WorldWideScience

Sample records for analyzing interactome networks

  1. Interactome Networks and Human Disease

    OpenAIRE

    Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

    2011-01-01

    Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties ma...

  2. Building and analyzing protein interactome networks by cross-species comparisons

    Directory of Open Access Journals (Sweden)

    Blackman Barron

    2010-03-01

    Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

  3. Information flow analysis of interactome networks.

    Directory of Open Access Journals (Sweden)

    Patrycja Vasilyev Missiuro

    2009-04-01

    Full Text Available Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we

  4. A proteome-scale map of the human interactome network

    Science.gov (United States)

    Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J.; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D.; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E.; Braun, Pascal; Brehme, Marc; Broly, Martin P.; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J.; Hardy, Madeleine F.; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R.; Palagi, Alexandre; Poulin, Matthew M.; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M.; Scholz, Annemarie; Shah, Akash A.; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O.; Trigg, Shelly A.; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E.; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M.; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A.; Hill, David E.; Hao, Tong; Roth, Frederick P.; Vidal, Marc

    2014-01-01

    SUMMARY Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ~14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ~30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a “broader” human interactome network than currently appreciated. The map also uncovers significant inter-connectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high quality interactome models will help “connect the dots” of the genomic revolution. PMID:25416956

  5. A proteome-scale map of the human interactome network.

    Science.gov (United States)

    Rolland, Thomas; Taşan, Murat; Charloteaux, Benoit; Pevzner, Samuel J; Zhong, Quan; Sahni, Nidhi; Yi, Song; Lemmens, Irma; Fontanillo, Celia; Mosca, Roberto; Kamburov, Atanas; Ghiassian, Susan D; Yang, Xinping; Ghamsari, Lila; Balcha, Dawit; Begg, Bridget E; Braun, Pascal; Brehme, Marc; Broly, Martin P; Carvunis, Anne-Ruxandra; Convery-Zupan, Dan; Corominas, Roser; Coulombe-Huntington, Jasmin; Dann, Elizabeth; Dreze, Matija; Dricot, Amélie; Fan, Changyu; Franzosa, Eric; Gebreab, Fana; Gutierrez, Bryan J; Hardy, Madeleine F; Jin, Mike; Kang, Shuli; Kiros, Ruth; Lin, Guan Ning; Luck, Katja; MacWilliams, Andrew; Menche, Jörg; Murray, Ryan R; Palagi, Alexandre; Poulin, Matthew M; Rambout, Xavier; Rasla, John; Reichert, Patrick; Romero, Viviana; Ruyssinck, Elien; Sahalie, Julie M; Scholz, Annemarie; Shah, Akash A; Sharma, Amitabh; Shen, Yun; Spirohn, Kerstin; Tam, Stanley; Tejeda, Alexander O; Trigg, Shelly A; Twizere, Jean-Claude; Vega, Kerwin; Walsh, Jennifer; Cusick, Michael E; Xia, Yu; Barabási, Albert-László; Iakoucheva, Lilia M; Aloy, Patrick; De Las Rivas, Javier; Tavernier, Jan; Calderwood, Michael A; Hill, David E; Hao, Tong; Roth, Frederick P; Vidal, Marc

    2014-11-20

    Just as reference genome sequences revolutionized human genetics, reference maps of interactome networks will be critical to fully understand genotype-phenotype relationships. Here, we describe a systematic map of ?14,000 high-quality human binary protein-protein interactions. At equal quality, this map is ?30% larger than what is available from small-scale studies published in the literature in the last few decades. While currently available information is highly biased and only covers a relatively small portion of the proteome, our systematic map appears strikingly more homogeneous, revealing a "broader" human interactome network than currently appreciated. The map also uncovers significant interconnectivity between known and candidate cancer gene products, providing unbiased evidence for an expanded functional cancer landscape, while demonstrating how high-quality interactome models will help "connect the dots" of the genomic revolution.

  6. Defining a Modular Signalling Network from the Fly Interactome

    Directory of Open Access Journals (Sweden)

    Jacq Bernard

    2008-05-01

    Full Text Available Abstract Background Signalling pathways relay information by transmitting signals from cell surface receptors to intracellular effectors that eventually activate the transcription of target genes. Since signalling pathways involve several types of molecular interactions including protein-protein interactions, we postulated that investigating their organization in the context of the global protein-protein interaction network could provide a new integrated view of signalling mechanisms. Results Using a graph-theory based method to analyse the fly protein-protein interaction network, we found that each signalling pathway is organized in two to three different signalling modules. These modules contain canonical proteins of the signalling pathways, known regulators as well as other proteins thereby predicted to participate to the signalling mechanisms. Connections between the signalling modules are prominent as compared to the other network's modules and interactions within and between signalling modules are among the more central routes of the interaction network. Conclusion Altogether, these modules form an interactome sub-network devoted to signalling with particular topological properties: modularity, density and centrality. This finding reflects the integration of the signalling system into cell functioning and its important role connecting and coordinating different biological processes at the level of the interactome.

  7. Manifold learning in protein interactomes.

    Science.gov (United States)

    Marras, Elisabetta; Travaglione, Antonella; Capobianco, Enrico

    2011-01-01

    Many studies and applications in the post-genomic era have been devoted to analyze complex biological systems by computational inference methods. We propose to apply manifold learning methods to protein-protein interaction networks (PPIN). Despite their popularity in data-intensive applications, these methods have received limited attention in the context of biological networks. We show that there is both utility and unexplored potential in adopting manifold learning for network inference purposes. In particular, the following advantages are highlighted: (a) fusion with diagnostic statistical tools designed to assign significance to protein interactions based on pre-selected topological features; (b) dissection into components of the interactome in order to elucidate global and local connectivity organization; (c) relevance of embedding the interactome in reduced dimensions for biological validation purposes. We have compared the performances of three well-known techniques--kernel-PCA, RADICAL ICA, and ISOMAP--relatively to their power of mapping the interactome onto new coordinate dimensions where important associations among proteins can be detected, and then back projected such that the corresponding sub-interactomes are reconstructed. This recovery has been done selectively, by using significant information according to a robust statistical procedure, and then standard biological annotation has been provided to validate the results. We expect that a byproduct of using subspace analysis by the proposed techniques is a possible calibration of interactome modularity studies. Supplementary Material is available online at www.libertonlinec.com.

  8. Mining protein interactomes to improve their reliability and support the advancement of network medicine

    Directory of Open Access Journals (Sweden)

    Gregorio eAlanis-Lobato

    2015-09-01

    Full Text Available High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease aetiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

  9. Mining protein interactomes to improve their reliability and support the advancement of network medicine

    KAUST Repository

    Alanis Lobato, Gregorio

    2015-09-23

    High-throughput detection of protein interactions has had a major impact in our understanding of the intricate molecular machinery underlying the living cell, and has permitted the construction of very large protein interactomes. The protein networks that are currently available are incomplete and a significant percentage of their interactions are false positives. Fortunately, the structural properties observed in good quality social or technological networks are also present in biological systems. This has encouraged the development of tools, to improve the reliability of protein networks and predict new interactions based merely on the topological characteristics of their components. Since diseases are rarely caused by the malfunction of a single protein, having a more complete and reliable interactome is crucial in order to identify groups of inter-related proteins involved in disease etiology. These system components can then be targeted with minimal collateral damage. In this article, an important number of network mining tools is reviewed, together with resources from which reliable protein interactomes can be constructed. In addition to the review, a few representative examples of how molecular and clinical data can be integrated to deepen our understanding of pathogenesis are discussed.

  10. Systematic interactome mapping and genetic perturbation analysis of a C. elegans TGF-beta signaling network.

    Science.gov (United States)

    Tewari, Muneesh; Hu, Patrick J; Ahn, Jin Sook; Ayivi-Guedehoussou, Nono; Vidalain, Pierre-Olivier; Li, Siming; Milstein, Stuart; Armstrong, Chris M; Boxem, Mike; Butler, Maurice D; Busiguina, Svetlana; Rual, Jean-François; Ibarrola, Nieves; Chaklos, Sabrina T; Bertin, Nicolas; Vaglio, Philippe; Edgley, Mark L; King, Kevin V; Albert, Patrice S; Vandenhaute, Jean; Pandey, Akhilesh; Riddle, Donald L; Ruvkun, Gary; Vidal, Marc

    2004-02-27

    To initiate a system-level analysis of C. elegans DAF-7/TGF-beta signaling, we combined interactome mapping with single and double genetic perturbations. Yeast two-hybrid (Y2H) screens starting with known DAF-7/TGF-beta pathway components defined a network of 71 interactions among 59 proteins. Coaffinity purification (co-AP) assays in mammalian cells confirmed the overall quality of this network. Systematic perturbations of the network using RNAi, both in wild-type and daf-7/TGF-beta pathway mutant animals, identified nine DAF-7/TGF-beta signaling modifiers, seven of which are conserved in humans. We show that one of these has functional homology to human SNO/SKI oncoproteins and that mutations at the corresponding genetic locus daf-5 confer defects in DAF-7/TGF-beta signaling. Our results reveal substantial molecular complexity in DAF-7/TGF-beta signal transduction. Integrating interactome maps with systematic genetic perturbations may be useful for developing a systems biology approach to this and other signaling modules.

  11. Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

    CERN Document Server

    Baianu, I C

    2004-01-01

    A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

  12. Exploitation of complex network topology for link prediction in biological interactomes

    KAUST Repository

    Alanis Lobato, Gregorio

    2014-06-01

    The network representation of the interactions between proteins and genes allows for a holistic perspective of the complex machinery underlying the living cell. However, the large number of interacting entities within the cell makes network construction a daunting and arduous task, prone to errors and missing information. Fortunately, the structure of biological networks is not different from that of other complex systems, such as social networks, the world-wide web or power grids, for which growth models have been proposed to better understand their structure and function. This means that we can design tools based on these models in order to exploit the topology of biological interactomes with the aim to construct more complete and reliable maps of the cell. In this work, we propose three novel and powerful approaches for the prediction of interactions in biological networks and conclude that it is possible to mine the topology of these complex system representations and produce reliable and biologically meaningful information that enriches the datasets to which we have access today.

  13. A predicted protein interactome identifies conserved global networks and disease resistance subnetworks in maize.

    Directory of Open Access Journals (Sweden)

    Matt eGeisler

    2015-06-01

    Full Text Available Interactomes are genome-wide roadmaps of protein-protein interactions. They have been produced for humans, yeast, the fruit fly, and Arabidopsis thaliana and have become invaluable tools for generating and testing hypotheses. A predicted interactome for Zea mays (PiZeaM is presented here as an aid to the research community for this valuable crop species. PiZeaM was built using a proven method of interologs (interacting orthologs that were identified using both one-to-one and many-to-many orthology between genomes of maize and reference species. Where both maize orthologs occurred for an experimentally determined interaction in the reference species, we predicted a likely interaction in maize. A total of 49,026 unique interactions for 6,004 maize proteins were predicted. These interactions are enriched for processes that are evolutionarily conserved, but include many otherwise poorly annotated proteins in maize. The predicted maize interactions were further analyzed by comparing annotation of interacting proteins, including different layers of ontology. A map of pairwise gene co-expression was also generated and compared to predicted interactions. Two global subnetworks were constructed for highly conserved interactions. These subnetworks showed clear clustering of proteins by function. Another subnetwork was created for disease response using a bait and prey strategy to capture interacting partners for proteins that respond to other organisms. Closer examination of this subnetwork revealed the connectivity between biotic and abiotic hormone stress pathways. We believe PiZeaM will provide a useful tool for the prediction of protein function and analysis of pathways for Z. mays researchers and is presented in this paper as a reference tool for the exploration of protein interactions in maize.

  14. Statistical network analysis for analyzing policy networks

    DEFF Research Database (Denmark)

    Robins, Garry; Lewis, Jenny; Wang, Peng

    2012-01-01

    and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs...... has much to offer in analyzing the policy process....

  15. Complex networks theory for analyzing metabolic networks

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jing; YU Hong; LUO Jianhua; CAO Z.W.; LI Yixue

    2006-01-01

    One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism,while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.

  16. Graph-theoretical model of global human interactome reveals enhanced long-range communicability in cancer networks.

    Science.gov (United States)

    Gladilin, Evgeny

    2017-01-01

    Malignant transformation is known to involve substantial rearrangement of the molecular genetic landscape of the cell. A common approach to analysis of these alterations is a reductionist one and consists of finding a compact set of differentially expressed genes or associated signaling pathways. However, due to intrinsic tumor heterogeneity and tissue specificity, biomarkers defined by a small number of genes/pathways exhibit substantial variability. As an alternative to compact differential signatures, global features of genetic cell machinery are conceivable. Global network descriptors suggested in previous works are, however, known to potentially be biased by overrepresentation of interactions between frequently studied genes-proteins. Here, we construct a cellular network of 74538 directional and differential gene expression weighted protein-protein and gene regulatory interactions, and perform graph-theoretical analysis of global human interactome using a novel, degree-independent feature-the normalized total communicability (NTC). We apply this framework to assess differences in total information flow between different cancer (BRCA/COAD/GBM) and non-cancer interactomes. Our experimental results reveal that different cancer interactomes are characterized by significant enhancement of long-range NTC, which arises from circulation of information flow within robustly organized gene subnetworks. Although enhancement of NTC emerges in different cancer types from different genomic profiles, we identified a subset of 90 common genes that are related to elevated NTC in all studied tumors. Our ontological analysis shows that these genes are associated with enhanced cell division, DNA replication, stress response, and other cellular functions and processes typically upregulated in cancer. We conclude that enhancement of long-range NTC manifested in the correlated activity of genes whose tight coordination is required for survival and proliferation of all tumor cells

  17. System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max).

    Science.gov (United States)

    Xu, Yungang; Guo, Maozu; Zou, Quan; Liu, Xiaoyan; Wang, Chunyu; Liu, Yang

    2014-01-01

    Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN), a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max), due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs), in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional interactome at the genome

  18. The Cardiac TBX5 Interactome Reveals a Chromatin Remodeling Network Essential for Cardiac Septation.

    Science.gov (United States)

    Waldron, Lauren; Steimle, Jeffrey D; Greco, Todd M; Gomez, Nicholas C; Dorr, Kerry M; Kweon, Junghun; Temple, Brenda; Yang, Xinan Holly; Wilczewski, Caralynn M; Davis, Ian J; Cristea, Ileana M; Moskowitz, Ivan P; Conlon, Frank L

    2016-02-08

    Human mutations in the cardiac transcription factor gene TBX5 cause congenital heart disease (CHD), although the underlying mechanism is unknown. We report characterization of the endogenous TBX5 cardiac interactome and demonstrate that TBX5, long considered a transcriptional activator, interacts biochemically and genetically with the nucleosome remodeling and deacetylase (NuRD) repressor complex. Incompatible gene programs are repressed by TBX5 in the developing heart. CHD mis-sense mutations that disrupt the TBX5-NuRD interaction cause depression of a subset of repressed genes. Furthermore, the TBX5-NuRD interaction is required for heart development. Phylogenetic analysis showed that the TBX5-NuRD interaction domain evolved during early diversification of vertebrates, simultaneous with the evolution of cardiac septation. Collectively, this work defines a TBX5-NuRD interaction essential to cardiac development and the evolution of the mammalian heart, and when altered may contribute to human CHD.

  19. POINeT: protein interactome with sub-network analysis and hub prioritization

    Directory of Open Access Journals (Sweden)

    Lai Jin-Mei

    2009-04-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs are critical to every aspect of biological processes. Expansion of all PPIs from a set of given queries often results in a complex PPI network lacking spatiotemporal consideration. Moreover, the reliability of available PPI resources, which consist of low- and high-throughput data, for network construction remains a significant challenge. Even though a number of software tools are available to facilitate PPI network analysis, an integrated tool is crucial to alleviate the burden on querying across multiple web servers and software tools. Results We have constructed an integrated web service, POINeT, to simplify the process of PPI searching, analysis, and visualization. POINeT merges PPI and tissue-specific expression data from multiple resources. The tissue-specific PPIs and the numbers of research papers supporting the PPIs can be filtered with user-adjustable threshold values and are dynamically updated in the viewer. The network constructed in POINeT can be readily analyzed with, for example, the built-in centrality calculation module and an integrated network viewer. Nodes in global networks can also be ranked and filtered using various network analysis formulas, i.e., centralities. To prioritize the sub-network, we developed a ranking filtered method (S3 to uncover potential novel mediators in the midbody network. Several examples are provided to illustrate the functionality of POINeT. The network constructed from four schizophrenia risk markers suggests that EXOC4 might be a novel marker for this disease. Finally, a liver-specific PPI network has been filtered with adult and fetal liver expression profiles. Conclusion The functionalities provided by POINeT are highly improved compared to previous version of POINT. POINeT enables the identification and ranking of potential novel genes involved in a sub-network. Combining with tissue-specific gene expression profiles, PPIs specific to

  20. Analysis of the robustness of network-based disease-gene prioritization methods reveals redundancy in the human interactome and functional diversity of disease-genes.

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    Emre Guney

    Full Text Available Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO analysis highlighted the role of functional diversity for such diseases.

  1. System-level insights into the cellular interactome of a non-model organism: inferring, modelling and analysing functional gene network of soybean (Glycine max.

    Directory of Open Access Journals (Sweden)

    Yungang Xu

    Full Text Available Cellular interactome, in which genes and/or their products interact on several levels, forming transcriptional regulatory-, protein interaction-, metabolic-, signal transduction networks, etc., has attracted decades of research focuses. However, such a specific type of network alone can hardly explain the various interactive activities among genes. These networks characterize different interaction relationships, implying their unique intrinsic properties and defects, and covering different slices of biological information. Functional gene network (FGN, a consolidated interaction network that models fuzzy and more generalized notion of gene-gene relations, have been proposed to combine heterogeneous networks with the goal of identifying functional modules supported by multiple interaction types. There are yet no successful precedents of FGNs on sparsely studied non-model organisms, such as soybean (Glycine max, due to the absence of sufficient heterogeneous interaction data. We present an alternative solution for inferring the FGNs of soybean (SoyFGNs, in a pioneering study on the soybean interactome, which is also applicable to other organisms. SoyFGNs exhibit the typical characteristics of biological networks: scale-free, small-world architecture and modularization. Verified by co-expression and KEGG pathways, SoyFGNs are more extensive and accurate than an orthology network derived from Arabidopsis. As a case study, network-guided disease-resistance gene discovery indicates that SoyFGNs can provide system-level studies on gene functions and interactions. This work suggests that inferring and modelling the interactome of a non-model plant are feasible. It will speed up the discovery and definition of the functions and interactions of other genes that control important functions, such as nitrogen fixation and protein or lipid synthesis. The efforts of the study are the basis of our further comprehensive studies on the soybean functional

  2. Dynamic Zebrafish Interactome Reveals Transcriptional Mechanisms of Dioxin Toxicity

    Science.gov (United States)

    Alexeyenko, Andrey; Wassenberg, Deena M.; Lobenhofer, Edward K.; Yen, Jerry; Linney, Elwood; Sonnhammer, Erik L. L.; Meyer, Joel N.

    2010-01-01

    Background In order to generate hypotheses regarding the mechanisms by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin) causes toxicity, we analyzed global gene expression changes in developing zebrafish embryos exposed to this potent toxicant in the context of a dynamic gene network. For this purpose, we also computationally inferred a zebrafish (Danio rerio) interactome based on orthologs and interaction data from other eukaryotes. Methodology/Principal Findings Using novel computational tools to analyze this interactome, we distinguished between dioxin-dependent and dioxin-independent interactions between proteins, and tracked the temporal propagation of dioxin-dependent transcriptional changes from a few genes that were altered initially, to large groups of biologically coherent genes at later times. The most notable processes altered at later developmental stages were calcium and iron metabolism, embryonic morphogenesis including neuronal and retinal development, a variety of mitochondria-related functions, and generalized stress response (not including induction of antioxidant genes). Within the interactome, many of these responses were connected to cytochrome P4501A (cyp1a) as well as other genes that were dioxin-regulated one day after exposure. This suggests that cyp1a may play a key role initiating the toxic dysregulation of those processes, rather than serving simply as a passive marker of dioxin exposure, as suggested by earlier research. Conclusions/Significance Thus, a powerful microarray experiment coupled with a flexible interactome and multi-pronged interactome tools (which are now made publicly available for microarray analysis and related work) suggest the hypothesis that dioxin, best known in fish as a potent cardioteratogen, has many other targets. Many of these types of toxicity have been observed in mammalian species and are potentially caused by alterations to cyp1a. PMID:20463971

  3. Dynamic zebrafish interactome reveals transcriptional mechanisms of dioxin toxicity.

    Directory of Open Access Journals (Sweden)

    Andrey Alexeyenko

    Full Text Available BACKGROUND: In order to generate hypotheses regarding the mechanisms by which 2,3,7,8-tetrachlorodibenzo-p-dioxin (dioxin causes toxicity, we analyzed global gene expression changes in developing zebrafish embryos exposed to this potent toxicant in the context of a dynamic gene network. For this purpose, we also computationally inferred a zebrafish (Danio rerio interactome based on orthologs and interaction data from other eukaryotes. METHODOLOGY/PRINCIPAL FINDINGS: Using novel computational tools to analyze this interactome, we distinguished between dioxin-dependent and dioxin-independent interactions between proteins, and tracked the temporal propagation of dioxin-dependent transcriptional changes from a few genes that were altered initially, to large groups of biologically coherent genes at later times. The most notable processes altered at later developmental stages were calcium and iron metabolism, embryonic morphogenesis including neuronal and retinal development, a variety of mitochondria-related functions, and generalized stress response (not including induction of antioxidant genes. Within the interactome, many of these responses were connected to cytochrome P4501A (cyp1a as well as other genes that were dioxin-regulated one day after exposure. This suggests that cyp1a may play a key role initiating the toxic dysregulation of those processes, rather than serving simply as a passive marker of dioxin exposure, as suggested by earlier research. CONCLUSIONS/SIGNIFICANCE: Thus, a powerful microarray experiment coupled with a flexible interactome and multi-pronged interactome tools (which are now made publicly available for microarray analysis and related work suggest the hypothesis that dioxin, best known in fish as a potent cardioteratogen, has many other targets. Many of these types of toxicity have been observed in mammalian species and are potentially caused by alterations to cyp1a.

  4. Methods for Analyzing Pipe Networks

    DEFF Research Database (Denmark)

    Nielsen, Hans Bruun

    1989-01-01

    The governing equations for a general network are first set up and then reformulated in terms of matrices. This is developed to show that the choice of model for the flow equations is essential for the behavior of the iterative method used to solve the problem. It is shown that it is better...... to formulate the flow equations in terms of pipe discharges than in terms of energy heads. The behavior of some iterative methods is compared in the initial phase with large errors. It is explained why the linear theory method oscillates when the iteration gets close to the solution, and it is further...... demonstrated that this method offers good starting values for a Newton-Raphson iteration....

  5. Curating the innate immunity interactome

    Science.gov (United States)

    2010-01-01

    Background The innate immune response is the first line of defence against invading pathogens and is regulated by complex signalling and transcriptional networks. Systems biology approaches promise to shed new light on the regulation of innate immunity through the analysis and modelling of these networks. A key initial step in this process is the contextual cataloguing of the components of this system and the molecular interactions that comprise these networks. InnateDB (http://www.innatedb.com) is a molecular interaction and pathway database developed to facilitate systems-level analyses of innate immunity. Results Here, we describe the InnateDB curation project, which is manually annotating the human and mouse innate immunity interactome in rich contextual detail, and present our novel curation software system, which has been developed to ensure interactions are curated in a highly accurate and data-standards compliant manner. To date, over 13,000 interactions (protein, DNA and RNA) have been curated from the biomedical literature. Here, we present data, illustrating how InnateDB curation of the innate immunity interactome has greatly enhanced network and pathway annotation available for systems-level analysis and discuss the challenges that face such curation efforts. Significantly, we provide several lines of evidence that analysis of the innate immunity interactome has the potential to identify novel signalling, transcriptional and post-transcriptional regulators of innate immunity. Additionally, these analyses also provide insight into the cross-talk between innate immunity pathways and other biological processes, such as adaptive immunity, cancer and diabetes, and intriguingly, suggests links to other pathways, which as yet, have not been implicated in the innate immune response. Conclusions In summary, curation of the InnateDB interactome provides a wealth of information to enable systems-level analysis of innate immunity. PMID:20727158

  6. Electrical spectrum & network analyzers a practical approach

    CERN Document Server

    Helfrick, Albert D

    1991-01-01

    This book presents fundamentals and the latest techniques of electrical spectrum analysis. It focuses on instruments and techniques used on spectrum and network analysis, rather than theory. The book covers the use of spectrum analyzers, tracking generators, and network analyzers. Filled with practical examples, the book presents techniques that are widely used in signal processing and communications applications, yet are difficult to find in most literature.Key Features* Presents numerous practical examples, including actual spectrum analyzer circuits* Instruction on how to us

  7. Architecture of the human interactome defines protein communities and disease networks.

    Science.gov (United States)

    Huttlin, Edward L; Bruckner, Raphael J; Paulo, Joao A; Cannon, Joe R; Ting, Lily; Baltier, Kurt; Colby, Greg; Gebreab, Fana; Gygi, Melanie P; Parzen, Hannah; Szpyt, John; Tam, Stanley; Zarraga, Gabriela; Pontano-Vaites, Laura; Swarup, Sharan; White, Anne E; Schweppe, Devin K; Rad, Ramin; Erickson, Brian K; Obar, Robert A; Guruharsha, K G; Li, Kejie; Artavanis-Tsakonas, Spyros; Gygi, Steven P; Harper, J Wade

    2017-05-25

    The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification-mass spectrometry methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

  8. Analyzing negative ties in social networks

    Directory of Open Access Journals (Sweden)

    Mankirat Kaur

    2016-03-01

    Full Text Available Online social networks are a source of sharing information and maintaining personal contacts with other people through social interactions and thus forming virtual communities online. Social networks are crowded with positive and negative relations. Positive relations are formed by support, endorsement and friendship and thus, create a network of well-connected users whereas negative relations are a result of opposition, distrust and avoidance creating disconnected networks. Due to increase in illegal activities such as masquerading, conspiring and creating fake profiles on online social networks, exploring and analyzing these negative activities becomes the need of hour. Usually negative ties are treated in same way as positive ties in many theories such as balance theory and blockmodeling analysis. But the standard concepts of social network analysis do not yield same results in respect of each tie. This paper presents a survey on analyzing negative ties in social networks through various types of network analysis techniques that are used for examining ties such as status, centrality and power measures. Due to the difference in characteristics of flow in positive and negative tie networks some of these measures are not applicable on negative ties. This paper also discusses new methods that have been developed specifically for analyzing negative ties such as negative degree, and h∗ measure along with the measures based on mixture of positive and negative ties. The different types of social network analysis approaches have been reviewed and compared to determine the best approach that can appropriately identify the negative ties in online networks. It has been analyzed that only few measures such as Degree and PN centrality are applicable for identifying outsiders in network. For applicability in online networks, the performance of PN measure needs to be verified and further, new measures should be developed based upon negative clique concept.

  9. Network analysis using organizational risk analyzer

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The tool system of the organizational risk analyzer (ORA) to study the network of East Turkistan terrorists is selected. The model of the relationships among its personnel, knowledge, resources and task entities is represented by the meta-matrix in ORA, with which to analyze the risks and vulnerabilities of organizational structure quantitatively, and obtain the last vulnerabilities and risks of the organization. Case study in this system shows that it should be a shortcut to destroy effectively the network...

  10. Virtual Interactomics of Proteins from Biochemical Standpoint

    Directory of Open Access Journals (Sweden)

    Jaroslav Kubrycht

    2012-01-01

    Full Text Available Virtual interactomics represents a rapidly developing scientific area on the boundary line of bioinformatics and interactomics. Protein-related virtual interactomics then comprises instrumental tools for prediction, simulation, and networking of the majority of interactions important for structural and individual reproduction, differentiation, recognition, signaling, regulation, and metabolic pathways of cells and organisms. Here, we describe the main areas of virtual protein interactomics, that is, structurally based comparative analysis and prediction of functionally important interacting sites, mimotope-assisted and combined epitope prediction, molecular (protein docking studies, and investigation of protein interaction networks. Detailed information about some interesting methodological approaches and online accessible programs or databases is displayed in our tables. Considerable part of the text deals with the searches for common conserved or functionally convergent protein regions and subgraphs of conserved interaction networks, new outstanding trends and clinically interesting results. In agreement with the presented data and relationships, virtual interactomic tools improve our scientific knowledge, help us to formulate working hypotheses, and they frequently also mediate variously important in silico simulations.

  11. Triangle network motifs predict complexes by complementing high-error interactomes with structural information

    Directory of Open Access Journals (Sweden)

    Labudde Dirk

    2009-06-01

    Full Text Available Abstract Background A lot of high-throughput studies produce protein-protein interaction networks (PPINs with many errors and missing information. Even for genome-wide approaches, there is often a low overlap between PPINs produced by different studies. Second-level neighbors separated by two protein-protein interactions (PPIs were previously used for predicting protein function and finding complexes in high-error PPINs. We retrieve second level neighbors in PPINs, and complement these with structural domain-domain interactions (SDDIs representing binding evidence on proteins, forming PPI-SDDI-PPI triangles. Results We find low overlap between PPINs, SDDIs and known complexes, all well below 10%. We evaluate the overlap of PPI-SDDI-PPI triangles with known complexes from Munich Information center for Protein Sequences (MIPS. PPI-SDDI-PPI triangles have ~20 times higher overlap with MIPS complexes than using second-level neighbors in PPINs without SDDIs. The biological interpretation for triangles is that a SDDI causes two proteins to be observed with common interaction partners in high-throughput experiments. The relatively few SDDIs overlapping with PPINs are part of highly connected SDDI components, and are more likely to be detected in experimental studies. We demonstrate the utility of PPI-SDDI-PPI triangles by reconstructing myosin-actin processes in the nucleus, cytoplasm, and cytoskeleton, which were not obvious in the original PPIN. Using other complementary datatypes in place of SDDIs to form triangles, such as PubMed co-occurrences or threading information, results in a similar ability to find protein complexes. Conclusion Given high-error PPINs with missing information, triangles of mixed datatypes are a promising direction for finding protein complexes. Integrating PPINs with SDDIs improves finding complexes. Structural SDDIs partially explain the high functional similarity of second-level neighbors in PPINs. We estimate that

  12. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

    Directory of Open Access Journals (Sweden)

    Kirouac Daniel C

    2012-05-01

    Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

  13. How to Analyze Company Using Social Network?

    Science.gov (United States)

    Palus, Sebastian; Bródka, Piotr; Kazienko, Przemysław

    Every single company or institution wants to utilize its resources in the most efficient way. In order to do so they have to be have good structure. The new way to analyze company structure by utilizing existing within company natural social network and example of its usage on Enron company are presented in this paper.

