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## What's in a crowd? Analysis of face-to-face behavioral networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

#Physics - Physics and Society#Computer Science - Human-Computer Interaction#Nonlinear Sciences - Adaptation and Self-Organizing Systems#Quantitative Biology - Other Quantitative Biology

The availability of new data sources on human mobility is opening new avenues
for investigating the interplay of social networks, human mobility and
dynamical processes such as epidemic spreading. Here we analyze data on the
time-resolved face-to-face proximity of individuals in large-scale real-world
scenarios. We compare two settings with very different properties, a scientific
conference and a long-running museum exhibition. We track the behavioral
networks of face-to-face proximity, and characterize them from both a static
and a dynamic point of view, exposing important differences as well as striking
similarities. We use our data to investigate the dynamics of a
susceptible-infected model for epidemic spreading that unfolds on the dynamical
networks of human proximity. The spreading patterns are markedly different for
the conference and the museum case, and they are strongly impacted by the
causal structure of the network data. A deeper study of the spreading paths
shows that the mere knowledge of static aggregated networks would lead to
erroneous conclusions about the transmission paths on the dynamical networks.

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## Phase transition in a class of non-linear random networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

#Nonlinear Sciences - Adaptation and Self-Organizing Systems#Quantitative Biology - Other Quantitative Biology

We discuss the complex dynamics of a non-linear random networks model, as a
function of the connectivity k between the elements of the network. We show
that this class of networks exhibit an order-chaos phase transition for a
critical connectivity k = 2. Also, we show that both, pairwise correlation and
complexity measures are maximized in dynamically critical networks. These
results are in good agreement with the previously reported studies on random
Boolean networks and random threshold networks, and show once again that
critical networks provide an optimal coordination of diverse behavior.; Comment: 9 pages, 3 figures, revised version

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## Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 09/09/2015
Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Tissues and Organs#Quantitative Biology - Populations and Evolution#Quantitative Biology - Quantitative Methods

Scientists have long sought to understand how vascular networks supply blood
and oxygen to cells throughout the body. Recent work focuses on principles that
constrain how vessel size changes through branching generations from the aorta
to capillaries and uses scaling exponents to quantify these changes. Prominent
scaling theories predict that combinations of these exponents explain how
metabolic, growth, and other biological rates vary with body size.
Nevertheless, direct measurements of individual vessel segments have been
limited because existing techniques for measuring vasculature are invasive,
time consuming, and technically difficult. We developed software that extracts
the length, radius, and connectivity of in vivo vessels from contrast-enhanced
3D Magnetic Resonance Angiography. Using data from 20 human subjects, we
calculated scaling exponents by four methods--two derived from local properties
of branching junctions and two from whole-network properties. Although these
methods are often used interchangeably in the literature, we do not find
general agreement between these methods, particularly for vessel lengths.
Measurements for length of vessels also diverge from theoretical values, but
those for radius show stronger agreement. Our results demonstrate that vascular
network models cannot ignore certain complexities of real vascular systems and
indicate the need to discover new principles regarding vessel lengths.

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## Evolution of networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.68%

We review the recent fast progress in statistical physics of evolving
networks. Interest has focused mainly on the structural properties of random
complex networks in communications, biology, social sciences and economics. A
number of giant artificial networks of such a kind came into existence
recently. This opens a wide field for the study of their topology, evolution,
and complex processes occurring in them. Such networks possess a rich set of
scaling properties. A number of them are scale-free and show striking
resilience against random breakdowns. In spite of large sizes of these
networks, the distances between most their vertices are short -- a feature
known as the ``small-world'' effect. We discuss how growing networks
self-organize into scale-free structures and the role of the mechanism of
preferential linking. We consider the topological and structural properties of
evolving networks, and percolation in these networks. We present a number of
models demonstrating the main features of evolving networks and discuss current
approaches for their simulation and analytical study. Applications of the
general results to particular networks in Nature are discussed. We demonstrate
the generic connections of the network growth processes with the general
problems of non-equilibrium physics...

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## Neutral Networks of Sequence to Shape Maps

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Quantitative Methods#Mathematical Physics#Mathematics - Combinatorics#Quantitative Biology - Biomolecules

