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Social Foraging
Dynamics of Social Interaction
Curated by Ashish Umre
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Why Do Humans Cry? Scientist Says Tears Served as a Means of Communication Before the Evolution of Language

Why Do Humans Cry? Scientist Says Tears Served as a Means of Communication Before the Evolution of Language | Social Foraging | Scoop.it
A leading scientist says that the human phenomenon of emotional crying is hugely important and developed as a way for humans to communicate how they feel before the emergence of language.

 

Tears, what are they good for? They certainly embarrass us when they suddenly start gushing out of your eyes at the theater when the leading character finally finds long lost love or when your significant other unexpectedly decides to break up with you over dinner at a busy restaurant. However, a leading scientist says that the human phenomenon of emotional crying is hugely important and developed as a way for humans to communicate how they feel before the emergence of language.

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The Underlying Molecular and Network Level Mechanisms in the Evolution of Robustness in Gene Regulatory Networks

The Underlying Molecular and Network Level Mechanisms in the Evolution of Robustness in Gene Regulatory Networks | Social Foraging | Scoop.it

Gene regulatory networks show robustness to perturbations. Previous works identified robustness as an emergent property of gene network evolution but the underlying molecular mechanisms are poorly understood. We used a multi-tier modeling approach that integrates molecular sequence and structure information with network architecture and population dynamics. Structural models of transcription factor-DNA complexes are used to estimate relative binding specificities. In this model, mutations in the DNA cause changes on two levels: (a) at the sequence level in individual binding sites (modulating binding specificity), and (b) at the network level (creating and destroying binding sites). We used this model to dissect the underlying mechanisms responsible for the evolution of robustness in gene regulatory networks. Results suggest that in sparse architectures (represented by short promoters), a mixture of local-sequence and network-architecture level changes are exploited. At the local-sequence level, robustness evolves by decreasing the probabilities of both the destruction of existent and generation of new binding sites. Meanwhile, in highly interconnected architectures (represented by long promoters), robustness evolves almost entirely via network level changes, deleting and creating binding sites that modify the network architecture.

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Saccadic Momentum and Facilitation of Return Saccades Contribute to an Optimal Foraging Strategy

Saccadic Momentum and Facilitation of Return Saccades Contribute to an Optimal Foraging Strategy | Social Foraging | Scoop.it

The interest in saccadic IOR is funneled by the hypothesis that it serves a clear functional purpose in the selection of fixation points: the facilitation of foraging. In this study, we arrive at a different interpretation of saccadic IOR. First, we find that return saccades are performed much more often than expected from the statistical properties of saccades and saccade pairs. Second, we find that fixation durations before a saccade are modulated by the relative angle of the saccade, but return saccades show no sign of an additional temporal inhibition. Thus, we do not find temporal saccadic inhibition of return. Interestingly, we find that return locations are more salient, according to empirically measured saliency (locations that are fixated by many observers) as well as stimulus dependent saliency (defined by image features), than regular fixation locations. These results and the finding that return saccades increase the match of individual trajectories with a grand total priority map evidences the return saccades being part of a fixation selection strategy that trades off exploration and exploitation.

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Reward from Punishment Does Not Emerge at All Costs

Reward from Punishment Does Not Emerge at All Costs | Social Foraging | Scoop.it

The conundrum of cooperation has received increasing attention during the last decade. In this quest, the role of altruistic punishment has been identified as a mechanism promoting cooperation. Here we investigate the role of altruistic punishment on the emergence and maintenance of cooperation in structured populations exhibiting connectivity patterns recently identified as key elements of social networks. We do so in the framework of Evolutionary Game Theory, employing the Prisoner's Dilemma and the Stag-Hunt metaphors to model the conflict between individual and collective interests regarding cooperation. We find that the impact of altruistic punishment strongly depends on the ratio q/p between the cost of punishing a defecting partner (q) and the actual punishment incurred by the partner (p). We show that whenever q/p<1, altruistic punishment turns out to be detrimental for cooperation for a wide range of payoff parameters, when compared to the scenario without punishment. The results imply that while locally, the introduction of peer punishment may seem to reduce the chances of free-riding, realistic population structure may drive the population towards the opposite scenario. Hence, structured populations effectively reduce the expected beneficial contribution of punishment to the emergence of cooperation which, if not carefully dosed, may in fact hinder the chances of widespread cooperation.

