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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VI. Earth Life Emergence: Development of Body, Brain, Selves and Societies

A. A Survey of Common Principles

Schuster, Peter. Nonlinear Dynamics from Physics to Biology. Complexity. 12/4, 2007. The Austrian editor-in-chief of this journal perceives the self-organization paradigm to now reach a broad acceptance across the scientific disciplines and rightly apply to human intention. This article was prompted by the 2006 conference of the European Complex Systems Society, check their website for more such info.

Sigaki, Higor, et al. History of Art Paintings through the Lens of Entropy and Complexity. Proceedings of the National Academy of Sciences. 115/E8585, 2018. Akin to how Nakamura and Kaneko (above) find nonlinear patterns amongst musical compositions, systems physicists Sigaki and Haroldo Ribeiro, Univerisidade Estadual de Maringa, Brazil and Matjaz Perc, University of Maribor, Slovenia discern the presence of intrinsic recurrent forms across a wide array (over fifty) of artistic schools from Romanticism to Art-Deco.

Art is the ultimate expression of human creativity that is deeply influenced by the philosophy and culture of the corresponding historical epoch. Here, we present a large-scale quantitative analysis of almost 140,000 paintings, spanning nearly a millennium. Based on local spatial patterns in the images of these paintings, we estimate the permutation entropy and the statistical complexity. These measures map the degree of visual order of artworks into a scale of order–disorder and simplicity–complexity. The dynamical behavior of these measures reveals a clear temporal evolution of art, marked by transitions that agree with the main historical periods of art. Our research shows that different artistic styles have a distinct average degree of entropy and complexity, thus allowing a hierarchical organization and clustering of styles. (Abstract excerpt)

Singh Sandhu, Kuljeet, et al. Large-Scale Functional Organization of Long-Range Chromatin Interaction Networks. Cell Reports. Vol. 2/Pg. 1207, 2012. “Chromatin is the combined DNA and proteins that make up the nucleus of a cell.” Various headings are Chromatin Communities Organize Functional Compartmentalization, Transcription-Associated Chromatin Interactions Form a Complex Hierarchical Network, Chromatin Communities are Evolutionarily Constrained. In this new online journal from Cell Press, 17 co-authors from Singapore, India, Australia, Croatia, USA, and Hungary, perceive in self-organizing genomes an innate propensity to form into invariant, communally nested networks. This paper could be paired with “Community Landscapes,” Istvan Kovacs, et al, herein, with Peter Csermely listed on both, because they realize that this lively phenomena is an iconic exemplar of nature’s universal sustainable reciprocity of agency and communion.

Chromatin interactions play important roles in transcription regulation. To better understand the underlying evolutionary and functional constraints of these interactions, we implemented a systems approach to examine RNA polymerase-II-associated chromatin interactions in human cells. We found that 40% of the total genomic elements involved in chromatin interactions converged to a giant, scale-free-like, hierarchical network organized into chromatin communities. The communities were enriched in specific functions and were syntenic (see next) through evolution. Altogether, our analyses reveal a systems-level evolutionary framework that shapes functionally compartmentalized and error-tolerant transcriptional regulation of human genome in three dimensions. (Summary excerpts)

In classical genetics, synteny describes the physical co-localization of genetic loci on the same chromosome within an individual or species. Today, however, biologists usually refer to synteny as the conservation of blocks of order within two sets of chromosomes that are being compared with each other. This concept can also be referred to as shared synteny. (Wikipedia)

Smith, Eric and Harold Morowitz. Universality in Intermediary Metabolism. Proceedings of the National Academy of Sciences. 101/13168, 2004. The stoichiometry, energetics, and reaction concentration dependence of the reductive tricarboxylic acid cycle, via its network and autocatalytic properties, is proposed as a primordial metabolic core.

Widespread or universal structures and processes in cellular biochemistry are central to a coherent understanding of life, much as universality in physics has become central to understanding order in condensed-matter systems. (13168)

Sole, Ricard and Sergi Valverde. Macroevolution in Silico: Scales, Constraints and Universals. Santa Fe Institute Working Papers. 12-11-019, November, 2012. Barcelona systems biologists continue their project to gain quantified insights into life’s iterative, sequential advance into somatic and behavioral complexities.

Large-scale evolution involves several layers of complexity spanning multiple scales, from genes and organisms to whole ecosystems. In this paper we review several models involving the macroevolution of artificial organisms, communities or ecosystems, highlighting their importance and potential role in expanding the modern synthesis. Afterwards, we summarize the key results obtained from our model of artificially evolved ecosystems where individuals are defined as embodied entities within a physical, simulated world where they can evolve different traits and exploit multiple resources. Starting from an initial state where single cells with identical genotypes are present, the system evolves towards complex communities where the feedbacks between population expansion, evolved cell adhesion and the structure of the environment leads to a major innovation resulting from the emergence of ecosystem engineering. The tempo and mode of this process illustrates the relevance in considering a physical embedding as part of the model description, and the feedbacks between different scales within the evolutionary hierarchy. (Abstract)

The existence of universal trends in large scale evolution might seem a rather bold idea. In the end, the paths followed by evolutionary trajectories are tangled and seem unique. Even so, convergent dynamics might be widespread. Such convergence is in itself a major component of evolution. Convergence is also a mark of universality and the common laws pervading the physics of adhesion or diffusion are likely to constrain potential pattern forming mechanisms. Disparate systems often display very common traits (particularly in their large scale patterns) associated with universal properties of the underlying dynamics.

