Disconnected, Fragmented, or United? A Trans-disciplinary Review of Network Science

Bookmarked Disconnected, Fragmented, or United? A Trans-disciplinary Review of Network Science by César A. HidalgoCésar A. Hidalgo (Applied Network Science | SpringerLink)

Applied Network Science

Abstract

During decades the study of networks has been divided between the efforts of social scientists and natural scientists, two groups of scholars who often do not see eye to eye. In this review I present an effort to mutually translate the work conducted by scholars from both of these academic fronts hoping to continue to unify what has become a diverging body of literature. I argue that social and natural scientists fail to see eye to eye because they have diverging academic goals. Social scientists focus on explaining how context specific social and economic mechanisms drive the structure of networks and on how networks shape social and economic outcomes. By contrast, natural scientists focus primarily on modeling network characteristics that are independent of context, since their focus is to identify universal characteristics of systems instead of context specific mechanisms. In the following pages I discuss the differences between both of these literatures by summarizing the parallel theories advanced to explain link formation and the applications used by scholars in each field to justify their approach to network science. I conclude by providing an outlook on how these literatures can be further unified.

Peter Webb’s A Course in Finite Group Representation Theory

Bookmarked A Course in Finite Group Representation Theory by Peter WebbPeter Webb (math.umn.edu)
Download a pre-publication version of the book which will be published by Cambridge University Press. The book arises from notes of courses taught at the second year graduate level at the University of Minnesota and is suitable to accompany study at that level.

“Why should we want to know about representations over rings that are not fields of characteristic zero? It is because they arise in many parts of mathematics. Group representations appear any time we have a group of symmetries where there is some linear structure present, over some commutative ring. That ring need not be a field of characteristic zero.

Here are some examples.

  • […]
  • In the theory of error-correcting codes many important codes have a non-trivial symmetry group and are vector spaces over a finite field, thereby providing a representation of the group over that field.”
Peter Webb, February 23, 2016, Professor of Mathematics, University of Minnesota
in A Course in Finite Group Representation Theory to be published soon by Cambridge University Press

 

Ten Simple Rules for Taking Advantage of Git and GitHub

Bookmarked Ten Simple Rules for Taking Advantage of Git and GitHub (journals.plos.org)
Bioinformatics is a broad discipline in which one common denominator is the need to produce and/or use software that can be applied to biological data in different contexts. To enable and ensure the replicability and traceability of scientific claims, it is essential that the scientific publication, the corresponding datasets, and the data analysis are made publicly available [1,2]. All software used for the analysis should be either carefully documented (e.g., for commercial software) or, better yet, openly shared and directly accessible to others [3,4]. The rise of openly available software and source code alongside concomitant collaborative development is facilitated by the existence of several code repository services such as SourceForge, Bitbucket, GitLab, and GitHub, among others. These resources are also essential for collaborative software projects because they enable the organization and sharing of programming tasks between different remote contributors. Here, we introduce the main features of GitHub, a popular web-based platform that offers a free and integrated environment for hosting the source code, documentation, and project-related web content for open-source projects. GitHub also offers paid plans for private repositories (see Box 1) for individuals and businesses as well as free plans including private repositories for research and educational use.

Human Collective Memory from Biographical Data

Bookmarked Estimating technological breaks in the size and composition of human collective memory from biographical data (arxiv.org)

The ability of humans to accumulate knowledge and information across generations is a defining feature of our species. This ability depends on factors that range from the psychological biases that predispose us to learn from skillful, accomplished, and prestigious people, to the development of technologies for recording and communicating information: from clay tablets to the Internet. In this paper we present empirical evidence documenting how communication technologies have shaped human collective memory. We show that changes in communication technologies, including the introduction of printing and the maturity of shorter forms of printed media, such as newspapers, journals, and pamphlets, were accompanied by sharp changes (or breaks) in the per-capita number of memorable biographies from a time period that are present in current online and offline sources. Moreover, we find that changes in technology, such as the introduction of printing, film, radio, and television, coincide with sharp shifts in the occupations of the individuals present in these biographical records. These two empirical facts provide evidence in support of theories arguing that human collective memory is shaped by the technologies we use to record and communicate information.