In this paper we present a novel framework for sequence to shape maps. These
combinatorial maps realize exponentially many shapes, and have preimages which
contain extended connected subgraphs of diameter n (neutral networks). We prove
that all basic properties of RNA folding maps also hold for combinatorial maps.
Our construction is as follows: suppose we are given a graph $H$ over the $\{1
>...,n\}$ and an alphabet of nucleotides together with a symmetric relation
$\mathcal{R}$, implied by base pairing rules. Then the shape of a sequence of
length n is the maximal H subgraph in which all pairs of nucleotides incident
to H-edges satisfy $\mathcal{R}$. Our main result is to prove the existence of
at least $\sqrt{2}^{n-1}$ shapes with extended neutral networks, i.e. shapes
that have a preimage with diameter $n$ and a connected component of size at
least $(\frac{1+\sqrt{5}}{2})^n+(\frac{1-\sqrt{5}}{2})^n$. Furthermore, we show
that there exists a certain subset of shapes which carries a natural graph
structure. In this graph any two shapes are connected by a path of shapes with
respective neutral networks of distance one. We finally discuss our results and
provide a comparison with RNA folding maps.; Comment: 24 pages,4 figures

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## Spreading dynamics on small-world networks with connectivity fluctuations and correlations

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Populations and Evolution#Condensed Matter - Disordered Systems and Neural Networks#Physics - Physics and Society#Quantitative Biology - Quantitative Methods

Infectious diseases and computer malwares spread among humans and computers
through the network of contacts among them. These networks are characterized by
wide connectivity fluctuations, connectivity correlations and the small-world
property. In a previous work [A. Vazquez, Phys. Rev. Lett. 96, 038702 (2006)] I
have shown that the connectivity fluctuations together with the small-world
property lead to a novel spreading law, characterized by an initial power law
growth with an exponent determined by the average node distance on the network.
Here I extend these results to consider the influence of connectivity
correlations which are generally observed in real networks. I show that
assortative and disassortative connectivity correlations enhance and diminish,
respectively, the range of validity of this spreading law. As a corollary I
obtain the region of connectivity fluctuations and degree correlations
characterized by the absence of an epidemic threshold. These results are
relevant for the spreading of infectious diseases, rumors, and information
among humans and the spreading of computer viruses, email worms and hoaxes
among computer users.; Comment: 10 pages, 1 figure, RevTex. Phys. Rev. E (In press)

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## Structural distance and evolutionary relationship of networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Quantitative Methods#Condensed Matter - Statistical Mechanics#Physics - Data Analysis, Statistics and Probability#Quantitative Biology - Populations and Evolution

Evolutionary mechanism in a self-organized system cause some functional
changes that force to adapt new conformation of the interaction pattern between
the components of that system. Measuring the structural differences one can
retrace the evolutionary relation between two systems. We present a method to
quantify the topological distance between two networks of different sizes,
finding that the architectures of the networks are more similar within the same
class than the outside of their class. With 43 cellular networks of different
species, we show that the evolutionary relationship can be elucidated from the
structural distances.; Comment: 16 pages, 6 figures, 1 table

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## Two metrics for general phylogenetic networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 15/01/2008
Português

Relevância na Pesquisa

45.69%

We prove that Nakhleh's latest dissimilarity measure for phylogenetic
networks separates distinguishable phylogenetic networks, and that a slight
modification of it provides a true distance on the class of all phylogenetic
networks.; Comment: 9 pages

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## BiMAT: a MATLAB(R) package to facilitate the analysis and visualization of bipartite networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

The statistical analysis of the structure of bipartite ecological networks
has increased in importance in recent years. Yet, both algorithms and software
packages for the analysis of network structure focus on properties of
unipartite networks. In response, we describe BiMAT, an object-oriented MATLAB
package for the study of the structure of bipartite ecological networks. BiMAT
can analyze the structure of networks, including features such as modularity
and nestedness, using a selection of widely-adopted algorithms. BiMAT also
includes a variety of null models for evaluating the statistical significance
of network properties. BiMAT is capable of performing multi-scale analysis of
structure - a potential (and under-examined) feature of many biological
networks. Finally, BiMAT relies on the graphics capabilities of MATLAB to
enable the visualization of the statistical structure of bipartite networks in
either matrix or graph layout representations. BiMAT is available as an
open-source package at http://ecotheory.biology.gatech.edu/cflores.; Comment: 15 pages, 5 figures. Plan to be submitted to a Journal

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## Perfect Sampling of the Master Equation for Gene Regulatory Networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

We present a Perfect Sampling algorithm that can be applied to the Master
Equation of Gene Regulatory Networks (GRNs). The method recasts Gillespie's
Stochastic Simulation Algorithm (SSA) in the light of Markov Chain Monte Carlo
methods and combines it with the Dominated Coupling From The Past (DCFTP)
algorithm to provide guaranteed sampling from the stationary distribution. We
show how the DCFTP-SSA can be generically applied to genetic networks with
feedback formed by the interconnection of linear enzymatic reactions and
nonlinear Monod- and Hill-type elements. We establish rigorous bounds on the
error and convergence of the DCFTP-SSA, as compared to the standard SSA,
through a set of increasingly complex examples. Once the building blocks for
GRNs have been introduced, the algorithm is applied to study properly averaged
dynamic properties of two experimentally relevant genetic networks: the toggle
switch, a two-dimensional bistable system, and the repressilator, a
six-dimensional genetic oscillator.; Comment: Minor rewriting; final version to be published in Biophysical Journal