  14. Analyzing Network Coding Gossip Made Easy

    CERN Document Server

    Haeupler, Bernhard

    2010-01-01

    We give a new technique to analyze the stopping time of gossip protocols that are based on random linear network coding (RLNC). Our analysis drastically simplifies, extends and strengthens previous results. We analyze RLNC gossip in a general framework for network and communication models that encompasses and unifies the models used previously in this context. We show, in most settings for the first time, that it converges with high probability in the information-theoretically optimal time. Most stopping times are of the form O(k + T) where k is the number of messages to be distributed and T is the time it takes to disseminate one message. This means RLNC gossip achieves "perfect pipelining". Our analysis directly extends to highly dynamic networks in which the topology can change completely at any time. This remains true even if the network dynamics are controlled by a fully adaptive adversary that knows the complete network state. Virtually nothing besides simple O(kT) sequential flooding protocols was prev...

  15. Analyzed Virtual Routing Protocol for Future Networks (MANET & topological network

    Directory of Open Access Journals (Sweden)

    R. Viswanathan

    2012-08-01

    Full Text Available The mobile ad-hoc network (MANET is a wireless unstructured network and this has mostly suggested for multimedia streaming efficiency. The hackers attacks are reduce the capacity and efficiency of network in MANET. There are various types of protocol are used for the communication in MANET, but security is lacking in those techniques and some insoluble problems present in MANET. In this paper exhibits, a layered protocol network for secured data transmission called Analyzed Virtual Routing Protocol (AVRP. This protocol used to provide more secured data transmission and this not disturbing data streaming in the network.

  16. Analyzing Evolving Social Network 2 (EVOLVE2)

    Science.gov (United States)

    2015-04-01

    COVERED (From - To) JUN 2012 – OCT 2014 4. TITLE AND SUBTITLE ANALYZING EVOLVING SOCIAL NETWORKS 2 (EVOLVE2) 5a. CONTRACT NUMBER FA8750-12-2-0186... jazz 198 2742 274 0.14 connect 1095 7825 783 0.014 hep-th 8710 14254 1425 0.0003 netscience 1461 2742 274 0.0013 imdb 6260 98235 9824 0.005 technological

  17. CALIBRATION OF ONLINE ANALYZERS USING NEURAL NETWORKS

    Energy Technology Data Exchange (ETDEWEB)

    Rajive Ganguli; Daniel E. Walsh; Shaohai Yu

    2003-12-05

    Neural networks were used to calibrate an online ash analyzer at the Usibelli Coal Mine, Healy, Alaska, by relating the Americium and Cesium counts to the ash content. A total of 104 samples were collected from the mine, with 47 being from screened coal, and the rest being from unscreened coal. Each sample corresponded to 20 seconds of coal on the running conveyor belt. Neural network modeling used the quick stop training procedure. Therefore, the samples were split into training, calibration and prediction subsets. Special techniques, using genetic algorithms, were developed to representatively split the sample into the three subsets. Two separate approaches were tried. In one approach, the screened and unscreened coal was modeled separately. In another, a single model was developed for the entire dataset. No advantage was seen from modeling the two subsets separately. The neural network method performed very well on average but not individually, i.e. though each prediction was unreliable, the average of a few predictions was close to the true average. Thus, the method demonstrated that the analyzers were accurate at 2-3 minutes intervals (average of 6-9 samples), but not at 20 seconds (each prediction).

  18. Analyzing Multimode Wireless Sensor Networks Using the Network Calculus

    Directory of Open Access Journals (Sweden)

    Xi Jin

    2015-01-01

    Full Text Available The network calculus is a powerful tool to analyze the performance of wireless sensor networks. But the original network calculus can only model the single-mode wireless sensor network. In this paper, we combine the original network calculus with the multimode model to analyze the maximum delay bound of the flow of interest in the multimode wireless sensor network. There are two combined methods A-MM and N-MM. The method A-MM models the whole network as a multimode component, and the method N-MM models each node as a multimode component. We prove that the maximum delay bound computed by the method A-MM is tighter than or equal to that computed by the method N-MM. Experiments show that our proposed methods can significantly decrease the analytical delay bound comparing with the separate flow analysis method. For the large-scale wireless sensor network with 32 thousands of sensor nodes, our proposed methods can decrease about 70% of the analytical delay bound.

  19. Novel topological descriptors for analyzing biological networks

    Directory of Open Access Journals (Sweden)

    Varmuza Kurt K

    2010-06-01

    Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.

  20. Analyzing security protocols in hierarchical networks

    DEFF Research Database (Denmark)

    Zhang, Ye; Nielson, Hanne Riis

    2006-01-01

    Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

  1. Analyzing negative ties in social networks

    OpenAIRE

    Mankirat Kaur; Sarbjeet Singh

    2016-01-01

    Online social networks are a source of sharing information and maintaining personal contacts with other people through social interactions and thus forming virtual communities online. Social networks are crowded with positive and negative relations. Positive relations are formed by support, endorsement and friendship and thus, create a network of well-connected users whereas negative relations are a result of opposition, distrust and avoidance creating disconnected networks. Due to increase i...

  2. Inferring modules from human protein interactome classes

    Directory of Open Access Journals (Sweden)

    Chaurasia Gautam

    2010-07-01

    Full Text Available Abstract Background The integration of protein-protein interaction networks derived from high-throughput screening approaches and complementary sources is a key topic in systems biology. Although integration of protein interaction data is conventionally performed, the effects of this procedure on the result of network analyses has not been examined yet. In particular, in order to optimize the fusion of heterogeneous interaction datasets, it is crucial to consider not only their degree of coverage and accuracy, but also their mutual dependencies and additional salient features. Results We examined this issue based on the analysis of modules detected by network clustering methods applied to both integrated and individual (disaggregated data sources, which we call interactome classes. Due to class diversity, we deal with variable dependencies of data features arising from structural specificities and biases, but also from possible overlaps. Since highly connected regions of the human interactome may point to potential protein complexes, we have focused on the concept of modularity, and elucidated the detection power of module extraction algorithms by independent validations based on GO, MIPS and KEGG. From the combination of protein interactions with gene expressions, a confidence scoring scheme has been proposed before proceeding via GO with further classification in permanent and transient modules. Conclusions Disaggregated interactomes are shown to be informative for inferring modularity, thus contributing to perform an effective integrative analysis. Validation of the extracted modules by multiple annotation allows for the assessment of confidence measures assigned to the modules in a protein pathway context. Notably, the proposed multilayer confidence scheme can be used for network calibration by enabling a transition from unweighted to weighted interactomes based on biological evidence.

  3. Discovering and Analyzing Network Function and Structure

    Science.gov (United States)

    2015-07-08

    that the numerical linear algebra community has been seeking for a long time: sparse approximate inverses. To explain these, I recall that the classical...accelerate the computation. Our presently best algorithm computes the matrices L and U and applies them to solve a linear system in parallel time O(log6 n...imization, comes from Zhu, Ghahramani and Lafferty [ZGL+03], and only applies to undirected networks. Formally, one is given a network with vertex set

  4. Interactome Mapping Reveals Important Pathways in Skeletal Muscle Development of Pigs

    Directory of Open Access Journals (Sweden)

    Jianhua Cao

    2014-11-01

    Full Text Available The regulatory relationship and connectivity among genes involved in myogenesis and hypertrophy of skeletal muscle in pigs still remain large challenges. Presentation of gene interactions is a potential way to understand the mechanisms of developmental events in skeletal muscle. In this study, genome-wide transcripts and miRNA profiling was determined for Landrace pigs at four time points using microarray chips. A comprehensive method integrating gene ontology annotation and interactome network mapping was conducted to analyze the biological patterns and interaction modules of muscle development events based on differentially expressed genes and miRNAs. Our results showed that in total 484 genes and 34 miRNAs were detected for the duration from embryonic stage to adult in pigs, which composed two linear expression patterns with consensus changes. Moreover, the gene ontology analysis also disclosed that there were three typical biological events i.e., microstructure assembly of sarcomere at early embryonic stage, myofibril formation at later embryonic stage and function establishments of myoblast cells at postnatal stage. The interactome mappings of different time points also found the down-regulated trend of gene expression existed across the whole duration, which brought a possibility to introduce the myogenesis related miRNAs into the interactome regulatory networks of skeletal muscle in pigs.

  5. Uncovering disease-disease relationships through the incomplete human interactome

    Science.gov (United States)

    Menche, Jörg; Sharma, Amitabh; Kitsak, Maksim; Ghiassian, Susan; Vidal, Marc; Loscalzo, Joseph; Barabási, Albert-László

    2015-01-01

    According to the disease module hypothesis the cellular components associated with a disease segregate in the same neighborhood of the human interactome, the map of biologically relevant molecular interactions. Yet, given the incompleteness of the interactome and the limited knowledge of disease-associated genes, it is not obvious if the available data has sufficient coverage to map out modules associated with each disease. Here we derive mathematical conditions for the identifiability of disease modules and show that the network-based location of each disease module determines its pathobiological relationship to other diseases. For example, diseases with overlapping network modules show significant co-expression patterns, symptom similarity, and comorbidity, while diseases residing in separated network neighborhoods are clinically distinct. These tools represent an interactome-based platform to predict molecular commonalities between clinically related diseases, even if they do not share disease genes. PMID:25700523

  6. From link-prediction in brain connectomes and protein interactomes to the local-community-paradigm in complex networks.

    KAUST Repository

    Cannistraci, C.V.

    2013-04-08

    Growth and remodelling impact the network topology of complex systems, yet a general theory explaining how new links arise between existing nodes has been lacking, and little is known about the topological properties that facilitate link-prediction. Here we investigate the extent to which the connectivity evolution of a network might be predicted by mere topological features. We show how a link/community-based strategy triggers substantial prediction improvements because it accounts for the singular topology of several real networks organised in multiple local communities - a tendency here named local-community-paradigm (LCP). We observe that LCP networks are mainly formed by weak interactions and characterise heterogeneous and dynamic systems that use self-organisation as a major adaptation strategy. These systems seem designed for global delivery of information and processing via multiple local modules. Conversely, non-LCP networks have steady architectures formed by strong interactions, and seem designed for systems in which information/energy storage is crucial.

  7. Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature.

    Science.gov (United States)

    Poornima, Paramasivan; Kumar, Jothi Dinesh; Zhao, Qiaoli; Blunder, Martina; Efferth, Thomas

    2016-09-01

    Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and due to lower side effects. In this review, we discuss the application of network pharmacology for cancer drug discovery. We provide an overview of the current state of knowledge on network pharmacology, focus on different technical approaches and implications for cancer therapy (e.g. polypharmacology and synthetic lethality), and illustrate the therapeutic potential with selected examples green tea polyphenolics, Eleutherococcus senticosus, Rhodiola rosea, and Schisandra chinensis). Finally, we present future perspectives on their plausible applications for diagnosis and therapy of cancer.

  8. Proteomic profiling of the TRAF3 interactome network reveals a new role for the ER-to-Golgi transport compartments in innate immunity.

    Directory of Open Access Journals (Sweden)

    Wendy J van Zuylen

    Full Text Available Tumor Necrosis Factor receptor-associated factor-3 (TRAF3 is a central mediator important for inducing type I interferon (IFN production in response to intracellular double-stranded RNA (dsRNA. Here, we report the identification of Sec16A and p115, two proteins of the ER-to-Golgi vesicular transport system, as novel components of the TRAF3 interactome network. Notably, in non-infected cells, TRAF3 was found associated with markers of the ER-Exit-Sites (ERES, ER-to-Golgi intermediate compartment (ERGIC and the cis-Golgi apparatus. Upon dsRNA and dsDNA sensing however, the Golgi apparatus fragmented into cytoplasmic punctated structures containing TRAF3 allowing its colocalization and interaction with Mitochondrial AntiViral Signaling (MAVS, the essential mitochondria-bound RIG-I-like Helicase (RLH adaptor. In contrast, retention of TRAF3 at the ER-to-Golgi vesicular transport system blunted the ability of TRAF3 to interact with MAVS upon viral infection and consequently decreased type I IFN response. Moreover, depletion of Sec16A and p115 led to a drastic disorganization of the Golgi paralleled by the relocalization of TRAF3, which under these conditions was unable to associate with MAVS. Consequently, upon dsRNA and dsDNA sensing, ablation of Sec16A and p115 was found to inhibit IRF3 activation and anti-viral gene expression. Reciprocally, mild overexpression of Sec16A or p115 in Hec1B cells increased the activation of IFNβ, ISG56 and NF-κB -dependent promoters following viral infection and ectopic expression of MAVS and Tank-binding kinase-1 (TBK1. In line with these results, TRAF3 was found enriched in immunocomplexes composed of p115, Sec16A and TBK1 upon infection. Hence, we propose a model where dsDNA and dsRNA sensing induces the formation of membrane-bound compartments originating from the Golgi, which mediate the dynamic association of TRAF3 with MAVS leading to an optimal induction of innate immune responses.

  9. Complementing the Eukaryotic Protein Interactome.

    Directory of Open Access Journals (Sweden)

    Robert Pesch

    Full Text Available Protein interaction networks are important for the understanding of regulatory mechanisms, for the explanation of experimental data and for the prediction of protein functions. Unfortunately, most interaction data is available only for model organisms. As a possible remedy, the transfer of interactions to organisms of interest is common practice, but it is not clear when interactions can be transferred from one organism to another and, thus, the confidence in the derived interactions is low. Here, we propose to use a rich set of features to train Random Forests in order to score transferred interactions. We evaluated the transfer from a range of eukaryotic organisms to S. cerevisiae using orthologs. Directly transferred interactions to S. cerevisiae are on average only 24% consistent with the current S. cerevisiae interaction network. By using commonly applied filter approaches the transfer precision can be improved, but at the cost of a large decrease in the number of transferred interactions. Our Random Forest approach uses various features derived from both the target and the source network as well as the ortholog annotations to assign confidence values to transferred interactions. Thereby, we could increase the average transfer consistency to 85%, while still transferring almost 70% of all correctly transferable interactions. We tested our approach for the transfer of interactions to other species and showed that our approach outperforms competing methods for the transfer of interactions to species where no experimental knowledge is available. Finally, we applied our predictor to score transferred interactions to 83 targets species and we were able to extend the available interactome of B. taurus, M. musculus and G. gallus with over 40,000 interactions each. Our transferred interaction networks are publicly available via our web interface, which allows to inspect and download transferred interaction sets of different sizes, for various

  10. Analyzing Bullwhip Effect in Supply Networks under Exogenous Uncertainty

    Directory of Open Access Journals (Sweden)

    Mitra Darvish

    2014-05-01

    Full Text Available This paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. The stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. In fact, we propose an exact formula in order to measure the bullwhip effect in the addressed supply network topology considering the system in Markovian chain framework and presenting a matrix of network member relationships and relevant order sequences. The formula turns out using a mathematical method called frequency domain analysis. The major contribution of this paper is analyzing the bullwhip effect considering exogenous uncertainty in supply networks and using the Fourier transform in order to simplify the relevant calculations. We present a number of numerical examples to assess the analytical results accuracy in quantifying the bullwhip effect.

  11. Analyzing covert social network foundation behind terrorism disaster

    CERN Document Server

    Maeno, Yoshiharu

    2007-01-01

    This paper addresses a method to analyze the covert social network foundation hidden behind the terrorism disaster. It is to solve a node discovery problem, which means to discover a node, which functions relevantly in a social network, but escaped from monitoring on the presence and mutual relationship of nodes. The method aims at integrating the expert investigator's prior understanding, insight on the terrorists' social network nature derived from the complex graph theory, and computational data processing. The social network responsible for the 9/11 attack in 2001 is used to execute simulation experiment to evaluate the performance of the method.

  12. Cell Interactomics and Carcinogenetic Mechanisms

    CERN Document Server

    Baianu, IC; Report to the Institute of Genomics

    2004-01-01

    Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quant...

  13. A framework for analyzing contagion in assortative banking networks

    CERN Document Server

    Hurd, Thomas R; Melnik, Sergey

    2016-01-01

    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (e.g., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition that characterizes whether or not an infinitesimal shock to the network can grow to a finite size cascade, in analogy to the basic reproduction number $R_0$ in epidemic modelling. The cascade condition provides an easily computed measure of the systemic risk inherent in a given banking network topology. Using the percolation theory for random networks we also derive an analytic formula for the frequency of global cas...

  14. A Vector Network Analyzer Based on Pulse Generators

    Directory of Open Access Journals (Sweden)

    B. Schulte

    2005-01-01

    Full Text Available A fast four channel network analyzer is introduced to measure S-parameters in a frequency range from 10MHz to 3GHz. The signal generation for this kind of analyzer is based on pulse generators, which are realized with bipolar transistors. The output signal of the transistor is differentiated and two short pulses, a slow and a fast one, with opposite polarities are generated. The slow pulse is suppressed with a clipping network. Thus the generation of very short electrical pulses with a duration of about 100ps is possible. The structure of the following network analyzer is similar to the structure of a conventional four channel network analyzer. All four pulses, which contain the high frequency information of the device under test, are evaluated after the digitalization of intermediate frequencies. These intermediate frequencies are generated with sampling mixers. The recorded data is evaluated with a special analysis technique, which is based on a Fourier transformation. The calibration techniques used are the same as for conventional four channel network analyzers, no new calibration techniques need to be developed.

  15. Vector network analyzer (VNA) measurements and uncertainty assessment

    CERN Document Server

    Shoaib, Nosherwan

    2017-01-01

    This book describes vector network analyzer measurements and uncertainty assessments, particularly in waveguide test-set environments, in order to establish their compatibility to the International System of Units (SI) for accurate and reliable characterization of communication networks. It proposes a fully analytical approach to measurement uncertainty evaluation, while also highlighting the interaction and the linear propagation of different uncertainty sources to compute the final uncertainties associated with the measurements. The book subsequently discusses the dimensional characterization of waveguide standards and the quality of the vector network analyzer (VNA) calibration techniques. The book concludes with an in-depth description of the novel verification artefacts used to assess the performance of the VNAs. It offers a comprehensive reference guide for beginners to experts, in both academia and industry, whose work involves the field of network analysis, instrumentation and measurements.

  16. Analyzing complex networks evolution through Information Theory quantifiers

    Energy Technology Data Exchange (ETDEWEB)

    Carpi, Laura C., E-mail: Laura.Carpi@studentmail.newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Rosso, Osvaldo A., E-mail: rosso@fisica.ufmg.b [Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina); Saco, Patricia M., E-mail: Patricia.Saco@newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Hidraulica, Facultad de Ciencias Exactas, Ingenieria y Agrimensura, Universidad Nacional de Rosario, Avenida Pellegrini 250, Rosario (Argentina); Ravetti, Martin Gomez, E-mail: martin.ravetti@dep.ufmg.b [Departamento de Engenharia de Producao, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte (31270-901), MG (Brazil)

    2011-01-24

    A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

  17. Analyzing milestoning networks for molecular kinetics: definitions, algorithms, and examples.

    Science.gov (United States)

    Viswanath, Shruthi; Kreuzer, Steven M; Cardenas, Alfredo E; Elber, Ron

    2013-11-07

    Network representations are becoming increasingly popular for analyzing kinetic data from techniques like Milestoning, Markov State Models, and Transition Path Theory. Mapping continuous phase space trajectories into a relatively small number of discrete states helps in visualization of the data and in dissecting complex dynamics to concrete mechanisms. However, not only are molecular networks derived from molecular dynamics simulations growing in number, they are also getting increasingly complex, owing partly to the growth in computer power that allows us to generate longer and better converged trajectories. The increased complexity of the networks makes simple interpretation and qualitative insight of the molecular systems more difficult to achieve. In this paper, we focus on various network representations of kinetic data and algorithms to identify important edges and pathways in these networks. The kinetic data can be local and partial (such as the value of rate coefficients between states) or an exact solution to kinetic equations for the entire system (such as the stationary flux between vertices). In particular, we focus on the Milestoning method that provides fluxes as the main output. We proposed Global Maximum Weight Pathways as a useful tool for analyzing molecular mechanism in Milestoning networks. A closely related definition was made in the context of Transition Path Theory. We consider three algorithms to find Global Maximum Weight Pathways: Recursive Dijkstra's, Edge-Elimination, and Edge-List Bisection. The asymptotic efficiency of the algorithms is analyzed and numerical tests on finite networks show that Edge-List Bisection and Recursive Dijkstra's algorithms are most efficient for sparse and dense networks, respectively. Pathways are illustrated for two examples: helix unfolding and membrane permeation. Finally, we illustrate that networks based on local kinetic information can lead to incorrect interpretation of molecular mechanisms.

  18. Analyzing the Bitcoin Network: The First Four Years

    Directory of Open Access Journals (Sweden)

    Matthias Lischke

    2016-03-01

    Full Text Available In this explorative study, we examine the economy and transaction network of the decentralized digital currency Bitcoin during the first four years of its existence. The objective is to develop insights into the evolution of the Bitcoin economy during this period. For this, we establish and analyze a novel integrated dataset that enriches data from the Bitcoin blockchain with off-network data such as business categories and geo-locations. Our analyses reveal the major Bitcoin businesses and markets. Our results also give insights on the business distribution by countries and how businesses evolve over time. We also show that there is a gambling network that features many very small transactions. Furthermore, regional differences in the adoption and business distribution could be found. In the network analysis, the small world phenomenon is investigated and confirmed for several subgraphs of the Bitcoin network.

  19. The wireshark field guide analyzing and troubleshooting network traffic

    CERN Document Server

    Shimonski, Robert

    2013-01-01

    The Wireshark Field Guide provides hackers, pen testers, and network administrators with practical guidance on capturing and interactively browsing computer network traffic. Wireshark is the world's foremost network protocol analyzer, with a rich feature set that includes deep inspection of hundreds of protocols, live capture, offline analysis and many other features. The Wireshark Field Guide covers the installation, configuration and use of this powerful multi-platform tool. The book give readers the hands-on skills to be more productive with Wireshark as they drill

  20. Systems and methods for modeling and analyzing networks

    Science.gov (United States)

    Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

    2013-10-29

    The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

  1. Towards establishment of a rice stress response interactome.

    Directory of Open Access Journals (Sweden)

    Young-Su Seo

    2011-04-01

    Full Text Available Rice (Oryza sativa is a staple food for more than half the world and a model for studies of monocotyledonous species, which include cereal crops and candidate bioenergy grasses. A major limitation of crop production is imposed by a suite of abiotic and biotic stresses resulting in 30%-60% yield losses globally each year. To elucidate stress response signaling networks, we constructed an interactome of 100 proteins by yeast two-hybrid (Y2H assays around key regulators of the rice biotic and abiotic stress responses. We validated the interactome using protein-protein interaction (PPI assays, co-expression of transcripts, and phenotypic analyses. Using this interactome-guided prediction and phenotype validation, we identified ten novel regulators of stress tolerance, including two from protein classes not previously known to function in stress responses. Several lines of evidence support cross-talk between biotic and abiotic stress responses. The combination of focused interactome and systems analyses described here represents significant progress toward elucidating the molecular basis of traits of agronomic importance.

  2. Analyzing Reactive Routing Protocols in Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Dr. Kamaljit I. Lakhtaria

    2012-05-01

    Full Text Available Mobile Ad Hoc Network (MANET is an autonomous mobile nodes forming network in an infrastructure less environment and has dynamic topology. MANET reactive protocols always not have low control overhead. The control overhead for reactive protocols is more sensitive to the traffic load, in terms of the number of traffic rows, and mobility, in terms of link connectivity change rates, than other protocols. Therefore, reactive protocols may only be suitable for MANETs with small number of traffic loads and small link connectivity change rates. It is already proved that, it is more feasible to maintain full network topology in a MANET with low control overhead. In this Research Paper through simulations that were carried out by using Network Simulator-2 (NS-2 we had analyze Reactive/ On-demand protocols such as Ad Hoc On-Demand Distance Vector Routing (AODV, Temporally-Ordered Routing Algorithm (TORA, and Dynamic Source Routing (DSR,

  3. A framework for analyzing contagion in assortative banking networks.

    Science.gov (United States)

    Hurd, Thomas R; Gleeson, James P; Melnik, Sergey

    2017-01-01

    We introduce a probabilistic framework that represents stylized banking networks with the aim of predicting the size of contagion events. Most previous work on random financial networks assumes independent connections between banks, whereas our framework explicitly allows for (dis)assortative edge probabilities (i.e., a tendency for small banks to link to large banks). We analyze default cascades triggered by shocking the network and find that the cascade can be understood as an explicit iterated mapping on a set of edge probabilities that converges to a fixed point. We derive a cascade condition, analogous to the basic reproduction number R0 in epidemic modelling, that characterizes whether or not a single initially defaulted bank can trigger a cascade that extends to a finite fraction of the infinite network. This cascade condition is an easily computed measure of the systemic risk inherent in a given banking network topology. We use percolation theory for random networks to derive a formula for the frequency of global cascades. These analytical results are shown to provide limited quantitative agreement with Monte Carlo simulation studies of finite-sized networks. We show that edge-assortativity, the propensity of nodes to connect to similar nodes, can have a strong effect on the level of systemic risk as measured by the cascade condition. However, the effect of assortativity on systemic risk is subtle, and we propose a simple graph theoretic quantity, which we call the graph-assortativity coefficient, that can be used to assess systemic risk.

  4. Analyzing the multilevel structure of the European airport network

    Directory of Open Access Journals (Sweden)

    Oriol Lordan

    2017-04-01

    Full Text Available The multilayered structure of the European airport network (EAN, composed of connections and flights between European cities, is analyzed through the k-core decomposition of the connections network. This decomposition allows to identify the core, bridge and periphery layers of the EAN. The core layer includes the best-connected cities, which include important business air traffic destinations. The periphery layer includes cities with lesser connections, which serve low populated areas where air travel is an economic alternative. The remaining cities form the bridge of the EAN, including important leisure travel origins and destinations. The multilayered structure of the EAN affects network robustness, as the EAN is more robust to isolation of nodes of the core, than to the isolation of a combination of core and bridge nodes.

  5. Analyzing Enterprise Networks Needs: Action Research from the Mechatronics Sector

    Science.gov (United States)

    Cagnazzo, Luca; Taticchi, Paolo; Bidini, Gianni; Baglieri, Enzo

    New business models and theories are developing nowadays towards collaborative environments direction, and many new tools in sustaining companies involved in these organizations are emerging. Among them, a plethora of methodologies to analyze their needs are already developed for single companies. Few academic works are available about Enterprise Networks (ENs) need analysis. This paper presents the learning from an action research (AR) in the mechatronics sector: AR has been used in order to experience the issue of evaluating network needs and therefore define, develop, and test a complete framework for network evaluation. Reflection on the story in the light of the experience and the theory is presented, as well as extrapolation to a broader context and articulation of usable knowledge.

  6. Innovation Networks New Approaches in Modelling and Analyzing

    CERN Document Server

    Pyka, Andreas

    2009-01-01

    The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly. In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state. The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.

  7. Analyzing neuronal networks using discrete-time dynamics

    Science.gov (United States)

    Ahn, Sungwoo; Smith, Brian H.; Borisyuk, Alla; Terman, David

    2010-05-01

    We develop mathematical techniques for analyzing detailed Hodgkin-Huxley like models for excitatory-inhibitory neuronal networks. Our strategy for studying a given network is to first reduce it to a discrete-time dynamical system. The discrete model is considerably easier to analyze, both mathematically and computationally, and parameters in the discrete model correspond directly to parameters in the original system of differential equations. While these networks arise in many important applications, a primary focus of this paper is to better understand mechanisms that underlie temporally dynamic responses in early processing of olfactory sensory information. The models presented here exhibit several properties that have been described for olfactory codes in an insect’s Antennal Lobe. These include transient patterns of synchronization and decorrelation of sensory inputs. By reducing the model to a discrete system, we are able to systematically study how properties of the dynamics, including the complex structure of the transients and attractors, depend on factors related to connectivity and the intrinsic and synaptic properties of cells within the network.

  8. Analyzing the Low Power Wireless Links for Wireless Sensor Networks

    CERN Document Server

    Mamun, Md Mainul Islam; Kumar, Sumon; Islam, Md Zahidul

    2010-01-01

    There is now an increased understanding of the need for realistic link layer models in the wireless sensor networks. In this paper, we have used mathematical techniques from communication theory to model and analyze low power wireless links. Our work provides theoretical models for the link layer showing how Packet Reception Rate vary with Signal to Noise Ratio and distance for different modulation schemes and a comparison between MICA2 and TinyNode in terms of PRR.