C. Jara-Figueroa, Amy Z. Yu, and Cesar A. Hidalgo
in Estimating technological breaks in the size and composition of human collective memory from biographical data via arXiv

 

Design and Control of Self-organizing Systems

Bookmarked Design and Control of Self-organizing Systems by Carlos Gershenson (scifunam.fisica.unam.mx)

UNAM Mexico City has an available free download of Carlos Gershenson’s 2007 text.

Complex systems are usually difficult to design and control. There are several particular methods for coping with complexity, but there is no general approach to build complex systems. In this book I propose a methodology to aid engineers in the design and control of complex systems. This is based on the description of systems as self-organizing. Starting from the agent metaphor, the methodology proposes a conceptual framework and a series of steps to follow to find proper mechanisms that will promote elements to find solutions by actively interacting among themselves.

Design and Control of Self-organizing Systems by Carlos Gershenson (2007)
Design and Control of Self-organizing Systems by Carlos Gershenson (2007)

Calculating the Middle Ages?

Bookmarked Calculating the Middle Ages? The Project "Complexities and Networks in the Medieval Mediterranean and Near East" (COMMED) [1606.03433] (arxiv.org)
The project "Complexities and networks in the Medieval Mediterranean and Near East" (COMMED) at the Division for Byzantine Research of the Institute for Medieval Research (IMAFO) of the Austrian Academy of Sciences focuses on the adaptation and development of concepts and tools of network theory and complexity sciences for the analysis of societies, polities and regions in the medieval world in a comparative perspective. Key elements of its methodological and technological toolkit are applied, for instance, in the new project "Mapping medieval conflicts: a digital approach towards political dynamics in the pre-modern period" (MEDCON), which analyses political networks and conflict among power elites across medieval Europe with five case studies from the 12th to 15th century. For one of these case studies on 14th century Byzantium, the explanatory value of this approach is presented in greater detail. The presented results are integrated in a wider comparison of five late medieval polities across Afro-Eurasia (Byzantium, China, England, Hungary and Mamluk Egypt) against the background of the {guillemotright}Late Medieval Crisis{guillemotleft} and its political and environmental turmoil. Finally, further perspectives of COMMED are outlined.

Network and Complexity Theory Applied to History

This interesting paper (summary below) appears to apply network and complexity science to history and is sure to be of interest to those working at the intersection of some of these types of interdisciplinary studies. In particular, I’d be curious to see more coming out of this type of area to support theses written by scholars like Francis Fukuyama in the development of societal structures. Those interested in the emerging area of Big History are sure to enjoy this type of treatment. I’m also curious how researchers in economics (like Cesar Hidalgo) might make use of available(?) historical data in such related analyses. I’m curious if Dave Harris might consider such an analysis in his ancient Near East work?

Those interested in a synopsis of the paper might find some benefit from an overview from MIT Technology Review: How the New Science of Computational History Is Changing the Study of the Past.

The emotional arcs of stories are dominated by six basic shapes

Bookmarked The emotional arcs of stories are dominated by six basic shapes (arxiv.org)
Advances in computing power, natural language processing, and digitization of text now make it possible to study our a culture's evolution through its texts using a "big data" lens. Our ability to communicate relies in part upon a shared emotional experience, with stories often following distinct emotional trajectories, forming patterns that are meaningful to us. Here, by classifying the emotional arcs for a filtered subset of 1,737 stories from Project Gutenberg's fiction collection, we find a set of six core trajectories which form the building blocks of complex narratives. We strengthen our findings by separately applying optimization, linear decomposition, supervised learning, and unsupervised learning. For each of these six core emotional arcs, we examine the closest characteristic stories in publication today and find that particular emotional arcs enjoy greater success, as measured by downloads.