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## Evolutionary and Ecological Trees and Networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 30/03/2007
Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Populations and Evolution#Condensed Matter - Statistical Mechanics#Quantitative Biology - Quantitative Methods

Evolutionary relationships between species are usually represented in
phylogenies, i.e. evolutionary trees, which are a type of networks. The
terminal nodes of these trees represent species, which are made of individuals
and populations among which gene flow occurs. This flow can also be represented
as a network. In this paper we briefly show some properties of these complex
networks of evolutionary and ecological relationships. First, we characterize
large scale evolutionary relationships in the Tree of Life by a degree
distribution. Second, we represent genetic relationships between individuals of
a Mediterranean marine plant, Posidonia oceanica, in terms of a Minimum
Spanning Tree. Finally, relationships among plant shoots inside populations are
represented as networks of genetic similarity.; Comment: 6 pages, 5 figures. To appear in Proceedings of the Medyfinol06
Conference

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## Modeling Endogenous Social Networks: the Example of Emergence and Stability of Cooperation without Refusal

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 19/12/2005
Português

Relevância na Pesquisa

45.7%

#Nonlinear Sciences - Adaptation and Self-Organizing Systems#Condensed Matter - Other Condensed Matter#Computer Science - Computer Science and Game Theory#Computer Science - Multiagent Systems#Computer Science - Other Computer Science#Quantitative Biology - Other Quantitative Biology#Quantitative Biology - Populations and Evolution

Aggregated phenomena in social sciences and economics are highly dependent on
the way individuals interact. To help understanding the interplay between
socio-economic activities and underlying social networks, this paper studies a
sequential prisoner's dilemma with binary choice. It proposes an analytical and
computational insight about the role of endogenous networks in emergence and
sustainability of cooperation and exhibits an alternative to the choice and
refusal mechanism that is often proposed to explain cooperation. The study
focuses on heterogeneous equilibriums and emergence of cooperation from an
all-defector state that are the two stylized facts that this model successfully
reconstructs.; Comment: 36 p

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## Density-based and transport-based core-periphery structures in networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.71%

#Physics - Physics and Society#Condensed Matter - Disordered Systems and Neural Networks#Computer Science - Social and Information Networks#Quantitative Biology - Other Quantitative Biology

Networks often possess mesoscale structures, and studying them can yield
insights into both structure and function. It is most common to study community
structure, but numerous other types of mesoscale structures also exist. In this
paper, we examine core-periphery structures based on both density and
transport. In such structures, core network components are well-connected both
among themselves and to peripheral components, which are not well-connected to
anything. We examine core-periphery structures in a wide range of examples of
transportation, social, and financial networks---including road networks in
large urban areas, a rabbit warren, a dolphin social network, a European
interbank network, and a migration network between counties in the United
States. We illustrate that a recently developed transport-based notion of node
coreness is very useful for characterizing transportation networks. We also
generalize this notion to examine core versus peripheral edges, and we show
that the resulting diagnostic is also useful for transportation networks. To
examine the properties of transportation networks further, we develop a family
of generative models of roadlike networks. We illustrate the effect of the
dimensionality of the embedding space on transportation networks...

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## Criticality of spreading dynamics in hierarchical cluster networks without inhibition

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 18/02/2008
Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Neurons and Cognition#Physics - Physics and Society#Quantitative Biology - Populations and Evolution

An essential requirement for the representation of functional patterns in
complex neural networks, such as the mammalian cerebral cortex, is the
existence of stable network activations within a limited critical range. In
this range, the activity of neural populations in the network persists between
the extremes of quickly dying out, or activating the whole network. The nerve
fiber network of the mammalian cerebral cortex possesses a modular organization
extending across several levels of organization. Using a basic spreading model
without inhibition, we investigated how functional activations of nodes
propagate through such a hierarchically clustered network. The simulations
demonstrated that persistent and scalable activation could be produced in
clustered networks, but not in random networks of the same size. Moreover, the
parameter range yielding critical activations was substantially larger in
hierarchical cluster networks than in small-world networks of the same size.
These findings indicate that a hierarchical cluster architecture may provide
the structural basis for the stable and diverse functional patterns observed in
cortical networks.