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The Human Functional Brain Network Demonstrates Structural and Dynamical Resilience to Targeted Attack

The Human Functional Brain Network Demonstrates Structural and Dynamical Resilience to Targeted Attack | Social Foraging | Scoop.it

In recent years, the field of network science has enabled researchers to represent the highly complex interactions in the brain in an approachable yet quantitative manner. One exciting finding since the advent of brain network research was that the brain network can withstand extensive damage, even to highly connected regions. However, these highly connected nodes may not be the most critical regions of the brain network, and it is unclear how the network dynamics are impacted by removal of these key nodes. This work seeks to further investigate the resilience of the human functional brain network. Network attack experiments were conducted on voxel-wise functional brain networks and region-of-interest (ROI) networks of 5 healthy volunteers. Networks were attacked at key nodes using several criteria for assessing node importance, and the impact on network structure and dynamics was evaluated. The findings presented here echo previous findings that the functional human brain network is highly resilient to targeted attacks, both in terms of network structure and dynamics.

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Starling Flock Networks Manage Uncertainty in Consensus at Low Cost

Starling Flock Networks Manage Uncertainty in Consensus at Low Cost | Social Foraging | Scoop.it

Flocks of starlings exhibit a remarkable ability to maintain cohesion as a group in highly uncertain environments and with limited, noisy information. Recent work demonstrated that individual starlings within large flocks respond to a fixed number of nearest neighbors, but until now it was not understood why this number is seven. We analyze robustness to uncertainty of consensus in empirical data from multiple starling flocks and show that the flock interaction networks with six or seven neighbors optimize the trade-off between group cohesion and individual effort. We can distinguish these numbers of neighbors from fewer or greater numbers using our systems-theoretic approach to measuring robustness of interaction networks as a function of the network structure, i.e., who is sensing whom. The metric quantifies the disagreement within the network due to disturbances and noise during consensus behavior and can be evaluated over a parameterized family of hypothesized sensing strategies (here the parameter is number of neighbors). We use this approach to further show that for the range of flocks studied the optimal number of neighbors does not depend on the number of birds within a flock; rather, it depends on the shape, notably the thickness, of the flock. The results suggest that robustness to uncertainty may have been a factor in the evolution of flocking for starlings. More generally, our results elucidate the role of the interaction network on uncertainty management in collective behavior, and motivate the application of our approach to other biological networks.

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Maximizing the Information Content of Experiments in Systems Biology

Maximizing the Information Content of Experiments in Systems Biology | Social Foraging | Scoop.it

Our understanding of most biological systems is in its infancy. Learning their structure and intricacies is fraught with challenges, and often side-stepped in favour of studying the function of different gene products in isolation from their physiological context. Constructing and inferring global mathematical models from experimental data is, however, central to systems biology. Different experimental setups provide different insights into such systems. Here we show how we can combine concepts from Bayesian inference and information theory in order to identify experiments that maximize the information content of the resulting data. This approach allows us to incorporate preliminary information; it is global and not constrained to some local neighbourhood in parameter space and it readily yields information on parameter robustness and confidence. Here we develop the theoretical framework and apply it to a range of exemplary problems that highlight how we can improve experimental investigations into the structure and dynamics of biological systems and their behavior.

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The evolutionary origins of modularity

A central biological question is how natural organisms are so evolvable (capable of quickly adapting to new environments). A key driver of evolvability is the widespread modularity of biological networks—their organization as functional, sparsely connected subunits—but there is no consensus regarding why modularity itself evolved. Although most hypotheses assume indirect selection for evolvability, here we demonstrate that the ubiquitous, direct selection pressure to reduce the cost of connections between network nodes causes the emergence of modular networks. Computational evolution experiments with selection pressures to maximize network performance and minimize connection costs yield networks that are significantly more modular and more evolvable than control experiments that only select for performance. These results will catalyse research in numerous disciplines, such as neuroscience and genetics, and enhance our ability to harness evolution for engineering purposes.

