Network motifs emerge from interconnections that favour stability

The microscopic principles organizing dynamic units in complex networks—from proteins to power generators—can be understood in terms of network ‘motifs’: small interconnection patterns that appear much more frequently in real networks than expected in random networks. When considered as small subgraphs isolated from a large network, these motifs are more robust to parameter variations, easier to synchronize than other possible subgraphs, and can provide specific functionalities. But one can isolate these subgraphs only by assuming, for example, a significant separation of timescales, and the origin of network motifs and their functionalities when embedded in larger networks remain unclear. Here we show that most motifs emerge from interconnection patterns that best exploit the intrinsic stability characteristics at different scales of interconnection, from simple nodes to whole modules. This functionality suggests an efficient mechanism to stably build complex systems by recursively interconnecting nodes and modules as motifs. We present direct evidence of this mechanism in several biological networks

Evolutionary constraints on the complexity of genetic regulatory networks allow predictions of the total number of genetic interactions

Genetic regulatory networks (GRNs) have been widely studied, yet there is a lack of understanding with regards to the final size and properties of these networks, mainly due to no network currently being complete. In this study, we analyzed the distribution of GRN structural properties across a large set of distinct prokaryotic organisms and found a set of constrained characteristics such as network density and number of regulators. Our results allowed us to estimate the number of interactions that complete networks would have, a valuable insight that could aid in the daunting task of network curation, prediction, and validation. Using state-of-the-art statistical approaches, we also provided new evidence to settle a previously stated controversy that raised the possibility of complete biological networks being random and therefore attributing the observed scale-free properties to an artifact emerging from the sampling process during network discovery. Furthermore, we identified a set of properties that enabled us to assess the consistency of the connectivity distribution for various GRNs against different alternative statistical distributions. Our results favor the hypothesis that highly connected nodes (hubs) are not a consequence of network incompleteness. Finally, an interaction coverage computed for the GRNs as a proxy for completeness revealed that high-throughput based reconstructions of GRNs could yield biased networks with a low average clustering coefficient, showing that classical targeted discovery of interactions is still needed.Comment: 28 pages, 5 figures, 12 pages supplementary informatio

Statistically validated coeherence and intensity in temporal networks of information flows

We propose a method for characterizing the local structure of weighted multivariate time series networks. We draw intensity and coherence of network motifs, i.e. statistically recurrent subgraphs, to characterize the system behavior via higher-order structures derived upon effective transfer entropy networks. The latter consists of a model-free methodology enabling to correct for small sample biases affecting Shannon transfer entropy, other than conducting inference on the estimated directional time series information flows. We demonstrate the usefulness of our proposed method with an application to a set of global commodity prices. Our main result shows that, despite simple triadic structures are the most intense, coherent and statistically recurrent over time, their intensity suddenly decreases after the Global Financial Crisis, in favor of most complex triadic structures, while all types of subgraphs tend to become more coherent thereafter

Network Evolution of Body Plans

Segmentation in arthropod embryogenesis represents a well-known example of body plan diversity. Striped patterns of gene expression that lead to the future body segments appear simultaneously or sequentially in long and short germ-band development, respectively. Regulatory genes relevant for stripe formation are evolutionarily conserved among arthropods, therefore the differences in the observed traits are thought to have originated from how the genes are wired. To reveal the basic differences in the network structure, we have numerically evolved hundreds of gene regulatory networks that produce striped patterns of gene expression. By analyzing the topologies of the generated networks, we show that the characteristics of stripe formation in long and short germ-band development are determined by Feed-Forward Loops (FFLs) and negative Feed-Back Loops (FBLs) respectively. Network architectures, gene expression patterns and knockout responses exhibited by the artificially evolved networks agree with those reported in the fly Drosophila melanogaster and the beetle Tribolium castaneum. For other arthropod species, principal network architectures that remain largely unknown are predicted.Comment: 35 pages, 4 figures and 1 tabl

Interconnected musical networks : bringing expression and thoughtfulness to collaborative group playing

Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.Includes bibliographical references (p. 211-219).(cont.) In order to addressee the latter challenge I have decided to employ the digital network--a promising candidate for bringing a unique added value to the musical experience of collaborative group playing. I have chosen to address both challenges by embedding cognitive and educational concepts in newly designed interconnect instruments and applications, which led to the development of a number of such Interconnected Musical Networks (IMNs)--live performance systems that allow players to influence, share, and shape each other's music in real-time. In my thesis I discuss the concepts, motivations, and aesthetics of IMNs and review a number of historical and current technological landmarks that led the way to the development of the field. I then suggest a comprehensive theoretical framework for artistic interdependency, based on which I developed a set of instruments and activities in an effort to turn IMNs into an expressive and intuitive art form that provides meaningful learning experiences, engaging collaborative interactions, and worthy music.Music today is more ubiquitous, accessible, and democratized than ever. Thanks to technologies such as high-end home studios, audio compression, and digital distribution, music now surrounds us in everyday life, almost every piece of music is a few minutes of download away, and almost any western musician, novice or expert, can compose, perform and distribute their music directly to their listeners from their home studios. But at the same time these technologies lead to some concerning social effects on the culture of consuming and creating music. Although music is available for more people, in more locations, and for longer periods of time, most listeners experience it in an incidental, unengaged, or utilitarian manner. On the creation side, home studios promote private and isolated practice of music making where hardly any musical instruments or even musicians are needed, and where the value of live group interaction is marginal. My thesis work attempts to use technology to address these same concerning effects that it had created by developing tools and applications that would address two main challenges: 1. Facilitating engaged and thoughtful as well as intuitive and expressive musical experiences for novices and children 2. Enhancing the inherent social attributes of music making by connecting to and intensifying the roots of music as a collaborative socialritual. My approach for addressing the first challenge is to study and model music cognition and education theories and to design algorithms that would bridge between the thoughtful and the expressive, allowing novices and children an access to meaningful and engaging musical experiences.by Gil Weinberg.Ph.D

