IV. Ecosmomics: Independent Complex Network Systems, Computational Programs, Genetic Ecode Scripts

1. Network Physics: A Vital Interlinked Anatomy and Physiology

Arenas, Alex and Manlio De Domenico. Nonlinear Dynamics on Interconnected Networks. Physica D. 323-324/3, 2016. An introduction to a special issue on the latest finesses of ubiquitous, animate network properties. Some entries are Cascades in Interdependent Flow Networks, Random Walk Centrality in Interconnected Multilayer Networks, and On Degree-Degree Correlations in Multilayer Networks.

Arora, Viplove and Mario Ventresca. Action-Based Modeling of Complex Networks. Nature Scientific Reports. 7/6673, 2017. Purdue University engineers advance a better generic method to analyze and design real-world interconnective systems, which is shown to apply across a wide range of applications from airports, power grids, and social media to neural and protein webs. See Csoma, et al herein for a similar 2017 take.

Complex networks can model a wide range of complex systems in nature and society, and many algorithms (network generators) capable of synthesizing networks with few and very specific structural characteristics (degree distribution, average path length, etc.) have been developed. However, there remains a significant lack of generators capable of synthesizing networks with strong resemblance to those observed in the real-world, which can subsequently be used as a null model, or to perform tasks such as extrapolation, compression and control. In this paper, a robust new approach we term Action-based Modeling is presented that creates a compact probabilistic model of a given target network, which can then be used to synthesize networks of arbitrary size. (Abstract)

Artime, Oriol, et al. Multilayer Network Science: from Cells to Societies. arXiv:2401.04589. Ten physicists posted across Italy and Spain including Arsham Ghavasieh and Manlio De Domenico (search names) provide a latest theoretical review and preview as this 21st century, 2010s to date, revolution all about nature’s apparent anatomy and physiology becomes vividly evident across every animate phase from prokaryotes to peoples. See also Robustness and resilience of complex networks by this team in Nature Reviews Physics (January 2024).

Network structures are mathematical way to represent life’s complex systems from cells to societies. In the past decade, multilayer network science was found to be an effective analytical framework for a wide spectrum from biopolymer interactome and metabolomes to neuronal connectomes to urban and transportation regimes. Here we review salient theoretical aspects of functional dynamics and their applications to real-world interdependent phenomena. We discuss corresponding challenges in the field for the future. (Abstract)

Aste, Tomaso, et al. Complex, Inter-Networked Economic and Social Systems. European Physical Journal Special Topics. 225/10, 2016. n introduction to this subject issue as the ubiquitous presence of generic network phenomena becomes found in every cultural aspect. Papers vary from generic features in Discretized Kinetic Theory on Scale-Free Networks, and On the Convergence of the Fitness-Complexity Algorithm to practical examples in A Generation-Attraction Model for Renewable Energy Flows in Italy, and Interests Diffusion on a Semantic Multiplex.

Baccini, Frederica, et al.. Similarity Matrix Average for Aggregating Multiplex Networks. Journal of Physics: Complexity. 4/025017, 2023. University of Pisa, Siena and Torinl bioinformatic scientists conceive a tested approach to join and unify an array of social interactivities into a unified strata.

We introduce a novel method of average similarity matrices so as to integrate the layers of a multiplex network into a single monoplex form. Multiplex networks are used when relations of different nature (layers) arise between a set of elements from a given population (nodes). A way to analyze them is to aggregate the different layers in a single monoplex as a valid representation. Here we propose a theoretical approach and practical usage based on a similarity matrix average. This method is then applied to the Cambridge Journal of Economics contain co-citations, issue editors and article authors.

Bagrow, James and Dirk Brockmann. Natural Emergence of Clusters and Bursts in Network Evolution. Physical Review X. 3/021016, 2013. We cite this entry by Northwestern University mathematicians as a quantification of what seems to be a universal source of self-organizing, complex adaptive systems that exists on their independent own, as they manifest everywhere from cosmos to culture.

Baptista, Anthony, et al. Mining higher-order triadic interactions. arXiv:2404.14997. Into this year, Queen Mary University of London, Alan Turing Institute, Central European University, Vienna, University of Southampton, UK, and Potsdam Institute for Climate Impact Research system theorists including Ginestra Bianconi, and Jurgen Kurths exemplify how vast and richly adorned nature’s network anatomy and physiology really is by still finding further multiplex dimensions.