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Swarm Creativity:Competitive Advantage through Collaborative Innovation Networks

Swarm Creativity:Competitive Advantage through Collaborative Innovation Networks | Social Foraging | Scoop.it

Swarm Creativity introduces a powerful new concept-Collaborative Innovation Networks, or COINs. Its aim is to make the concept of COINs as ubiquitous among business managers as any methodology to enhance quality and competitive advantage. The difference though is that COINs are nothing like other methodologies. A COIN is a cyberteam of self-motivated people with a collective vision, enabled by technology to collaborate in achieving a common goal--n innovation-by sharing ideas, information, and work. It is no exaggeration to state that COINs are the most productive engines of innovation ever. COINs have been around for hundreds of years. Many of us have already been a part of one without knowing it. What makes COINs so relevant today, though is that the concept has reached its tipping point-thanks to the Internet and the World Wide Web. This book explores why COINS are so important to business success in the new century. It explains the traits that characterize COIN members and COIN behavior. It makes the case for why businesses ought to be rushing to uncover their COINs and nurture them, and provides tools for building organizations that are more creative, productive and efficient by applying principles of creative collaboration, knowledge sharing and social networking. Through real-life examples in several business sectors, the book shows how to leverage COINs to develop successful products in R & D, grow better customer relationships, establish better project management, and build higher-performing teams. In short, this book answers four key questions: Why are COINs better at innovation? What are the key elements of COINs? Who are the people that participate in COINs and how do they become members? And how does an organization transform itself into a Collaborative Innovation Network?

 

http://www.tlu.ee/~kpata/uusmeedia/Swarm%20Creativity_Competitive%20Advantage%20through%20Collaborative%20Innovation%20Networks.pdf

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luiy's curator insight, January 30, 2013 11:34 AM

CONTENTS


Introduction: At the Tipping Point 3


1 COINs and Their Benefits 9
2 Collaborative Innovation through Swarm Creativity 19
3 The DNA of COINS: Creativity, Collaboration,
and Communication 49
4 Ethical Codes in Small Worlds 71
5 Real-Life Examples: Lessons Learned from COINs 91
6 COINs and Communications Technology 115
appendixes 125
A Collaborative Knowledge Networks (CKNs) 127
B Temporal Communication Flow Analysis (TeCFlow) 141
C Knowledge Flow Optimization (KFO) 173
Notes 193
References 199
Additional Resources 203
Index 209

 

http://www.tlu.ee/~kpata/uusmeedia/Swarm%20Creativity_Competitive%20Advantage%20through%20Collaborative%20Innovation%20Networks.pdf

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Highly Efficient Light-Trapping Structure Design Inspired By Natural Evolution

Highly Efficient Light-Trapping Structure Design Inspired By Natural Evolution | Social Foraging | Scoop.it

Recent advances in nanophotonic light trapping open up the new gateway to enhance the absorption of solar energy beyond the so called Yablonovitch Limit. It addresses the urgent needs in developing low cost thin-film solar photovoltaic technologies. However, current design strategy mainly relies on the parametric approach that is subject to the predefined topological design concepts based on physical intuition. Incapable of dealing with the topological variation severely constrains the design of optimal light trapping structure. Inspired by natural evolution process, here we report a design framework driven by topology optimization based on genetic algorithms to achieve a highly efficient light trapping structure. It has been demonstrated that the optimal light trapping structures obtained in this study exhibit more than 3-fold increase over the Yablonovitch Limit with the broadband absorption efficiency of 48.1%, beyond the reach of intuitive designs.

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Diet, parental behavior and preschool can boost children's IQ

Diet, parental behavior and preschool can boost children's IQ | Social Foraging | Scoop.it

Supplementing children's diets with fish oil, enrolling them in quality preschool, and engaging them in interactive reading all turn out to be effective ways to raise a young child's intelligence, according to a new report published in Perspectives on Psychological Science, a journal of the Association for Psychological Science.

 

Using a technique called meta-analysis, a team led by John Protzko, a doctoral student at the NYU Steinhardt School of Culture, Education, and Human Development, combined the findings from existing studies to evaluate the overall effectiveness of each type of intervention. In collaboration with NYU Steinhardt professors Joshua Aronson and Clancy Blair, leaders in the field of intelligence, Protzko analyzed the best available studies involving samples of children from birth and kindergarten from their newlyassembled "Database of Raising Intelligence."

 

"Our aim in creating this database is to learn what works and what doesn't work to raise people's intelligence," said Protzko. "For too long, findings have been disconnected and scattered throughout a wide variety of journals. The broad consensus about what works is founded on only two or three very high-profile studies."

 

All of the studies in this database rely on a normal population (participants without clinical diagnoses of intellectual disabilities), focus on interventions that are sustained over time, use widely accepted measures of intelligence, and, most importantly, are randomly controlled trials (participants selected at random to receive one of the interventions).

