(logo) Natural Genesis (logo text)
A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
Table of Contents
Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
Recent Additions

IV. Cosmomics: A Genomic Source Code in Procreative Effect

Biocomplexity Institute. http://www.indiana.edu/~bioc/. Accessed June 2011, this is an interdisciplinary endeavor of Indiana University at the leading edge of these lively sciences. Biophysicist James Glazier is director, members include biophysicist John Beggs, information visionary Katy Borner, psychologist Robert Goldstone, Allessandro Flammini and Luis Rocha, bioinformatics, and neuroscientist Olaf Sporns. We quote the Institute’s main definition, along with a statement for Goldstone’s Percepts and Concepts Laboratory, as they convey this revolutionary engagement with and discovery of a radical genesis nature.

Biocomplexity is the study of the emergence of self-organized, complex behaviors from the interaction of many simple agents. Such emergent complexity is a hallmark of life, from the organization of molecules into cellular machinery, through the organization of cells into tissues, to the organization of individuals into communities. The other key element of biocomplexity is the unavoidable presence of multiple scales. Often, agents organize into much larger structures; those structures organize into much larger structures, etc. A classic example is the primary, secondary, tertiary, and quaternary folding of DNA into chromosomes that allows a strand of a length of several centimeters to fold, without tangling or losing function, into a chromosome about one micron long. Biocomplexity is a methodology and philosophy as well as a field of study. It focuses on networks of interactions and the general rules governing such networks.

Typically, complex adaptive system models are applied to natural phenomena, such as the pattern of stripes on zebras or seeds on sunflowers. Our research goal is to apply these models to understanding how individual people learn and perceive, and how groups of people organize themselves into emergent structures which none of the individuals in the group may understand or even perceive. Our laboratory is currently exploring interactions between perceptual and conceptual learning, methods for learning abstract concepts using computer simulations, the perception of similarity and analogy, and group behavior from a complex systems perspective. Our typical modus operandi is to simultaneously conduct psychological experiments on humans and develop computational models of the observed behavior. The results from the experiments help to constrain and inform our computational models, and the computational models serve to organize and explain our empirical results. (R. Goldstone)

Center for Models of Life. www.cmol.nbi.dk. A graphically informative website for this endeavor located at the Niels Bohr Institute, University of Copenhagen and directed by Kim Sneppen. Research is pursued such areas as: Physics of Gene Regulation, Models of Biological Circuits, Networks and Communication, and Evolution and Dynamical Systems, each with referenced publications. If our extant nature from cell to city is found to exhibit these pervasive innate and invariant phenomena, by what sufficient proof, might it prompt and allow us to realize a greater genesis?

Complexity Digest. www.comdig.org. Founded by the late Gottfried Mayer, the present Editor-in-Chief is Carlos Gershenson who with international collaborators and audience, suggest and post new citations apropos the wavefront of the complex systems revolution. The engaging site enters the latest advances in articles, books, presentations and conferences, along with university programs, and more. Complexity Digest represents a premier resource for learning about and keeping up with the frontiers of a self-organizing universe and sustainable future.

New England Complex Systems Institute. www.necsi.org. Founded and run by systems scholar Yaneer Bar-Yam and colleagues, this multifaceted site is a rich resource for general and specific content all about the nonlinear systems revolution from evolution to economies. The group has run a biannual International Conference on Complex Systems in the Boston area since the late 1990s. I went to four of these incredible events to which luminaries such as Edward Lorenz, Stephen Wolfram, Stuart Kauffman, Gene Stanley, and everyone else it seems presents or attends. The Proceedings for the 2011 gala are accessible from the home page, click ICCS under Events.

The New England Complex Systems Institute (NECSI) is an independent academic research and educational institution with students, postdoctoral fellows and faculty. In addition to the in-house research team, NECSI has co-faculty, students and affiliates from MIT, Harvard, Brandeis and other universities nationally and internationally.

NECSI has been instrumental in the development of complex systems science and its applications. We study how interactions within a system lead to its behavioral patterns, and how the system interacts with its environment. Our new tools overcome the limitations of classical approximations for the scientific study of complex systems, such as social organizations, biological organisms and ecological communities. NECSI's unified mathematically-based approach transcends the boundaries of physical, biological and social sciences, as well as engineering, management, and medicine (see Complex Systems Resources).

NECSI research advances fundamental science and its applications to real world problems, including social policy matters. NECSI researchers study networks, agent-based modeling, multiscale analysis and complexity, chaos and predictability, evolution, ecology, biodiversity, altruism, systems biology, cellular response, health care, systems engineering, negotiation, military conflict, ethnic violence, and international development. (see NECSI Research).

NECSI conducts classes, seminars and conferences to assist students, faculty and professionals in their understanding of complex systems. NECSI sponsors postdoctoral fellows, provides research resources online, and hosts the International Conference on Complex Systems. Through its education, NECSI strives to contribute to science and the betterment of society (see NECSI Education).

