3,964 research outputs found
Functional cartography of complex metabolic networks
High-throughput techniques are leading to an explosive growth in the size of
biological databases and creating the opportunity to revolutionize our
understanding of life and disease. Interpretation of these data remains,
however, a major scientific challenge. Here, we propose a methodology that
enables us to extract and display information contained in complex networks.
Specifically, we demonstrate that one can (i) find functional modules in
complex networks, and (ii) classify nodes into universal roles according to
their pattern of intra- and inter-module connections. The method thus yields a
``cartographic representation'' of complex networks. Metabolic networks are
among the most challenging biological networks and, arguably, the ones with
more potential for immediate applicability. We use our method to analyze the
metabolic networks of twelve organisms from three different super-kingdoms. We
find that, typically, 80% of the nodes are only connected to other nodes within
their respective modules, and that nodes with different roles are affected by
different evolutionary constraints and pressures. Remarkably, we find that
low-degree metabolites that connect different modules are more conserved than
hubs whose links are mostly within a single module.Comment: 17 pages, 4 figures. Go to http://amaral.northwestern.edu for the PDF
file of the reprin
Size reduction of complex networks preserving modularity
The ubiquity of modular structure in real-world complex networks is being the
focus of attention in many trials to understand the interplay between network
topology and functionality. The best approaches to the identification of
modular structure are based on the optimization of a quality function known as
modularity. However this optimization is a hard task provided that the
computational complexity of the problem is in the NP-hard class. Here we
propose an exact method for reducing the size of weighted (directed and
undirected) complex networks while maintaining invariant its modularity. This
size reduction allows the heuristic algorithms that optimize modularity for a
better exploration of the modularity landscape. We compare the modularity
obtained in several real complex-networks by using the Extremal Optimization
algorithm, before and after the size reduction, showing the improvement
obtained. We speculate that the proposed analytical size reduction could be
extended to an exact coarse graining of the network in the scope of real-space
renormalization.Comment: 14 pages, 2 figure
Efficiency and response of conilon coffee genotypes to nitrogen supply
The objective of the study was to differentiate genotypes with higher efficiency and responsiveness to nitrogen supply, to understand how the nitrogen supply can impact the dry matter allocation and the accumulation of this nutrient in the different plant compartments of genotypes of conilon coffee, cultivated under contrasting conditions of nitrogen availability in the soil. The plants were cultivated during 150 days in pots containing 10 kg of soil, in greenhouse. The experiment was set up in a 13×2 factorial scheme, following a completely randomized design (CRD) with three replications. The factors were: 13 genotypes and two levels of nitrogen fertilization (0 and 100% of the N recommended level). The N supply increased between 70 and 210% of the total dry matter and between 360 and 680% of the concentration of N content in leaves of the genotypes of conilon coffee. It was possible to observe that the expression of the genotypes was modulated by the availability of N in the soil, since they presented different behaviors in the studied environments (with 0 or 100% of N supply in the soil). The genotypes CV-03, CV-07 and CV-08 were classified as non-efficient and non-responsive, while the genotypes CV- 01, CV-04 and CV-09 of conilon coffee were classified as efficient and responsive.Keywords: Alpha parameter, Coffea canephora (Pierre ex A. Froehner), mineral nutritio
Hierarchical Organization in Complex Networks
Many real networks in nature and society share two generic properties: they
are scale-free and they display a high degree of clustering. We show that these
two features are the consequence of a hierarchical organization, implying that
small groups of nodes organize in a hierarchical manner into increasingly large
groups, while maintaining a scale-free topology. In hierarchical networks the
degree of clustering characterizing the different groups follows a strict
scaling law, which can be used to identify the presence of a hierarchical
organization in real networks. We find that several real networks, such as the
World Wide Web, actor network, the Internet at the domain level and the
semantic web obey this scaling law, indicating that hierarchy is a fundamental
characteristic of many complex systems
Finding and evaluating community structure in networks
We propose and study a set of algorithms for discovering community structure
in networks -- natural divisions of network nodes into densely connected
subgroups. Our algorithms all share two definitive features: first, they
involve iterative removal of edges from the network to split it into
communities, the edges removed being identified using one of a number of
possible "betweenness" measures, and second, these measures are, crucially,
recalculated after each removal. We also propose a measure for the strength of
the community structure found by our algorithms, which gives us an objective
metric for choosing the number of communities into which a network should be
divided. We demonstrate that our algorithms are highly effective at discovering
community structure in both computer-generated and real-world network data, and
show how they can be used to shed light on the sometimes dauntingly complex
structure of networked systems.Comment: 16 pages, 13 figure
Network 'small-world-ness': a quantitative method for determining canonical network equivalence
Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified.
Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process.
Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing
Lethality and centrality in protein networks
In this paper we present the first mathematical analysis of the protein
interaction network found in the yeast, S. cerevisiae. We show that, (a) the
identified protein network display a characteristic scale-free topology that
demonstrate striking similarity to the inherent organization of metabolic
networks in particular, and to that of robust and error-tolerant networks in
general. (b) the likelihood that deletion of an individual gene product will
prove lethal for the yeast cell clearly correlates with the number of
interactions the protein has, meaning that highly-connected proteins are more
likely to prove essential than proteins with low number of links to other
proteins. These results suggest that a scale-free architecture is a generic
property of cellular networks attributable to universal self-organizing
principles of robust and error-tolerant networks and that will likely to
represent a generic topology for protein-protein interactions.Comment: See also http:/www.nd.edu/~networks and
http:/www.nd.edu/~networks/cel
Conservation of geosites as a tool to protect geoheritage: the inventory of Ceará Central Domain, Borborema Province - NE/Brazil
The Ceará Central Domain, in the northern Borborema Province/NE Brazil, encompasses important geological records (geosites) which allow understanding a relevant period of the Earth’s evolution, mainly associated to Neoproterozoic Brazilian/Pan-African Cycle and West Gondwana amalgamation, besides Neoarchean to Ordovician records. The presented geoheritage inventory aims to characterise the geosites with scienti c relevance of Ceará Central Domain. By applying a method for large areas, the nal selection resulted in eight geological frameworks represented by 52 geosites documented in a single database. This is the rst step for a geoconservation strategy based on systematic inventories, statutory protection, geoethical behaviour and awareness about scienti c, educational and/or cultural relevance of geosites.We specially thank all experts that helped us with
this inventory: Afonso Almeida, Carlos E.G. de
Araújo, César Veríssimo, Christiano Magini, Clóvis
Vaz Parente, Felipe G. Costa, Irani C. Mattos,
Neivaldo de Castro, Otaciel de Melo, Sebástian G.
Chiozza, Ticiano Santos and Stefano Zincone. We
are also thankful to Kátia Mansur, Ricardo Fraga
Pereira and anonymous reviewers for their valuable
contributions. PM is grateful to Coordenação de
Aperfeiçoamento de Pessoal de Nível Superior
(CAPES) for PhD mobility scholarship PDSE
Program/Process n 88881.132168/2016-01info:eu-repo/semantics/publishedVersio
Search for a Fourth-Generation Quark More Massive than the Z0 Boson in ppbar Collisions at sqrt(s) = 1.8 TeV
We present the results of a search for pair production of a fourth-generation
charge -1/3 quark (b') in sqrt(s)=1.8 TeV ppbar collisions using 88 pb^(-1) of
data obtained with the Collider Detector at Fermilab. We assume that both
quarks decay via the flavor-changing neutral current process b' -> bZ and that
the b' mass is greater than m_Z + m_b. We studied the decay mode b'b'bar -> ZZ
b bbar where one Z0 decays into e^+e^- or mu^+ mu^- and the other decays
hadronically, giving a signature of two leptons plus jets. An upper limit on
the cross section of ppbar -> b'b'bar times [BR (b' -> bZ)]^2 is established as
a function of the b' mass. We exclude at 95% confidence level a b' quark with
mass between 100 and 199 GeV/c^2 for BR(b' -> bZ) = 100%.Comment: 12 pages, 2 figures, submitted to Phys. Rev. Letters on 9/12/9
Search for the Supersymmetric Partner of the Top-Quark in Collisions at
We report on a search for the supersymmetric partner of the top quark (stop)
produced in events using of
collisions at recorded with the Collider Detector at
Fermilab. In the case of a light stop squark, the decay of the top quark into
stop plus the lightest supersymmetric particle (LSP) could have a significant
branching ratio. The observed events are consistent with Standard Model production and decay. Hence, we set limits on the branching ratio of
the top quark decaying into stop plus LSP, excluding branching ratios above 45%
for a LSP mass up to 40 {\rm GeV/c}.Comment: 11 pages, 4 figure
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