  9. Bridging Women Rights Networks: Analyzing Interconnected Online Collective Actions

    OpenAIRE

    Serpil T. Yuce; Nitin Agarwal; Wigand, Rolf T.; Merlyna Lim; Rebecca S. Robinson

    2014-01-01

    In recent mass protests such as the Arab Spring and Occupy movements, protesters used social media to spread awareness, coordinate, and mobilize support. Social media-assisted collective action has attracted much attention from journalists, political observers, and researchers of various disciplines. In this article, the authors study transnational online collective action through the lens of inter-network cooperation. The authors analyze interaction and support between the women's rights net...

  10. Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

    Directory of Open Access Journals (Sweden)

    Yunpeng Xiao

    2012-01-01

    Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

  11. Alzheimer disease: An interactome of many diseases

    Directory of Open Access Journals (Sweden)

    Balaji S Rao

    2014-01-01

    Full Text Available Alzheimer Disease (AD is an outcome as well as source of many diseases. Alzheimer is linked with many other diseases like Diabetes type 2, cholesterolemia, hypertension and many more. But how each of these diseases affecting other is still unknown to scientific community. Signaling Pathways of one disease is interlinked with other disease. But to what extent healthy brain is affected when any signaling in human body is disturbed is the question that matters. There is a need of Pathway analysis, Protein-Protein interaction (PPI and the conserved interactome study in AD and linked diseases. It will be helpful in finding the potent drug or vaccine target in conscious manner. In the present research the Protein-Protein interaction of all the proteins involved in Alzheimer Disease is analyzed using ViSANT and osprey tools and pathway analysis further reveals the significant genes/proteins linking AD with other diseases.

  12. Network analyzer calibration for cryogenic on-wafer measurements

    Energy Technology Data Exchange (ETDEWEB)

    Hietala, V.M.; Housel, M.S.; Caldwell, R.B.

    1994-04-01

    A cryogenic probe station for on-wafer microwave measurements has been developed at Sandia National Laboratories to explore the basic device physics and characterize advanced components for low-temperature applications. The station was designed to operate over a temperature range of 20 to 300 K with a frequency range of DC to 50 GHz. Due to the vacuum and the low temperature environment, the use of microwave probes and the calibration of network analyzer measurements are somewhat elaborate. This paper presents guidelines for probe use and calibration in this environment.

  13. A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

    Science.gov (United States)

    Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

    2005-01-01

    This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

  14. Construction of Dynamic-weighted Protein Interactome Network and Its Application%动态加权蛋白质相互作用网络构建及其应用研究

    Institute of Scientific and Technical Information of China (English)

    胡赛; 熊慧军; 赵碧海; 李学勇; 王晶

    2015-01-01

    A protein would interact with different proteins under different conditions or at different time instants, which is the dynamic attribute of interactions. Proteins participate in different functional modules in different stages of molecular processing to perform different functions with other proteins. So, research of dynamic protein-protein interaction would contribute to the accuracy improvement of protein functions prediction. We construct a dynamic protein interaction network (D-PIN) by integrating protein-protein interaction network and time course gene expression data. To reduce the negative effect of false "negative" on the protein function prediction, we predict and generate some new protein interactions which combine with proteins' domain information and protein complexes information and weight all the interactions. Based on the weighted dynamic network, we propose a method for predicting protein function, named D-PIN. Experimental results compared with using three different yeast interactome networks indicate that the comprehensive performance of D-PIN is 14% higher other competing methods. Results also verify the effectiveness of the constructed dynamic-weighted protein interactome network.%一个蛋白质可能在不同条件或不同时刻与不同的蛋白质发生相互作用, 这称为蛋白质的动态特性. 蛋白质在分子处理的不同阶段参与到不同的模块, 与其他的蛋白质共同完成某项功能. 因此, 动态蛋白质相互作用的研究有助于提高蛋白质功能预测的准确率. 结合蛋白质相互作用网络和时间序列基因表达数据, 构建动态蛋白质相互作用网络. 为降低PPI 网络中假阴性对功能预测产生的负面影响, 结合结构域信息和复合物信息, 预测和产生新的相互作用, 并对相互作用加权. 基于构建的动态加权网络, 提出一种功能预测方法D-PIN (Dynamic protein interaction networks). 基于三个不同的酵母相互

  15. A data-integrated method for analyzing stochastic biochemical networks.

    Science.gov (United States)

    Chevalier, Michael W; El-Samad, Hana

    2011-12-07

    Variability and fluctuations among genetically identical cells under uniform experimental conditions stem from the stochastic nature of biochemical reactions. Understanding network function for endogenous biological systems or designing robust synthetic genetic circuits requires accounting for and analyzing this variability. Stochasticity in biological networks is usually represented using a continuous-time discrete-state Markov formalism, where the chemical master equation (CME) and its kinetic Monte Carlo equivalent, the stochastic simulation algorithm (SSA), are used. These two representations are computationally intractable for many realistic biological problems. Fitting parameters in the context of these stochastic models is particularly challenging and has not been accomplished for any but very simple systems. In this work, we propose that moment equations derived from the CME, when treated appropriately in terms of higher order moment contributions, represent a computationally efficient framework for estimating the kinetic rate constants of stochastic network models and subsequent analysis of their dynamics. To do so, we present a practical data-derived moment closure method for these equations. In contrast to previous work, this method does not rely on any assumptions about the shape of the stochastic distributions or a functional relationship among their moments. We use this method to analyze a stochastic model of a biological oscillator and demonstrate its accuracy through excellent agreement with CME/SSA calculations. By coupling this moment-closure method with a parameter search procedure, we further demonstrate how a model's kinetic parameters can be iteratively determined in order to fit measured distribution data. © 2011 American Institute of Physics

  16. Mapping the human protein interactome

    Institute of Scientific and Technical Information of China (English)

    Daniel Figeys

    2008-01-01

    Interactions are the essence of all biomolecules because they cannot fulfill their roles without interacting with other molecules. Hence, mapping the interactions of biomolecules can be useful for understanding their roles and functions. Furthermore, the development of molecular based systems biology requires an understanding of the biomolecular interactions. In recent years, the mapping of protein-protein interactions in different species has been reported, but few reports have focused on the large-scale mapping of protein-protein interactions in human. Here, we review the developments in protein interaction mapping and we discuss issues and strategies for the mapping of the human protein interactome.

  17. The HTLV-1 Tax interactome

    Directory of Open Access Journals (Sweden)

    Kettmann Richard

    2008-08-01

    Full Text Available Abstract The Tax1 oncoprotein encoded by Human T-lymphotropic virus type I is a major determinant of viral persistence and pathogenesis. Tax1 affects a wide variety of cellular signalling pathways leading to transcriptional activation, proliferation and ultimately transformation. To carry out these functions, Tax1 interacts with and modulates activity of a number of cellular proteins. In this review, we summarize the present knowledge of the Tax1 interactome and propose a rationale for the broad range of cellular proteins identified so far.

  18. A commercial application of survivable network design: ITP/INPLANS CCS Network Topology Analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Mihail, M.; Shallcross, D.; Dean, N.; Mostrel, M.

    1996-12-31

    The ITP/INPLANS CCS Network Topology Analyzer is a Bellcore product which performs automated design of cost effective survivable CCS (Common Channel Signaling) networks, with survivability meaning that certain path-connectivity is preserved under limited failures of network elements. The algorithmic core of this product consists of suitable extensions of primal-dual approximation schemes for Steiner network problems. Even though most of the survivability problems arising in CCS networks are not strictly of the form for which the approximation algorithms with proven performance guarantees apply, we implemented modifications of these algorithms with success: In addition to duality-based performance guarantees that indicate, mathematically, discrepancy of no more than 20% from optimality for generic Steiner problems and no more than 40% for survivable CCS networks, our software passed all commercial benchmark tests, and our code was deployed with the August 94 release of the product. CCS networks fall in the general category of low bit-rate backbone networks. The main characteristic of survivability problems for these networks is that each edge, once present, can be assumed to carry arbitrarily many paths. For high bit-rate backbone networks, such as the widely used ATM and SONET, this is no longer the case. We discuss versions of network survivability with capacitated edges that appear to model survivability considerations in such networks.

  19. Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic and African-American groups.

    Directory of Open Access Journals (Sweden)

    Naif Zaman

    Full Text Available The androgen receptor (AR remains an important contributor to the neoplastic evolution of prostate cancer (CaP. CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A, located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate. In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems.

  20. Proteomic-coupled-network analysis of T877A-androgen receptor interactomes can predict clinical prostate cancer outcomes between White (non-Hispanic) and African-American groups.

    Science.gov (United States)

    Zaman, Naif; Giannopoulos, Paresa N; Chowdhury, Shafinaz; Bonneil, Eric; Thibault, Pierre; Wang, Edwin; Trifiro, Mark; Paliouras, Miltiadis

    2014-01-01

    The androgen receptor (AR) remains an important contributor to the neoplastic evolution of prostate cancer (CaP). CaP progression is linked to several somatic AR mutational changes that endow upon the AR dramatic gain-of-function properties. One of the most common somatic mutations identified is Thr877-to-Ala (T877A), located in the ligand-binding domain, that results in a receptor capable of promiscuous binding and activation by a variety of steroid hormones and ligands including estrogens, progestins, glucocorticoids, and several anti-androgens. In an attempt to further define somatic mutated AR gain-of-function properties, as a consequence of its promiscuous ligand binding, we undertook a proteomic/network analysis approach to characterize the protein interactome of the mutant T877A-AR in LNCaP cells under eight different ligand-specific treatments (dihydrotestosterone, mibolerone, R1881, testosterone, estradiol, progesterone, dexamethasone, and cyproterone acetate). In extending the analysis of our multi-ligand complexes of the mutant T877A-AR we observed significant enrichment of specific complexes between normal and primary prostatic tumors, which were furthermore correlated with known clinical outcomes. Further analysis of certain mutant T877A-AR complexes showed specific population preferences distinguishing primary prostatic disease between white (non-Hispanic) vs. African-American males. Moreover, these cancer-related AR-protein complexes demonstrated predictive survival outcomes specific to CaP, and not for breast, lung, lymphoma or medulloblastoma cancers. Our study, by coupling data generated by our proteomics to network analysis of clinical samples, has helped to define real and novel biological pathways in complicated gain-of-function AR complex systems.

  1. Multifrequency polarimetric microwave scatterometer based on a vector network analyzer

    Science.gov (United States)

    D'Alessio, Angelo C.; Posa, Francesco; Sabatelli, Vincenzo; Casarano, Domenico

    1999-12-01

    In order to test a multi-frequency polarimetric scatterometer based on a Vector Network Analyzer, calibration measurements have been performed over point targets. Two trihedral corner reflectors with different dimensions have been employed. The radar cross sections have been measured at different frequency bands (L, C and X) and for different look angles between 23 degree(s) and 50 degree(s). Satisfactory results have been obtained in all three bands, however in the L-band the electromagnetic smog, due to mobile phones and airport radars, caused some difficulties in the extinction of the radiometric information. Other calibration tests have been planned before using the instrument as a ground-truth data acquisition device on the test-sites envisaged for the spaceborne SRTM and ENVISAT SAR missions.

  2. Analyzing Nonblocking Switching Networks using Linear Programming (Duality)

    CERN Document Server

    Ngo, Hung Q; Le, Anh N; Nguyen, Thanh-Nhan

    2012-01-01

    The main task in analyzing a switching network design (including circuit-, multirate-, and photonic-switching) is to determine the minimum number of some switching components so that the design is non-blocking in some sense (e.g., strict- or wide-sense). We show that, in many cases, this task can be accomplished with a simple two-step strategy: (1) formulate a linear program whose optimum value is a bound for the minimum number we are seeking, and (2) specify a solution to the dual program, whose objective value by weak duality immediately yields a sufficient condition for the design to be non-blocking. We illustrate this technique through a variety of examples, ranging from circuit to multirate to photonic switching, from unicast to $f$-cast and multicast, and from strict- to wide-sense non-blocking. The switching architectures in the examples are of Clos-type and Banyan-type, which are the two most popular architectural choices for designing non-blocking switching networks. To prove the result in the multir...

  3. Strategizing through analyzing and influencing the network horizon

    NARCIS (Netherlands)

    Holmen, Elsebeth; Pedersen, Ann-Charlott

    2003-01-01

    How does a firm keep on being valuable in a network? One requirement is that the firm has a sufficient overview of the network and its dynamics. In other words, a firm's strategy depends on the firm's overview of the network—its network horizon. How comprehensive or limited should its network

  4. Biasing vector network analyzers using variable frequency and amplitude signals

    Science.gov (United States)

    Nobles, J. E.; Zagorodnii, V.; Hutchison, A.; Celinski, Z.

    2016-08-01

    We report the development of a test setup designed to provide a variable frequency biasing signal to a vector network analyzer (VNA). The test setup is currently used for the testing of liquid crystal (LC) based devices in the microwave region. The use of an AC bias for LC based devices minimizes the negative effects associated with ionic impurities in the media encountered with DC biasing. The test setup utilizes bias tees on the VNA test station to inject the bias signal. The square wave biasing signal is variable from 0.5 to 36.0 V peak-to-peak (VPP) with a frequency range of DC to 10 kHz. The test setup protects the VNA from transient processes, voltage spikes, and high-frequency leakage. Additionally, the signals to the VNA are fused to ½ amp and clipped to a maximum of 36 VPP based on bias tee limitations. This setup allows us to measure S-parameters as a function of both the voltage and the frequency of the applied bias signal.

  5. Towards a theoretical framework for analyzing complex linguistic networks

    CERN Document Server

    Lücking, Andy; Banisch, Sven; Blanchard, Philippe; Job, Barbara

    2016-01-01

    The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities.This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statisticalmodels of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information scien...

  6. Interactome and Gene Ontology provide congruent yet subtly different views of a eukaryotic cell

    Directory of Open Access Journals (Sweden)

    Marín Ignacio

    2009-07-01

    Full Text Available Abstract Background The characterization of the global functional structure of a cell is a major goal in bioinformatics and systems biology. Gene Ontology (GO and the protein-protein interaction network offer alternative views of that structure. Results This study presents a comparison of the global structures of the Gene Ontology and the interactome of Saccharomyces cerevisiae. Sensitive, unsupervised methods of clustering applied to a large fraction of the proteome led to establish a GO-interactome correlation value of +0.47 for a general dataset that contains both high and low-confidence interactions and +0.58 for a smaller, high-confidence dataset. Conclusion The structures of the yeast cell deduced from GO and interactome are substantially congruent. However, some significant differences were also detected, which may contribute to a better understanding of cell function and also to a refinement of the current ontologies.

  7. Using ordinal partition transition networks to analyze ECG data

    Science.gov (United States)

    Kulp, Christopher W.; Chobot, Jeremy M.; Freitas, Helena R.; Sprechini, Gene D.

    2016-07-01

    Electrocardiogram (ECG) data from patients with a variety of heart conditions are studied using ordinal pattern partition networks. The ordinal pattern partition networks are formed from the ECG time series by symbolizing the data into ordinal patterns. The ordinal patterns form the nodes of the network and edges are defined through the time ordering of the ordinal patterns in the symbolized time series. A network measure, called the mean degree, is computed from each time series-generated network. In addition, the entropy and number of non-occurring ordinal patterns (NFP) is computed for each series. The distribution of mean degrees, entropies, and NFPs for each heart condition studied is compared. A statistically significant difference between healthy patients and several groups of unhealthy patients with varying heart conditions is found for the distributions of the mean degrees, unlike for any of the distributions of the entropies or NFPs.

  8. Image Cytometry Data From Breast Lesions Analyzed using Hybrid Networks.

    Science.gov (United States)

    Mat Sakim, H A; Mat Isa, N A; G Naguib, Raouf; Sherbet, Gajanan

    2005-01-01

    The treatment and therapy to be administered on breast cancer patients are dependent on the stage of the disease at time of diagnosis. It is therefore crucial to determine the stage at the earliest time possible. Tumor dissemination to axillary lymph nodes has been regarded as an indication of tumor aggression, thus the stage of the disease. Neural networks have been employed in many applications including breast cancer prognosis. The performance of the networks have often been quoted based on accuracy and mean squared error. In this paper, the performance of hybrid networks based on Multilayer Perceptron and Radial Basis Function networks to predict axillary lymph node involvement have been investigated. A measurement of how confident the networks are with respect to the results produced is also proposed. The input layer of the networks include four image cytometry features extracted from fine needle aspiration of breast lesions. The highest accuracy achieved by the hybrid networks was 69% only. However, most of the correctly predicted cases had a high confidence level.

  9. Analyzing GAIAN Database (GaianDB) on a Tactical Network

    Science.gov (United States)

    2015-11-30

    NAME(S) AND ADDRESS(ES) US Army Research Laboratory ATTN: RDRL-CIN-T 2800 Powder Mill Road Adelphi, MD 20783-1138 8. PERFORMING ORGANIZATION...with the second-generation CSRs, we discovered that Internet Protocol (IP) encapsulation of GaianDB traffic in radio frequency (RF) transmissions...create a network bridge or, in our case, create an ad-hoc network by encapsulating raw packets (which contain preambles and Ethernet frames) inside

  10. MODELING AND AVAILABILITY ANALYZES OF A COMPLEX GAS PIPELINE NETWORK

    Energy Technology Data Exchange (ETDEWEB)

    Ainouche, A.; Ainouche, H.

    2007-07-01

    The network reliability, in the way of security of supply of international markets, is proved to be an essential criterion for the conservation of the market shares and the conquest of new customers. In relation with the importance and the existing configurations diversity of gas pipelines networks, the obtaining of a global availability model of a network is difficult to implement by the use of a classic approach based on the analysis of the whole of failure risks, the definition of their probability and the estimation of their impact in term of productivity. This because mainly of the huge dimensions of the phase space that would result from such a conception. To get round this problem we implemented a systemic type approach for the modeling of the availability of a complex gas pipelines network. The approach of modeling is of 'bottom-up' type. The model of coordination is a model of flow maximization whose formalization requires the representation of the gas pipeline network by the graphs theory. The developed tool can also be used as a stand of experimentation and to define by simulation the impact of every decision having the tendency to improve the availability of the network. (auth)

  11. ANAT: a tool for constructing and analyzing functional protein networks.

    Science.gov (United States)

    Yosef, Nir; Zalckvar, Einat; Rubinstein, Assaf D; Homilius, Max; Atias, Nir; Vardi, Liram; Berman, Igor; Zur, Hadas; Kimchi, Adi; Ruppin, Eytan; Sharan, Roded

    2011-10-25

    Genome-scale screening studies are gradually accumulating a wealth of data on the putative involvement of hundreds of genes in various cellular responses or functions. A fundamental challenge is to chart the molecular pathways that underlie these systems. ANAT is an interactive software tool, implemented as a Cytoscape plug-in, for elucidating functional networks of proteins. It encompasses a number of network inference algorithms and provides access to networks of physical associations in several organisms. In contrast to existing software tools, ANAT can be used to infer subnetworks that connect hundreds of proteins to each other or to a given set of "anchor" proteins, a fundamental step in reconstructing cellular subnetworks. The interactive component of ANAT provides an array of tools for evaluating and exploring the resulting subnetwork models and for iteratively refining them. We demonstrate the utility of ANAT by studying the crosstalk between the autophagic and apoptotic cell death modules in humans, using a network of physical interactions. Relative to published software tools, ANAT is more accurate and provides more features for comprehensive network analysis. The latest version of the software is available at http://www.cs.tau.ac.il/~bnet/ANAT_SI.

  12. Analyzing rocket plume spectral data with neural networks

    Science.gov (United States)

    Whitaker, Kevin W.; Krishnakumar, K. S.; Benzing, Daniel A.

    1995-01-01

    The Optical Plume Anomaly Detection (OPAD) system is under development to provide early-warning failure detection in support of ground-level testing of the Space Shuttle Main Engine (SSME). Failure detection is to be achieved through the acquisition of spectrally resolved plume emissions and subsequent identification of abnormal levels indicative of engine corrosion or component failure. Two computer codes (one linear and the other non-linear) are used by the OPAD system to iteratively determine specific element concentrations in the SSME plume, given emission intensity and wavelength information. Since this analysis is extremely labor intensive, a study was initiated to develop neural networks that would model the 'inverse' of these computer codes. Optimally connected feed-forward networks with imperceptible prediction error have been developed for each element modeled by the linear code, SPECTRA4. Radial basis function networks were developed for the non-linear code, SPECTRA5, and predict combustion temperature in addition to element concentrations.

  13. Analyzing rocket plume spectral data with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Whitaker, K.W.; Krishnakumar, K.S.; Benzing, D.A.

    1995-09-01

    The Optical Plume Anomaly Detection (OPAD) system is under development to provide early-warning failure detection in support of ground-level testing of the Space Shuttle Main Engine (SSME). Failure detection is to be achieved through the acquisition of spectrally resolved plume emissions and subsequent identification of abnormal levels indicative of engine corrosion or component failure. Two computer codes (one linear and the other non-linear) are used by the OPAD system to iteratively determine specific element concentrations in the SSME plume, given emission intensity and wavelength information. Since this analysis is extremely labor intensive, a study was initiated to develop neural networks that would model the `inverse` of these computer codes. Optimally connected feed-forward networks with imperceptible prediction error have been developed for each element modeled by the linear code, SPECTRA4. Radial basis function networks were developed for the non-linear code, SPECTRA5, and predict combustion temperature in addition to element concentrations.

  14. Analyzing rocket plume spectral data with neural networks

    Science.gov (United States)

    Whitaker, Kevin W.; Krishnakumar, K. S.; Benzing, Daniel A.

    The Optical Plume Anomaly Detection (OPAD) system is under development to provide early-warning failure detection in support of ground-level testing of the Space Shuttle Main Engine (SSME). Failure detection is to be achieved through the acquisition of spectrally resolved plume emissions and subsequent identification of abnormal levels indicative of engine corrosion or component failure. Two computer codes (one linear and the other non-linear) are used by the OPAD system to iteratively determine specific element concentrations in the SSME plume, given emission intensity and wavelength information. Since this analysis is extremely labor intensive, a study was initiated to develop neural networks that would model the 'inverse' of these computer codes. Optimally connected feed-forward networks with imperceptible prediction error have been developed for each element modeled by the linear code, SPECTRA4. Radial basis function networks were developed for the non-linear code, SPECTRA5, and predict combustion temperature in addition to element concentrations.

  15. Analyzing Human Communication Networks in Organizations: Applications to Management Problems.

    Science.gov (United States)

    Farace, Richard V.; Danowski, James A.

    Investigating the networks of communication in organizations leads to an understanding of efficient and inefficient information dissemination as practiced in large systems. Most important in organizational communication is the role of the "liaison person"--the coordinator of intercommunication. When functioning efficiently, coordinators maintain…

  16. Analyzing the international exergy flow network of ferrous metal ores.

    Science.gov (United States)

    Qi, Hai; An, Haizhong; Hao, Xiaoqing; Zhong, Weiqiong; Zhang, Yanbing

    2014-01-01

    This paper employs an un-weighted and weighted exergy network to study the properties of ferrous metal ores in countries worldwide and their evolution from 2002 to 2012. We find that there are few countries controlling most of the ferrous metal ore exports in terms of exergy and that the entire exergy flow network is becoming more heterogeneous though the addition of new nodes. The increasing of the average clustering coefficient indicates that the formation of an international exergy flow system and regional integration is improving. When we contrast the average out strength of exergy and the average out strength of currency, we find both similarities and differences. Prices are affected largely by human factors; thus, the growth rate of the average out strength of currency has fluctuated acutely in the eleven years from 2002 to 2012. Exergy is defined as the maximum work that can be extracted from a system and can reflect the true cost in the world, and this parameter fluctuates much less. Performing an analysis based on the two aspects of exergy and currency, we find that the network is becoming uneven.

  17. Analyzing the International Exergy Flow Network of Ferrous Metal Ores

    Science.gov (United States)

    Qi, Hai; An, Haizhong; Hao, Xiaoqing; Zhong, Weiqiong; Zhang, Yanbing

    2014-01-01

    This paper employs an un-weighted and weighted exergy network to study the properties of ferrous metal ores in countries worldwide and their evolution from 2002 to 2012. We find that there are few countries controlling most of the ferrous metal ore exports in terms of exergy and that the entire exergy flow network is becoming more heterogeneous though the addition of new nodes. The increasing of the average clustering coefficient indicates that the formation of an international exergy flow system and regional integration is improving. When we contrast the average out strength of exergy and the average out strength of currency, we find both similarities and differences. Prices are affected largely by human factors; thus, the growth rate of the average out strength of currency has fluctuated acutely in the eleven years from 2002 to 2012. Exergy is defined as the maximum work that can be extracted from a system and can reflect the true cost in the world, and this parameter fluctuates much less. Performing an analysis based on the two aspects of exergy and currency, we find that the network is becoming uneven. PMID:25188407

  18. Look Together: Analyzing Gaze Coordination with Epistemic Network Analysis

    Directory of Open Access Journals (Sweden)

    Sean eAndrist

    2015-07-01

    Full Text Available When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique—epistemic network analysis—to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1 properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2 optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3 differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

  19. Using Social Network Analysis to Analyze Collaboration in Batik Smes

    Directory of Open Access Journals (Sweden)

    Ade Iriani

    2013-12-01

    Full Text Available As a creative industry, batik industry should always create a breakthrough in the form of innovative batik motifs to attract buyers. Manufacturers of batik in Indonesia are batik SMEs with very simple organization and management. However, they are in a competitive business environment that threatens their survival. In order to continue to create innovative products, collaboration of employees in batik SMEs is absolute important. Collaboration between individuals is more likely to occur in the patterns of informal relationships rather than in formal ways. This article examines and analyses the patterns of informal relations in WindaSari batik. Winda Sari batik SME is one of big SMEs in Sragen. Using Social Network Analysis (SNA for analysis, the results of this study indicate that the relationships between individuals are highly dependent and focused on the specific individuals as intermediaries. In addition, there are patterns of relationships in the subgroups, or cliques, which have only a few numbers of members. In addition, the relationships appear to be one-way relationships than reciprocal relationships. This kind of relationships is less support to collaboration.

  20. ANALYZING SOCIAL NETWORKS FROM THE PERSPECTIVE OF MARKETING DECISIONS

    Directory of Open Access Journals (Sweden)

    Logica BANICA

    2015-12-01

    Full Text Available Nowadays, the Web became more than a space for product presentation, but also a capitalization market (e-commerce and an efficient way to know the customer preferences and to meet their requirements. Large companies have the financial potential to use various marketing strategies and, in particular, digital-marketing. Instead, small businesses are looking for lower cost or no cost methods (also called guerrilla marketing. A small company can compete with a large company by approaching a particular range of products that excel in quality, and also by inventiveness in the marketing strategy. During 2010-2015 the potential of Information Technology and Communications (IT&C sector was proved for the companies which aimed towards modernization of technologies and introduced new strategies in order to commercialize new products. An important challenge for companies was to be aware of the changes in customer behaviour, using social networks software. Finally, research centers have set up new IT&C services and improved marketing and communications following the crisis. More and more companies invest in analytic tools to monitor their marketing strategies and Big Data becomes extremely useful for this purpose, using information like customer demographics and spending habits, oscillation between simplicity, comfort and glamour. There are various tools that can transform in a very short time, massive amounts of data into real business value in a very short time, helping companies and retailers to understand, at any point in the product lifecycle, which trends are gaining and which are losing ground. These insights give them the possibility to reduce the risk of not selling their products by making adjustments to the design, production or promotional strategies, before putting the goods on the market. In this paper we aim to present the advantages of exploring customer requirements from social media for marketing strategy of an enterprise, by using SNA

  1. In vitro nuclear interactome of the HIV-1 Tat protein.

    LENUS (Irish Health Repository)

    Gautier, Virginie W

    2009-01-01

    BACKGROUND: One facet of the complexity underlying the biology of HIV-1 resides not only in its limited number of viral proteins, but in the extensive repertoire of cellular proteins they interact with and their higher-order assembly. HIV-1 encodes the regulatory protein Tat (86-101aa), which is essential for HIV-1 replication and primarily orchestrates HIV-1 provirus transcriptional regulation. Previous studies have demonstrated that Tat function is highly dependent on specific interactions with a range of cellular proteins. However they can only partially account for the intricate molecular mechanisms underlying the dynamics of proviral gene expression. To obtain a comprehensive nuclear interaction map of Tat in T-cells, we have designed a proteomic strategy based on affinity chromatography coupled with mass spectrometry. RESULTS: Our approach resulted in the identification of a total of 183 candidates as Tat nuclear partners, 90% of which have not been previously characterised. Subsequently we applied in silico analysis, to validate and characterise our dataset which revealed that the Tat nuclear interactome exhibits unique signature(s). First, motif composition analysis highlighted that our dataset is enriched for domains mediating protein, RNA and DNA interactions, and helicase and ATPase activities. Secondly, functional classification and network reconstruction clearly depicted Tat as a polyvalent protein adaptor and positioned Tat at the nexus of a densely interconnected interaction network involved in a range of biological processes which included gene expression regulation, RNA biogenesis, chromatin structure, chromosome organisation, DNA replication and nuclear architecture. CONCLUSION: We have completed the in vitro Tat nuclear interactome and have highlighted its modular network properties and particularly those involved in the coordination of gene expression by Tat. Ultimately, the highly specialised set of molecular interactions identified will

  2. Interactome analyses of Salmonella pathogenicity islands reveal SicA indispensable for virulence.

    Science.gov (United States)

    Lahiri, Chandrajit; Pawar, Shrikant; Sabarinathan, Radhakrishnan; Ashraf, Md Izhar; Chand, Yamini; Chakravortty, Dipshikha

    2014-12-21

    Serovars of Salmonella enterica, namely Typhi and Typhimurium, reportedly, are the bacterial pathogens causing systemic infections like gastroenteritis and typhoid fever. To elucidate the role and importance in such infection, the proteins of the Type III secretion system of Salmonella pathogenicity islands and two component signal transduction systems, have been mainly focused. However, the most indispensable of these virulent ones and their hierarchical role has not yet been studied extensively. We have adopted a theoretical approach to build an interactome comprising the proteins from the Salmonella pathogeneicity islands (SPI) and two component signal transduction systems. This interactome was then analyzed by using network parameters like centrality and k-core measures. An initial step to capture the fingerprint of the core network resulted in a set of proteins which are involved in the process of invasion and colonization, thereby becoming more important in the process of infection. These proteins pertained to the Inv, Org, Prg, Sip, Spa, Ssa and Sse operons along with chaperone protein SicA. Amongst them, SicA was figured out to be the most indispensable protein from different network parametric analyses. Subsequently, the gene expression levels of all these theoretically identified important proteins were confirmed by microarray data analysis. Finally, we have proposed a hierarchy of the proteins involved in the total infection process. This theoretical approach is the first of its kind to figure out potential virulence determinants encoded by SPI for therapeutic targets for enteric infection. A set of responsible virulent proteins was identified and the expression level of their genes was validated by using independent, published microarray data. The result was a targeted set of proteins that could serve as sensitive predictors and form the foundation for a series of trials in the wet-lab setting. Understanding these regulatory and virulent proteins would

  3. Synthesize, optimize, analyze, repeat (SOAR): Application of neural network tools to ECG patient monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Watrous, R.; Towell, G.; Glassman, M.S. [Siemens Corporate Research, Princeton, NJ (United States)

    1995-12-31

    Results are reported from the application of tools for synthesizing, optimizing and analyzing neural networks to an ECG Patient Monitoring task. A neural network was synthesized from a rule-based classifier and optimized over a set of normal and abnormal heartbeats. The classification error rate on a separate and larger test set was reduced by a factor of 2. When the network was analyzed and reduced in size by a factor of 40%, the same level of performance was maintained.

