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UNLABELLED: In this paper, we review the central concepts and implementations of tools for working with network structures in Bioconductor. Interfaces to open source resources for visualization (AT&T Graphviz) and network algorithms (Boost) have been developed to support analysis of graphical structures in genomics and computational biology. AVAILABILITY: Packages graph, Rgraphviz, RBGL of Bioconductor (www.bioconductor.org).
OBJECTIVE: To describe, analyse and discuss the activities in the Network of Community Activities of the Programme of Community Activities in Primary Care of the Spanish Society of Family and Community Medicine. DESIGN: Description of the activities within this Network.Setting. Network of Community Activities of the Spanish Society of Family and Community Medicine. MAIN MEASUREMENTS: Specifications of the variables of geography, target population and experience descriptives were obtained from the qualitative analysis of the activity summary composed by its authors. The measurements are frequency tables expressed in graphs and analysis of the summaries contributed by the groups on objectives, kinds of programme, methodologies, evaluation and conclusions reached. The community orientation activities undertaken by the health centres registered on the Network came mostly (54%) from the autonomous communities of Madrid and Andalusia. A great many of them were aimed at the adult population, tackling problems of chronic diseases, and particularly at women, in this case tackling gender themes such as menopause and pregnancy, etc. CONCLUSIONS: There was uneven distribution between autonomous communities of the experiences included on the web. Central to community orientation are the replies to questions such as: inside or out of the health centre?, the importance of transferring leadership to society, and adaptation to the needs and demands of the population cared for.
In this paper, introducing stochastic dynamics into an optimal competitive Hopfield network model (OCHOM), we propose a new algorithm that permits temporary energy increases which helps the OCHOM escape from local minima. The goal of the maximum cut problem, which is an NP-complete problem, is to partition the node set of an undirected graph into two parts in order to maximize the cardinality of the set of edges cut by the partition. The problem has many important applications including the design of VLSI circuits and design of communication networks. Recently, Galán-Marín et al. proposed the OCHOM, which can guarantee convergence to a global/local minimum of the energy function, and performs better than the other competitive neural approaches. However, the OCHOM has no mechanism to escape from local minima. The proposed algorithm introduces stochastic dynamics which helps the OCHOM escape from local minima, and it is applied to the maximum cut problem. A number of instances have been simulated to verify the proposed algorithm.
Most recent models of the immune network are based upon a phenomenological log bell-shaped interaction function. This function depends on a single parameter, the "field," which is the sum of all ligand concentrations weighted by their respective affinities. The typical behavior of these models is dominated by percolation, a phenomenon in which a local stimulus spreads globally throughout the network. The usual reason for employing a log bell-shaped interaction function is that B cells are activated by cross-linking of their surface immunoglobulin receptors. Here we formally derive a new phenomenological log bell-shaped function from the chemistry of receptor cross-linking by bivalent ligand. Specifying how this new function depends on the ligand concentrations requires two fields: a binding field and a cross-linking field. When we compare the activation functions for ligand-receptor pairs with different affinities, the one-field and the two-field functions differ markedly. In the case of the one-field activation function, its graph is shifted to increasingly higher concentration as the affinity decreases but keeps its width and height. In the case of the two-field activation function, the graph of a low-affinity interaction is nested within the graphs of all higher-affinity interactions. We show that this difference in the relations among activation functions for different affinities radically changes the network behavior. In models that described B cell proliferation using the one-field activation function, network behavior was dominated by low-affinity interactions. Conversely, in our new model, the high-affinity interactions are the most significant. As a consequence, percolation is no longer the only typical network behavior.