Molecular mechanisms of eukaryotic pre-mRNA 3′ end processing regulation

Messenger RNA (mRNA) 3′ end formation is a nuclear process through which all eukaryotic primary transcripts are endonucleolytically cleaved and most of them acquire a poly(A) tail. This process, which consists in the recognition of defined poly(A) signals of the pre-mRNAs by a large cleavage/polyadenylation machinery, plays a critical role in gene expression. Indeed, the poly(A) tail of a mature mRNA is essential for its functions, including stability, translocation to the cytoplasm and translation. In addition, this process serves as a bridge in the network connecting the different transcription, capping, splicing and export machineries. It also participates in the quantitative and qualitative regulation of gene expression in a variety of biological processes through the selection of single or alternative poly(A) signals in transcription units. A large number of protein factors associates with this machinery to regulate the efficiency and specificity of this process and to mediate its interaction with other nuclear events. Here, we review the eukaryotic 3′ end processing machineries as well as the comprehensive set of regulatory factors and discuss the different molecular mechanisms of 3′ end processing regulation by proposing several overlapping models of regulation

Efficient Physical Embedding of Topologically Complex Information Processing Networks in Brains and Computer Circuits

Nervous systems are information processing networks that evolved by natural selection, whereas very large scale integrated (VLSI) computer circuits have evolved by commercially driven technology development. Here we follow historic intuition that all physical information processing systems will share key organizational properties, such as modularity, that generally confer adaptivity of function. It has long been observed that modular VLSI circuits demonstrate an isometric scaling relationship between the number of processing elements and the number of connections, known as Rent's rule, which is related to the dimensionality of the circuit's interconnect topology and its logical capacity. We show that human brain structural networks, and the nervous system of the nematode C. elegans, also obey Rent's rule, and exhibit some degree of hierarchical modularity. We further show that the estimated Rent exponent of human brain networks, derived from MRI data, can explain the allometric scaling relations between gray and white matter volumes across a wide range of mammalian species, again suggesting that these principles of nervous system design are highly conserved. For each of these fractal modular networks, the dimensionality of the interconnect topology was greater than the 2 or 3 Euclidean dimensions of the space in which it was embedded. This relatively high complexity entailed extra cost in physical wiring: although all networks were economically or cost-efficiently wired they did not strictly minimize wiring costs. Artificial and biological information processing systems both may evolve to optimize a trade-off between physical cost and topological complexity, resulting in the emergence of homologous principles of economical, fractal and modular design across many different kinds of nervous and computational networks

Developing Theory Through Integrating Human and Machine Pattern Recognition

New forms of digital trace data are becoming ubiquitous. Traditional methods of qualitative research that aim at developing theory, however, are often overwhelmed by the sheer volume of such data. To remedy this situation, qualitative researchers can engage not only with digital traces, but also with computational tools that are increasingly able to model digital trace data in ways that support the process of developing theory. To facilitate such research, this paper crafts a research design framework based on the philosophical tradition of pragmatism, which provides intellectual tools for dealing with multifaceted digital trace data, and offers an abductive analysis approach suitable for leveraging both human and machine pattern recognition. This framework provides opportunities for researchers to engage with digital traces and computational tools in a way that is sensitive to qualitative researchers’ concerns about theory development. The paper concludes by showing how this framework puts human imaginative capacities at the center of the push for qualitative researchers to engage with computational tools and digital trace

The Politicization of Art on the Internet: From net.art to post-internet art

Este estudo tem como objetivo apresentar uma breve perspetiva sobre as manifestações socioculturais que se propagaram a partir do surgimento da Web; tendo como principal foco de análise o desenvolvimento da produção de Internet Arte na Europa e na América do Norte ao longo dos últimos 30 anos. Estruturado como um estudo de caso, três conceitos-chave fundamentam a base desta pesquisa: uma breve história da Internet, o desenvolvimento do termo hacker e a produção de arte web-based; da net.art até a Arte Pós-Internet. Em abordagem cronológica, estes campos serão descritos e posteriormente utilizados como guias para um final encadeamento comparativo que visa sustentar a hipótese da gradual dissolução de um ciberespaço utópico até o distópico cenário corporativo que constitui a Internet dos dias atuais.This study aims to present a brief perspective of the sociocultural manifestations that emerged after the Web birth, focusing on the development of Internet Art and the countercultural movements that emerged inside Europe and North America over the last 30 years. Under a case study structure, three fundamental subjects will be firstly explained: Internet history, the development of hacker concept and the web-based Art transformations: from net.art till Post-Internet Art. Chronologically described, these fields will lead to a final comparison of chained events that aim to sustain the hypothesis of the gradual dissolution of the early cyberspace utopias till the dystopic scene existent in nowadays Internet