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## Epidemic spreading in evolving networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 22/01/2010
Português

Relevância na Pesquisa

45.69%

#Physics - Physics and Society#Condensed Matter - Statistical Mechanics#Quantitative Biology - Other Quantitative Biology

A model for epidemic spreading on rewiring networks is introduced and
analyzed for the case of scale free steady state networks. It is found that
contrary to what one would have naively expected, the rewiring process
typically tends to suppress epidemic spreading. In particular it is found that
as in static networks, rewiring networks with degree distribution exponent
$\gamma >3$ exhibit a threshold in the infection rate below which epidemics die
out in the steady state. However the threshold is higher in the rewiring case.
For $2<\gamma \leq 3$ no such threshold exists, but for small infection rate
the steady state density of infected nodes (prevalence) is smaller for rewiring
networks.; Comment: 7 pages, 7 figures

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## Systems biology beyond degree, hubs and scale-free networks: the case for multiple metrics in complex networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.71%

#Quantitative Biology - Quantitative Methods#Condensed Matter - Statistical Mechanics#Computer Science - Social and Information Networks#Physics - Physics and Society

Modeling and topological analysis of networks in biological and other complex
systems, must venture beyond the limited consideration of very few network
metrics like degree, betweenness or assortativity. A proper identification of
informative and redundant entities from many different metrics, using recently
demonstrated techniques, is essential. A holistic comparison of networks and
growth models is best achieved only with the use of such methods.; Comment: To appear in Systems and Synthetic Biology (Springer)

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## Modelling slowly changing dynamic gene-regulatory networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 12/05/2012
Português

Relevância na Pesquisa

45.7%

Dynamic gene-regulatory networks are complex since the number of potential
components involved in the system is very large. Estimating dynamic networks is
an important task because they compromise valuable information about
interactions among genes. Graphical models are a powerful class of models to
estimate conditional independence among random variables, e.g. interactions in
dynamic systems. Indeed, these interactions tend to vary over time. However,
the literature has been focused on static networks, which can only reveal
overall structures. Time-course experiments are performed in order to tease out
significant changes in networks. It is typically reasonable to assume that
changes in genomic networks are few because systems in biology tend to be
stable. We introduce a new model for estimating slowly changes in dynamic
gene-regulatory networks which is suitable for a high-dimensional dataset, e.g.
time-course genomic data. Our method is based on i) the penalized likelihood
with $\ell_1$-norm, ii) the penalized differences between conditional
independence elements across time points and iii) the heuristic search strategy
to find optimal smoothing parameters. We implement a set of linear constraints
necessary to estimate sparse graphs and penalized changing in dynamic networks.
These constraints are not in the linear form. For this reason...

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## Quantifying Stochastic Effects in Biochemical Reaction Networks using Partitioned Leaping

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Subcellular Processes#Physics - Chemical Physics#Quantitative Biology - Quantitative Methods

"Leaping" methods show great promise for significantly accelerating
stochastic simulations of complex biochemical reaction networks. However, few
practical applications of leaping have appeared in the literature to date.
Here, we address this issue using the "partitioned leaping algorithm" (PLA)
[L.A. Harris and P. Clancy, J. Chem. Phys. 125, 144107 (2006)], a
recently-introduced multiscale leaping approach. We use the PLA to investigate
stochastic effects in two model biochemical reaction networks. The networks
that we consider are simple enough so as to be accessible to our intuition but
sufficiently complex so as to be generally representative of real biological
systems. We demonstrate how the PLA allows us to quantify subtle effects of
stochasticity in these systems that would be difficult to ascertain otherwise
as well as not-so-subtle behaviors that would strain commonly-used "exact"
stochastic methods. We also illustrate bottlenecks that can hinder the approach
and exemplify and discuss possible strategies for overcoming them. Overall, our
aim is to aid and motivate future applications of leaping by providing stark
illustrations of the benefits of the method while at the same time elucidating
obstacles that are often encountered in practice.; Comment: v3: Final accepted version. 15 pages...

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## Stochastic models and numerical algorithms for a class of regulatory gene networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 01/10/2008
Português

Relevância na Pesquisa

45.69%

Regulatory gene networks contain generic modules like those involving
feedback loops, which are essential for the regulation of many biological
functions. We consider a class of self-regulated genes which are the building
blocks of many regulatory gene networks, and study the steady state
distributions of the associated Gillespie algorithm by providing efficient
numerical algorithms. We also study a regulatory gene network of interest in
synthetic biology and in gene therapy, using mean-field models with time
delays. Convergence of the related time-nonhomogeneous Markov chain is
established for a class of linear catalytic networks with feedback loops

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## Starling flock networks manage uncertainty in consensus at low cost

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 13/02/2013
Português

Relevância na Pesquisa

45.69%

#Quantitative Biology - Populations and Evolution#Nonlinear Sciences - Adaptation and Self-Organizing Systems#Physics - Biological Physics#Quantitative Biology - Quantitative Methods

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...

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