Santa Fe Institute. www.santafe.edu. The original, innovative center since 1984 for the theoretical and practical study of complex, dynamical system insights into natural and social worlds. Typical subject areas include the Physics of Complex Systems, Emergence and Innovation in Evolutionary Systems, Information Processing and Computation in Nature and Society, and Emergence, Organization and Dynamics of Living Systems. For publications, the SFI Bulletin, (e.g., Volume 24, 2009), a long list of Working Papers each year, and under Research, a Bibliography of papers by SFI members cited on the website convey the leading edge of nonlinear studies.

Mission The Santa Fe Institute is a transdisciplinary research community that expands the boundaries of scientific understanding. Its aim is to discover, comprehend, and communicate the common fundamental principles in complex physical, computational, biological, and social systems that underlie many of the most profound problems facing science and society today.

Vision Many of society’s most pressing problems fall far from the confines of disciplinary research. Complex problems require novel ideas that result from thinking about non-equilibrium and highly connected complex adaptive systems. We are dedicated to developing advanced concepts and methods for these problems, and pursuing solutions at the interfaces between fields through wide-ranging collaborations, conversations, and educational programs. SFI combines expertise in quantitative theory and model building with a community and infrastructure able to support cutting-edge, distributed and team-based science. At the Santa Fe Institute, we are asking big questions that matter to science and society.

One of the grand challenges of 21st century science is the search for fundamental principles beyond the genetic code and Darwinian evolutionary process that govern how the complexity of life emerges from its underlying simplicity.

Altmann, G. and Walter Koch, eds. Systems: New Paradigms for the Human Sciences. Berlin: de Gruyter, 1998. A European compendium which situates and contemplates the human phase within a self-developing universe.

Amaral, L. and J. Ottino. Augmenting the Framework for the Study of Complex Systems. European Physics Journal B. 38/2, 2004. An introduction to a special issue on the ubiquitous presence of scale-free dynamic networks from food webs and epidemics to neural phenomena and especially the worldwide Internet. In this regard a generic definition of complex systems is attempted, see the quote below. These elemental units and interactions then self-organize into a universal, nested self-similarity.

A complex system is a system with a large number of elements, building blocks or agents, capable of interacting with each other and with their environment. The common characteristic of all complex systems is that they display organization without any external organizing being applied. The whole is much more than the sum of its parts. (148)

Anderson, Philip. More Is Different - One More Time. N. Phuan Ong and Ravin Bhatt, eds. More Is Different. Princeton: Princeton University Press, 2001. The Nobel laureate physicist revisits his landmark 1967 paper which helped turn science from a fixation on subatomic domains to the complexity revolution.

The actual universe is the consequence of layer upon layer of emergence, and the concepts and laws necessary to understand it are as complicated, subtle and, in some cases, as universal as anything the particle folks are likely to come up with. (7)

Anderson, Philip, et al, eds. Downward Causation. Arrhus, Denmark: Arrhus University Press, 2000. Papers that explore how self-organizing, agent-based systems lead to an increasing influence by ‘higher,’ more consciously informed levels, over lower or prior stages, which is present from physical theory to literary genres.

Aschwanden, Markus, et al. Order Out of Randomness: Self-Organization Processes Astrophysics. arXiv:1708.03394. Reviewed at length in Systems Cosmology, this is an 18 author, 97 page treatise which could be seen as a premier affirmation of an inherently nonlinear, lively, complexifying cosmic genesis.

Ashtiani, Minoo, et al. A System Survey of Centrality Measures for Protein-Protein Interaction Networks. BMC Systems Biology. 12/80, 2018. Our interest in this entry by bioinformatic theorists with postings in Iran and Germany is to record in 2018 how this biochemical domain can be treated by the same multiplex geometries as neural brains. In reflective regard, we peoples may at last be able to confirm the natural presence from quantum and genomic to cerebral and cosmic realms of a node/link, DNA/AND, universe to human image.

Numerous centrality measures have been introduced to identify “central” nodes in large networks. The availability of a wide range of measures for ranking influential nodes leaves the user to decide which measure may best suit the analysis of a given network. The choice of a suitable measure is furthermore complicated by the impact of the network topology on ranking influential nodes by centrality measures. To approach this problem systematically, we examined the centrality profile of nodes of yeast protein-protein interaction networks (PPINs) in order to detect which centrality measure is succeeding in predicting influential proteins. We studied how different topological network features are reflected in a large set of commonly used centrality measures. (Abstract)

Auffray, Charles, et al. Self-organized Living Systems. Philosophical Transactions of the Royal Society of London A. 361/1125, 2003. After centuries of the reductionist method which identified the components of nature, a new biosystemic paradigm is recommended which can integrate the relational dynamics of living entities and processes. In this view, biology is a science of information in a hierarchical flux, formed by a creative balance between order and chaos.

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