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Social norms guide internet behaviour

Social norms guide internet behaviour | Social Foraging | Scoop.it

"Most people think if you are not an engineer you have nothing to say about technology", regrets social scientist Suvi Silfverberg, "I think it's quite the opposite: as a technology user you have a lot to contribute."

 

In her PhD thesis Silfverberg discusses how Facebook, Foursqare, LinkedIn and Last.fm user profiles relate to self and identity. She is collecting her data from interviews as well as from real-life and online focus groups.

 

"People keep their online profiles as products; information is manipulated in order to sell a self-chosen concept of themselves," states Silfverberg. "But this is not it yet," she continues. "Quite like cultural norms influence the way we speak, our internet behaviour is determined by norms, too. Some of these norms support what we do on the net, some restrict our behaviour."

 

A female Facebook user might, for instance, avoid publishing an attractive photo of herself in a bikini because she expects criticism. A Last.fm user might feel forced to listen to a variety of music considered good taste just to mask his liking for a cheesy song. "As a consequence," concludes Silfverberg, "we all start behaving similarly, which continuously re-enforces these norms."

 

A set of unwritten social rules have developed for each social media platform. "Finns for example do not appreciate the sharing of too much content, or obviously tuning your profile to put yourself into a favourable light. This 'pursuit of authenticity' also applies to Last.fm where the user is expected to stay true to their taste and to really listen to the music they play on their computer", summarizes Silfverberg.

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Harry Madigan's curator insight, October 4, 2014 2:56 AM

A very very interesting article, not directly related to my topic/ criteria, however it explores compelling theories and ideas such as ""People keep their online profiles as products; information is manipulated in order to sell a self-chosen concept of themselves,"


what i gathered from this article was that individuals are hesitating to share, post and write certain things online due to the fear of being placed in a negative light. 

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Darwin’s extra sense: How mathematics is revolutionizing biology

Darwin’s extra sense: How mathematics is revolutionizing biology | Social Foraging | Scoop.it

“Darwin’s Extra Sense,” a new video produced by SFI External Professor Dan Rockmore and collaborators, explores the ways applied mathematics is opening doors to astonishing insights in the life sciences – from evolutionary biology to protein folding and brain science.

 

Watch “Darwin’s Extra Sense” here (45 minutes)

 

“The field of biology had taken awhile for quantitative efforts to enter it, and now it has been truly transformed,” says Rockmore, a professor of mathematics and computer science at Dartmouth College. He produced the film in collaboration with filmmakers Wendy Conquest and Bob Drake, with financial support from the National Science Foundation and SFI.

 

The film tells the story of how the mathematical articulation of heredity by Gregor Mendel and others saved Charles Darwin’s initially flawed theory of evolution theory.

 

Darwin is quoted on his inability to apply math rigorously to his research: “I deeply regretted that I did not proceed far enough at least to understand something of the great leading principles of mathematics, for men thus endowed seem to have an extra sense.”

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Some Structural Aspects of Language Are More Stable than Others: A Comparison of Seven Methods

Some Structural Aspects of Language Are More Stable than Others: A Comparison of Seven Methods | Social Foraging | Scoop.it

Understanding the patterns and causes of differential structural stability is an area of major interest for the study of language change and evolution. It is still debated whether structural features have intrinsic stabilities across language families and geographic areas, or if the processes governing their rate of change are completely dependent upon the specific context of a given language or language family. We conducted an extensive literature review and selected seven different approaches to conceptualising and estimating the stability of structural linguistic features, aiming at comparing them using the same dataset, the World Atlas of Language Structures. We found that, despite profound conceptual and empirical differences between these methods, they tend to agree in classifying some structural linguistic features as being more stable than others. This suggests that there are intrinsic properties of such structural features influencing their stability across methods, language families and geographic areas. This finding is a major step towards understanding the nature of structural linguistic features and their interaction with idiosyncratic, lineage- and area-specific factors during language change and evolution.