  4. OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks

    CERN Document Server

    Boeing, Geoff

    2016-01-01

    Scholars have studied street networks in many ways. However, there are some limitations to the current urban planning/street network analysis literature. To address these challenges, this study presents a new tool to make the collection of data and creation and analysis of street networks simple, consistent, and automatable. OSMnx is a new Python package that downloads administrative boundary shapes and street networks from OpenStreetMap. OSMnx contributes five significant new capabilities for researchers and city planners: first, the automatic downloading of administrative place boundaries and shapefiles; second, the tailored and automated downloading and constructing of street networks from OpenStreetMap (including driving, walking, biking, etc.); third, the automated correction and simplification of network topology; fourth, the ability to save street networks to disk as shapefiles, GraphML, or SVG files; and fifth, the ability to analyze street networks, calculate routes, project and visualize the network...

  5. Curating the innate immunity interactome.

    LENUS (Irish Health Repository)

    Lynn, David J

    2010-01-01

    The innate immune response is the first line of defence against invading pathogens and is regulated by complex signalling and transcriptional networks. Systems biology approaches promise to shed new light on the regulation of innate immunity through the analysis and modelling of these networks. A key initial step in this process is the contextual cataloguing of the components of this system and the molecular interactions that comprise these networks. InnateDB (http:\\/\\/www.innatedb.com) is a molecular interaction and pathway database developed to facilitate systems-level analyses of innate immunity.

  6. Ocean plankton. Determinants of community structure in the global plankton interactome.

    Science.gov (United States)

    Lima-Mendez, Gipsi; Faust, Karoline; Henry, Nicolas; Decelle, Johan; Colin, Sébastien; Carcillo, Fabrizio; Chaffron, Samuel; Ignacio-Espinosa, J Cesar; Roux, Simon; Vincent, Flora; Bittner, Lucie; Darzi, Youssef; Wang, Jun; Audic, Stéphane; Berline, Léo; Bontempi, Gianluca; Cabello, Ana M; Coppola, Laurent; Cornejo-Castillo, Francisco M; d'Ovidio, Francesco; De Meester, Luc; Ferrera, Isabel; Garet-Delmas, Marie-José; Guidi, Lionel; Lara, Elena; Pesant, Stéphane; Royo-Llonch, Marta; Salazar, Guillem; Sánchez, Pablo; Sebastian, Marta; Souffreau, Caroline; Dimier, Céline; Picheral, Marc; Searson, Sarah; Kandels-Lewis, Stefanie; Gorsky, Gabriel; Not, Fabrice; Ogata, Hiroyuki; Speich, Sabrina; Stemmann, Lars; Weissenbach, Jean; Wincker, Patrick; Acinas, Silvia G; Sunagawa, Shinichi; Bork, Peer; Sullivan, Matthew B; Karsenti, Eric; Bowler, Chris; de Vargas, Colomban; Raes, Jeroen

    2015-05-22

    Species interaction networks are shaped by abiotic and biotic factors. Here, as part of the Tara Oceans project, we studied the photic zone interactome using environmental factors and organismal abundance profiles and found that environmental factors are incomplete predictors of community structure. We found associations across plankton functional types and phylogenetic groups to be nonrandomly distributed on the network and driven by both local and global patterns. We identified interactions among grazers, primary producers, viruses, and (mainly parasitic) symbionts and validated network-generated hypotheses using microscopy to confirm symbiotic relationships. We have thus provided a resource to support further research on ocean food webs and integrating biological components into ocean models.

  7. InteractoMIX: a suite of computational tools to exploit interactomes in biological and clinical research.

    Science.gov (United States)

    Poglayen, Daniel; Marín-López, Manuel Alejandro; Bonet, Jaume; Fornes, Oriol; Garcia-Garcia, Javier; Planas-Iglesias, Joan; Segura, Joan; Oliva, Baldo; Fernandez-Fuentes, Narcis

    2016-06-15

    Virtually all the biological processes that occur inside or outside cells are mediated by protein-protein interactions (PPIs). Hence, the charting and description of the PPI network, initially in organisms, the interactome, but more recently in specific tissues, is essential to fully understand cellular processes both in health and disease. The study of PPIs is also at the heart of renewed efforts in the medical and biotechnological arena in the quest of new therapeutic targets and drugs. Here, we present a mini review of 11 computational tools and resources tools developed by us to address different aspects of PPIs: from interactome level to their atomic 3D structural details. We provided details on each specific resource, aims and purpose and compare with equivalent tools in the literature. All the tools are presented in a centralized, one-stop, web site: InteractoMIX (http://interactomix.com).

  8. Next Generation Protein Interactomes for Plant Systems Biology and Biomass Feedstock Research

    Energy Technology Data Exchange (ETDEWEB)

    Ecker, Joseph Robert [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Trigg, Shelly [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Univ. of California, San Diego, CA (United States). Biological Sciences Dept.; Garza, Renee [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Song, Haili [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; MacWilliams, Andrew [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Nery, Joseph [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Reina, Joaquin [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Bartlett, Anna [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Castanon, Rosa [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Goubil, Adeline [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Feeney, Joseph [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; O' Malley, Ronan [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Huang, Shao-shan Carol [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Zhang, Zhuzhu [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.; Galli, Mary [The Salk Inst. for Biological Studies, La Jolla, CA (United States). Genome Analysis and Plant Biology Lab.

    2016-11-30

    Biofuel crop cultivation is a necessary step in heading towards a sustainable future, making their genomic studies a priority. While technology platforms that currently exist for studying non-model crop species, like switch-grass or sorghum, have yielded large quantities of genomic and expression data, still a large gap exists between molecular mechanism and phenotype. The aspect of molecular activity at the level of protein-protein interactions has recently begun to bridge this gap, providing a more global perspective. Interactome analysis has defined more specific functional roles of proteins based on their interaction partners, neighborhoods, and other network features, making it possible to distinguish unique modules of immune response to different plant pathogens(Jiang, Dong, and Zhang 2016). As we work towards cultivating heartier biofuel crops, interactome data will lead to uncovering crop-specific defense and development networks. However, the collection of protein interaction data has been limited to expensive, time-consuming, hard-to-scale assays that mostly require cloned ORF collections. For these reasons, we have successfully developed a highly scalable, economical, and sensitive yeast two-hybrid assay, ProCREate, that can be universally applied to generate proteome-wide primary interactome data. ProCREate enables en masse pooling and massively paralleled sequencing for the identification of interacting proteins by exploiting Cre-lox recombination. ProCREate can be used to screen ORF/cDNA libraries from feedstock plant tissues. The interactome data generated will yield deeper insight into many molecular processes and pathways that can be used to guide improvement of feedstock productivity and sustainability.

  9. System, apparatus and methods to implement high-speed network analyzers

    Science.gov (United States)

    Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

    2015-11-10

    Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

  10. The Breast Cancer DNA Interactome

    Science.gov (United States)

    2014-12-01

    DOCX) Author Contributions Conceived and designed the experiments: MJZ JDH PLL BNS. Performed the experiments: MJZ JDH PLL . Analyzed the data: MJZ...JDH PLL FA WSN ARH. Wrote the paper: MJZ JDH PLL FA. Designed and conducted bioinformatics and statistical analysis: FA WSN. References 1. Misteli T

  11. Control of Polishing Machine of Crystal Blank which Used Network Analyzer

    Science.gov (United States)

    Wakamoto, Satoru; Nakazawa, Mitsuo

    Quartz crystal devices have become an essential factor in electronic equipment such as mobile communication equipment or PC. As prices of electronic equipment have lowered, the cost-down of quartz crystal devices has been strongly demanded. To achieve the cost-down of quartz crystal device manufacturing, which uses a complex manufacturing process, the yield of the quartz crystal blank lapping process, which is the preliminary process of the quartz crystal device manufacturing process, must be increased. By introducing the network analyzer to the quartz crystal blank lapping process, we have obtained real time lapping characteristics. By obtaining the new process characteristics in real-time and visualizing them when changing lapping conditions, the network analyzer can now optimize the conditions of the process. In addition, the network analyzer can now measure the optical quartz crystal blank polishing process, which was difficult to measure by using a conventional controller.

  12. The L1TD1 Protein Interactome Reveals the Importance of Post-transcriptional Regulation in Human Pluripotency

    Directory of Open Access Journals (Sweden)

    Maheswara Reddy Emani

    2015-03-01

    Full Text Available The RNA-binding protein L1TD1 is one of the most specific and abundant proteins in pluripotent stem cells and is essential for the maintenance of pluripotency in human cells. Here, we identify the protein interaction network of L1TD1 in human embryonic stem cells (hESCs and provide insights into the interactome network constructed in human pluripotent cells. Our data reveal that L1TD1 has an important role in RNA splicing, translation, protein traffic, and degradation. L1TD1 interacts with multiple stem-cell-specific proteins, many of which are still uncharacterized in the context of development. Further, we show that L1TD1 is a part of the pluripotency interactome network of OCT4, SOX2, and NANOG, bridging nuclear and cytoplasmic regulation and highlighting the importance of RNA biology in pluripotency.

  13. The L1TD1 protein interactome reveals the importance of post-transcriptional regulation in human pluripotency.

    Science.gov (United States)

    Emani, Maheswara Reddy; Närvä, Elisa; Stubb, Aki; Chakroborty, Deepankar; Viitala, Miro; Rokka, Anne; Rahkonen, Nelly; Moulder, Robert; Denessiouk, Konstantin; Trokovic, Ras; Lund, Riikka; Elo, Laura L; Lahesmaa, Riitta

    2015-03-10

    The RNA-binding protein L1TD1 is one of the most specific and abundant proteins in pluripotent stem cells and is essential for the maintenance of pluripotency in human cells. Here, we identify the protein interaction network of L1TD1 in human embryonic stem cells (hESCs) and provide insights into the interactome network constructed in human pluripotent cells. Our data reveal that L1TD1 has an important role in RNA splicing, translation, protein traffic, and degradation. L1TD1 interacts with multiple stem-cell-specific proteins, many of which are still uncharacterized in the context of development. Further, we show that L1TD1 is a part of the pluripotency interactome network of OCT4, SOX2, and NANOG, bridging nuclear and cytoplasmic regulation and highlighting the importance of RNA biology in pluripotency.

  14. Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

    Directory of Open Access Journals (Sweden)

    Tuomas Rönnberg

    Full Text Available Hantaviruses (Bunyaviridae are negative-strand RNA viruses with a tripartite genome. The small (S segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs. The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

  15. Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome.

    Science.gov (United States)

    Rönnberg, Tuomas; Jääskeläinen, Kirsi; Blot, Guillaume; Parviainen, Ville; Vaheri, Antti; Renkonen, Risto; Bouloy, Michele; Plyusnin, Alexander

    2012-01-01

    Hantaviruses (Bunyaviridae) are negative-strand RNA viruses with a tripartite genome. The small (S) segment encodes the nucleocapsid protein and, in some hantaviruses, also the nonstructural protein (NSs). The aim of this study was to find potential cellular partners for the hantaviral NSs protein. Toward this aim, yeast two-hybrid (Y2H) screening of mouse cDNA library was performed followed by a search for potential NSs protein counterparts via analyzing a cellular interactome. The resulting interaction network was shown to form logical, clustered structures. Furthermore, several potential binding partners for the NSs protein, for instance ACBD3, were identified and, to prove the principle, interaction between NSs and ACBD3 proteins was demonstrated biochemically.

  16. Interactome-wide prediction of protein-protein binding sites reveals effects of protein sequence variation in Arabidopsis thaliana.

    Directory of Open Access Journals (Sweden)

    Felipe Leal Valentim

    Full Text Available The specificity of protein-protein interactions is encoded in those parts of the sequence that compose the binding interface. Therefore, understanding how changes in protein sequence influence interaction specificity, and possibly the phenotype, requires knowing the location of binding sites in those sequences. However, large-scale detection of protein interfaces remains a challenge. Here, we present a sequence- and interactome-based approach to mine interaction motifs from the recently published Arabidopsis thaliana interactome. The resultant proteome-wide predictions are available via www.ab.wur.nl/sliderbio and set the stage for further investigations of protein-protein binding sites. To assess our method, we first show that, by using a priori information calculated from protein sequences, such as evolutionary conservation and residue surface accessibility, we improve the performance of interface prediction compared to using only interactome data. Next, we present evidence for the functional importance of the predicted sites, which are under stronger selective pressure than the rest of protein sequence. We also observe a tendency for compensatory mutations in the binding sites of interacting proteins. Subsequently, we interrogated the interactome data to formulate testable hypotheses for the molecular mechanisms underlying effects of protein sequence mutations. Examples include proteins relevant for various developmental processes. Finally, we observed, by analysing pairs of paralogs, a correlation between functional divergence and sequence divergence in interaction sites. This analysis suggests that large-scale prediction of binding sites can cast light on evolutionary processes that shape protein-protein interaction networks.

  17. Comparing Models GRM, Refraction Tomography and Neural Network to Analyze Shallow Landslide

    Directory of Open Access Journals (Sweden)

    Armstrong F. Sompotan

    2011-11-01

    Full Text Available Detailed investigations of landslides are essential to understand fundamental landslide mechanisms. Seismic refraction method has been proven as a useful geophysical tool for investigating shallow landslides. The objective of this study is to introduce a new workflow using neural network in analyzing seismic refraction data and to compare the result with some methods; that are general reciprocal method (GRM and refraction tomography. The GRM is effective when the velocity structure is relatively simple and refractors are gently dipping. Refraction tomography is capable of modeling the complex velocity structures of landslides. Neural network is found to be more potential in application especially in time consuming and complicated numerical methods. Neural network seem to have the ability to establish a relationship between an input and output space for mapping seismic velocity. Therefore, we made a preliminary attempt to evaluate the applicability of neural network to determine velocity and elevation of subsurface synthetic models corresponding to arrival times. The training and testing process of the neural network is successfully accomplished using the synthetic data. Furthermore, we evaluated the neural network using observed data. The result of the evaluation indicates that the neural network can compute velocity and elevation corresponding to arrival times. The similarity of those models shows the success of neural network as a new alternative in seismic refraction data interpretation.

  18. The Symbiosis Interactome: a computational approach reveals novel components, functional interactions and modules in Sinorhizobium meliloti

    Directory of Open Access Journals (Sweden)

    Rodriguez-Llorente Ignacio

    2009-06-01

    Full Text Available Abstract Background Rhizobium-Legume symbiosis is an attractive biological process that has been studied for decades because of its importance in agriculture. However, this system has undergone extensive study and although many of the major factors underpinning the process have been discovered using traditional methods, much remains to be discovered. Results Here we present an analysis of the 'Symbiosis Interactome' using novel computational methods in order to address the complex dynamic interactions between proteins involved in the symbiosis of the model bacteria Sinorhizobium meliloti with its plant hosts. Our study constitutes the first large-scale analysis attempting to reconstruct this complex biological process, and to identify novel proteins involved in establishing symbiosis. We identified 263 novel proteins potentially associated with the Symbiosis Interactome. The topology of the Symbiosis Interactome was used to guide experimental techniques attempting to validate novel proteins involved in different stages of symbiosis. The contribution of a set of novel proteins was tested analyzing the symbiotic properties of several S. meliloti mutants. We found mutants with altered symbiotic phenotypes suggesting novel proteins that provide key complementary roles for symbiosis. Conclusion Our 'systems-based model' represents a novel framework for studying host-microbe interactions, provides a theoretical basis for further experimental validations, and can also be applied to the study of other complex processes such as diseases.

  19. Tiny Integrated Network Analyzer for Noninvasive Measurements of Electrically Small Antennas

    DEFF Research Database (Denmark)

    Buskgaard, Emil Feldborg; Krøyer, Ben; Tatomirescu, Alexandru

    2016-01-01

    Antenna mismatch and crosstalk are recurring issues in telecommunications. For electrically small antenna systems, these are very hard to measure without affecting the radiation performance of the system and, consequently, the measurement itself. Electrically small antennas are found in many...... applications ranging from consumer electronics to industrial systems. We propose a radically new approach to characterize crosstalk and mismatch based on vector network analysis. By miniaturizing the network analyzer, it can be integrated in the system under test, eliminating the need for cables leaving...... the system. The tiny integrated network analyzer is a stand-alone Arduino-based measurement system that utilizes the transmit signal of the system under test as its reference. It features a power meter with triggering ability, on-board memory, universal serial bus, and easy extendibility with general...

  20. Detection of driver protein complexes in breast cancer metastasis by large-scale transcriptome-interactome integration.

    Science.gov (United States)

    Garcia, Maxime; Finetti, Pascal; Bertucci, Francois; Birnbaum, Daniel; Bidaut, Ghislain

    2014-01-01

    With the development of high-throughput gene expression profiling technologies came the opportunity to define genomic signatures predicting clinical condition or cancer patient outcome. However, such signatures show dependency on training set, lack of generalization, and instability, partly due to microarray data topology. Additional issues for analyzing tumor gene expression are that subtle molecular perturbations in driver genes leading to cancer and metastasis (masked in typical differential expression analysis) may provoke expression changes of greater amplitude in downstream genes (easily detected). In this chapter, we are describing an interactome-based algorithm, Interactome-Transcriptome Integration (ITI) that is used to find a generalizable signature for prediction of breast cancer relapse by superimposition of a large-scale protein-protein interaction data (human interactome) over several gene expression datasets. ITI extracts regions in the interactome whose expression is discriminating for predicting relapse-free survival in cancer and allow detection of subnetworks that constitutes a generalizable and stable genomic signature. In this chapter, we describe the practical aspects of running the full ITI pipeline (subnetwork detection and classification) on six microarray datasets.

  1. Shared molecular and functional frameworks among five complex human disorders: a comparative study on interactomes linked to susceptibility genes.

    Directory of Open Access Journals (Sweden)

    Ramesh Menon

    Full Text Available BACKGROUND: Genome-wide association studies (gwas are invaluable in revealing the common variants predisposing to complex human diseases. Yet, until now, the large volumes of data generated from such analyses have not been explored extensively enough to identify the molecular and functional framework hosting the susceptibility genes. METHODOLOGY/PRINCIPAL FINDINGS: We investigated the relationships among five neurodegenerative and/or autoimmune complex human diseases (Parkinson's disease--Park, Alzheimer's disease--Alz, multiple sclerosis--MS, rheumatoid arthritis--RA and Type 1 diabetes--T1D by characterising the interactomes linked to their gwas-genes. An initial study on the MS interactome indicated that several genes predisposing to the other autoimmune or neurodegenerative disorders may come into contact with it, suggesting that susceptibility to distinct diseases may converge towards common molecular and biological networks. In order to test this hypothesis, we performed pathway enrichment analyses on each disease interactome independently. Several issues related to immune function and growth factor signalling pathways appeared in all autoimmune diseases, and, surprisingly, in Alzheimer's disease. Furthermore, the paired analyses of disease interactomes revealed significant molecular and functional relatedness among autoimmune diseases, and, unexpectedly, between T1D and Alz. CONCLUSIONS/SIGNIFICANCE: The systems biology approach highlighted several known pathogenic processes, indicating that changes in these functions might be driven or sustained by the framework linked to genetic susceptibility. Moreover, the comparative analyses among the five genetic interactomes revealed unexpected genetic relationships, which await further biological validation. Overall, this study outlines the potential of systems biology to uncover links between genetics and pathogenesis of complex human disorders.

  2. Identification and functional analysis of the BIM interactome; new clues on its possible involvement in Epstein-Barr Virus-associated diseases.

    Science.gov (United States)

    Rouka, Erasmia; Kyriakou, Despoina

    2015-12-01

    Epigenetic deregulation is a common feature in the pathogenesis of Epstein-Barr Virus (EBV)-related lymphomas and carcinomas. Previous studies have demonstrated a strong association between EBV latency in B-cells and epigenetic silencing of the tumor suppressor gene BIM. This study aimed to the construction and functional analysis of the BIM interactome in order to identify novel host genes that may be targeted by EBV. Fifty-nine unique interactors were found to compose the BIM gene network. Ontological analysis at the pathway level highlighted infectious diseases along with neuropathologies. These results underline the possible interplay between the BIM interactome and EBV-associated disorders.

  3. Analyzing energy consumption of wireless networks. A model-based approach

    Energy Technology Data Exchange (ETDEWEB)

    Yue, Haidi

    2013-03-04

    During the last decades, wireless networking has been continuously a hot topic both in academy and in industry. Many different wireless networks have been introduced like wireless local area networks, wireless personal networks, wireless ad hoc networks, and wireless sensor networks. If these networks want to have a long term usability, the power consumed by the wireless devices in each of these networks needs to be managed efficiently. Hence, a lot of effort has been carried out for the analysis and improvement of energy efficiency, either for a specific network layer (protocol), or new cross-layer designs. In this thesis, we apply model-based approach for the analysis of energy consumption of different wireless protocols. The protocols under consideration are: one leader election protocol, one routing protocol, and two medium access control protocols. By model-based approach we mean that all these four protocols are formalized as some formal models, more precisely, as discrete-time Markov chains (DTMCs), Markov decision processes (MDPs), or stochastic timed automata (STA). For the first two models, DTMCs and MDPs, we model them in PRISM, a prominent model checker for probabilistic model checking, and apply model checking technique to analyze them. Model checking belongs to the family of formal methods. It discovers exhaustively all possible (reachable) states of the models, and checks whether these models meet a given specification. Specifications are system properties that we want to study, usually expressed by some logics, for instance, probabilistic computer tree logic (PCTL). However, while model checking relies on rigorous mathematical foundations and automatically explores the entire state space of a model, its applicability is also limited by the so-called state space explosion problem -- even systems of moderate size often yield models with an exponentially larger state space that thwart their analysis. Hence for the STA models in this thesis, since there

  4. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder.

    Science.gov (United States)

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6-7% of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  5. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

    Science.gov (United States)

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  6. Identifying unexpected therapeutic targets via chemical-protein interactome.

    Directory of Open Access Journals (Sweden)

    Lun Yang

    Full Text Available Drug medications inevitably affect not only their intended protein targets but also other proteins as well. In this study we examined the hypothesis that drugs that share the same therapeutic effect also share a common therapeutic mechanism by targeting not only known drug targets, but also by interacting unexpectedly on the same cryptic targets. By constructing and mining an Alzheimer's disease (AD drug-oriented chemical-protein interactome (CPI using a matrix of 10 drug molecules known to treat AD towards 401 human protein pockets, we found that such cryptic targets exist. We recovered from CPI the only validated therapeutic target of AD, acetylcholinesterase (ACHE, and highlighted several other putative targets. For example, we discovered that estrogen receptor (ER and histone deacetylase (HDAC, which have recently been identified as two new therapeutic targets of AD, might already have been targeted by the marketed AD drugs. We further established that the CPI profile of a drug can reflect its interacting character towards multi-protein sets, and that drugs with the same therapeutic attribute will share a similar interacting profile. These findings indicate that the CPI could represent the landscape of chemical-protein interactions and uncover "behind-the-scenes" aspects of the therapeutic mechanisms of existing drugs, providing testable hypotheses of the key nodes for network pharmacology or brand new drug targets for one-target pharmacology paradigm.

  7. Transcriptional atlas of cardiogenesis maps congenital heart disease interactome.

    Science.gov (United States)

    Li, Xing; Martinez-Fernandez, Almudena; Hartjes, Katherine A; Kocher, Jean-Pierre A; Olson, Timothy M; Terzic, Andre; Nelson, Timothy J

    2014-07-01

    Mammalian heart development is built on highly conserved molecular mechanisms with polygenetic perturbations resulting in a spectrum of congenital heart diseases (CHD). However, knowledge of cardiogenic ontogeny that regulates proper cardiogenesis remains largely based on candidate-gene approaches. Mapping the dynamic transcriptional landscape of cardiogenesis from a genomic perspective is essential to integrate the knowledge of heart development into translational applications that accelerate disease discovery efforts toward mechanistic-based treatment strategies. Herein, we designed a time-course transcriptome analysis to investigate the genome-wide dynamic expression landscape of innate murine cardiogenesis ranging from embryonic stem cells to adult cardiac structures. This comprehensive analysis generated temporal and spatial expression profiles, revealed stage-specific gene functions, and mapped the dynamic transcriptome of cardiogenesis to curated pathways. Reconciling known genetic underpinnings of CHD, we deconstructed a disease-centric dynamic interactome encoded within this cardiogenic atlas to identify stage-specific developmental disturbances clustered on regulation of epithelial-to-mesenchymal transition (EMT), BMP signaling, NF-AT signaling, TGFb-dependent EMT, and Notch signaling. Collectively, this cardiogenic transcriptional landscape defines the time-dependent expression of cardiac ontogeny and prioritizes regulatory networks at the interface between health and disease. Copyright © 2014 the American Physiological Society.

  8. Predicting the Interactome of Xanthomonas oryzae pathovar oryzae for target selection and DB service

    Directory of Open Access Journals (Sweden)

    Yoon Kyong-Oh

    2008-01-01

    Full Text Available Abstract Background Protein-protein interactions (PPIs play key roles in various cellular functions. In addition, some critical inter-species interactions such as host-pathogen interactions and pathogenicity occur through PPIs. Phytopathogenic bacteria infect hosts through attachment to host tissue, enzyme secretion, exopolysaccharides production, toxins release, iron acquisition, and effector proteins secretion. Many such mechanisms involve some kind of protein-protein interaction in hosts. Our first aim was to predict the whole protein interaction pairs (interactome of Xanthomonas oryzae pathovar oryzae (Xoo that is an important pathogenic bacterium that causes bacterial blight (BB in rice. We developed a detection protocol to find possibly interacting proteins in its host using whole genome PPI prediction algorithms. The second aim was to build a DB server and a bioinformatic procedure for finding target proteins in Xoo for developing pesticides that block host-pathogen protein interactions within critical biochemical pathways. Description A PPI network in Xoo proteome was predicted by bioinformatics algorithms: PSIMAP, PEIMAP, and iPfam. We present the resultant species specific interaction network and host-pathogen interaction, XooNET. It is a comprehensive predicted initial PPI data for Xoo. XooNET can be used by experimentalists to pick up protein targets for blocking pathological interactions. XooNET uses most of the major types of PPI algorithms. They are: 1 Protein Structural Interactome MAP (PSIMAP, a method using structural domain of SCOP, 2 Protein Experimental Interactome MAP (PEIMAP, a common method using public resources of experimental protein interaction information such as HPRD, BIND, DIP, MINT, IntAct, and BioGrid, and 3 Domain-domain interactions, a method using Pfam domains such as iPfam. Additionally, XooNET provides information on network properties of the Xoo interactome. Conclusion XooNET is an open and free public

  9. Analyzing resilience of urban networks: a preliminary step towards more flood resilient cities

    Directory of Open Access Journals (Sweden)

    S. Lhomme

    2013-02-01

    Full Text Available In Europe, river floods have been increasing in frequency and severity. These circumstances require the management of flood risk by integrating new concepts like urban resilience. Nevertheless, urban resilience seems to have no accurate meanings. That is why researchers are primarily concerned with defining resilience. Nevertheless, focus on research object seems to be more important than focus on conceptual debate (Resilience of what? Rather than what is resilience?. Thus the methodology designed here is focused on urban considerations. In fact, a system approach emphasizes technical networks' importance concerning urban resilience. Principles and assumptions applied in this research finally lead to the analysis of how urban networks are able to face natural hazards. In this context, a Web-GIS has been developed for analyzing resistance capacity, absorption capacity and recovery capacity of different technical networks. A first application has been carried out on a French agglomeration in order to analyze road network absorption capacity. This application is very specific but, thanks to this example, it is already possible to highlight the methodology's usefulness.