Complex systems often present higher-order interactions which require us to go beyond their description in terms of pairwise networks. Triadic interactions are a fundamental type of higher-order interaction that occurs when one node regulates the interaction between two other nodes. Triadic interactions are a fundamental type of higher-order networks, found in a large variety of biological systems from neuron-glia to gene-regulation and ecosystems. In this article, a theoretical principle is used to model and mine this triune phase from node metadata, which is applied to Acute Myeloid Leukemia. Our work reveals higher-order properties which to advance our understanding of complex systems ranging from biology to the climate. (Excerpt)

Barabasi, Albert-Laszlo. Linked: The New Science of Networks. Cambridge, MA: Perseus Books, 2002. In the past few years, sparked by this University of Notre Dame physicist and colleagues, a significant finding has been made that complex networks are not random geometries but exhibit a nested, scale-free topology of how their nodes (agents) and links (local relations) are interconnected and weighted. A well-written story of nested, dynamic natural networks of great consistency everywhere from genes to galaxies and especially the World Wide Web. (This review was written a decade ago. Since this early work by its main founder, as this section attests natural networks abound and connect everywhere in an intricate cosmos.)

A string of recent breathtaking discoveries has forced us to acknowledge that amazingly simple and far-reaching natural laws govern the structure and evolution of all the complex networks that surround us. (6) Taken together, the similar large-scale topology of the metabolic and the protein interaction networks indicate the existence of a high degree of harmony in the cell’s architecture: Whichever organizational level we examine, a scale-free topology greets us. (189)

Barabasi, Albert-Laszlo. Love is All You Need. https://www.barabasilab.com/post/love-is-all-you-need. The co-conceiver (search) of scale-free networks in the late 1990s and their prolific advocate and articulator as they were found everywhere in nature and society writes a rebuttal to a Scale Free Networks are Rare posting at arXiv:1801.03400. The six page statement is also a succinct survey of the revolutionary endeavor and how pervasive this universal mode of multiplex nodes and linkages actually has proven to be.

Barabasi, Albert-Laszlo. Network Science: From Structure to Control. www.physics.umass.edu/seminars. A departmental colloquium at the University of Massachusetts, Amherst on October 30, 2015 by the main founder of this scale-free natural topology from proteins to people. Presently at Northeastern University, he has several international postings and many collaborations. Google “Barabasi Lab” for activities, publications, and Nature Physics papers such as The Network Takeover (Jan. 2012) and Universality in Network Dynamics (Oct. 2013). A salutary discovery may lately be realized from these worldwide theoretical and practical studies over the past 15 years. A generic geometry and dynamics is established with archetypal node elements and link connections within a whole modular system, which is found to repeat in kind from cosmos to culture. As one views the now familiar images of complementary nodes and links, however could this 21st century paradigm revise national politics which are locked in a battle of node and link parties?

Systems as diverse as the world wide web, Internet or the cell are described by highly interconnected networks with amazingly complex topology. Recent studies indicate that these networks are the result of self-organizing processes governed by simple but generic laws, resulting in architectural features that makes them much more similar to each other than one would have expected by chance. I will discuss the order characterizing our interconnected world and its implications to network robustness, and control. Indeed, while control theory offers mathematical tools to steer engineered and natural systems towards a desired state, we lack a framework to control complex self-organized systems. I will discuss a recently developed analytical framework to study the controllability of an arbitrary complex directed network, identifying the set of driver nodes whose time-dependent control can guide the system’s dynamics. (Abstract)

Barabasi, Albert-Laszlo. The Network Takeover. Nature Physics. 8/1, 2012. In a special stock-taking Complexity section, the Northeastern University, Center for Complex Network Research, physicist and founder from the late 1990s, with many colleagues, of the theory of scale-free networks across nature and society advances this scenario as the true essence of nonlinear phenomena.

Born at the twilight of the twentieth century, network theory aims to understand the origins and characteristics of networks that hold together the components in various complex systems. By simultaneously looking at the World Wide Web and genetic networks, Internet and social systems, it led to the discovery that despite the many differences in the nature of the nodes and the interactions between them, the networks behind most complex systems are governed by a series of fundamental laws that determine and limit their behaviour. (15)

Reductionism deconstructed complex systems, bringing us a theory of individual nodes and links. Network theory is painstakingly reassembling them, helping us to see the whole again. One thing is increasingly clear: no theory of the cell, of social media or of the Internet can ignore the profound network effects that their interconnectedness cause. Therefore, if we are ever to have a theory of complexity, it will sit on the shoulders of network theory. (15)

Barrat, Alain, et al. Complex Networks: From Biology to Information Technology. Journal of Physics A: Mathematical and Theoretical. 41/22, 2008. An introduction to the proceedings of a July 2007 STATPHYS23 meeting on the subject which then divides into two main categories – their common Structure and Dynamics, and ubiquitous Biological, Social, and Technological applications. See Porter, et al below for more on this genesis nature.

Previous   1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10  Next  [More Pages]