🔖 Paper: Paging Through History by Mark Kurlansky

Bookmarked Paper: Paging Through History by Mark Kurlansky (Amazon.com)
Paper is one of the simplest and most essential pieces of human technology. For the past two millennia, the ability to produce it in ever more efficient ways has supported the proliferation of literacy, media, religion, education, commerce, and art; it has formed the foundation of civilizations, promoting revolutions and restoring stability. One has only to look at history’s greatest press run, which produced 6.5 billion copies of Máo zhuxí yulu, Quotations from Chairman Mao Tse-tung (Zedong)―which doesn’t include editions in 37 foreign languages and in braille―to appreciate the range and influence of a single publication, in paper. Or take the fact that one of history’s most revered artists, Leonardo da Vinci, left behind only 15 paintings but 4,000 works on paper. And though the colonies were at the time calling for a boycott of all British goods, the one exception they made speaks to the essentiality of the material; they penned the Declaration of Independence on British paper. Now, amid discussion of “going paperless”―and as speculation about the effects of a digitally dependent society grows rampant―we’ve come to a world-historic juncture. Thousands of years ago, Socrates and Plato warned that written language would be the end of “true knowledge,” replacing the need to exercise memory and think through complex questions. Similar arguments were made about the switch from handwritten to printed books, and today about the role of computer technology. By tracing paper’s evolution from antiquity to the present, with an emphasis on the contributions made in Asia and the Middle East, Mark Kurlansky challenges common assumptions about technology’s influence, affirming that paper is here to stay. Paper will be the commodity history that guides us forward in the twenty-first century and illuminates our times.

🔖 Marked as “want to read” Paper: Paging Through History by Mark Kurlansky (W. W. Norton & Company; 1st edition, May 10, 2016; ISBN: 9780393239614)

Exhibition at BC Space | Amerikan Krazy: Life Out of Balance

Bookmarked Artists take aim at their country and their county by Antoine BoessenkoolAntoine Boessenkool (The Orange County Register)
“Amerikan Krazy: Life Out of Balance” takes part of its name from the new book <a href="http://boffosockobooks.com/books/authors/henry-james-korn/amerikan-krazy/">"Amerikan Krazy”</a> by <a href="http://www.henryjameskorn.com">Henry James Korn</a>. From 2008 to 2013, Korn worked at the Orange County Great Park. He was responsible for the creation of the Palm Court arts complex and culture, music, art and history programs.<br /><br /> “The book is very much about total corporate control of public and private space,” Korn said. The story follows a wounded Marine veteran haunted after having missed the chance to assassinate a presidential candidate who later causes massive human suffering and wreaks havoc on America’s wealth and democracy.<br /><br /> It’s a way of understanding what’s happening in politics now, Korn said.<br /><br /> “Because if ever there was a recognition that our public life and politics have gone crazy, it’s this moment.”

If you haven’t manage to make it down, this exhibition is running for another week at BC Space!

A New Thermodynamics Theory of the Origin of Life | Quanta Magazine

Bookmarked A New Physics Theory of Life by Natalie Wolchover (quantamagazine.org)
Jeremy England, a 31-year-old physicist at MIT, thinks he has found the underlying physics driving the origin and evolution of life.

References:

Hypothesis annotations

[ hypothesis user = 'chrisaldrich' tags = 'EnglandQM']

Workshop on Methods of Information Theory in Computational Neuroscience | CNS 2016

Bookmarked Workshop on Methods of Information Theory in Computational Neuroscience (CNS 2016) by Joseph T. Lizier (lizier.me)
Methods originally developed in Information Theory have found wide applicability in computational neuroscience. Beyond these original methods there is a need to develop novel tools and approaches that are driven by problems arising in neuroscience. A number of researchers in computational/systems neuroscience and in information/communication theory are investigating problems of information representation and processing. While the goals are often the same, these researchers bring different perspectives and points of view to a common set of neuroscience problems. Often they participate in different fora and their interaction is limited. The goal of the workshop is to bring some of these researchers together to discuss challenges posed by neuroscience and to exchange ideas and present their latest work. The workshop is targeted towards computational and systems neuroscientists with interest in methods of information theory as well as information/communication theorists with interest in neuroscience.

16w5113: Stochastic and Deterministic Models for Evolutionary Biology | Banff International Research Station

Bookmarked Stochastic and Deterministic Models for Evolutionary Biology (Banff International Research Station)
A BIRS / Casa Matemática Oaxaca Workshop arriving in Oaxaca, Mexico Sunday, July 31 and departing Friday August 5, 2016