  10. Development of a new software for analyzing 3-D fracture network

    Science.gov (United States)

    Um, Jeong-Gi; Noh, Young-Hwan; Choi, Yosoon

    2014-05-01

    A new software is presented to analyze fracture network in 3-D. Recently, we completed the software package based on information given in EGU2013. The software consists of several modules that play roles in management of borehole data, stochastic modelling of fracture network, construction of analysis domain, visualization of fracture geometry in 3-D, calculation of equivalent pipes and production of cross-section diagrams. Intel Parallel Studio XE 2013, Visual Studio.NET 2010 and the open source VTK library were utilized as development tools to efficiently implement the modules and the graphical user interface of the software. A case study was performed to analyze 3-D fracture network system at the Upper Devonian Grosmont Formation in Alberta, Canada. The results have suggested that the developed software is effective in modelling and visualizing 3-D fracture network system, and can provide useful information to tackle the geomechanical problems related to strength, deformability and hydraulic behaviours of the fractured rock masses. This presentation describes the concept and details of the development and implementation of the software.

  11. A recurrence network approach to analyzing forced synchronization in hydrodynamic systems

    Science.gov (United States)

    Murugesan, Meenatchidevi; Zhu, Yuanhang; Li, Larry K. B.

    2016-11-01

    Hydrodynamically self-excited systems can lock into external forcing, but their lock-in boundaries and the specific bifurcations through which they lock in can be difficult to detect. We propose using recurrence networks to analyze forced synchronization in a hydrodynamic system: a low-density jet. We find that as the jet bifurcates from periodicity (unforced) to quasiperiodicity (weak forcing) and then to lock-in (strong forcing), its recurrence network changes from a regular distribution of links between nodes (unforced) to a disordered topology (weak forcing) and then to a regular distribution again at lock-in (strong forcing). The emergence of order at lock-in can be either smooth or abrupt depending on the specific lock-in route taken. Furthermore, we find that before lock-in, the probability distribution of links in the network is a function of the characteristic scales of the system, which can be quantified with network measures and used to estimate the proximity to the lock-in boundaries. This study shows that recurrence networks can be used (i) to detect lock-in, (ii) to distinguish between different routes to lock-in, and (iii) as an early warning indicator of the proximity of a system to its lock-in boundaries. This work was supported by the Research Grants Council of Hong Kong (Project No. 16235716 and 26202815).

  12. How Unstable Are Complex Financial Systems? Analyzing an Inter-bank Network of Credit Relations

    Science.gov (United States)

    Sinha, Sitabhra; Thess, Maximilian; Markose, Sheri

    The recent worldwide economic crisis of 2007-09 has focused attention on the need to analyze systemic risk in complex financial networks. We investigate the problem of robustness of such systems in the context of the general theory of dynamical stability in complex networks and, in particular, how the topology of connections influence the risk of the failure of a single institution triggering a cascade of successive collapses propagating through the network. We use data on bilateral liabilities (or exposure) in the derivatives market between 202 financial intermediaries based in USA and Europe in the last quarter of 2009 to empirically investigate the network structure of the over-the-counter (OTC) derivatives market. We observe that the network exhibits both heterogeneity in node properties and the existence of communities. It also has a prominent core-periphery organization and can resist large-scale collapse when subjected to individual bank defaults (however, failure of any bank in the core may result in localized collapse of the innermost core with substantial loss of capital) but is vulnerable to system-wide breakdown as a result of an accompanying liquidity crisis.

  13. Grouping annotations on the subcellular layered interactome demonstrates enhanced autophagy activity in a recurrent experimental autoimmune uveitis T cell line.

    Directory of Open Access Journals (Sweden)

    Xiuzhi Jia

    Full Text Available Human uveitis is a type of T cell-mediated autoimmune disease that often shows relapse-remitting courses affecting multiple biological processes. As a cytoplasmic process, autophagy has been seen as an adaptive response to cell death and survival, yet the link between autophagy and T cell-mediated autoimmunity is not certain. In this study, based on the differentially expressed genes (GSE19652 between the recurrent versus monophasic T cell lines, whose adoptive transfer to susceptible animals may result in respective recurrent or monophasic uveitis, we proposed grouping annotations on a subcellular layered interactome framework to analyze the specific bioprocesses that are linked to the recurrence of T cell autoimmunity. That is, the subcellular layered interactome was established by the Cytoscape and Cerebral plugin based on differential expression, global interactome, and subcellular localization information. Then, the layered interactomes were grouping annotated by the ClueGO plugin based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. The analysis showed that significant bioprocesses with autophagy were orchestrated in the cytoplasmic layered interactome and that mTOR may have a regulatory role in it. Furthermore, by setting up recurrent and monophasic uveitis in Lewis rats, we confirmed by transmission electron microscopy that, in comparison to the monophasic disease, recurrent uveitis in vivo showed significantly increased autophagy activity and extended lymphocyte infiltration to the affected retina. In summary, our framework methodology is a useful tool to disclose specific bioprocesses and molecular targets that can be attributed to a certain disease. Our results indicated that targeted inhibition of autophagy pathways may perturb the recurrence of uveitis.

  14. Analyzing topological characteristics of neuronal functional networks in the rat brain

    Energy Technology Data Exchange (ETDEWEB)

    Lu, Hu [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); School of Computer Science, Fudan University, Shanghai 200433 (China); Yang, Shengtao [Institutes of Brain Science, Fudan University, Shanghai 200433 (China); Song, Yuqing [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); Wei, Hui [School of Computer Science, Fudan University, Shanghai 200433 (China)

    2014-08-28

    In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics.

  15. ImmunemiR - a database of prioritized immune miRNA disease associations and its interactome.

    Science.gov (United States)

    Prabahar, Archana; Natarajan, Jeyakumar

    2017-01-17

    MicroRNAs are the key regulators of gene expression and their abnormal expression in the immune system may be associated with several human diseases such as inflammation, cancer and autoimmune diseases. Elucidation of microRNA (miRNA) disease association through the interactome will deepen the understanding of its disease mechanisms. In this present study, miRNAs specific to immune related diseases were retrieved from curated databases and literature based on MeSH classification of immune system diseases. In total 245 immune miRNAs associated with 92 OMIM disease categories were identified and they are prioritized to specific immune diseases using random walk ranking algorithm. These data were compiled as ImmunemiR, a database of prioritized immune miRNA disease associations. This database provides both text based annotation information and network visualization of its interactome network. To our knowledge, ImmunemiR is the first available database to provide a comprehensive repository of human immune disease associated miRNAs with network visualization options of its target genes, protein-protein interactions (PPI).

  16. A social network approach to analyzing water governance: The case of the Mkindo catchment, Tanzania

    Science.gov (United States)

    Stein, C.; Ernstson, H.; Barron, J.

    The governance dimension of water resources management is just as complex and interconnected as the hydrological processes it aims to influence. There is an increasing need (i) to understand the multi-stakeholder governance arrangements that emerge from the cross-scale nature and multifunctional role of water; and (ii) to develop appropriate research tools to analyze them. In this study we demonstrate how social network analysis (SNA), a well-established technique from sociology and organizational research, can be used to empirically map collaborative social networks between actors that either directly or indirectly influence water flows in the Mkindo catchment in Tanzania. We assess how these collaborative social networks affect the capacity to govern water in this particular catchment and explore how knowledge about such networks can be used to facilitate more effective or adaptive water resources management. The study is novel as it applies social network analysis not only to organizations influencing blue water (the liquid water in rivers, lakes and aquifers) but also green water (the soil moisture used by plants). Using a questionnaire and semi-structured interviews, we generated social network data of 70 organizations, ranging from local resource users and village leaders, to higher-level governmental agencies, universities and NGOs. Results show that there is no organization that coordinates the various land and water related activities at the catchment scale. Furthermore, an important result is that village leader play a crucial role linking otherwise disconnected actors, but that they are not adequately integrated into the formal water governance system. Water user associations (WUAs) are in the process of establishment and could bring together actors currently not part of the formal governance system. However, the establishment of WUAs seems to follow a top-down approach not considering the existing informal organization of water users that are revealed

  17. Analyzing miRNA co-expression networks to explore TF-miRNA regulation

    Directory of Open Access Journals (Sweden)

    Bhattacharyya Malay

    2009-05-01

    Full Text Available Abstract Background Current microRNA (miRNA research in progress has engendered rapid accumulation of expression data evolving from microarray experiments. Such experiments are generally performed over different tissues belonging to a specific species of metazoan. For disease diagnosis, microarray probes are also prepared with tissues taken from similar organs of different candidates of an organism. Expression data of miRNAs are frequently mapped to co-expression networks to study the functions of miRNAs, their regulation on genes and to explore the complex regulatory network that might exist between Transcription Factors (TFs, genes and miRNAs. These directions of research relating miRNAs are still not fully explored, and therefore, construction of reliable and compatible methods for mining miRNA co-expression networks has become an emerging area. This paper introduces a novel method for mining the miRNA co-expression networks in order to obtain co-expressed miRNAs under the hypothesis that these might be regulated by common TFs. Results Three co-expression networks, configured from one patient-specific, one tissue-specific and a stem cell-based miRNA expression data, are studied for analyzing the proposed methodology. A novel compactness measure is introduced. The results establish the statistical significance of the sets of miRNAs evolved and the efficacy of the self-pruning phase employed by the proposed method. All these datasets yield similar network patterns and produce coherent groups of miRNAs. The existence of common TFs, regulating these groups of miRNAs, is empirically tested. The results found are very promising. A novel visual validation method is also proposed that reflects the homogeneity as well as statistical properties of the grouped miRNAs. This visual validation method provides a promising and statistically significant graphical tool for expression analysis. Conclusion A heuristic mining methodology that resembles a

  18. A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China

    Science.gov (United States)

    Zhao, Shuangming; Zhao, Pengxiang; Cui, Yunfan

    2017-07-01

    In this paper, we propose an improved network centrality measure framework that takes into account both the topological characteristics and the geometric properties of a road network in order to analyze urban traffic flow in relation to different modes: intersection, road, and community, which correspond to point mode, line mode, and area mode respectively. Degree, betweenness, and PageRank centralities are selected as the analysis measures, and GPS-enabled taxi trajectory data is used to evaluate urban traffic flow. The results show that the mean value of the correlation coefficients between the modified degree, the betweenness, and the PageRank centralities and the traffic flow in all periods are higher than the mean value of the correlation coefficients between the conventional degree, the betweenness, the PageRank centralities and the traffic flow at different modes; this indicates that the modified measurements, for analyzing traffic flow, are superior to conventional centrality measurements. This study helps to shed light into the understanding of urban traffic flow in relation to different modes from the perspective of complex networks.

  19. Identifying and Analyzing Strong Components of an Industrial Network Based on Cycle Degree

    Directory of Open Access Journals (Sweden)

    Zhiying Zhang

    2016-01-01

    Full Text Available In the era of big data and cloud computing, data research focuses not only on describing the individual characteristics but also on depicting the relationships among individuals. Studying dependence and constraint relationships among industries has aroused significant interest in the academic field. From the network perspective, this paper tries to analyze industrial relational structures based on cycle degree. The cycle degree of a vertex, that is, the number of cycles through a vertex in an industrial network, can describe the roles of the vertices of strong components in industrial circulation. In most cases, different vertices in a strong component have different cycle degrees, and the one with a larger cycle degree plays more important roles. However, the concept of cycle degree does not involve the lengths of the cycles, which are also important for circulations. The more indirect the relationship between two industries is, the weaker it is. In order to analyze strong components thoroughly, this paper proposes the concept of circular centrality taking into consideration the influence by two factors: the lengths and the numbers of cycles through a vertex. Exemplification indicates that a profound analysis of strong components in an industrial network can reveal the features of an economy.

  20. Granger causality-based synaptic weights estimation for analyzing neuronal networks.

    Science.gov (United States)

    Shao, Pei-Chiang; Huang, Jian-Jia; Shann, Wei-Chang; Yen, Chen-Tung; Tsai, Meng-Li; Yen, Chien-Chang

    2015-06-01

    Granger causality (GC) analysis has emerged as a powerful analytical method for estimating the causal relationship among various types of neural activity data. However, two problems remain not very clear and further researches are needed: (1) The GC measure is designed to be nonnegative in its original form, lacking of the trait for differentiating the effects of excitations and inhibitions between neurons. (2) How is the estimated causality related to the underlying synaptic weights? Based on the GC, we propose a computational algorithm under a best linear predictor assumption for analyzing neuronal networks by estimating the synaptic weights among them. Under this assumption, the GC analysis can be extended to measure both excitatory and inhibitory effects between neurons. The method was examined by three sorts of simulated networks: those with linear, almost linear, and nonlinear network structures. The method was also illustrated to analyze real spike train data from the anterior cingulate cortex (ACC) and the striatum (STR). The results showed, under the quinpirole administration, the significant existence of excitatory effects inside the ACC, excitatory effects from the ACC to the STR, and inhibitory effects inside the STR.

  1. Analyzing Delay in Wireless Multi-hop Heterogeneous Body Area Networks

    Directory of Open Access Journals (Sweden)

    N. Javaid

    2014-01-01

    Full Text Available With increase in ageing population, health care market keeps growing. There is a need for monitoring of health issues. Wireless Body Area Network (WBAN consists of wireless sensors attached on or inside human body for monitoring vital health related problems e.g., Electro Cardiogram (ECG, Electro Encephalogram (EEG, Electrony Stagmography (ENG etc. Due to life threatening situations, timely sending of data is essential. For data to reach health care center, there must be a proper way of sending data through reliable connection and with minimum delay. In this study transmission delay of different paths, through which data is sent from sensor to health care center over heterogeneous multi-hop wireless channel is analyzed. Data of medical related diseases is sent through three different paths. In all three paths, data from sensors first reaches ZigBee, which is the common link in all three paths. Wireless Local Area Network (WLAN, Worldwide Interoperability for Microwave Access (WiMAX, Universal Mobile Telecommunication System (UMTS are connected with ZigBee. Each network (WLAN, WiMAX, UMTS is setup according to environmental conditions, suitability of device and availability of structure for that device. Data from these networks is sent to IP-Cloud, which is further connected to health care center. Delay of data reaching each device is calculated and represented graphically. Main aim of this study is to calculate delay of each link in each path over multi-hop wireless channel.

  2. Analyzing long-term correlated stochastic processes by means of recurrence networks: Potentials and pitfalls

    CERN Document Server

    Zou, Yong; Kurths, Jürgen

    2014-01-01

    Long-range correlated processes are ubiquitous, ranging from climate variables to financial time series. One paradigmatic example for such processes is fractional Brownian motion (fBm). In this work, we highlight the potentials and conceptual as well as practical limitations when applying the recently proposed recurrence network (RN) approach to fBm and related stochastic processes. In particular, we demonstrate that the results of a previous application of RN analysis to fBm (Liu \\textit{et al.,} Phys. Rev. E \\textbf{89}, 032814 (2014)) are mainly due to an inappropriate treatment disregarding the intrinsic non-stationarity of such processes. Complementarily, we analyze some RN properties of the closely related stationary fractional Gaussian noise (fGn) processes and find that the resulting network properties are well-defined and behave as one would expect from basic conceptual considerations. Our results demonstrate that RN analysis can indeed provide meaningful results for stationary stochastic processes, ...

  3. Distributed Density Estimation Based on a Mixture of Factor Analyzers in a Sensor Network

    Directory of Open Access Journals (Sweden)

    Xin Wei

    2015-08-01

    Full Text Available Distributed density estimation in sensor networks has received much attention due to its broad applicability. When encountering high-dimensional observations, a mixture of factor analyzers (MFA is taken to replace mixture of Gaussians for describing the distributions of observations. In this paper, we study distributed density estimation based on a mixture of factor analyzers. Existing estimation algorithms of the MFA are for the centralized case, which are not suitable for distributed processing in sensor networks. We present distributed density estimation algorithms for the MFA and its extension, the mixture of Student’s t-factor analyzers (MtFA. We first define an objective function as the linear combination of local log-likelihoods. Then, we give the derivation process of the distributed estimation algorithms for the MFA and MtFA in details, respectively. In these algorithms, the local sufficient statistics (LSS are calculated at first and diffused. Then, each node performs a linear combination of the received LSS from nodes in its neighborhood to obtain the combined sufficient statistics (CSS. Parameters of the MFA and the MtFA can be obtained by using the CSS. Finally, we evaluate the performance of these algorithms by numerical simulations and application example. Experimental results validate the promising performance of the proposed algorithms.

  4. Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

    Science.gov (United States)

    Vashisht, Rohit; Mondal, Anupam Kumar; Jain, Akanksha; Shah, Anup; Vishnoi, Priti; Priyadarshini, Priyanka; Bhattacharyya, Kausik; Rohira, Harsha; Bhat, Ashwini G; Passi, Anurag; Mukherjee, Keya; Choudhary, Kumari Sonal; Kumar, Vikas; Arora, Anshula; Munusamy, Prabhakaran; Subramanian, Ahalyaa; Venkatachalam, Aparna; Gayathri, S; Raj, Sweety; Chitra, Vijaya; Verma, Kaveri; Zaheer, Salman; Balaganesh, J; Gurusamy, Malarvizhi; Razeeth, Mohammed; Raja, Ilamathi; Thandapani, Madhumohan; Mevada, Vishal; Soni, Raviraj; Rana, Shruti; Ramanna, Girish Muthagadhalli; Raghavan, Swetha; Subramanya, Sunil N; Kholia, Trupti; Patel, Rajesh; Bhavnani, Varsha; Chiranjeevi, Lakavath; Sengupta, Soumi; Singh, Pankaj Kumar; Atray, Naresh; Gandhi, Swati; Avasthi, Tiruvayipati Suma; Nisthar, Shefin; Anurag, Meenakshi; Sharma, Pratibha; Hasija, Yasha; Dash, Debasis; Sharma, Arun; Scaria, Vinod; Thomas, Zakir; Chandra, Nagasuma; Brahmachari, Samir K; Bhardwaj, Anshu

    2012-01-01

    A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

  5. Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis.

    Directory of Open Access Journals (Sweden)

    Rohit Vashisht

    Full Text Available A decade since the availability of Mycobacterium tuberculosis (Mtb genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW, encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

  6. An Intrusive Analyzer for Hadoop Systems Based on Wireless Sensor Networks

    OpenAIRE

    Byoung-Jin Bae; Young-Joo Kim; Young-Kuk Kim; Ok-Kyoon Ha; Yong-Kee Jun

    2014-01-01

    Owing to the acceleration of IoT- (Internet of Things-) based wireless sensor networks, cloud-computing services using Big Data are rapidly growing. In order to manage and analyze Big Data efficiently, Hadoop frameworks have been used in a variety of fields. Hadoop processes Big Data as record values by using MapReduce programming in a distributed environment. Through MapReduce, data are stored in a Hadoop file system, and that form is not structured but unstructured. For this, it is not easy...

  7. Tiny Integrated Network Analyzer for Noninvasive Measurements of Electrically Small Antennas

    DEFF Research Database (Denmark)

    Buskgaard, Emil Feldborg; Krøyer, Ben; Tatomirescu, Alexandru;

    2016-01-01

    Antenna mismatch and crosstalk are recurring issues in telecommunications. For electrically small antenna systems, these are very hard to measure without affecting the radiation performance of the system and, consequently, the measurement itself. Electrically small antennas are found in many...... the system. The tiny integrated network analyzer is a stand-alone Arduino-based measurement system that utilizes the transmit signal of the system under test as its reference. It features a power meter with triggering ability, on-board memory, universal serial bus, and easy extendibility with general...

  8. Quantum Interactomics and Cancer Molecular Mechanisms: I. Report Outline

    CERN Document Server

    Baianu, I C

    2004-01-01

    Single cell interactomics in simpler organisms, as well as somatic cell interactomics in multicellular organisms, involve biomolecular interactions in complex signalling pathways that were recently represented in modular terms by quantum automata with ‘reversible behavior’ representing normal cell cycling and division. Other implications of such quantum automata, modular modeling of signaling pathways and cell differentiation during development are in the fields of neural plasticity and brain development leading to quantum-weave dynamic patterns and specific molecular processes underlying extensive memory, learning, anticipation mechanisms and the emergence of human consciousness during the early brain development in children. Cell interactomics is here represented for the first time as a mixture of ‘classical’ states that determine molecular dynamics subject to Boltzmann statistics and ‘steady-state’, metabolic (multi-stable) manifolds, together with ‘configuration’ spaces of metastable quant...

  9. Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Main, P. [Dpto. Estadistica e I.O., Fac. Ciencias Matematicas, Univ. Complutense de Madrid, 28040 Madrid (Spain)], E-mail: pmain@mat.ucm.es; Navarro, H. [Dpto. de Estadistica, I.O. y Calc. Numerico, Fac. Ciencias, UNED, 28040 Madrid (Spain)

    2009-05-15

    Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect.

  10. Forward Individualized Medicine from Personal Genomes to Interactomes.

    Science.gov (United States)

    Zhang, Xiang; Kuivenhoven, Jan A; Groen, Albert K

    2015-01-01

    When considering the variation in the genome, transcriptome, proteome and metabolome, and their interaction with the environment, every individual can be rightfully considered as a unique biological entity. Individualized medicine promises to take this uniqueness into account to optimize disease treatment and thereby improve health benefits for every patient. The success of individualized medicine relies on a precise understanding of the genotype-phenotype relationship. Although omics technologies advance rapidly, there are several challenges that need to be overcome: Next generation sequencing can efficiently decipher genomic sequences, epigenetic changes, and transcriptomic variation in patients, but it does not automatically indicate how or whether the identified variation will cause pathological changes. This is likely due to the inability to account for (1) the consequences of gene-gene and gene-environment interactions, and (2) (post)transcriptional as well as (post)translational processes that eventually determine the concentration of key metabolites. The technologies to accurately measure changes in these latter layers are still under development, and such measurements in humans are also mainly restricted to blood and circulating cells. Despite these challenges, it is already possible to track dynamic changes in the human interactome in healthy and diseased states by using the integration of multi-omics data. In this review, we evaluate the potential value of current major bioinformatics and systems biology-based approaches, including genome wide association studies, epigenetics, gene regulatory and protein-protein interaction networks, and genome-scale metabolic modeling. Moreover, we address the question whether integrative analysis of personal multi-omics data will help understanding of personal genotype-phenotype relationships.

  11. Quasi-Optical Network Analyzers and High-Reliability RF MEMS Switched Capacitors

    Science.gov (United States)

    Grichener, Alexander

    The thesis first presents a 2-port quasi-optical scalar network analyzer consisting of a transmitter and receiver both built in planar technology. The network analyzer is based on a Schottky-diode mixer integrated inside a planar antenna and fed differentially by a CPW transmission line. The antenna is placed on an extended hemispherical high-resistivity silicon substrate lens. The LO signal is swept from 3-5 GHz and high-order harmonic mixing in both up- and down- conversion mode is used to realize the 15-50 GHz RF bandwidth. The network analyzer resulted in a dynamic range of greater than 40 dB and was successfully used to measure a frequency selective surface with a second-order bandpass response. Furthermore, the system was built with circuits and components for easy scaling to millimeter-wave frequencies which is the primary motivation for this work. The application areas for a millimeter and submillimeter-wave network analyzer include material characterization and art diagnostics. The second project presents several RF MEMS switched capacitors designed for high-reliability operation and suitable for tunable filters and reconfigurable networks. The first switched-capacitor resulted in a digital capacitance ratio of 5 and an analog capacitance ratio of 5-9. The analog tuning of the down-state capacitance is enhanced by a positive vertical stress gradient in the the beam, making it ideal for applications that require precision tuning. A thick electroplated beam resulted in Q greater than 100 at C to X-band frequencies, and power handling of 0.6-1.1 W. The design also minimized charging in the dielectric, resulting in excellent reliability performance even under hot-switched and high power (1 W) conditions. The second switched-capacitor was designed without any dielectric to minimize charging. The device was hot-switched at 1 W of RF power for greater than 11 billion cycles with virtually no change in the C-V curve. The final project presents a 7-channel

  12. Towards a Framework to Analyze Causal Relations From Digital Information Networks To Micro Economic Productivity

    NARCIS (Netherlands)

    Madureira, A.; Baken, N.; Bouwman, H.

    2009-01-01

    Digital Information Networks (DINs) refer to information networks supported by telecommunication infrastructures and terminated by microprocessors. In the recent past, there is a consolidated recognition that the public digital network infrastructure is of high economic importance, being generally r

  13. Analyzing Comprehensive QoS with Security Constraints for Services Composition Applications in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Naixue Xiong

    2014-12-01

    Full Text Available Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs. The quality of service (QoS of services composition applications (SCAs are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique—vector universal generating function (VUGF—which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

  14. Analyzing comprehensive QoS with security constraints for services composition applications in wireless sensor networks.

    Science.gov (United States)

    Xiong, Naixue; Wu, Zhao; Huang, Yannong; Xu, Degang

    2014-12-01

    Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique-vector universal generating function (VUGF)-which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

  15. A core of kinase-regulated interactomes defines the neoplastic MDSC lineage

    Science.gov (United States)

    Zudaire, Isabel; Liechtenstein, Therese; Arasanz, Hugo; Lozano, Teresa; Casares, Noelia; Chaikuad, Apirat; Knapp, Stefan; Guerrero-Setas, David; Escors, David; Kochan, Grazyna; Santamaría, Enrique

    2015-01-01

    Myeloid-derived suppressor cells (MDSCs) differentiate from bone marrow precursors, expand in cancer-bearing hosts and accelerate tumor progression. MDSCs have become attractive therapeutic targets, as their elimination strongly enhances anti-neoplastic treatments. Here, immature myeloid dendritic cells (DCs), MDSCs modeling tumor-infiltrating subsets or modeling non-cancerous (NC)-MDSCs were compared by in-depth quantitative proteomics. We found that neoplastic MDSCs differentially expressed a core of kinases which controlled lineage-specific (PI3K-AKT and SRC kinases) and cancer-induced (ERK and PKC kinases) protein interaction networks (interactomes). These kinases contributed to some extent to myeloid differentiation. However, only AKT and ERK specifically drove MDSC differentiation from myeloid precursors. Interfering with AKT and ERK with selective small molecule inhibitors or shRNAs selectively hampered MDSC differentiation and viability. Thus, we provide compelling evidence that MDSCs constitute a distinct myeloid lineage distinguished by a “kinase signature” and well-defined interactomes. Our results define new opportunities for the development of anti-cancer treatments targeting these tumor-promoting immune cells. PMID:26320174

  16. The timeline of corona formation around silica nanocarriers highlights the role of the protein interactome.

    Science.gov (United States)

    Pisani, Cédric; Gaillard, Jean-Charles; Odorico, Michaël; Nyalosaso, Jeff L; Charnay, Clarence; Guari, Yannick; Chopineau, Joël; Devoisselle, Jean-Marie; Armengaud, Jean; Prat, Odette

    2017-02-02

    Magnetic mesoporous silica nanoparticles (M-MSNs) represent promising targeting tools for theranostics. Engineering the interaction of nanoparticles (NPs) with biological systems requires an understanding of protein corona formation around the nanoparticles as this drives the biological fate of nanocarriers. We investigated the behavior of proteins in contact with M-MSNs by high-throughput comparative proteomics, using human and bovine sera as biological fluids, in order to assess the adsorption dynamics of proteins in these media. Using system biology tools, and especially protein-protein interaction databases, we demonstrated how the protein network builds up within the corona over the course of the experiment. Based on these results, we introduce and discuss the role of the "corona interactome" as an important factor influencing protein corona evolution. The concept of the "corona interactome" is an original methodology which could be generalized to all NP candidates. Based on this, pre-coating nanocarriers with specific proteins presenting minimal interactions with opsonins might provide them with properties such as stealth.

  17. Biana: a software framework for compiling biological interactions and analyzing networks

    Directory of Open Access Journals (Sweden)

    Planas-Iglesias Joan

    2010-01-01

    Full Text Available Abstract Background The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. Results We introduce BIANA (Biologic Interactions and Network Analysis, a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i the integration of multiple sources of biological information, including biological entities and their relationships, and ii the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. Conclusions BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

  18. Analyzing the Effects of Gap Junction Blockade on Neural Synchrony via a Motoneuron Network Computational Model

    Directory of Open Access Journals (Sweden)

    Heraldo Memelli

    2012-01-01

    Full Text Available In specific regions of the central nervous system (CNS, gap junctions have been shown to participate in neuronal synchrony. Amongst the CNS regions identified, some populations of brainstem motoneurons are known to be coupled by gap junctions. The application of various gap junction blockers to these motoneuron populations, however, has led to mixed results regarding their synchronous firing behavior, with some studies reporting a decrease in synchrony while others surprisingly find an increase in synchrony. To address this discrepancy, we employ a neuronal network model of Hodgkin-Huxley-style motoneurons connected by gap junctions. Using this model, we implement a series of simulations and rigorously analyze their outcome, including the calculation of a measure of neuronal synchrony. Our simulations demonstrate that under specific conditions, uncoupling of gap junctions is capable of producing either a decrease or an increase in neuronal synchrony. Subsequently, these simulations provide mechanistic insight into these different outcomes.

  19. Analyzing Distributed Generation Impact on the Reliability of Electric Distribution Network

    Directory of Open Access Journals (Sweden)

    Sanaullah Ahmad

    2016-10-01

    Full Text Available With proliferation of Distribution Generation (DG and renewable energy technologies the power system is becoming more complex, with passage of time the development of distributed generation technologies is becoming diverse and broad. Power system reliability is one of most vital area in electric power system which deals with continuous supply of power and customer satisfaction. Distribution network in power system contributed up to 80% of reliability problems. This paper analyzes the impact of Wind Turbine Generator (WTG as a distribution generation source on reliability of distribution system. Injecting single WTG and close to load point has positive impact on reliability, while injecting multiple WTGs at single place has adverse impact on distribution system reliability. These analyses are performed on bus 2 of Roy Billinton Test System (RBTS.