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Stefano Piotto's curator insight, February 3, 2013 8:40 AM

Un'altra applicazione per il nostro ProtComp

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Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex

Network Self-Organization Explains the Statistics and Dynamics of Synaptic Connection Strengths in Cortex | Social Foraging | Scoop.it

The information processing abilities of neural circuits arise from their synaptic connection patterns. Understanding the laws governing these connectivity patterns is essential for understanding brain function. The overall distribution of synaptic strengths of local excitatory connections in cortex and hippocampus is long-tailed, exhibiting a small number of synaptic connections of very large efficacy. At the same time, new synaptic connections are constantly being created and individual synaptic connection strengths show substantial fluctuations across time. It remains unclear through what mechanisms these properties of neural circuits arise and how they contribute to learning and memory. In this study we show that fundamental characteristics of excitatory synaptic connections in cortex and hippocampus can be explained as a consequence of self-organization in a recurrent network combining spike-timing-dependent plasticity (STDP), structural plasticity and different forms of homeostatic plasticity. In the network, associative synaptic plasticity in the form of STDP induces a rich-get-richer dynamics among synapses, while homeostatic mechanisms induce competition. Under distinctly different initial conditions, the ensuing self-organization produces long-tailed synaptic strength distributions matching experimental findings. We show that this self-organization can take place with a purely additive STDP mechanism and that multiplicative weight dynamics emerge as a consequence of network interactions. The observed patterns of fluctuation of synaptic strengths, including elimination and generation of synaptic connections and long-term persistence of strong connections, are consistent with the dynamics of dendritic spines found in rat hippocampus. Beyond this, the model predicts an approximately power-law scaling of the lifetimes of newly established synaptic connection strengths during development. Our results suggest that the combined action of multiple forms of neuronal plasticity plays an essential role in the formation and maintenance of cortical circuits.

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Durable Resistance to Crop Pathogens: An Epidemiological Framework to Predict Risk under Uncertainty

Durable Resistance to Crop Pathogens: An Epidemiological Framework to Predict Risk under Uncertainty | Social Foraging | Scoop.it

Increasing the durability of crop resistance to plant pathogens is one of the key goals of virulence management. Despite the recognition of the importance of demographic and environmental stochasticity on the dynamics of an epidemic, their effects on the evolution of the pathogen and durability of resistance has not received attention. We formulated a stochastic epidemiological model, based on the Kramer-Moyal expansion of the Master Equation, to investigate how random fluctuations affect the dynamics of an epidemic and how these effects feed through to the evolution of the pathogen and durability of resistance. We focused on two hypotheses: firstly, a previous deterministic model has suggested that the effect of cropping ratio (the proportion of land area occupied by the resistant crop) on the durability of crop resistance is negligible. Increasing the cropping ratio increases the area of uninfected host, but the resistance is more rapidly broken; these two effects counteract each other. We tested the hypothesis that similar counteracting effects would occur when we take account of demographic stochasticity, but found that the durability does depend on the cropping ratio. Secondly, we tested whether a superimposed external source of stochasticity (for example due to environmental variation or to intermittent fungicide application) interacts with the intrinsic demographic fluctuations and how such interaction affects the durability of resistance. We show that in the pathosystem considered here, in general large stochastic fluctuations in epidemics enhance extinction of the pathogen. This is more likely to occur at large cropping ratios and for particular frequencies of the periodic external perturbation (stochastic resonance). The results suggest possible disease control practises by exploiting the natural sources of stochasticity.

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How Evolving Heterogeneity Distributions of Resource Allocation Strategies Shape Mortality Patterns

How Evolving Heterogeneity Distributions of Resource Allocation Strategies Shape Mortality Patterns | Social Foraging | Scoop.it

It is well established that individuals age differently. Yet the nature of these inter-individual differences is still largely unknown. For humans, two main hypotheses have been recently formulated: individuals may experience differences in aging rate or aging timing. This issue is central because it directly influences predictions for human lifespan and provides strong insights into the biological determinants of aging. In this article, we propose a model which lets population heterogeneity emerge from an evolutionary algorithm. We find that whether individuals differ in (i) aging rate or (ii) timing leads to different emerging population heterogeneity. Yet, in both cases, the same mortality patterns are observed at the population level. These patterns qualitatively reproduce those of yeasts, flies, worms and humans. Such findings, supported by an extensive parameter exploration, suggest that mortality patterns across species and their potential shapes belong to a limited and robust set of possible curves. In addition, we use our model to shed light on the notion of subpopulations, link population heterogeneity with the experimental results of stress induction experiments and provide predictions about the expected mortality patterns. As biology is moving towards the study of the distribution of individual-based measures, the model and framework we propose here paves the way for evolutionary interpretations of empirical and experimental data linking the individual level to the population level.