Evolutionary biology is a rapidly changing field, confronted to many societal problems of increasing importance: impact of global changes, emerging epidemics, antibiotic resistant bacteria… As a consequence, a number of new problematics have appeared over the last decade, challenging the existing mathematical models. There exists thus a demand in the biology community for new mathematical models allowing a qualitative or quantitative description of complex evolution problems. In particular, in the societal problems mentioned above, evolution is often interacting with phenomena of a different nature: interaction with other organisms, spatial dynamics, age structure, invasion processes, time/space heterogeneous environment… The development of mathematical models able to deal with those complex interactions is an ambitious task. Evolutionary biology is interested in the evolution of species. This process is a combination of several phenomena, some occurring at the individual level (e.g. mutations), others at the level of the entire population (competition for resources), often consisting of a very large number of individuals. the presence of very different scales is indeed at the core of theoretical evolutionary biology, and at the origin of many of the difficulties that biologists are facing. The development of new mathematical models thus requires a joint work of three different communities of researchers: specialists of partial differential equations, specialists of probability theory, and theoretical biologists. The goal of this workshop is to gather researchers from each of these communities, currently working on close problematics. Those communities have usually few interactions, and this meeting would give them the opportunity to discuss and work around a few biological thematics that are especially challenging mathematically, and play a crucial role for biological applications.

The role of a spatial structure in models for evolution: The introduction of a spatial structure in evolutionary biology models is often challenging. It is however well known that local adaptation is frequent in nature: field data show that the phenotypes of a given species change considerably across its range. The spatial dynamics of a population can also have a deep impact on its evolution. Assessing e.g. the impact of global changes on species requires the development of robust mathematical models for spatially structured populations.

The first type of models used by theoretical biologists for this type of problems are IBM (Individual Based Models), which describe the evolution of a finite number of individuals, characterized by their position and a phenotype. The mathematical analysis of IBM in spatially homogeneous situations has provided several methods that have been successful in the theoretical biology community (see the theory of Adaptive Dynamics). On the contrary, very few results exist so far on the qualitative properties of such models for spatially structured populations.

The second class of mathematical approach for this type of problem is based on ”infinite dimensional” reaction-diffusion: the population is structured by a continuous phenotypic trait, that affects its ability to disperse (diffusion), or to reproduce (reaction). This type of model can be obtained as a large population limit of IBM. The main difficulty of these models (in the simpler case of asexual populations) is the term modeling the competition from resources, that appears as a non local competition term. This term prevents the use of classical reaction diffusion tools such as the comparison principle and sliding methods. Recently, promising progress has been made, based on tools from elliptic equations and/or Hamilton-Jacobi equations. The effects of small populations can however not be observed on such models. The extension of these models and methods to include these effects will be discussed during the workshop.

Eco-evolution models for sexual populations:An essential question already stated by Darwin and Fisher and which stays for the moment without answer (although it continues to intrigue the evolutionary biologists) is: ”Why does sexual reproduction maintain?” Indeed this reproduction way is very costly since it implies a large number of gametes, the mating and the choice of a compatible partner. During the meiosis phasis, half of the genetical information is lost. Moreover, the males have to be fed and during the sexual mating, individual are easy preys for predators. A partial answer is that recombination plays a main role by better eliminating the deleterious mutations and by increasing the diversity. Nevertheless, this theory is not completely satisfying and many researches are devoted to understanding evolution of sexual populations and comparison between asexual and sexual reproduction. Several models exist to model the influence of sexual reproduction on evolving species. The difficulty compared to asexual populations is that a detailed description of the genetic basis of phenotypes is required, and in particular include recombinations. For sexual populations, recombination plays a main role and it is essential to understand. All models require strong biological simplifications, the development of relevant mathematical methods for such mechanisms then requires a joint work of mathematicians and biologists. This workshop will be an opportunity to set up such collaborations.

The first type of model considers a small number of diploid loci (typically one locus and two alleles), while the rest of the genome is considered as fixed. One can then define the fitness of every combination of alleles. While allowing the modeling of specific sexual effects (such as dominant/recessive alleles), this approach neglects the rest of the genome (and it is known that phenotypes are typically influenced by a large number of loci). An opposite approach is to consider a large number of loci, each locus having a small and additive impact on the considered phenotype. This approach then neglects many microscopic phenomena (epistasis, dominant/recessive alleles…), but allows the derivation of a deterministic model, called the infinitesimal model, in the case of a large population. The construction of a good mathematical framework for intermediate situation would be an important step forward.

The evolution of recombination and sex is very sensitive to the interaction between several evolutionary forces (selection, migration, genetic drift…). Modeling these interactions is particularly challenging and our understanding of the recombination evolution is often limited by strong assumptions regarding demography, the relative strength of these different evolutionary forces, the lack of spatial structure… The development of a more general theoretical framework based on new mathematical developments would be particularly valuable.

