universal feature of self-organized networks: fractal of size and density connections. This fractal scaling is independent of network types, as the analysis spanned a wide gamut of networks, including biological, information, social, and technological. Thus, it appears that there is an underlying principle to organizing these self-emergent networks, a principle that probably ensures optimal network functioning. (Conclusion, 5)

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