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Dynamic Finite Size Effects in Spiking Neural Networks

We investigate the dynamics of a deterministic finite-sized network of synaptically coupled spiking neurons and present a formalism for computing the network statistics in a perturbative expansion. The small parameter for the expansion is the inverse number of neurons in the network. The network dynamics are fully characterized by a neuron population density that obeys a conservation law analogous to the Klimontovich equation in the kinetic theory of plasmas. The Klimontovich equation does not possess well-behaved solutions but can be recast in terms of a coupled system of well-behaved moment equations, known as a moment hierarchy. The moment hierarchy is impossible to solve but in the mean field limit of an infinite number of neurons, it reduces to a single well-behaved conservation law for the mean neuron density. For a large but finite system, the moment hierarchy can be truncated perturbatively with the inverse system size as a small parameter but the resulting set of reduced moment equations that are still very difficult to solve. However, the entire moment hierarchy can also be re-expressed in terms of a functional probability distribution of the neuron density. The moments can then be computed perturbatively using methods from statistical field theory. Here we derive the complete mean field theory and the lowest order second moment corrections for physiologically relevant quantities. Although we focus on finite-size corrections, our method can be used to compute perturbative expansions in any parameter.

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Bayesian Inference of Spatial Organizations of Chromosomes

Bayesian Inference of Spatial Organizations of Chromosomes | Social Foraging | Scoop.it

Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. Recently, chromosome conformation capture (3C) based technologies, such as Hi-C and TCC, have been developed to provide a genome-wide, three-dimensional (3D) view of chromatin organization. Appropriate methods for analyzing these data and fully characterizing the 3D chromosomal structure and its structural variations are still under development. Here we describe a novel Bayesian probabilistic approach, denoted as “Bayesian 3D constructor for Hi-C data” (BACH), to infer the consensus 3D chromosomal structure. In addition, we describe a variant algorithm BACH-MIX to study the structural variations of chromatin in a cell population. Applying BACH and BACH-MIX to a high resolution Hi-C dataset generated from mouse embryonic stem cells, we found that most local genomic regions exhibit homogeneous 3D chromosomal structures. We further constructed a model for the spatial arrangement of chromatin, which reveals structural properties associated with euchromatic and heterochromatic regions in the genome. We observed strong associations between structural properties and several genomic and epigenetic features of the chromosome. Using BACH-MIX, we further found that the structural variations of chromatin are correlated with these genomic and epigenetic features. Our results demonstrate that BACH and BACH-MIX have the potential to provide new insights into the chromosomal architecture of mammalian cells.

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Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks

Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks | Social Foraging | Scoop.it

A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of disease over a network of towns) because they do not account for the changing percolation states of individual nodes. We propose a new measure, percolation centrality, that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states. The measure can be extended to include random walk based definitions, and its computational complexity is shown to be of the same order as that of betweenness centrality. We demonstrate the usage of percolation centrality by applying it to a canonical network as well as simulated and real world scale-free and random networks.

 

Piraveenan M, Prokopenko M, Hossain L (2013) Percolation Centrality: Quantifying Graph-Theoretic Impact of Nodes during Percolation in Networks. PLoS ONE 8(1): e53095. doi:10.1371/journal.pone.0053095

 


Via Complexity Digest
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Engineers solve a biological mystery and boost artificial intelligence

Engineers solve a biological mystery and boost artificial intelligence | Social Foraging | Scoop.it
By simulating 25,000 generations of evolution within computers, Cornell University engineering and robotics researchers have discovered why biological networks tend to be organized as modules -- a finding that will lead to a deeper understanding of the evolution of complexity.

 

The new insight also will help evolve artificial intelligence, so robot brains can acquire the grace and cunning of animals.

 

From brains to gene regulatory networks, many biological entities are organized into modules -- dense clusters of interconnected parts within a complex network. For decades biologists have wanted to know why humans, bacteria and other organisms evolved in a modular fashion. Like engineers, nature builds things modularly by building and combining distinct parts, but that does not explain how such modularity evolved in the first place. Renowned biologists Richard Dawkins, Günter P. Wagner, and the late Stephen Jay

Gould identified the question of modularity as central to the debate over "the evolution of complexity."

 

For years, the prevailing assumption was simply that modules evolved because entities that were modular could respond to change more quickly, and therefore had an adaptive advantage over their non-modular competitors. But that may not be enough to explain the origin of the phenomena.