Song, Chaoming, et al. Self-Similarity of Complex Networks. Nature. 433/392, 2005. The power-law scaling which distinguishes small world networks is found to exhibit a self-repeating fractal geometry. This is achieved by a renormalization procedure that ‘coarse-grains’ the system into a nest of nodes and modules. This novel work is introduced by Steven Strogatz in the same issue (365) with the title Romanesque Networks since this property is ideally displayed by broccoli of this name.

Here we show that real complex networks, such as the world-wide web, social, protein-protein interaction networks and cellular networks are invariant or self-similar under a length-scale transformation. (392) These fundamental properties help to explain the scale-free nature of complex networks and suggest a common self-organization dynamics. (392)

Stanley, Eugene. Universality and Scale Invariance: Organizing Principles that Transcend Disciplines. www.societyforchaostheory.org/conf2003/abstracts.html. A keynote paper presented at the annual Society for Chaos Theory and Psychology Conference. The Boston University systems physicist describes how the same power-law behavior is being found in widely diverse realms from statistical physics to the “econophysics” of financial markets.

Stephens, Greg, et al. Searching for Simplicity: Approaches to the Analysis of Neurons and Behavior. arXiv:1012.3896. Posted in December 2010. By virtue of such many advances as this site tries to report, we altogether seem at the edge of some revelatory evidence, closer to history’s great secret answer. Geneticist Stephens and physicist William Bialek, Princeton University, and neurobiologist Leslie Osborne, University of Chicago, enter still another glimpse of constant analogs across widely diverse phenomena, ever suggestive of an implicate, iterative, genome-like source.

What fascinates us about animal behavior is its richness and complexity, but understanding behavior and its neural basis requires a simpler description. An alternative is to ask whether we can search through the dynamics of natural behaviors to and explicit evidence that these behaviors are simpler than they might have been. We review two mathematical approaches to simplification, dimensionality reduction and the maximum entropy method, and we draw on examples from different levels of biological organization, from the crawling behavior of C. elegans to the control of smooth pursuit eye movements in primates, and from the coding of natural scenes by networks of neurons in the retina to the rules of English spelling. In each case, we argue that the explicit search for simplicity uncovers new and unexpected features of the biological system, and that the evidence for simplification gives us a language with which to phrase new questions for the next generation of experiments. The fact that similar mathematical structures succeed in taming the complexity of very different biological systems hints that there is something more general to be discovered. (Abstract)

Strassmann, Joan, et al. In the Light of Evolution V: Cooperation and Conflict. Proceedings of the National Academy of Sciences. Supplement 2, 2011. With co-authors David Queller, John Avise, and Francisco Ayala, an Introduction to this edition in the title series in search and support of an evolutionary vision, namely in the light of Theodosius Dobzhansky. We note in this section to record its witness of a universal principle, in this case a creative tension or union between entity and group, autonomy and assembly, that spans life’s emergence. Papers cover selfish and cooperative genes, bacterial symbiosis, kinship in social insects, animal troops, hominid clans, and onto human adaptations via collective learning.

Swarup, Samarth and Les Gasser. Unifying Evolutionary and Network Dynamics. Physical Review E. 75/066114, 2007. University of Illinois computer scientists propose that the two realms noted in the article share common features and that a cross-fertilization between them would be beneficial.

Szabo, Gyorgy and Gabor Fath. Evolutionary Games on Graphs. Physics Reports. 446/4-6, 2007. An extensive tutorial on game theory as seen from a statistical physics viewpoint, which could be viewed as another encounter with, in translation, nature’s non-equilibrium, agent-based, self-organizing emergence.

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games. (97)

Tao, Terence. E pluribus unum: From Complexity, Universality. Daedalus. 141/3, 2012. In a special issue on Science in the 21st Century, the UCLA polymathematician draws on the latest statistical physics to at last confirm this extant Nature is in fact grounded in and distinguished by an intelligible, recurrent, programmatic quality. Whatever the material realm or substrate the same phenomenal organization appears due to the constant interactions of many communicative entities. As a result, it becomes strongly evident that such an independent formative source or agency must be involved. And how could one not notice, quite fittingly, here anew is the very essence of our archetypal Taoist wisdom.

In this brief survey, I discuss some examples of the fascinating phenomenon of universality in complex systems, in which universal macroscopic laws of nature emerge from a variety of different microscopic dynamics. This phenomenon is widely observed empirically, but the rigorous mathematical foundation for universality is not yet satisfactory in all cases. (Abstract, 23)

A remarkable phenomenon often occurs once the number of components becomes large enough: that is, the aggregate properties of the complex system can mysteriously become predictable again, governed by simple laws of nature. Even more surprising, these macroscopic laws for the overall system are often largely independent of their microscopic counterparts that govern the individual components of that system. One could replace the microscopic components by completely different types of objects and obtain the same governing law at the macroscopic level. When this occurs, we say that the macroscopic law is universal. The universality phenomenon has been observed both empirically and mathematically in many different contexts, several of which I discuss below. In some cases, the phenomenon is well understood, but in many situations, the underlying source of universality is mysterious and remains an active area of mathematical research. (24)

The law of large numbers is one of the simplest and best understood of the universal laws in mathematics and nature, but it is by no means the only one. Over the decades, many such universal laws have been found to govern the behavior of wide classes of complex systems, regardless of the components of a system or how they interact with each other. (25) That the macroscopic behavior of a large, complex system can be almost totally independent of its microscopic structure is the essence of universality. (25)

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