The goal of generalized logical analysis is to model complex biological systems, especially so-called regulatory systems, such as genetic networks. This theory is mainly characterized by its capacity to find all the steady states of a given system and the functional positive and negative circuits, which generate multistationarity and a cycle in the state sequence graph, respectively. So far, this has been achieved by exhaustive enumeration, which severely limits the size of the systems that can be analysed. In this paper, we introduce a mathematical function, called image function, which allows the calculation of the value of the logical parameter associated with a logical variable depending on the state of the system. Thus the state table of the system is represented analytically. We then show how all steady states can be derived as solutions to a system of steady-state equations. Constraint programming, a recent method for solving constraint satisfaction problems, is applied for that purpose. To illustrate the potential of our approach, we present results from computer experiments carried out on very large randomly-generated systems (graphs) with hundreds, or even thousands, of interacting components, and show that these systems can be solved using moderate computing time. Moreover, we illustrate the approach through two published applications, one of which concerns the computation times of all steady states for a large genetic network.
eLoom is an open source graph simulation software tool, developed at the University of New Mexico (UNM), that enables users to specify and simulate neural network models. Its specification language and libraries enables users to construct and simulate arbitrary, potentially hierarchical network structures on serial and parallel processing systems. In addition, eLoom is integrated with UNM's Flatland, an open source virtual environments development tool to provide real-time visualizations of the network structure and activity. Visualization is a useful method for understanding both learning and computation in artificial neural networks. Through 3D animated pictorially representations of the state and flow of information in the network, a better understanding of network functionality is achieved. ART-1, LAPART-II, MLP, and SOM neural networks are presented to illustrate eLoom and Flatland's capabilities.
UNLABELLED: We have developed several new navigation features for a Java graph applet previously released for visualizing protein-protein interactions. This graph viewer can be used to navigate any molecular interactome dataset. We have successfully implemented this tool for exploring protein networks stored in the Bioverse interaction database. AVAILABILITY: http://bioverse.compbio.washington.edu/viewer CONTACT: ram@compbio.washington.edu.
The concept of scopes is applied to analyse large metabolic networks. Scopes are defined as sets of metabolites that can be synthesised by a metabolic network when it is provided with given seeds (Sets of initial metabolic compounds). Thus, scopes represent synthesising capacities of the seeds in the network. A hierarchy is discussed in the sense that compounds, which are part of the scope of another compound, possess scopes themselves that are subsets of the former scope. This hierarchy is analysed by means of a directed acyclic graph. Using a simple chemical model, it is found that this hierarchy contains specific structures that can, to a large extent, be explained by the chemical composition of the participating compounds. In this way, it represents a new kind of map of metabolic networks, arranging the metabolic compounds according to their chemical capacity.
The title compound, [Fe(C5H5)(C10H7O2S)], an important precursor en route to organometallic donor-pi-acceptor systems, forms dimers in the solid state through cyclic intermolecular carboxylic acid O-H...O hydrogen bonds, graph set R2(2)(8) [O...O 2.661 (2) A and O-H...O 175 degrees ]. Intermolecular C(Cp)-H...pi(Cp) interactions between the unsubstituted cyclopentadienyl (Cp) rings and C(thiazole)-H...pi(Cp) interactions link neighbouring molecules into a three-dimensional network [C...Cg 3.753 (7) A and C-H...Cg 156 degrees, and C...Cg 3.687 (3) A and C-H...Cg 129 degrees; Cg is the ring centroid]. Intramolecular C-H...O interactions are present, graph set S(7) [C...O 2.925 (3) A and C-H...O 120 degrees, and the closest C-H...S(thienyl) contact has a C...S distance of 3.058 (2) A].