 

The team discovered that evolution produces modules not because they produce more adaptable designs, but because modular designs have fewer and shorter network connections, which are costly to build and maintain. As it turned out, it was enough to include a "cost of wiring" to make evolution favor modular architectures.

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Jose Santos's curator insight, May 26, 2013 11:54 AM

another role for modularity in network design

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Scientists build the One Million Dollar man

Scientists build the One Million Dollar man | Social Foraging | Scoop.it

Scientists have built a man from artificial limbs, and while he might not be a bionic superhero, he cost a lot less to create than The Six Million Dollar Man.

 

One million dollar Rex – short for robotic exoskeletons – was built using the most advanced artificial limbs and organs from across the world.

 

And he shows that from bionic arms and legs to artificial organs, science is beginning to catch up with science fiction in the race to replace body parts with man-made alternatives.

 

In the 70s TV series The Six Million Dollar Man astronaut Steve Austin, played by Lee Majors, was left horribly injured after his craft crashed and was given a bionic arm and legs and an artificial zoom-lens eye.

 

6ft Rex also raises ethical dilemmas, as research on advanced prosthetic arms and legs, as well as artificial eyes, hearts, lungs - and even hybrids between computer chips and living brains - means that scientists can not only replace body parts but may even be able to improve on human abilities.

 

This has led scientists to warn against creating a modern Frankenstein.

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PABLO SILVA's curator insight, November 27, 2013 12:28 AM

LOS SERES HUMANOS TRATAMOS DE CONSTRUIR ROBOTS SEMEJANTES A NOSOTROS PORQUE NO PODEMOS CONVIVIR CON ESPECIES QUE NO SEAN IGUALES, SE CREARIA UNA INCOMODIDAD CONSTANTE 

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Europeans to Fund Billion-euro Human Brain Project

Nature Magazine reports that the European Commission has awarded up to €1 billion in research funding for the Human Brain Project led by neuroscientist Henry Markram. And while the official announcement is not expected until January 28, part of the project will be dedicated to the development of a exaflop supercomputer that will be used for the simulation of the brain model.

 

Brain researchers are generating 60,000 papers per year,” said Markram as he explained the concept in Bern. “They’re all beautiful, fantastic studies — but all focused on their one little corner: this molecule, this brain region, this function, this map.” The HBP would integrate these discoveries, he said, and create models to explore how neural circuits are organized, and how they give rise to behaviour and cognition — among the deepest mysteries in neuroscience. Ultimately, said Markram, the HBP would even help researchers to grapple with disorders such as Alzheimer’s disease. “If we don’t have an integrated view, we won’t understand these diseases,” he declared.

 

The Human Brain Project is one of the two winner projects of the Future and Emerging Technologies Flagship competition launched by the European Commission, the other one being the “Graphene” project led by Swedish theoretical physicist Jari Kinaret.
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Dataset of 13 billion clicks available | Center for Complex Networks and Systems Research

Dataset of 13 billion clicks available | Center for Complex Networks and Systems Research | Social Foraging | Scoop.it

To foster the study of the structure and dynamics of Web traffic networks, we are making available to the research community a large Click Dataset of about 13 billion HTTP requests collected at Indiana University. During about seven months of collection in 2006-2007, our system generated data at a rate of about 60 million requests per day, or about 30 GB/day of raw data. We hope that this data will help develop a better understanding of user behavior online and create more realistic models of Web traffic. The potential applications of this data include improved designs for networks, sites, and server software; more accurate forecasting of traffic trends; classification of sites based on the patterns of activity they inspire; and improved ranking algorithms for search results.


Via Complexity Digest, Spaceweaver
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Fil Menczer's comment, January 31, 2013 9:24 AM
Actually it turns out the dataset has 53+ billion records and it spans until 2010.
Scooped by Ashish Umre
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Storing Digital Data in DNA

Storing Digital Data in DNA | Social Foraging | Scoop.it

Scientists have stored audio and text on fragments of DNA and then retrieved them with near-perfect fidelity—a technique that eventually may provide a way to handle the overwhelming data of the digital age.

 

The scientists encoded in DNA—the recipe of life—an audio clip of Martin Luther King Jr.'s "I Have a Dream" speech, a photograph, a copy of Francis Crick and James Watson's famous "double helix" scientific paper on DNA from 1953 and Shakespeare's 154 sonnets. They later were able to retrieve them with 99.99% accuracy.

 

The experiment was reported Wednesday in the journal Nature.

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