  20. An Artificial Neural Network for Analyzing Overall Uniformity in Outdoor Lighting Systems

    Directory of Open Access Journals (Sweden)

    Antonio del Corte-Valiente

    2017-02-01

    Full Text Available Street lighting installations are an essential service for modern life due to their capability of creating a welcoming feeling at nighttime. Nevertheless, several studies have highlighted that it is possible to improve the quality of the light significantly improving the uniformity of the illuminance. The main difficulty arises when trying to improve some of the installation’s characteristics based only on statistical analysis of the light distribution. This paper presents a new algorithm that is able to obtain the overall illuminance uniformity in order to improve this sort of installations. To develop this algorithm it was necessary to perform a detailed study of all the elements which are part of street lighting installations. Because classification is one of the most important tasks in the application areas of artificial neural networks, we compared the performances of six types of training algorithms in a feed forward neural network for analyzing the overall uniformity in outdoor lighting systems. We found that the best algorithm that minimizes the error is “Levenberg-Marquardt back-propagation”, which approximates the desired output of the training pattern. By means of this kind of algorithm, it is possible to help to lighting professionals optimize the quality of street lighting installations.

  1. Path-integral methods for analyzing the effects of fluctuations in stochastic hybrid neural networks.

    Science.gov (United States)

    Bressloff, Paul C

    2015-01-01

    We consider applications of path-integral methods to the analysis of a stochastic hybrid model representing a network of synaptically coupled spiking neuronal populations. The state of each local population is described in terms of two stochastic variables, a continuous synaptic variable and a discrete activity variable. The synaptic variables evolve according to piecewise-deterministic dynamics describing, at the population level, synapses driven by spiking activity. The dynamical equations for the synaptic currents are only valid between jumps in spiking activity, and the latter are described by a jump Markov process whose transition rates depend on the synaptic variables. We assume a separation of time scales between fast spiking dynamics with time constant [Formula: see text] and slower synaptic dynamics with time constant τ. This naturally introduces a small positive parameter [Formula: see text], which can be used to develop various asymptotic expansions of the corresponding path-integral representation of the stochastic dynamics. First, we derive a variational principle for maximum-likelihood paths of escape from a metastable state (large deviations in the small noise limit [Formula: see text]). We then show how the path integral provides an efficient method for obtaining a diffusion approximation of the hybrid system for small ϵ. The resulting Langevin equation can be used to analyze the effects of fluctuations within the basin of attraction of a metastable state, that is, ignoring the effects of large deviations. We illustrate this by using the Langevin approximation to analyze the effects of intrinsic noise on pattern formation in a spatially structured hybrid network. In particular, we show how noise enlarges the parameter regime over which patterns occur, in an analogous fashion to PDEs. Finally, we carry out a [Formula: see text]-loop expansion of the path integral, and use this to derive corrections to voltage-based mean-field equations, analogous

  2. Dynamic modularity in protein interaction networks predicts breast cancer outcome

    DEFF Research Database (Denmark)

    Taylor, Ian W; Linding, Rune; Warde-Farley, David

    2009-01-01

    Changes in the biochemical wiring of oncogenic cells drives phenotypic transformations that directly affect disease outcome. Here we examine the dynamic structure of the human protein interaction network (interactome) to determine whether changes in the organization of the interactome can be used...

  3. A critical and Integrated View of the Yeast Interactome

    Directory of Open Access Journals (Sweden)

    Stephen G. Oliver

    2006-04-01

    Full Text Available Global studies of protein–protein interactions are crucial to both elucidating gene function and producing an integrated view of the workings of living cells. High-throughput studies of the yeast interactome have been performed using both genetic and biochemical screens. Despite their size, the overlap between these experimental datasets is very limited. This could be due to each approach sampling only a small fraction of the total interactome. Alternatively, a large proportion of the data from these screens may represent false-positive interactions. We have used the Genome Information Management System (GIMS to integrate interactome datasets with transcriptome and protein annotation data and have found significant evidence that the proportion of false-positive results is high. Not all high-throughput datasets are similarly contaminated, and the tandem affinity purification (TAP approach appears to yield a high proportion of reliable interactions for which corroborating evidence is available. From our integrative analyses, we have generated a set of verified interactome data for yeast.

  4. Intelligent constellation diagram analyzer using convolutional neural network-based deep learning.

    Science.gov (United States)

    Wang, Danshi; Zhang, Min; Li, Jin; Li, Ze; Li, Jianqiang; Song, Chuang; Chen, Xue

    2017-07-24

    An intelligent constellation diagram analyzer is proposed to implement both modulation format recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using convolution neural network (CNN)-based deep learning technique. With the ability of feature extraction and self-learning, CNN can process constellation diagram in its raw data form (i.e., pixel points of an image) from the perspective of image processing, without manual intervention nor data statistics. The constellation diagram images of six widely-used modulation formats over a wide OSNR range (15~30 dB and 20~35 dB) are obtained from a constellation diagram generation module in oscilloscope. Both simulation and experiment are conducted. Compared with other 4 traditional machine learning algorithms, CNN achieves the better accuracies and is obviously superior to other methods at the cost of O(n) computation complexity and less than 0.5 s testing time. For OSNR estimation, the high accuracies are obtained at epochs of 200 (95% for 64QAM, and over 99% for other five formats); for MFR, 100% accuracies are achieved even with less training data at lower epochs. The experimental results show that the OSNR estimation errors for all the signals are less than 0.7 dB. Additionally, the effects of multiple factors on CNN performance are comprehensively investigated, including the training data size, image resolution, and network structure. The proposed technique has the potential to be embedded in the test instrument to perform intelligent signal analysis or applied for optical performance monitoring.

  5. Functional interactome of Aquaporin 1 sub-family reveals new physiological functions in Arabidopsis Thaliana

    Directory of Open Access Journals (Sweden)

    Mohamed Ragab Abdel Gawwad

    2013-09-01

    Full Text Available Aquaporins are channel proteins found in plasma membranes and intercellular membranes of different cellular compartments, facilitate the water flux, solutes and gases across the cellular plasma membranes. The present study highlights the sub-family plasma membrane intrinsic protein (PIP predicting the 3-D structure and analyzing the functional interactome of it homologs. PIP1 homologs integrate with many proteins with different plant physiological roles in Arabidopsis thaliana including; PIP1A and PIP1B: facilitate the transport of water, diffusion of amino acids and/or peptides from the vacuolar compartment to the cytoplasm, play a role in the control of cell turgor and cell expansion and involved in root water uptake respectively. In addition we found that PIP1B plays a defensive role against Pseudomonas syringae infection through the interaction with the plasma membrane Rps2 protein. Another substantial function of PIP1C via the interaction with PIP2E is the response to nematode infection. Generally, PIP1 sub-family interactome controlling many physiological processes in plant cell like; osmoregulation in plants under high osmotic stress such as under a high salt, response to nematode, facilitate the transport of water across cell membrane and regulation of floral initiation in Arabidopsis thaliana.

  6. Cisco Router and Switch Forensics Investigating and Analyzing Malicious Network Activity

    CERN Document Server

    Liu, Dale

    2009-01-01

    Cisco IOS (the software that runs the vast majority of Cisco routers and all Cisco network switches) is the dominant routing platform on the Internet and corporate networks. This widespread distribution, as well as its architectural deficiencies, makes it a valuable target for hackers looking to attack a corporate or private network infrastructure. Compromised devices can disrupt stability, introduce malicious modification, and endanger all communication on the network. For security of the network and investigation of attacks, in-depth analysis and diagnostics are critical, but no book current

  7. Using Bayesian networks to analyze occupational stress caused by work demands: preventing stress through social support.

    Science.gov (United States)

    García-Herrero, Susana; Mariscal, M A; Gutiérrez, J M; Ritzel, Dale O

    2013-08-01

    Occupational stress is a major health hazard and a serious challenge to the effective operation of any company and represents a major problem for both individuals and organizations. Previous researches have shown that high demands (e.g. workload, emotional) combined with low resources (e.g. support, control, rewards) are associated with adverse health (e.g. psychological, physical) and organizational impacts (e.g. reduced job satisfaction, sickness absence). The objective of the present work is to create a model to analyze how social support reduces the occupational stress caused by work demands. This study used existing Spanish national data on working conditions collected by the Spanish Ministry of Labour and Immigration in 2007, where 11,054 workers were interviewed by questionnaire. A probabilistic model was built using Bayesian networks to explain the relationships between work demands and occupational stress. The model also explains how social support contributes positively to reducing stress levels. The variables studied were intellectually demanding work, overwork, workday, stress, and social support. The results show the importance of social support and of receiving help from supervisors and co-workers in preventing occupational stress. The study provides a new methodology that explains and quantifies the effects of intellectually demanding work, overwork, and workday in occupational stress. Also, the study quantifies the importance of social support to reduce occupational stress.

  8. Radar cross-section measurements of ice particles using vector network analyzer

    Directory of Open Access Journals (Sweden)

    Jinhu Wang

    2016-09-01

    Full Text Available We carried out radar cross-section (RSC measurements of ice particles in a microwave anechoic chamber at Nanjing University of Information Science and Technology. We used microwave similarity theory to enlarge the size of particle from the micrometer to millimeter scale and to reduce the testing frequency from 94 GHz to 10 GHz. The microwave similarity theory was validated using the method of moments for single metal sphere, single dielectric sphere, and spherical and non-spherical dielectric particle swarms. The differences between the retrieved and theoretical results at 94 GHz were 0.016117%, 0.0023029%, 0.027627%, and 0.0046053%, respectively. We proposed a device that can measure the RCS of ice particles in the chamber based on the S21 parameter obtained from vector network analyzer. On the basis of the measured S21 parameter of the calibration material (metal plates and their corresponding theoretical RCS values, the RCS values of a spherical Teflon particle swarm and cuboid candle particle swarm was retrieved at 10 GHz. In this case, the differences between the retrieved and theoretical results were 12.72% and 24.49% for the Teflon particle swarm and cuboid candle swarm, respectively.

  9. Radar cross-section measurements of ice particles using vector network analyzer

    Science.gov (United States)

    Wang, Jinhu; Ge, Junxiang; Zhang, Qilin; Li, Xiangchao; Wei, Ming; Yang, Zexin; Liu, Yan-An

    2016-09-01

    We carried out radar cross-section (RSC) measurements of ice particles in a microwave anechoic chamber at Nanjing University of Information Science and Technology. We used microwave similarity theory to enlarge the size of particle from the micrometer to millimeter scale and to reduce the testing frequency from 94 GHz to 10 GHz. The microwave similarity theory was validated using the method of moments for single metal sphere, single dielectric sphere, and spherical and non-spherical dielectric particle swarms. The differences between the retrieved and theoretical results at 94 GHz were 0.016117%, 0.0023029%, 0.027627%, and 0.0046053%, respectively. We proposed a device that can measure the RCS of ice particles in the chamber based on the S21 parameter obtained from vector network analyzer. On the basis of the measured S21 parameter of the calibration material (metal plates) and their corresponding theoretical RCS values, the RCS values of a spherical Teflon particle swarm and cuboid candle particle swarm was retrieved at 10 GHz. In this case, the differences between the retrieved and theoretical results were 12.72% and 24.49% for the Teflon particle swarm and cuboid candle swarm, respectively.

  10. Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

    Science.gov (United States)

    Rap, Shelley; Blonder, Ron

    2016-02-01

    We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse events were tallied in the different groups. We analyzed the different events that were found in chemistry learning Facebook groups (CLFGs). The analysis revealed that seven types of interactions were observed in the CLFGs: The most common interaction (47 %) dealt with organizing learning (e.g., announcements regarding homework, the location of the next class); learning interactions were observed in 22 % of the posts, and links to learning materials and social interactions constituted about 20 % each. The learning events that were ascertained underwent a deeper examination and three different types of chemistry learning interactions were identified. This examination was based on the theoretical framework of the commognitive approach to learning (Sfard in Thinking as communicating. Cambridge University Press, Cambridge, 2008), which will be explained. The identified learning interactions that were observed in the Facebook groups illustrate the potential of SNs to serve as an additional tool for teachers to advance their students' learning of chemistry.

  11. Neural Network Based State of Health Diagnostics for an Automated Radioxenon Sampler/Analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Keller, Paul E.; Kangas, Lars J.; Hayes, James C.; Schrom, Brian T.; Suarez, Reynold; Hubbard, Charles W.; Heimbigner, Tom R.; McIntyre, Justin I.

    2009-05-13

    Artificial neural networks (ANNs) are used to determine the state-of-health (SOH) of the Automated Radioxenon Analyzer/Sampler (ARSA). ARSA is a gas collection and analysis system used for non-proliferation monitoring in detecting radioxenon released during nuclear tests. SOH diagnostics are important for automated, unmanned sensing systems so that remote detection and identification of problems can be made without onsite staff. Both recurrent and feed-forward ANNs are presented. The recurrent ANN is trained to predict sensor values based on current valve states, which control air flow, so that with only valve states the normal SOH sensor values can be predicted. Deviation between modeled value and actual is an indication of a potential problem. The feed-forward ANN acts as a nonlinear version of principal components analysis (PCA) and is trained to replicate the normal SOH sensor values. Because of ARSA’s complexity, this nonlinear PCA is better able to capture the relationships among the sensors than standard linear PCA and is applicable to both sensor validation and recognizing off-normal operating conditions. Both models provide valuable information to detect impending malfunctions before they occur to avoid unscheduled shutdown. Finally, the ability of ANN methods to predict the system state is presented.

  12. Discriminating different classes of biological networks by analyzing the graphs spectra distribution.

    Directory of Open Access Journals (Sweden)

    Daniel Yasumasa Takahashi

    Full Text Available The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1 protein-protein interaction networks of different species and (2 on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length failed.

  13. Discriminating different classes of biological networks by analyzing the graphs spectra distribution

    CERN Document Server

    Takahashi, Daniel Yasumasa; Ferreira, Carlos Eduardo; Fujita, André

    2012-01-01

    The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibl...

  14. Towards a Framework to Analyze Causal Relations From Digital Information Networks To Micro Economic Productivity

    OpenAIRE

    Madureira, A.; N. BAKEN; H. Bouwman

    2009-01-01

    Digital Information Networks (DINs) refer to information networks supported by telecommunication infrastructures and terminated by microprocessors. In the recent past, there is a consolidated recognition that the public digital network infrastructure is of high economic importance, being generally recognized as one of the pillars of the knowledge society. An economic agent uses DINs to increase his individual productivity and that of his organization. From a thorough literature review about w...

  15. Endogenous Protein Interactome of Human UDP-Glucuronosyltransferases Exposed by Untargeted Proteomics

    Science.gov (United States)

    Rouleau, Michèle; Audet-Delage, Yannick; Desjardins, Sylvie; Rouleau, Mélanie; Girard-Bock, Camille; Guillemette, Chantal

    2017-01-01

    The conjugative metabolism mediated by UDP-glucuronosyltransferase enzymes (UGTs) significantly influences the bioavailability and biological responses of endogenous molecule substrates and xenobiotics including drugs. UGTs participate in the regulation of cellular homeostasis by limiting stress induced by toxic molecules, and by controlling hormonal signaling networks. Glucuronidation is highly regulated at genomic, transcriptional, post-transcriptional and post-translational levels. However, the UGT protein interaction network, which is likely to influence glucuronidation, has received little attention. We investigated the endogenous protein interactome of human UGT1A enzymes in main drug metabolizing non-malignant tissues where UGT expression is most prevalent, using an unbiased proteomics approach. Mass spectrometry analysis of affinity-purified UGT1A enzymes and associated protein complexes in liver, kidney and intestine tissues revealed an intricate interactome linking UGT1A enzymes to multiple metabolic pathways. Several proteins of pharmacological importance such as transferases (including UGT2 enzymes), transporters and dehydrogenases were identified, upholding a potential coordinated cellular response to small lipophilic molecules and drugs. Furthermore, a significant cluster of functionally related enzymes involved in fatty acid β-oxidation, as well as in the glycolysis and glycogenolysis pathways were enriched in UGT1A enzymes complexes. Several partnerships were confirmed by co-immunoprecipitations and co-localization by confocal microscopy. An enhanced accumulation of lipid droplets in a kidney cell model overexpressing the UGT1A9 enzyme supported the presence of a functional interplay. Our work provides unprecedented evidence for a functional interaction between glucuronidation and bioenergetic metabolism. PMID:28217095

  16. ConvAn: a convergence analyzing tool for optimization of biochemical networks.

    Science.gov (United States)

    Kostromins, Andrejs; Mozga, Ivars; Stalidzans, Egils

    2012-01-01

    Dynamic models of biochemical networks usually are described as a system of nonlinear differential equations. In case of optimization of models for purpose of parameter estimation or design of new properties mainly numerical methods are used. That causes problems of optimization predictability as most of numerical optimization methods have stochastic properties and the convergence of the objective function to the global optimum is hardly predictable. Determination of suitable optimization method and necessary duration of optimization becomes critical in case of evaluation of high number of combinations of adjustable parameters or in case of large dynamic models. This task is complex due to variety of optimization methods, software tools and nonlinearity features of models in different parameter spaces. A software tool ConvAn is developed to analyze statistical properties of convergence dynamics for optimization runs with particular optimization method, model, software tool, set of optimization method parameters and number of adjustable parameters of the model. The convergence curves can be normalized automatically to enable comparison of different methods and models in the same scale. By the help of the biochemistry adapted graphical user interface of ConvAn it is possible to compare different optimization methods in terms of ability to find the global optima or values close to that as well as the necessary computational time to reach them. It is possible to estimate the optimization performance for different number of adjustable parameters. The functionality of ConvAn enables statistical assessment of necessary optimization time depending on the necessary optimization accuracy. Optimization methods, which are not suitable for a particular optimization task, can be rejected if they have poor repeatability or convergence properties. The software ConvAn is freely available on www.biosystems.lv/convan.

  17. The use of artificial neural networks to analyze and predict alongshore sediment transport

    Directory of Open Access Journals (Sweden)

    B. van Maanen

    2010-09-01

    Full Text Available An artificial neural network (ANN was developed to predict the depth-integrated alongshore suspended sediment transport rate using 4 input variables (water depth, wave height and period, and alongshore velocity. The ANN was trained and validated using a dataset obtained on the intertidal beach of Egmond aan Zee, the Netherlands. Root-mean-square deviation between observations and predictions was calculated to show that, for this specific dataset, the ANN (εrms=0.43 outperforms the commonly used Bailard (1981 formula (εrms=1.63, even when this formula is calibrated (εrms=0.66. Because of correlations between input variables, the predictive quality of the ANN can be improved further by considering only 3 out of the 4 available input variables (εrms=0.39. Finally, we use the partial derivatives method to "open and lighten" the generated ANNs with the purpose of showing that, although specific to the dataset in question, they are not "black-box" type models and can be used to analyze the physical processes associated with alongshore sediment transport. In this case, the alongshore component of the velocity, by itself or in combination with other input variables, has the largest explanatory power. Moreover, the behaviour of the ANN indicates that predictions can be unphysical and therefore unreliable when the input lies outside the parameter space over which the ANN has been developed. Our approach of combining the strong predictive power of ANNs with "lightening" the black box and testing its sensitivity, demonstrates that the use of an ANN approach can result in the development of generalized models of suspended sediment transport.

  18. [Using the Tabu-search-algorithm-based Bayesian network to analyze the risk factors of coronary heart diseases].

    Science.gov (United States)

    Wei, Z; Zhang, X L; Rao, H X; Wang, H F; Wang, X; Qiu, L X

    2016-06-01

    Under the available data gathered from a coronary study questionnaires with 10 792 cases, this article constructs a Bayesian network model based on the tabu search algorithm and calculates the conditional probability of each node, using the Maximum-likelihood. Pros and cons of the Bayesian network model are evaluated to compare against the logistic regression model in the analysis of coronary factors. Applicability of this network model in clinical study is also investigated. Results show that Bayesian network model can reveal the complex correlations among influencing factors on the coronary and the relationship with coronary heart diseases. Bayesian network model seems promising and more practical than the logistic regression model in analyzing the influencing factors of coronary heart disease.

  19. Analyzing fixed points of intracellular regulation networks with interrelated feedback topology

    Directory of Open Access Journals (Sweden)

    Radde Nicole

    2012-06-01

    Full Text Available Abstract Background Modeling the dynamics of intracellular regulation networks by systems of ordinary differential equations has become a standard method in systems biology, and it has been shown that the behavior of these networks is often tightly connected to the network topology. We have recently introduced the circuit-breaking algorithm, a method that uses the network topology to construct a one-dimensional circuit-characteristic of the system. It was shown that this characteristic can be used for an efficient calculation of the system’s fixed points. Results Here we extend previous work and show several connections between the circuit-characteristic and the stability of fixed points. In particular, we derive a sufficient condition on the characteristic for a fixed point to be unstable for certain graph structures and demonstrate that the characteristic does not contain the information to decide whether a fixed point is asymptotically stable. All statements are illustrated on biological network models. Conclusions Single feedback circuits and their role for complex dynamic behavior of biological networks have extensively been investigated, but a transfer of most of these concepts to more complex topologies is difficult. In this context, our algorithm is a powerful new approach for the analysis of regulation networks that goes beyond single isolated feedback circuits.

  20. Analyzing the urban development of Isfahan districts in the housing sector using analytic network process (ANP

    Directory of Open Access Journals (Sweden)

    S. Hadizadeh Zargar

    2013-01-01

    , appearance and building materials (the ratio of housing units with resistant materials to the total housing, the ratio of malformed residential units to the total housing and the relative share of old texture. It should be noted that the data associated with each of the above parameters were gathered separately for each area to be used in model process. In order to implement the analytic network process (ANP model, we need to design a proper network model that includes the objective of the study as well as the main and sub-criteria (index to perfectly address the research objective. In this model, the interdependence of the criteria and sub-criteria as well as the binary matrices in the model were analyzed using the ideas of experts to determine the final value of each indicator. Options (fourteen Isfahan districts were also examined separately in the model and after final weighing, the indicators were proposed in terms of evaluation matrix. 4-ConclusionThe main criteria as well as sub-criteria considered in this study are both interdependent and interrelated. Moreover, in cases where the interrelation of the indicators is an issue, the analytic hierarchy does not include such relationship and may thus lead to the misleading results. In such cases, the analytical network can be used as an alternative. The application of analytical network process even in presence of interrelated indicators does not interfere with the model. Thus, given the interrelation of the indicators in housing sector, analytic network process can be utilized. According to the results of research on the final evaluation of indicators, the housing quality indicators in terms of access to sociocultural services, land price and the annual production capacity of housing for every 1000 people were the most important indicators of housing development in urban areas. Furthermore, the results of study on districts ranking based on the housing development suggest that District 1 ranked first by gaining the

  1. Investigative Data Mining Toolkit: A Software Prototype for Visualizing, Analyzing and Destabilizing Terrorist Networks

    Science.gov (United States)

    2006-12-01

    None of these studies used advanced data mining technologies that have been applied widely in other domains such as finance , marketing, and business to...different kinds of criminal networks, for example in financing terrorists by illegal diamond and drug trafficking. Recently, computer scientists have...Complex Networks can help in developing Strategy against Terrorism, Chaos, Solitons and Fractals 20, 69-75 (2004) [28] Bali Night Club Bombing

  2. Analyzing the scaling of connectivity in neuromorphic hardware and in models of neural networks.

    Science.gov (United States)

    Partzsch, Johannes; Schüffny, René

    2011-06-01

    In recent years, neuromorphic hardware systems have significantly grown in size. With more and more neurons and synapses integrated in such systems, the neural connectivity and its configurability have become crucial design constraints. To tackle this problem, we introduce a generic extended graph description of connection topologies that allows a systematical analysis of connectivity in both neuromorphic hardware and neural network models. The unifying nature of our approach enables a close exchange between hardware and models. For an existing hardware system, the optimally matched network model can be extracted. Inversely, a hardware architecture may be fitted to a particular model network topology with our description method. As a further strength, the extended graph can be used to quantify the amount of configurability for a certain network topology. This is a hardware design variable that has widely been neglected, mainly because of a missing analysis method. To condense our analysis results, we develop a classification for the scaling complexity of network models and neuromorphic hardware, based on the total number of connections and the configurability. We find a gap between several models and existing hardware, making these hardware systems either impossible or inefficient to use for scaled-up network models. In this respect, our analysis results suggest models with locality in their connections as promising approach for tackling this scaling gap.

  3. Data management of protein interaction networks

    CERN Document Server

    Cannataro, Mario

    2012-01-01

    Interactomics: a complete survey from data generation to knowledge extraction With the increasing use of high-throughput experimental assays, more and more protein interaction databases are becoming available. As a result, computational analysis of protein-to-protein interaction (PPI) data and networks, now known as interactomics, has become an essential tool to determine functionally associated proteins. From wet lab technologies to data management to knowledge extraction, this timely book guides readers through the new science of interactomics, giving them the tools needed to: Generate

  4. Livelihood diversification in tropical coastal communities: a network-based approach to analyzing 'livelihood landscapes'.

    Science.gov (United States)

    Cinner, Joshua E; Bodin, Orjan

    2010-08-11

    Diverse livelihood portfolios are frequently viewed as a critical component of household economies in developing countries. Within the context of natural resources governance in particular, the capacity of individual households to engage in multiple occupations has been shown to influence important issues such as whether fishers would exit a declining fishery, how people react to policy, the types of resource management systems that may be applicable, and other decisions about natural resource use. This paper uses network analysis to provide a novel methodological framework for detailed systemic analysis of household livelihood portfolios. Paying particular attention to the role of natural resource-based occupations such as fisheries, we use network analyses to map occupations and their interrelationships- what we refer to as 'livelihood landscapes'. This network approach allows for the visualization of complex information about dependence on natural resources that can be aggregated at different scales. We then examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities in 5 western Indian Ocean countries. Network statistics, including in- and out-degree centrality, the density of the network, and the level of network centralization are compared along a multivariate index of community-level socioeconomic development and a gradient of human population density. The combination of network analyses suggests an increase in household-level specialization with development for most occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified. The novel modeling approach introduced here provides for various types of livelihood portfolio analyses at different scales of social aggregation. Our livelihood landscapes approach provides insights into communities' dependencies and usages of natural resources, and shows how patterns of

  5. Development status of a 420–1980 GHz vector network analyzer for time-domain reflectometry and imaging applications

    NARCIS (Netherlands)

    Jellema, Willem; Barychev, Andrei; Paveliev, D.; Hesler, J. L.; Wild, Wolfgang; Withington, S.

    2007-01-01

    With recent progress in the area of electronically tunable solid-state sources it is possible to fully extend microwave measurement techniques into the THz frequency range. In this paper we present the development status of a 420-1980 GHz vector network analyzer and illustrate how phase-sensitive

  6. Effect of Chromium on CCT Diagrams of Novel Air-Cooled Bainite Steels Analyzed by Neural Network

    Institute of Scientific and Technical Information of China (English)

    YOU Wei; XU Wei-hong; LIU Ya-xiu; BAI Bing-zhe; FANG Hong-sheng

    2007-01-01

    The quantitative effects of chromium content on continuous cooling transformation (CCT) diagrams of novel air-cooled bainite steels were analyzed using artificial neural network models. The results showed that the chromium may retard the high and medium-temperature martensite transformation.

  7. Development status of a 420–1980 GHz vector network analyzer for time-domain reflectometry and imaging applications

    NARCIS (Netherlands)

    Jellema, Willem; Barychev, Andrei; Paveliev, D.; Hesler, J. L.; Wild, Wolfgang; Withington, S.

    2007-01-01

    With recent progress in the area of electronically tunable solid-state sources it is possible to fully extend microwave measurement techniques into the THz frequency range. In this paper we present the development status of a 420-1980 GHz vector network analyzer and illustrate how phase-sensitive he

  8. Analyzing Web 2.0 Integration with Next Generation Networks for Services Rendering

    CERN Document Server

    Lakhtaria, Kamaljit I

    2010-01-01

    The Next Generation Networks (NGN) aims to integrate for IP-based telecom infrastructures and provide most advance & high speed emerging value added services. NGN capable to provide higher innovative services, these services will able to integrate communication and Web service into a single platform. IP Multimedia Subsystem, a NGN leading technology, enables a variety of NGN-compliant communications services to interoperate while being accessed through different kinds of access networks, preferably broadband. IMS–NGN services essential by both consumer and corporate users are by now used to access services, even communications services through the web and web-based communities and social networks, It is key for success of IMS-based services to be provided with efficient web access, so users can benefit from those new services by using web-based applications and user interfaces, not only NGN-IMS User Equipments and SIP protocol. Many Service are under planning which provided only under convergence of ...

  9. Analyzing the relationship between social networking addiction, interaction anxiousness and levels of loneliness of pre-service teachers

    Directory of Open Access Journals (Sweden)

    Hasan Özgür

    2013-10-01

    Full Text Available In this research, it was aimed to analyze the social networking addiction of pre-service teachers in terms of various variables and evaluate the relationship between social networking addiction and loneliness and interaction anxiousness. The research was designed according to the relational screening model. The study sample included 349 pre-service teachers studying at Trakya University Faculty of Education in 2012-2013 academic year fall term. The data were obtained using Facebook Addiction Scale, Interaction Anxiousness Scale, the UCLA-Loneliness Scale III and personal information form. In analysis of data, descriptive statistics, Mann Whitney U-Test, Kruskal-Wallis H and correlation tests were benefited. The research findings revealed that social networking addiction of pre-service teachers was at a low level, the relationship between interaction anxiousness and social networking addiction was high, and the relationship between the level of loneliness and social networking addiction was at a mid-level. Moreover, in the research a statistically significant difference was obtained between the variables of social networking addiction and frequency of using social networking, gender and the level of grade they study.