MOTIVATION: A noble and ultimate objective of phyloinformatic research is to assemble, synthesize, and explore the evolutionary history of life on earth. Data mining methods for performing these tasks are not yet well developed, but one avenue of research suggests that network connectivity dynamics will play an important role in future methods. Analysis of disordered networks, such as small-world networks, has applications as diverse as disease propagation, collaborative networks, and power grids. Here we apply similar analyses to networks of phylogenetic trees in order to understand how synthetic information can emerge from a database of phylogenies. RESULTS: Analyses of tree network connectivity in TreeBASE show that a collection of phylogenetic trees behaves as a small-world network-while on the one hand the trees are clustered, like a non-random lattice, on the other hand they have short characteristic path lengths, like a random graph. Tree connectivities follow a dual-scale power-law distribution (first power-law exponent approximately 1.87; second approximately 4.82). This unusual pattern is due, in part, to the presence of alternative tree topologies that enter the database with each published study. As expected, small collections of trees decrease connectivity as new trees are added, while large collections of trees increase connectivity. However, the inflection point is surprisingly low: after about 600 trees the network suddenly jumps to a higher level of coherence. More stringent definitions of 'neighbour' greatly delay the threshold whence a database achieves sufficient maturity for a coherent network to emerge. However, more stringent definitions of 'neighbour' would also likely show improved focus in data mining. AVAILABILITY: http://treebase.org
UNLABELLED: Patients treated with radiotherapy are prone to a constellation of local and systemic toxicities including mucositis, xerostomia, fatigue and anorexia. The biological complexities and similarities underlying the development of toxicities have recently been realized. Mucosal barrier injury is one of the best studied, and gene expression patterns, based on animal tissue samples, have added to its understanding. While investigations gene expression based on tissue samples was valuable, its use precludes more generalizable conclusions relative to common pathogenic mechanisms. Additionally, attempting to define the kinetics of changes in gene expression by sequential sampling is pragmatically unrealistic. Our objectives were: 1. to determine if changes in gene expression could be detected during toxicity development using PBM from patients receiving chemoradiation; 2. to characterize the relationship of expressed genes using graph theory and pathway analysis; and 3. to evaluate potential relationships between the expression of particular genes, canonical pathways, and functional networks in explaining the pathogenesis of regimen-related toxicities. DESIGN: Microarray analysis was performed using PBM-derived cRNA obtained before and 2 weeks after the initiation of chemoradiation in five patients with head and neck cancer who developed documented regimen-related toxicities. We created a database of those genes newly expressed at 2 weeks and evaluated their potential significance relative to toxicity, by canonical pathway analysis, compilation of regional networks around focus genes, and development of a model globalizing the individual functional networks. There was strong concordance between known pathogenic mechanisms of toxicity and the genes, pathways, and networks developed by our data. A role was elicited for unsuspected genes in toxicity development. Our results support the concept that radiation induced toxicities have common underlying mechanisms and demonstrate the utility of PBM as an RNA source for genetic studies. This methodology could be broadly applicable to the study of regimen-related toxicities.
Starting from a general ansatz, we show how community detection can be interpreted as finding the ground state of an infinite range spin glass. Our approach applies to weighted and directed networks alike. It contains the ad hoc introduced quality function from [J. Reichardt and S. Bornholdt, Phys. Rev. Lett. 93, 218701 (2004)] and the modularity Q as defined by Newman and Girvan [Phys. Rev. E 69, 026113 (2004)] as special cases. The community structure of the network is interpreted as the spin configuration that minimizes the energy of the spin glass with the spin states being the community indices. We elucidate the properties of the ground state configuration to give a concise definition of communities as cohesive subgroups in networks that is adaptive to the specific class of network under study. Further, we show how hierarchies and overlap in the community structure can be detected. Computationally efficient local update rules for optimization procedures to find the ground state are given. We show how the ansatz may be used to discover the community around a given node without detecting all communities in the full network and we give benchmarks for the performance of this extension. Finally, we give expectation values for the modularity of random graphs, which can be used in the assessment of statistical significance of community structure.
Nutritional conditions in the pre-gestacional period and during pregnancy were evaluated in 372 pregnant women based on the body mass index and Rosso's Graph. Approximately half (51%) the pregnant women presented normal pre-gestacional weight; however, 17.7% were underweight and 31.3% overweight. In the third trimester, 18.8% were underweight and 28.2% overweight. The weight at birth increased as nutritional conditions during pregnancy improved. These results show the importance of appropriate anthropometric control in order to prevent a bad neonatal prognosis and reaffirms the importance of such activity during the whole routine of pre-natal control.