Another problem, that has received little attention so far and is worth addressing, is the modeling of the genetic material exchanges in asexual population. This phenomena is frequent in micro-organisms : horizontal gene transfers in bacteria, reassortment or recombination in viruses. These phenomena share some features with sexual reproduction. It would be interesting to see if the effect of this phenomena can be seen as a perturbation of existing asexual models. This would in particular be interesting in spatially structured populations (e.g. viral epidemics), since the the mathematical analysis of spatially structured asexual populations is improving rapidly.

Modeling in evolutionary epidemiology: Mathematical epidemiology has been developing since more than a century ago. Yet, the integration of population genetics phenomena to epidemiology is relatively recent. Microbial pathogens (bacteria and viruses) are particularly interesting organisms because their short generation times and large mutation rates allow them to adapt relatively fast to changing environments. As a consequence, ecological (demography) and evolutionary (population genetics) processes often occur at the same pace. This raises many interesting problems.

A first challenge is the modeling of the spatial dynamics of an epidemics. The parasites can evolve during the epidemics of a new host population, either to adapt to a heterogeneous environment, or because it will itself modify the environment as it invades. The applications of such studies are numerous: antibiotic management, agriculture… An aspect of this problem for which our workshop can bring a significant contribution (thanks to the diversity of its participants) is the evolution of the pathogen diversity. During the large expansion produced by an epidemics, there is a loss of diversity in the invading parasites, since most pathogens originate from a few parents. The development of mathematical models for those phenomena is challenging: only a small number of pathogens are present ahead of the epidemic front, while the number of parasites rapidly become very large after the infection. The interaction between a stochastic micro scale and a deterministic macro scale is apparent here, and deserves a rigorous mathematical analysis.

Another interesting phenomena is the effect of a sudden change of the environment on a population of pathogens. Examples of such situations are for instance the antibiotic treatment of an infected patients, or the transmission of a parasite to a new host species (transmission of the avian influenza to human beings, for instance). Related experiments are relatively easy to perform, and called evolutionary rescue experiments. So far, this question has received limited attention from the mathematical community. The key is to estimate the probability that a mutant well adapted to the new environment existed in the original population, or will appear soon after the environmental change. Interactions between biologists specialists of those questions and mathematicians should lead to new mathematical problems.

Bits from Brains for Biologically Inspired Computing | Computational Intelligence

Bookmarked Bits from Brains for Biologically Inspired Computing (Frontiers in Robotics and AI | Computational Intelligence journal.frontiersin.org)
Inspiration for artificial biologically inspired computing is often drawn from neural systems. This article shows how to analyze neural systems using information theory with the aim of obtaining constraints that help to identify the algorithms run by neural systems and the information they represent. Algorithms and representations identified this way may then guide the design of biologically inspired computing systems. The material covered includes the necessary introduction to information theory and to the estimation of information-theoretic quantities from neural recordings. We then show how to analyze the information encoded in a system about its environment, and also discuss recent methodological developments on the question of how much information each agent carries about the environment either uniquely or redundantly or synergistically together with others. Last, we introduce the framework of local information dynamics, where information processing is partitioned into component processes of information storage, transfer, and modification – locally in space and time. We close by discussing example applications of these measures to neural data and other complex systems.

Quantum Information Meets Quantum Matter

Bookmarked Quantum Information Meets Quantum Matter -- From Quantum Entanglement to Topological Phase in Many-Body Systems (arxiv.org)
This is the draft version of a textbook, which aims to introduce the quantum information science viewpoints on condensed matter physics to graduate students in physics (or interested researchers). We keep the writing in a self-consistent way, requiring minimum background in quantum information science. Basic knowledge in undergraduate quantum physics and condensed matter physics is assumed. We start slowly from the basic ideas in quantum information theory, but wish to eventually bring the readers to the frontiers of research in condensed matter physics, including topological phases of matter, tensor networks, and symmetry-protected topological phases.

Matter, energy… knowledge: How to harness physics’ demonic power | New Scientist

Bookmarked Matter, energy… knowledge: How to harness physics' demonic power (New Scientist)
Running a brain-twisting thought experiment for real shows that information is a physical thing – so can we now harness the most elusive entity in the cosmos?

This is a nice little overview article of some of the history of thermodynamics relating to information in physics and includes some recent physics advances as well. There are a few references to applications in biology at the micro level as well.

References