  10. Analyzing Social Media Networks with NodeXL Insights from a Connected World

    CERN Document Server

    Hansen, Derek; Smith, Marc A

    2010-01-01

    Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

  11. Logistic growth for the Nuzi cuneiform tablets: Analyzing family networks in ancient Mesopotamia

    Science.gov (United States)

    Ueda, Sumie; Makino, Kumi; Itoh, Yoshiaki; Tsuchiya, Takashi

    2015-03-01

    We reconstruct the published year of each cuneiform tablet of the Nuzi society in ancient Mesopotamia. The tablets are on land transaction, marriage, loan, slavery contracts, etc. The number of tablets seems to increase by logistic growth. It may show the dynamics of concentration of lands or other properties into few powerful families in a period of about sixty years and most of them are in about thirty years. We reconstruct family trees and social networks of Nuzi and estimate the published years of cuneiform tablets consistently with the trees and networks, formulating least squares problems with linear inequality constraints.

  12. ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

    Science.gov (United States)

    Matsuyama, Shinako; Terano, Takao

    This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

  13. Application of nonlinear neural network to analyze the stope structure parameters

    Energy Technology Data Exchange (ETDEWEB)

    Lai, X.; Cai, M.; Zhang, B. [University of Science and Technoogy of Beijing (China). Civil and Environmental School

    2001-06-01

    In this paper, the state-of-the-art of neural computing in geotechnical structural analysis and design has been surveyed. Its computing strategies and research trends are given. The principle of the BP neural networks and computing for constitutive modelling have been discussed, then achieved in applying to analyse the underground stope structure parameters in the Xincheng gold mine with the applications of BP network, it is proven that the neurocomputing is a practical tool for solving large-scale rock underground structural engineering problems. 4 refs., 2 figs., 2 tabs.

  14. Theoretical Neuroanatomy:Analyzing the Structure, Dynamics,and Function of Neuronal Networks

    Science.gov (United States)

    Seth, Anil K.; Edelman, Gerald M.

    The mammalian brain is an extraordinary object: its networks give rise to our conscious experiences as well as to the generation of adaptive behavior for the organism within its environment. Progress in understanding the structure, dynamics and function of the brain faces many challenges. Biological neural networks change over time, their detailed structure is difficult to elucidate, and they are highly heterogeneous both in their neuronal units and synaptic connections. In facing these challenges, graph-theoretic and information-theoretic approaches have yielded a number of useful insights and promise many more.

  15. Analyzing Networked Learning Practices in HigherEducation and Continuing Professional Development

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    Deliverable 28.5.4 reports on the preparation of the book "Analysing Networked Learning Practices in Higher Education and Continuing Professional Development", which consists of an Introduction, case studies and a concluding section, which presents the theoretical work and empirical work conducted...

  16. Analyzing the effect of routing protocols on media access control protocols in radio networks

    Energy Technology Data Exchange (ETDEWEB)

    Barrett, C. L. (Christopher L.); Drozda, M. (Martin); Marathe, A. (Achla); Marathe, M. V. (Madhav V.)

    2002-01-01

    We study the effect of routing protocols on the performance of media access control (MAC) protocols in wireless radio networks. Three well known MAC protocols: 802.11, CSMA, and MACA are considered. Similarly three recently proposed routing protocols: AODV, DSR and LAR scheme 1 are considered. The experimental analysis was carried out using GloMoSim: a tool for simulating wireless networks. The main focus of our experiments was to study how the routing protocols affect the performance of the MAC protocols when the underlying network and traffic parameters are varied. The performance of the protocols was measured w.r.t. five important parameters: (i) number of received packets, (ii) average latency of each packet, (iii) throughput (iv) long term fairness and (v) number of control packets at the MAC layer level. Our results show that combinations of routing and MAC protocols yield varying performance under varying network topology and traffic situations. The result has an important implication; no combination of routing protocol and MAC protocol is the best over all situations. Also, the performance analysis of protocols at a given level in the protocol stack needs to be studied not locally in isolation but as a part of the complete protocol stack. A novel aspect of our work is the use of statistical technique, ANOVA (Analysis of Variance) to characterize the effect of routing protocols on MAC protocols. This technique is of independent interest and can be utilized in several other simulation and empirical studies.

  17. Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

    Science.gov (United States)

    Rap, Shelley; Blonder, Ron

    2016-01-01

    We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse…

  18. Analyzing Networked Learning Practices in HigherEducation and Continuing Professional Development

    DEFF Research Database (Denmark)

    Dirckinck-Holmfeld, Lone

    Deliverable 28.5.4 reports on the preparation of the book "Analysing Networked Learning Practices in Higher Education and Continuing Professional Development", which consists of an Introduction, case studies and a concluding section, which presents the theoretical work and empirical work conducted...

  19. A proteome-scale map of the human interactome network

    OpenAIRE

    Rolland, Thomas; Fontanillo, Celia; De Las Rivas, Javier; Vidal, Marc

    2014-01-01

    This work was supported primarily by NHGRI grant R01/U01HG001715 awarded to M.V., D.E.H., F.P.R., and J.T. and in part by the following grants and agencies: NHGRI P50HG004233 to M.V., F.P.R., and A.-L.B.; NHLBI U01HL098166 subaward to M.V.; NHLBI U01HL108630 subaward to A.-L.B.; NCI U54CA112962 subaward to M.V.; NCI R33CA132073 to M.V.; NIH RC4HG006066 to M.V., D.E.H., and T.H.; NICHD ARRA R01HD065288, R21MH104766, and R01MH105524 to L.M.I.; NIMH R01MH091350 to L.M.I. and T.H.; NSF CCF-121900...

  20. Livelihood diversification in tropical coastal communities: a network-based approach to analyzing 'livelihood landscapes'.

    Directory of Open Access Journals (Sweden)

    Joshua E Cinner

    Full Text Available BACKGROUND: Diverse livelihood portfolios are frequently viewed as a critical component of household economies in developing countries. Within the context of natural resources governance in particular, the capacity of individual households to engage in multiple occupations has been shown to influence important issues such as whether fishers would exit a declining fishery, how people react to policy, the types of resource management systems that may be applicable, and other decisions about natural resource use. METHODOLOGY/PRINCIPAL FINDINGS: This paper uses network analysis to provide a novel methodological framework for detailed systemic analysis of household livelihood portfolios. Paying particular attention to the role of natural resource-based occupations such as fisheries, we use network analyses to map occupations and their interrelationships- what we refer to as 'livelihood landscapes'. This network approach allows for the visualization of complex information about dependence on natural resources that can be aggregated at different scales. We then examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities in 5 western Indian Ocean countries. Network statistics, including in- and out-degree centrality, the density of the network, and the level of network centralization are compared along a multivariate index of community-level socioeconomic development and a gradient of human population density. The combination of network analyses suggests an increase in household-level specialization with development for most occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified. CONCLUSIONS/SIGNIFICANCE: The novel modeling approach introduced here provides for various types of livelihood portfolio analyses at different scales of social aggregation. Our livelihood landscapes approach provides insights

  1. Social network analysis as a method for analyzing interaction in collaborative online learning environments

    Directory of Open Access Journals (Sweden)

    Patricia Rice Doran

    2011-12-01

    Full Text Available Social network analysis software such as NodeXL has been used to describe participation and interaction in numerous social networks, but it has not yet been widely used to examine dynamics in online classes, where participation is frequently required rather than optional and participation patterns may be impacted by the requirements of the class, the instructor’s activities, or participants’ intrinsic engagement with the subject matter. Such social network analysis, which examines the dynamics and interactions among groups of participants in a social network or learning group, can be valuable in programs focused on teaching collaborative and communicative skills, including teacher preparation programs. Applied to these programs, social network analysis can provide information about instructional practices likely to facilitate student interaction and collaboration across diverse student populations. This exploratory study used NodeXL to visualize students’ participation in an online course, with the goal of identifying (1 ways in which NodeXL could be used to describe patterns in participant interaction within an instructional setting and (2 identifying specific patterns in participant interaction among students in this particular course. In this sample, general education teachers demonstrated higher measures of connection and interaction with other participants than did those from specialist (ESOL or special education backgrounds, and tended to interact more frequently with all participants than the majority of participants from specialist backgrounds. We recommend further research to delineate specific applications of NodeXL within an instructional context, particularly to identify potential patterns in student participation based on variables such as gender, background, cultural and linguistic heritage, prior training and education, and prior experience so that instructors can ensure their practice helps to facilitate student interaction

  2. Creating Network Attack Priority Lists by Analyzing Email Traffic With Predefined Profiles

    Science.gov (United States)

    2012-09-01

    gathering process begins again to identify mechanisms to gain access to trusted systems. Evaluate trusts, Search for passwords 5 Cover Tracks...f***! heart! honey! hump! infatuation! intrigue! jazz ! know! liking! love! loved! loveless! lovely! lovemaking! lover! loves! accomplished! appeal...2. REPORT TYPE Master’s Thesis 3. DATES COVERED (From – To) March 2011 – September 2012 4. TITLE AND SUBTITLE Creating Network Attack

  3. Analyzing Social Media And Learning Through Content And Social Network Analysis: A Faceted Methodological Approach

    OpenAIRE

    2016-01-01

    In just a short period of time, social media have altered many aspects of our daily lives, from how we form and maintain social relationships to how we discover, access and share information online. Now social media are also affecting how we teach and learn. In this paper, we discuss methods that can help researchers and educators evaluate and understand the observed and potential use of social media for teaching and learning through content and network analyses of social media texts and netw...

  4. Analyzing Web 2.0 Integration with Next Generation Networks for Services Rendering

    Directory of Open Access Journals (Sweden)

    Kamaljit I. Lakhtaria

    2010-08-01

    Full Text Available The Next Generation Networks (NGN aims to integrate for IP-based telecominfrastructures and provide most advance & high speed emerging value added services.NGN capable to provide higher innovative services, these services will able to integratecommunication and Web service into a single platform. IP Multimedia Subsystem, aNGN leading technology, enables a variety of NGN-compliant communications servicesto interoperate while being accessed through different kinds of access networks,preferably broadband. IMS–NGN services essential by both consumer and corporateusers are by now used to access services, even communications services through the weband web-based communities and social networks, It is key for success of IMS-basedservices to be provided with efficient web access, so users can benefit from those newservices by using web-based applications and user interfaces, not only NGN-IMS UserEquipments and SIP protocol. Many Service are under planning which provided onlyunder convergence of IMS & Web 2.0. Convergence between Web 2.0 and NGN-IMScreates and serves new invented innovative, entertainment and information appealing aswell as user centric services and applications. These services merge features from WWWand Communication worlds. On the one hand, interactivity, ubiquity, social orientation,user participation and content generation, etc. are relevant characteristics coming fromWeb 2.0 services. Parallel IMS enables services including multimedia telephony, mediasharing (video-audio, instant messaging with presence and context, online directory,etc. all of them applicable to mobile, fixed or convergent telecom networks. With thispaper, this paper brings out the benefits of adopting web 2.0 technologies for telecomservices. As the services are today mainly driven by the user's needs, and proposed theconcept of unique customizable service interface.

  5. Analyzing and interpreting genome data at the network level with ConsensusPathDB.

    Science.gov (United States)

    Herwig, Ralf; Hardt, Christopher; Lienhard, Matthias; Kamburov, Atanas

    2016-10-01

    ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq. The tool reports interaction network modules, biochemical pathways and functional information that are significantly enriched by the user's input, applying computational methods for statistical over-representation, enrichment and graph analysis. The results of this protocol can be observed within a few minutes, even with genome-wide data. The resulting network associations can be used to interpret high-throughput data mechanistically, to characterize and prioritize biomarkers, to integrate different omics levels, to design follow-up functional assay experiments and to generate topology for kinetic models at different scales.

  6. Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD) for brain cancer.

    Science.gov (United States)

    Huang, Ying; Ma, Jing; Porter, Alan L; Kwon, Seokbeom; Zhu, Donghua

    2015-01-01

    The rapid development of new and emerging science & technologies (NESTs) brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area - nano-enabled drug delivery (NEDD). NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1) international cooperation is increasing, but networking characteristics change over time; (2) highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3) research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

  7. Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD for brain cancer

    Directory of Open Access Journals (Sweden)

    Ying Huang

    2015-07-01

    Full Text Available The rapid development of new and emerging science & technologies (NESTs brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area – nano-enabled drug delivery (NEDD. NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1 international cooperation is increasing, but networking characteristics change over time; (2 highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3 research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

  8. ARTIFICIAL NEURAL-NETWORK PREDICTIONS OF URINARY CALCULUS COMPOSITIONS ANALYZED WITH INFRARED-SPECTROSCOPY

    NARCIS (Netherlands)

    VOLMER, M; WOLTHERS, BG; METTING, HJ; DEHAAN, THY; COENEGRACHT, PMJ; VANDERSLIK, W

    1994-01-01

    Infrared (IR) spectroscopy is used to analyze urinary calculus (renal stone) constituents. However, interpretation of IR spectra for quantifying urinary calculus constituents in mixtures is difficult, requiring expert knowledge by trained technicians. In our laboratory IR spectra of unknown calculi

  9. Analyzing the Potential of Full Duplex in 5G Ultra-Dense Small Cell Networks

    DEFF Research Database (Denmark)

    Gatnau, Marta; Berardinelli, Gilberto; Mahmood, Nurul Huda;

    2016-01-01

    Full duplex technology has become an attractive solution for future 5th Generation (5G) systems for accommodating the exponentially growing mobile traffic demand. Full duplex allows a node to transmit and receive simultaneously in the same frequency band, thus, theoretically, doubling the system......-interference cancellation are demonstrated using our own developed test bed. Secondly, a detailed evaluation of full duplex communication in 5G ultra-dense small cell networks via system level simulations is provided. The results are presented in terms of throughput and delay. Two types of full duplex are studied: when...

  10. Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks.

    Science.gov (United States)

    Rashed, Sarmad; Soyturk, Mujdat

    2017-02-20

    Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, datacollectionbecomesoneofthemajorissues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage-especially Unmanned Aerial Vehicles (UAVs)-is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern.

  11. Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

    Directory of Open Access Journals (Sweden)

    Songling Fu

    2014-01-01

    Full Text Available Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs. The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

  12. Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

    Science.gov (United States)

    He, Ligang; Liao, Xiangke; Huang, Chenlin

    2014-01-01

    Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs). The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today's online social networks (OSNs) due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction. PMID:24892095

  13. Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

    Directory of Open Access Journals (Sweden)

    Chihyun Park

    Full Text Available BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. RESULTS: In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. CONCLUSIONS: The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

  14. The Unfolding MD Simulations of Cyclophilin: Analyzed by Surface Contact Networks and Their Associated Metrics.

    Directory of Open Access Journals (Sweden)

    Sourav Roy

    Full Text Available Currently, considerable interest exists with regard to the dissociation of close packed aminoacids within proteins, in the course of unfolding, which could result in either wet or dry moltenglobules. The progressive disjuncture of residues constituting the hydrophobic core ofcyclophilin from L. donovani (LdCyp has been studied during the thermal unfolding of the molecule, by molecular dynamics simulations. LdCyp has been represented as a surface contactnetwork (SCN based on the surface complementarity (Sm of interacting residues within themolecular interior. The application of Sm to side chain packing within proteins make it a very sensitive indicator of subtle perturbations in packing, in the thermal unfolding of the protein. Network based metrics have been defined to track the sequential changes in the disintegration ofthe SCN spanning the hydrophobic core of LdCyp and these metrics prove to be highly sensitive compared to traditional metrics in indicating the increased conformational (and dynamical flexibility in the network. These metrics have been applied to suggest criteria distinguishing DMG, WMG and transition state ensembles and to identify key residues involved in crucial conformational/topological events during the unfolding process.

  15. Modeling and Analyzing the Interaction between Network Rumors and Authoritative Information

    Directory of Open Access Journals (Sweden)

    Lingling Xia

    2015-01-01

    Full Text Available In this paper, we propose a novel two-stage rumor spreading Susceptible-Infected-Authoritative-Removed (SIAR model for complex homogeneous and heterogeneous networks. The interaction Markov chains (IMC mean-field equations based on the SIAR model are derived to describe the dynamic interaction between the rumors and authoritative information. We use a Monte Carlo simulation method to characterize the dynamics of the Susceptible-Infected-Removed (SIR and SIAR models, showing that the SIAR model with consideration of authoritative information gives a more realistic description of propagation features of rumors than the SIR model. The simulation results demonstrate that the critical threshold λc of the SIAR model has the tiniest increase than the threshold of SIR model. The sooner the authoritative information is introduced, the less negative impact the rumors will bring. We also get the result that heterogeneous networks are more prone to the spreading of rumors. Additionally, the inhibition of rumor spreading, as one of the characteristics of the new SIAR model itself, is instructive for later studies on the rumor spreading models and the controlling strategies.

  16. Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks

    Science.gov (United States)

    Rashed, Sarmad; Soyturk, Mujdat

    2017-01-01

    Sensor nodes in a Wireless Sensor Network (WSN) can be dispersed over a remote sensing area (e.g., the regions that are hardly accessed by human beings). In such kinds of networks, data collection becomes one of the major issues. Getting connected to each sensor node and retrieving the information in time introduces new challenges. Mobile sink usage—especially Unmanned Aerial Vehicles (UAVs)—is the most convenient approach to covering the area and accessing each sensor node in such a large-scale WSN. However, the operation of the UAV depends on some parameters, such as endurance time, altitude, speed, radio type in use, and the path. In this paper, we explore various UAV mobility patterns that follow different paths to sweep the operation area in order to seek the best area coverage with the maximum number of covered nodes in the least amount of time needed by the mobile sink. We also introduce a new metric to formulate the tradeoff between maximizing the covered nodes and minimizing the operation time when choosing the appropriate mobility pattern. A realistic simulation environment is used in order to compare and evaluate the performance of the system. We present the performance results for the explored UAV mobility patterns. The results are very useful to present the tradeoff between maximizing the covered nodes and minimizing the operation time to choose the appropriate mobility pattern. PMID:28230727

  17. Electron cyclotron resonance ion source plasma chamber studies using a network analyzer as a loaded cavity probe

    Energy Technology Data Exchange (ETDEWEB)

    Toivanen, V.; Tarvainen, O.; Kauppinen, J.; Komppula, J.; Koivisto, H. [Department of Physics, University of Jyvaeskylae, Jyvaeskylae 40500 (Finland); Lyneis, C. [Lawrence Berkeley National Laboratory, Berkeley, California 94720 (United States)

    2012-02-15

    A method and first results utilizing a network analyzer as a loaded cavity probe to study the resonance properties of a plasma filled electron cyclotron resonance ion source (ECRIS) plasma chamber are presented. The loaded cavity measurements have been performed using a dual port technique, in which two separate waveguides were used simultaneously. One port was used to ignite and sustain the plasma with a microwave source operating around 11 GHz and the other was used to probe the cavity properties with the network analyzer using a frequency range around 14 GHz. The first results obtained with the JYFL 14 GHz ECRIS demonstrate that the presence of plasma has significant effects on the resonance properties of the cavity. With plasma the frequency dependent behavior is strongly damped and this trend strengthens with increasing microwave power.

  18. Analyzing the determinants of the UK consumer's engagement in Viral Marketing on Social Networking Sites : A university Student's perspective

    OpenAIRE

    Alkhateeb, Ali; Alli, Zahir; Moussa, Wissam

    2012-01-01

    Social media, especially the social networking sites (SNS) like Facebook.com, has experienced exponential growth all across the globe in the last decade. It is rapidly attracting the consumers and replacing the traditional media. Electronic word of mouth (eWOM) through social media has acquired substantial position in the marketing mix as well as integrated marketing communication of the business organizations. This research aimed at analyzing different social relationship factors or determin...

  19. Using Networks to Visualize and Analyze Process Data for Educational Assessment

    Science.gov (United States)

    Zhu, Mengxiao; Shu, Zhan; von Davier, Alina A.

    2016-01-01

    New technology enables interactive and adaptive scenario-based tasks (SBTs) to be adopted in educational measurement. At the same time, it is a challenging problem to build appropriate psychometric models to analyze data collected from these tasks, due to the complexity of the data. This study focuses on process data collected from SBTs. We…

  20. Using Networks to Visualize and Analyze Process Data for Educational Assessment

    Science.gov (United States)

    Zhu, Mengxiao; Shu, Zhan; von Davier, Alina A.

    2016-01-01

    New technology enables interactive and adaptive scenario-based tasks (SBTs) to be adopted in educational measurement. At the same time, it is a challenging problem to build appropriate psychometric models to analyze data collected from these tasks, due to the complexity of the data. This study focuses on process data collected from SBTs. We…

  1. A meta-analysis to evaluate the cellular processes regulated by the interactome of endogenous and over-expressed estrogen receptor alpha.

    Science.gov (United States)

    Simões, Joana; Amado, Francisco M; Vitorino, Rui; Helguero, Luisa A

    2015-01-01

    The nature of the proteins complexes that regulate ERα subcellular localization and activity is still an open question in breast cancer biology. Identification of such complexes will help understand development of endocrine resistance in ER+ breast cancer. Mass spectrometry (MS) has allowed comprehensive analysis of the ERα interactome. We have compared six published works analyzing the ERα interactome of MCF-7 and HeLa cells in order to identify a shared or different pathway-related fingerprint. Overall, 806 ERα interacting proteins were identified. The cellular processes were differentially represented according to the ERα purification methodology, indicating that the methodologies used are complementary. While in MCF-7 cells, the interactome of endogenous and over-expressed ERα essentially represents the same biological processes and cellular components, the proteins identified were not over-lapping; thus, suggesting that the biological response may differ as the regulatory/participating proteins in these complexes are different. Interestingly, biological processes uniquely associated to ERα over-expressed in HeLa cell line included L-serine biosynthetic process, cellular amino acid biosynthetic process and cell redox homeostasis. In summary, all the approaches analyzed in this meta-analysis are valid and complementary; in particular, for those cases where the processes occur at low frequency with normal ERα levels, and can be identified when the receptor is over-expressed. However special effort should be put into validating these findings in cells expressing physiological ERα levels.

  2. A theoretical framework for analyzing coupled neuronal networks: Application to the olfactory system.

    Science.gov (United States)

    Barreiro, Andrea K; Gautam, Shree Hari; Shew, Woodrow L; Ly, Cheng

    2017-10-02

    Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data. We apply our new technique to dual micro-electrode array in vivo recordings from two distinct regions: olfactory bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i) inhibition within the afferent region (OB) has to be weaker than the inhibition within PC, ii) excitation from PC to OB is generally stronger than excitation from OB to PC, iii) excitation from PC to OB and inhibition within PC have to both be relatively strong compared to presynaptic inputs from OB. These predictions are validated in a spiking neural network model of the OB-PC pathway that satisfies the many constraints from our experimental data. We find when the derived relationships are violated, the spiking statistics no longer satisfy the constraints from the data. In principle this modeling framework can be adapted to other systems and be used to investigate relationships between other neural attributes besides network connection strengths. Thus, this work can serve as a guide to further investigations into the relationships of various neural attributes within and across different regions during sensory processing.

  3. Software ecosystems analyzing and managing business networks in the software industry

    CERN Document Server

    Jansen, S; Cusumano, MA

    2013-01-01

    This book describes the state-of-the-art of software ecosystems. It constitutes a fundamental step towards an empirically based, nuanced understanding of the implications for management, governance, and control of software ecosystems. This is the first book of its kind dedicated to this emerging field and offers guidelines on how to analyze software ecosystems; methods for managing and growing; methods on transitioning from a closed software organization to an open one; and instruments for dealing with open source, licensing issues, product management and app stores. It is unique in bringing t

  4. Modeling and analyzing of the interaction between worms and antiworms during network worm propagation

    Institute of Scientific and Technical Information of China (English)

    YANG Feng; DUAN Haixin; LI Xing

    2005-01-01

    Interaction of antiworms with a worm population of e.g. hosts of worm infected and hosts of antiworm infected must be considered as a dynamic process. This study is an attempt for the first time to understand how introduction of antiworm affects the dynamic of network worm propagation. In this paper, we create a mathematical model (SIAR model) using ordinary differential equations to describe the interaction of worms and antiworms. Although idealized, the model demonstrates how the combination of a few proposed nonlinear interaction rules between antiworms and worms is able to generate a considerable variety of different kinds of responses. Taking the Blaster and Nachi worms as an example, we give a brief analysis for designing a practical antiworm system. To the best of our knowledge, there is no model for the spread of an antiworm that employs the passive scan and the finite lifetime and we believe that this is the first attempt on understanding the interaction between worms and antiworms.

  5. Enzyme-Based Logic Gates and Networks with Output Signals Analyzed by Various Methods.

    Science.gov (United States)

    Katz, Evgeny

    2017-07-05

    The paper overviews various methods that are used for the analysis of output signals generated by enzyme-based logic systems. The considered methods include optical techniques (optical absorbance, fluorescence spectroscopy, surface plasmon resonance), electrochemical techniques (cyclic voltammetry, potentiometry, impedance spectroscopy, conductivity measurements, use of field effect transistor devices, pH measurements), and various mechanoelectronic methods (using atomic force microscope, quartz crystal microbalance). Although each of the methods is well known for various bioanalytical applications, their use in combination with the biomolecular logic systems is rather new and sometimes not trivial. Many of the discussed methods have been combined with the use of signal-responsive materials to transduce and amplify biomolecular signals generated by the logic operations. Interfacing of biocomputing logic systems with electronics and "smart" signal-responsive materials allows logic operations be extended to actuation functions; for example, stimulating molecular release and switchable features of bioelectronic devices, such as biofuel cells. The purpose of this review article is to emphasize the broad variability of the bioanalytical systems applied for signal transduction in biocomputing processes. All bioanalytical systems discussed in the article are exemplified with specific logic gates and multi-gate networks realized with enzyme-based biocatalytic cascades. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. 应用类型网络研究模式分析社会网络%Applying Typology Network Research Model to Analyze of Social Networks

    Institute of Scientific and Technical Information of China (English)

    杨媛媛

    2013-01-01

    This paper reviews and analyzes the development situation of network research models, meanwhile points out several factors which affect the network study evolution. It still uses explanatory goals and mechanisms to construct a 2×2 table cross-classifying the study consequences into four types, which provides a new space for network research.%该论文回顾并分析了网络研究模式的发展情况,同时指出影响网络研究进展的几种因素。在此基础上利用解释目的和机制构建出2×2表格将网络研究结果交叉分类成4种类型,为网络研究开拓了一个新的空间。

  7. Mining Social Networks for Analyzing Students Learning Experience and their Problems

    Directory of Open Access Journals (Sweden)

    Blessy Geo.V.M

    2016-04-01

    Full Text Available On different social media sites, students discuss and contribute to their daily encounters in a casual and informal manner. Analyzing such data, though, can be difficult. The complication of students’ experiences reflected from social media content requires human understanding problem of a student’s experience exposes from social media sitedrequirehuman investigation or communication.Examining data from such a social media can be demanding task. In this article, we develop a workflow to combine both qualitative analysis and large-scale data mining techniques. It pays a concentration on engineering student’s Twitter posts to recognize the problem and the difficulty in their educational practices. Based on this result, a multi-label classification algorithm that is Naive Bayes Multi-label Classifier algorithm and Memetic classifier is applied to categorize tweets presenting students' problems.Memetic classifier is a population based approach to split individuals education for problem search, which has had their own advantages in solving optimization problems.

  8. Analyzing event stream dynamics in two-mode networks : An exploratory analysis of private communication in a question and answer community

    NARCIS (Netherlands)

    Stadtfeld, Christoph; Geyer-Schulz, Andreas

    2011-01-01

    Information about social networks can often be collected as event stream data. However, most methods in social network analysis are defined for static network snapshots or for panel data. We propose an actor oriented Markov process framework to analyze the structural dynamics in event streams. Estim

  9. Centrality in the host-pathogen interactome is associated with pathogen fitness during infection

    Science.gov (United States)

    Crua Asensio, Núria; Muñoz Giner, Elisabet; de Groot, Natalia Sánchez; Torrent Burgas, Marc

    2017-01-01

    To perform their functions proteins must interact with each other, but how these interactions influence bacterial infection remains elusive. Here we demonstrate that connectivity in the host-pathogen interactome is directly related to pathogen fitness during infection. Using Y. pestis as a model organism, we show that the centrality-lethality rule holds for pathogen fitness during infection but only when the host-pathogen interactome is considered. Our results suggest that the importance of pathogen proteins during infection is directly related to their number of interactions with the host. We also show that pathogen proteins causing an extensive rewiring of the host interactome have a higher impact in pathogen fitness during infection. Hence, we conclude that hubs in the host-pathogen interactome should be explored as promising targets for antimicrobial drug design.

  10. Measurement of Dielectric Properties at 75 - 325 GHz using a Vector Network Analyzer and Full Wave Simulator

    Directory of Open Access Journals (Sweden)

    S.Khanal

    2012-06-01

    Full Text Available This paper presents a fast and easy to use method to determine permittivity and loss tangent in the frequency range of 75 to 325 GHz. To obtain the permittivity and the loss tangent of the test material, the reflection and transmission S-parameters of a waveguide section filled with the test material are measured using a vector network analyzer and then compared with the simulated plots from a full wave simulator (HFSS, or alternatively the measurement results are used in mathematical formulas. The results are coherent over multiple waveguide bands.

  11. The transcriptional interactome: gene expression in 3D.

    Science.gov (United States)

    Schoenfelder, Stefan; Clay, Ieuan; Fraser, Peter

    2010-04-01

    Transcription in the eukaryotic nucleus has long been thought of as conforming to a model in which RNA polymerase complexes are recruited to and track along isolated templates. However, a more dynamic role for chromatin in transcriptional regulation is materializing: enhancer elements interact with promoters forming loops that often bridge considerable distances and genomic loci, even located on different chromosomes, undergo chromosomal associations. These associations amass to form an extensive 'transcriptional interactome', enacted at functional subnuclear compartments, to which genes dynamically relocate. The emerging view is that long-range chromosomal associations between genomic regions, and their repositioning in the three-dimensional space of the nucleus, are key contributors to the regulation of gene expression. 2010 Elsevier Ltd. All rights reserved.