The resolution achievable in vivo by magnetic resonance imaging (MRI) techniques is not sufficient to depict precisely individual trabeculae and, thus, does not permit the quantification of the "true" trabecular bone morphology and topology. Nevertheless, the characterization of the "apparent" trabecular bone network derived from high-resolution MR images (MRIs) and their potential to provide information in addition to bone mineral density (BMD) alone has been established in studies of osteoporosis. The aim of this work was to show the ability of the three-dimensional-line skeleton graph analysis (3D-LSGA) to characterize high-resolution MRIs of trabecular bone structure. Fifteen trabecular bone samples of the distal radius were imaged using the high-resolution MRI (156 x 156 x 300 microm3) and microcomputed tomography (microCT; 34 x 34 x 34 microm3). After thresholding, the 3D skeleton graph of each binary image was obtained. To remove the assimilated-noise branches of the skeleton graph and smooth this skeleton graph before it was analyzed, we defined a smoothing length criterion (l(c)), such that all "termini" branches having a length lower than l(c) were removed. Local topological and morphological LSGA measurements were performed from MRIs and microCT images of the same samples. The correlations between these two sets of measurements were dependent on the smoothing criterion l(c), reaching R2 = 0.85 for topological measurements and R2 = 0.57-0.64 for morphological measurements. 3D-LSGA technique could be applied to in vivo high-resolution MRIs of trabecular bone structure, giving an indirect characterization of the microtrabecular bone network.
We present an analysis of the statistical properties and growth of the free on-line encyclopedia Wikipedia. By describing topics by vertices and hyperlinks between them as edges, we can represent this encyclopedia as a directed graph. The topological properties of this graph are in close analogy with those of the World Wide Web, despite the very different growth mechanism. In particular, we measure a scale-invariant distribution of the in and out degree and we are able to reproduce these features by means of a simple statistical model. As a major consequence, Wikipedia growth can be described by local rules such as the preferential attachment mechanism, though users, who are responsible of its evolution, can act globally on the network.
Protein interaction networks provide us with contextual information within which protein function can be interpreted and will assist many biomedical studies. We have developed a new force-directed layout algorithm for visualizing protein interactions in three-dimensional space. Our algorithm divides nodes into three groups based on their interacting properties: bi-connected sub-graph in the center, terminal nodes at the outermost region, and the rest in between them. Experimental results show that our algorithm efficiently generates a clear and aesthetically pleasing drawing of large-scale protein interaction networks and that it is an order of magnitude faster than other force-directed layouts.
The objective of the work presented here was the modeling of a bipedal robot using a central pattern generator (CPG) formed by a set of mutually coupled Rayleigh oscillators. We analyzed a 2D model, with the three most important determinants of gait, that performs only motions parallel to the sagittal plane. Using oscillators with integer relation of frequency, we determined the transient motion and the stable limit cycles of the network formed by the three oscillators, showing the behavior of the knee angles and the hip angle. A comparison of the plotted graphs revealed that the system provided excellent results when compared to experimental analysis. Based on the results of the study, we come to the conclusion that the use of mutually coupled Rayleigh oscillators can represent an excellent method of signal generation, allowing their application for feedback control of a walking machine.
Simultaneous binary population biofilm formation by a bacterium and filamentous fungus was demonstrated by time-lapse image analysis in a flow cell system. The accumulation of attached bacterial cells followed an S-shaped graph similar to batch culture bacterial growth, with continual attachment, detachment, rotation, and movement of bacteria over the surface. An extensive hyphal network formed on the surface of the flow cell, protruding into the bulk flow, which subsequently detached. Multiple species mixed fungal-bacterial model biofilms were tested for isothiazolone biocide susceptibility. Biofilms were less susceptible to biocide treatment than planktonic cells of the same organisms. Mixed species biofilms, particularly for the bacterial species, offered greater protection against the action of the biocide compared to single species biofilms. Microbial loss as a result of biocide activity was shown by reduced cell surface coverage in electron micrographs.