  12. Emergence of plant and rhizospheric microbiota as stable interactomes.

    Science.gov (United States)

    Bandyopadhyay, Prasun; Bhuyan, Soubhagya Kumar; Yadava, Pramod Kumar; Varma, Ajit; Tuteja, Narendra

    2017-03-01

    The growing human population and depletion of resources have necessitated development of sustainable agriculture. Beneficial plant-microbe associations have been known for quite some time now. To maintain sustainability, one could show better reliance upon beneficial attributes of the rhizosphere microbiome. To harness the best agronomic traits, understanding the entire process of recruitment, establishment, and maintenance of microbiota as stable interactome within the rhizosphere is important. In this article, we highlight the process of recruitment and establishment of microbiota within rhizosphere. Further, we have discussed the interlinkages and the ability of multiple (microbial and plant) partners to interact with one another forming a stable plant holobiont system. Lastly, we address the possibility of exploring the knowledge gained from the holobiont system to tailor the rhizosphere microbiome for better productivity and maintenance of agroecosystems. The article provide new insights into the broad principles of stable plant-microbe interactions which could be useful for sustaining agriculture and food security.

  13. A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma.

    Science.gov (United States)

    Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

    2016-08-31

    Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

  14. Characterization of interdigitated electrode structures for water contaminant detection using a hybrid voltage divider and a vector network analyzer.

    Science.gov (United States)

    Rodríguez-Delgado, José Manuel; Rodríguez-Delgado, Melissa Marlene; Mendoza-Buenrostro, Christian; Dieck-Assad, Graciano; Omar Martínez-Chapa, Sergio

    2012-01-01

    Interdigitated capacitive electrode structures have been used to monitor or actuate over organic and electrochemical media in efforts to characterize biochemical properties. This article describes a method to perform a pre-characterization of interdigitated electrode structures using two methods: a hybrid voltage divider (HVD) and a vector network analyzer (VNA). Both methodologies develop some tests under two different conditions: free air and bi-distilled water media. Also, the HVD methodology is used for other two conditions: phosphate buffer with laccase (polyphenoloxidase; EC 1.10.3.2) and contaminated media composed by a mix of phosphate buffer and 3-ethylbenzothiazoline-6-sulfonic acid (ABTS). The purpose of this study is to develop and validate a characterization methodology using both, a hybrid voltage divider and VNA T-# network impedance models of the interdigitated capacitive electrode structure that will provide a shunt RC network of particular interest in detecting the amount of contamination existing in the water solution for the media conditions. This methodology should provide us with the best possible sensitivity in monitoring water contaminant media characteristics. The results show that both methods, the hybrid voltage divider and the VNA methodology, are feasible in determining impedance modeling parameters. These parameters can be used to develop electric interrogation procedures and devices such as dielectric characteristics to identify contaminant substances in water solutions.

  15. Altered Pathway Analyzer: A gene expression dataset analysis tool for identification and prioritization of differentially regulated and network rewired pathways

    Science.gov (United States)

    Kaushik, Abhinav; Ali, Shakir; Gupta, Dinesh

    2017-01-01

    Gene connection rewiring is an essential feature of gene network dynamics. Apart from its normal functional role, it may also lead to dysregulated functional states by disturbing pathway homeostasis. Very few computational tools measure rewiring within gene co-expression and its corresponding regulatory networks in order to identify and prioritize altered pathways which may or may not be differentially regulated. We have developed Altered Pathway Analyzer (APA), a microarray dataset analysis tool for identification and prioritization of altered pathways, including those which are differentially regulated by TFs, by quantifying rewired sub-network topology. Moreover, APA also helps in re-prioritization of APA shortlisted altered pathways enriched with context-specific genes. We performed APA analysis of simulated datasets and p53 status NCI-60 cell line microarray data to demonstrate potential of APA for identification of several case-specific altered pathways. APA analysis reveals several altered pathways not detected by other tools evaluated by us. APA analysis of unrelated prostate cancer datasets identifies sample-specific as well as conserved altered biological processes, mainly associated with lipid metabolism, cellular differentiation and proliferation. APA is designed as a cross platform tool which may be transparently customized to perform pathway analysis in different gene expression datasets. APA is freely available at http://bioinfo.icgeb.res.in/APA. PMID:28084397

  16. Expanding the Interactome of the Noncanonical NF-κB Signaling Pathway.

    Science.gov (United States)

    Willmann, Katharina L; Sacco, Roberto; Martins, Rui; Garncarz, Wojciech; Krolo, Ana; Knapp, Sylvia; Bennett, Keiryn L; Boztug, Kaan

    2016-09-02

    NF-κB signaling is a central pathway of immunity and integrates signal transduction upon a wide array of inflammatory stimuli. Noncanonical NF-κB signaling is activated by a small subset of TNF family receptors and characterized by NF-κB2/p52 transcriptional activity. The medical relevance of this pathway has recently re-emerged from the discovery of primary immunodeficiency patients that have loss-of-function mutations in the MAP3K14 gene encoding NIK. Nevertheless, knowledge of protein interactions that regulate noncanonical NF-κB signaling is sparse. Here we report a detailed state-of-the-art mass spectrometry-based protein-protein interaction network including the noncanonical NF-κB signaling nodes TRAF2, TRAF3, IKKα, NIK, and NF-κB2/p100. The value of the data set was confirmed by the identification of interactions already known to regulate this pathway. In addition, a remarkable number of novel interactors were identified. We provide validation of the novel NIK and IKKα interactor FKBP8, which may regulate processes downstream of noncanonical NF-κB signaling. To understand perturbed noncanonical NF-κB signaling in the context of misregulated NIK in disease, we also provide a differential interactome of NIK mutants that cause immunodeficiency. Altogether, this data set not only provides critical insight into how protein-protein interactions can regulate immune signaling but also offers a novel resource on noncanonical NF-κB signaling.

  17. M-Finder: Uncovering functionally associated proteins from interactome data integrated with GO annotations

    Science.gov (United States)

    2013-01-01

    Background Protein-protein interactions (PPIs) play a key role in understanding the mechanisms of cellular processes. The availability of interactome data has catalyzed the development of computational approaches to elucidate functional behaviors of proteins on a system level. Gene Ontology (GO) and its annotations are a significant resource for functional characterization of proteins. Because of wide coverage, GO data have often been adopted as a benchmark for protein function prediction on the genomic scale. Results We propose a computational approach, called M-Finder, for functional association pattern mining. This method employs semantic analytics to integrate the genome-wide PPIs with GO data. We also introduce an interactive web application tool that visualizes a functional association network linked to a protein specified by a user. The proposed approach comprises two major components. First, the PPIs that have been generated by high-throughput methods are weighted in terms of their functional consistency using GO and its annotations. We assess two advanced semantic similarity metrics which quantify the functional association level of each interacting protein pair. We demonstrate that these measures outperform the other existing methods by evaluating their agreement to other biological features, such as sequence similarity, the presence of common Pfam domains, and core PPIs. Second, the information flow-based algorithm is employed to discover a set of proteins functionally associated with the protein in a query and their links efficiently. This algorithm reconstructs a functional association network of the query protein. The output network size can be flexibly determined by parameters. Conclusions M-Finder provides a useful framework to investigate functional association patterns with any protein. This software will also allow users to perform further systematic analysis of a set of proteins for any specific function. It is available online at http

  18. Sub-terahertz spectroscopy of magnetic resonance in BiFeO3 using a vector network analyzer

    Science.gov (United States)

    Caspers, Christian; Gandhi, Varun P.; Magrez, Arnaud; de Rijk, Emile; Ansermet, Jean-Philippe

    2016-06-01

    Detection of sub-THz spin cycloid resonances (SCRs) of stoichiometric BiFeO3 (BFO) was demonstrated using a vector network analyzer. Continuous wave absorption spectroscopy is possible, thanks to heterodyning and electronic sweep control using frequency extenders for frequencies from 480 to 760 GHz. High frequency resolution reveals SCR absorption peaks with a frequency precision in the ppm regime. Three distinct SCR features of BFO were observed and identified as Ψ1 and Φ2 modes, which are out-of-plane and in-plane modes of the spin cycloid, respectively. A spin reorientation transition at 200 K is evident in the frequency vs temperature study. The global minimum in linewidth for both Ψ modes at 140 K is ascribed to the critical slowing down of spin fluctuations.

  19. The interactome of Streptococcus pneumoniae and its bacteriophages show highly specific patterns of interactions among bacteria and their phages.

    Science.gov (United States)

    Mariano, Rachelle; Wuchty, Stefan; Vizoso-Pinto, Maria G; Häuser, Roman; Uetz, Peter

    2016-04-22

    Although an abundance of bacteriophages exists, little is known about interactions between their proteins and those of their bacterial hosts. Here, we experimentally determined the phage-host interactomes of the phages Dp-1 and Cp-1 and their underlying protein interaction network in the host Streptococcus pneumoniae. We compared our results to the interaction patterns of E. coli phages lambda and T7. Dp-1 and Cp-1 target highly connected host proteins, occupy central network positions, and reach many protein clusters through the interactions of their targets. In turn, lambda and T7 targets cluster to conserved and essential proteins in E. coli, while such patterns were largely absent in S. pneumoniae. Furthermore, targets in E. coli were mutually strongly intertwined, while targets of Dp-1 and Cp-1 were strongly connected through essential and orthologous proteins in their immediate network vicinity. In both phage-host systems, the impact of phages on their protein targets appears to extend from their network neighbors, since proteins that interact with phage targets were located in central network positions, have a strong topologically disruptive effect and touch complexes with high functional heterogeneity. Such observations suggest that the phages, biological impact is accomplished through a surprisingly limited topological reach of their targets.

  20. Characterization and interactome study of white spot syndrome virus envelope protein VP11.

    Directory of Open Access Journals (Sweden)

    Wang-Jing Liu

    Full Text Available White spot syndrome virus (WSSV is a large enveloped virus. The WSSV viral particle consists of three structural layers that surround its core DNA: an outer envelope, a tegument and a nucleocapsid. Here we characterize the WSSV structural protein VP11 (WSSV394, GenBank accession number AF440570, and use an interactome approach to analyze the possible associations between this protein and an array of other WSSV and host proteins. Temporal transcription analysis showed that vp11 is an early gene. Western blot hybridization of the intact viral particles and fractionation of the viral components, and immunoelectron microscopy showed that VP11 is an envelope protein. Membrane topology software predicted VP11 to be a type of transmembrane protein with a highly hydrophobic transmembrane domain at its N-terminal. Based on an immunofluorescence assay performed on VP11-transfected Sf9 cells and a trypsin digestion analysis of the virion, we conclude that, contrary to topology software prediction, the C-terminal of this protein is in fact inside the virion. Yeast two-hybrid screening combined with co-immunoprecipitation assays found that VP11 directly interacted with at least 12 other WSSV structural proteins as well as itself. An oligomerization assay further showed that VP11 could form dimers. VP11 is also the first reported WSSV structural protein to interact with the major nucleocapsid protein VP664.

  1. SONAR Discovers RNA-Binding Proteins from Analysis of Large-Scale Protein-Protein Interactomes.

    Science.gov (United States)

    Brannan, Kristopher W; Jin, Wenhao; Huelga, Stephanie C; Banks, Charles A S; Gilmore, Joshua M; Florens, Laurence; Washburn, Michael P; Van Nostrand, Eric L; Pratt, Gabriel A; Schwinn, Marie K; Daniels, Danette L; Yeo, Gene W

    2016-10-20

    RNA metabolism is controlled by an expanding, yet incomplete, catalog of RNA-binding proteins (RBPs), many of which lack characterized RNA binding domains. Approaches to expand the RBP repertoire to discover non-canonical RBPs are currently needed. Here, HaloTag fusion pull down of 12 nuclear and cytoplasmic RBPs followed by quantitative mass spectrometry (MS) demonstrates that proteins interacting with multiple RBPs in an RNA-dependent manner are enriched for RBPs. This motivated SONAR, a computational approach that predicts RNA binding activity by analyzing large-scale affinity precipitation-MS protein-protein interactomes. Without relying on sequence or structure information, SONAR identifies 1,923 human, 489 fly, and 745 yeast RBPs, including over 100 human candidate RBPs that contain zinc finger domains. Enhanced CLIP confirms RNA binding activity and identifies transcriptome-wide RNA binding sites for SONAR-predicted RBPs, revealing unexpected RNA binding activity for disease-relevant proteins and DNA binding proteins.

  2. Characterization and interactome study of white spot syndrome virus envelope protein VP11.

    Science.gov (United States)

    Liu, Wang-Jing; Shiung, Hui-Jui; Lo, Chu-Fang; Leu, Jiann-Horng; Lai, Ying-Jang; Lee, Tai-Lin; Huang, Wei-Tung; Kou, Guang-Hsiung; Chang, Yun-Shiang

    2014-01-01

    White spot syndrome virus (WSSV) is a large enveloped virus. The WSSV viral particle consists of three structural layers that surround its core DNA: an outer envelope, a tegument and a nucleocapsid. Here we characterize the WSSV structural protein VP11 (WSSV394, GenBank accession number AF440570), and use an interactome approach to analyze the possible associations between this protein and an array of other WSSV and host proteins. Temporal transcription analysis showed that vp11 is an early gene. Western blot hybridization of the intact viral particles and fractionation of the viral components, and immunoelectron microscopy showed that VP11 is an envelope protein. Membrane topology software predicted VP11 to be a type of transmembrane protein with a highly hydrophobic transmembrane domain at its N-terminal. Based on an immunofluorescence assay performed on VP11-transfected Sf9 cells and a trypsin digestion analysis of the virion, we conclude that, contrary to topology software prediction, the C-terminal of this protein is in fact inside the virion. Yeast two-hybrid screening combined with co-immunoprecipitation assays found that VP11 directly interacted with at least 12 other WSSV structural proteins as well as itself. An oligomerization assay further showed that VP11 could form dimers. VP11 is also the first reported WSSV structural protein to interact with the major nucleocapsid protein VP664.

  3. Network Stack Analyzing and Protocol Add Technology in Linux%Linux网络协议栈分析及协议添加的实现

    Institute of Scientific and Technical Information of China (English)

    唐续; 刘心松; 杨峰

    2003-01-01

    In order to improve the performance of Linux network,new protocols should be implemented and added in original protocol stack. For this demand,this paper has analyzed Linux network stack architecture and implement technology,then presented a method that appended new protocols in the network stack of Linux. The processes of protocol register ,protocol operation,protocol header implement,packets receiving, user interface are involved in this method.

  4. Monitoring biomedical literature for post-market safety purposes by analyzing networks of text-based coded information.

    Science.gov (United States)

    Botsis, Taxiarchis; Foster, Matthew; Kreimeyer, Kory; Pandey, Abhishek; Forshee, Richard

    2017-01-01

    Literature review is critical but time-consuming in the post-market surveillance of medical products. We focused on the safety signal of intussusception after the vaccination of infants with the Rotashield Vaccine in 1999 and retrieved all PubMed abstracts for rotavirus vaccines published after January 1, 1998. We used the Event-based Text-mining of Health Electronic Records system, the MetaMap tool, and the National Center for Biomedical Ontologies Annotator to process the abstracts and generate coded terms stamped with the date of publication. Data were analyzed in the Pattern-based and Advanced Network Analyzer for Clinical Evaluation and Assessment to evaluate the intussusception-related findings before and after the release of the new rotavirus vaccines in 2006. The tight connection of intussusception with the historical signal in the first period and the absence of any safety concern for the new vaccines in the second period were verified. We demonstrated the feasibility for semi-automated solutions that may assist medical reviewers in monitoring biomedical literature.

  5. Evidence That a Psychopathology Interactome Has Diagnostic Value, Predicting Clinical Needs: An Experience Sampling Study

    Science.gov (United States)

    van Os, Jim; Lataster, Tineke; Delespaul, Philippe; Wichers, Marieke; Myin-Germeys, Inez

    2014-01-01

    Background For the purpose of diagnosis, psychopathology can be represented as categories of mental disorder, symptom dimensions or symptom networks. Also, psychopathology can be assessed at different levels of temporal resolution (monthly episodes, daily fluctuating symptoms, momentary fluctuating mental states). We tested the diagnostic value, in terms of prediction of treatment needs, of the combination of symptom networks and momentary assessment level. Method Fifty-seven patients with a psychotic disorder participated in an ESM study, capturing psychotic experiences, emotions and circumstances at 10 semi-random moments in the flow of daily life over a period of 6 days. Symptoms were assessed by interview with the Positive and Negative Syndrome Scale (PANSS); treatment needs were assessed using the Camberwell Assessment of Need (CAN). Results Psychotic symptoms assessed with the PANSS (Clinical Psychotic Symptoms) were strongly associated with psychotic experiences assessed with ESM (Momentary Psychotic Experiences). However, the degree to which Momentary Psychotic Experiences manifested as Clinical Psychotic Symptoms was determined by level of momentary negative affect (higher levels increasing probability of Momentary Psychotic Experiences manifesting as Clinical Psychotic Symptoms), momentary positive affect (higher levels decreasing probability of Clinical Psychotic Symptoms), greater persistence of Momentary Psychotic Experiences (persistence predicting increased probability of Clinical Psychotic Symptoms) and momentary environmental stress associated with events and activities (higher levels increasing probability of Clinical Psychotic Symptoms). Similarly, the degree to which momentary visual or auditory hallucinations manifested as Clinical Psychotic Symptoms was strongly contingent on the level of accompanying momentary paranoid delusional ideation. Momentary Psychotic Experiences were associated with CAN unmet treatment needs, over and above PANSS

  6. GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

    Directory of Open Access Journals (Sweden)

    S M Hadi Hosseini

    Full Text Available In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC and functional data analyses (FDA, in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL and healthy matched Controls (CON. The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

  7. Synaptic Interactome Mining Reveals p140Cap as a New Hub for PSD Proteins Involved in Psychiatric and Neurological Disorders

    Science.gov (United States)

    Alfieri, Annalisa; Sorokina, Oksana; Adrait, Annie; Angelini, Costanza; Russo, Isabella; Morellato, Alessandro; Matteoli, Michela; Menna, Elisabetta; Boeri Erba, Elisabetta; McLean, Colin; Armstrong, J. Douglas; Ala, Ugo; Buxbaum, Joseph D.; Brusco, Alfredo; Couté, Yohann; De Rubeis, Silvia; Turco, Emilia; Defilippi, Paola

    2017-01-01

    Altered synaptic function has been associated with neurological and psychiatric conditions including intellectual disability, schizophrenia and autism spectrum disorder (ASD). Amongst the recently discovered synaptic proteins is p140Cap, an adaptor that localizes at dendritic spines and regulates their maturation and physiology. We recently showed that p140Cap knockout mice have cognitive deficits, impaired long-term potentiation (LTP) and long-term depression (LTD), and immature, filopodia-like dendritic spines. Only a few p140Cap interacting proteins have been identified in the brain and the molecular complexes and pathways underlying p140Cap synaptic function are largely unknown. Here, we isolated and characterized the p140Cap synaptic interactome by co-immunoprecipitation from crude mouse synaptosomes, followed by mass spectrometry-based proteomics. We identified 351 p140Cap interactors and found that they cluster to sub complexes mostly located in the postsynaptic density (PSD). p140Cap interactors converge on key synaptic processes, including transmission across chemical synapses, actin cytoskeleton remodeling and cell-cell junction organization. Gene co-expression data further support convergent functions: the p140Cap interactors are tightly co-expressed with each other and with p140Cap. Importantly, the p140Cap interactome and its co-expression network show strong enrichment in genes associated with schizophrenia, autism, bipolar disorder, intellectual disability and epilepsy, supporting synaptic dysfunction as a shared biological feature in brain diseases. Overall, our data provide novel insights into the molecular organization of the synapse and indicate that p140Cap acts as a hub for postsynaptic complexes relevant to psychiatric and neurological disorders. PMID:28713243

  8. Notch3 interactome analysis identified WWP2 as a negative regulator of Notch3 signaling in ovarian cancer.

    Directory of Open Access Journals (Sweden)

    Jin-Gyoung Jung

    2014-10-01

    Full Text Available The Notch3 signaling pathway is thought to play a critical role in cancer development, as evidenced by the Notch3 amplification and rearrangement observed in human cancers. However, the molecular mechanism by which Notch3 signaling contributes to tumorigenesis is largely unknown. In an effort to identify the molecular modulators of the Notch3 signaling pathway, we screened for Notch3-intracellular domain (N3-ICD interacting proteins using a human proteome microarray. Pathway analysis of the Notch3 interactome demonstrated that ubiquitin C was the molecular hub of the top functional network, suggesting the involvement of ubiquitination in modulating Notch3 signaling. Thereby, we focused on functional characterization of an E3 ubiquitin-protein ligase, WWP2, a top candidate in the Notch3 interactome list. Co-immunoprecipitation experiments showed that WWP2 interacted with N3-ICD but not with intracellular domains from other Notch receptors. Wild-type WWP2 but not ligase-deficient mutant WWP2 increases mono-ubiquitination of the membrane-tethered Notch3 fragment, therefore attenuating Notch3 pathway activity in cancer cells and leading to cell cycle arrest. The mono-ubiquitination by WWP2 may target an endosomal/lysosomal degradation fate for Notch3 as suggested by the fact that the process could be suppressed by the endosomal/lysosomal inhibitor. Analysis of The Cancer Genome Atlas dataset showed that the majority of ovarian carcinomas harbored homozygous or heterozygous deletions in WWP2 locus, and there was an inverse correlation in the expression levels between WWP2 and Notch3 in ovarian carcinomas. Furthermore, ectopic expression of WWP2 decreased tumor development in a mouse xenograft model and suppressed the Notch3-induced phenotypes including increase in cancer stem cell-like cell population and platinum resistance. Taken together, our results provide evidence that WWP2 serves as a tumor suppressor by negatively regulating Notch3 signaling

  9. Current Approaches Toward Quantitative Mapping of the Interactome.

    Science.gov (United States)

    Buntru, Alexander; Trepte, Philipp; Klockmeier, Konrad; Schnoegl, Sigrid; Wanker, Erich E

    2016-01-01

    Protein-protein interactions (PPIs) play a key role in many, if not all, cellular processes. Disease is often caused by perturbation of PPIs, as recently indicated by studies of missense mutations. To understand the associations of proteins and to unravel the global picture of PPIs in the cell, different experimental detection techniques for PPIs have been established. Genetic and biochemical methods such as the yeast two-hybrid system or affinity purification-based approaches are well suited to high-throughput, proteome-wide screening and are mainly used to obtain qualitative results. However, they have been criticized for not reflecting the cellular situation or the dynamic nature of PPIs. In this review, we provide an overview of various genetic methods that go beyond qualitative detection and allow quantitative measuring of PPIs in mammalian cells, such as dual luminescence-based co-immunoprecipitation, Förster resonance energy transfer or luminescence-based mammalian interactome mapping with bait control. We discuss the strengths and weaknesses of different techniques and their potential applications in biomedical research.

  10. Interactomic and pharmacological insights on human sirt-1.

    Science.gov (United States)

    Sharma, Ankush; Gautam, Vasu; Costantini, Susan; Paladino, Antonella; Colonna, Giovanni

    2012-01-01

    Sirt-1 is defined as a nuclear protein involved in the molecular mechanisms of inflammation and neurodegeneration through the de-acetylation of many different substrates even if experimental data in mouse suggest both its cytoplasmatic presence and nucleo-cytoplasmic shuttling upon oxidative stress. Since the experimental structure of human Sirt-1 has not yet been reported, we have modeled its 3D structure, highlighted that it is composed by four different structural regions: N-terminal region, allosteric site, catalytic core and C-terminal region, and underlined that the two terminal regions have high intrinsic disorder propensity and numerous putative phosphorylation sites. Many different papers report experimental studies related to its functional activators because Sirt-1 is implicated in various diseases and cancers. The aim of this article is (i) to present interactomic studies based human Sirt-1 to understand its most important functional relationships in the light of the gene-protein interactions that control major metabolic pathways and (ii) to show by docking studies how this protein binds some activator molecules in order to evidence structural determinants, physico-chemical features and those residues involved in the formation of complexes.

  11. Interactomic and pharmacological insights on human Sirt-1

    Directory of Open Access Journals (Sweden)

    Ankush eSharma

    2012-03-01

    Full Text Available Sirtuin family, in humans as well as in all mammalia, is composed by seven different homologous proteins with NAD-dependent deacetylase/ADP-ribosyltransferase activity. Numerous studies have determined their cellular location and their biological functions. In particular, Sirt-1 is defined as a nuclear protein involved in the molecular mechanisms of inflammation and neurodegeneration through the de-acetylation of many different substrates (PGC-α, FOXOs, NFκB. However experimental data in mouse suggest both its cytoplasmatic presence and nucleo-cytoplasmic shuttling upon oxidative stress. Recently we have modeled the three-dimensional structure of human Sirt-1, and highlighted that it is composed by four different regions: N-terminal region, allosteric site, catalytic core and C-terminal region and underlined that the two terminal regions have high intrinsic disorder propensity. Since Sirt-1 is implicated in various diseases and cancers, many different papers report experimental studies related to its functional activators. The aim of this article is i to present interactomic studies on human SIRT-1 to understand its most important functional relationships in the light of the gene-protein interactions that control major metabolic pathways and ii to show how this protein binds some activator molecules in order to evidence structural determinants, physico-chemical features and those residues involved in the formation of complexes. It is believed that these data will be useful to synthesize new effectors through drug design approaches.

  12. Proteomic Analysis of the Mediator Complex Interactome in Saccharomyces cerevisiae

    Science.gov (United States)

    Uthe, Henriette; Vanselow, Jens T.; Schlosser, Andreas

    2017-01-01

    Here we present the most comprehensive analysis of the yeast Mediator complex interactome to date. Particularly gentle cell lysis and co-immunopurification conditions allowed us to preserve even transient protein-protein interactions and to comprehensively probe the molecular environment of the Mediator complex in the cell. Metabolic 15N-labeling thereby enabled stringent discrimination between bona fide interaction partners and nonspecifically captured proteins. Our data indicates a functional role for Mediator beyond transcription initiation. We identified a large number of Mediator-interacting proteins and protein complexes, such as RNA polymerase II, general transcription factors, a large number of transcriptional activators, the SAGA complex, chromatin remodeling complexes, histone chaperones, highly acetylated histones, as well as proteins playing a role in co-transcriptional processes, such as splicing, mRNA decapping and mRNA decay. Moreover, our data provides clear evidence, that the Mediator complex interacts not only with RNA polymerase II, but also with RNA polymerases I and III, and indicates a functional role of the Mediator complex in rRNA processing and ribosome biogenesis. PMID:28240253

  13. Enhancing and Analyzing Search performance in Unstructured Peer to Peer Networks Using Enhanced Guided search protocol (EGSP)

    CERN Document Server

    Anusuya, R; Julie, E Golden

    2010-01-01

    Peer-to-peer (P2P) networks establish loosely coupled application-level overlays on top of the Internet to facilitate efficient sharing of resources. It can be roughly classified as either structured or unstructured networks. Without stringent constraints over the network topology, unstructured P2P networks can be constructed very efficiently and are therefore considered suitable to the Internet environment. However, the random search strategies adopted by these networks usually perform poorly with a large network size. To enhance the search performance in unstructured P2P networks through exploiting users' common interest patterns captured within a probability-theoretic framework termed the user interest model (UIM). A search protocol and a routing table updating protocol are further proposed in order to expedite the search process through self organizing the P2P network into a small world. Both theoretical and experimental analyses are conducted and demonstrated the effectiveness and efficiency of the appro...

  14. RNA-Binding Proteins Revisited – The Emerging Arabidopsis mRNA Interactome

    KAUST Repository

    Köster, Tino

    2017-04-13

    RNA–protein interaction is an important checkpoint to tune gene expression at the RNA level. Global identification of proteins binding in vivo to mRNA has been possible through interactome capture – where proteins are fixed to target RNAs by UV crosslinking and purified through affinity capture of polyadenylated RNA. In Arabidopsis over 500 RNA-binding proteins (RBPs) enriched in UV-crosslinked samples have been identified. As in mammals and yeast, the mRNA interactomes came with a few surprises. For example, a plethora of the proteins caught on RNA had not previously been linked to RNA-mediated processes, for example proteins of intermediary metabolism. Thus, the studies provide unprecedented insights into the composition of the mRNA interactome, highlighting the complexity of RNA-mediated processes.

  15. A "candidate-interactome" aggregate analysis of genome-wide association data in multiple sclerosis

    DEFF Research Database (Denmark)

    Mechelli, Rosella; Umeton, Renato; Policano, Claudia

    2013-01-01

    of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge...... immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated...... emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms....

  16. Optical Vector Network Analyzer with an Improved Dynamic Range Based on a Polarization Multiplexing Electro-Optic Modulator

    Science.gov (United States)

    Wang, Qi; Wang, Wen-Ting; Chen, Wei; Liu, Jian-Guo; Zhu, Ning-Hua

    2017-05-01

    We present a new method to achieve an optical vector network analyzer (OVNA) based on a polarization multiplexing electro-optic modulator (PM-EOM) without an optical bandpass filter. Optical single sideband (OSSB) modulated signals with a tunable optical carrier-sideband ratio (OCSR) are obtained at the output of the PM-EOM. The OCSR can be flexibly tuned by controlling bias voltages of the PM-EOM. The dynamic range of the OVNA is expanded by taking the improvement of the OCSR into account. The transmission response of an optical device under test (ODUT) is measured based on one-to-one mapping from optical domain to electrical domain. By optimizing the OCSR of the OSSB modulated signals, the dynamic range of the OVNA can be effectively improved with 3.7 dB. An analytical model is derived to describe the transfer function of the ODUT. The magnitude and phase responses of a fiber Bragg grating are characterized with a large dynamic range. Supported by the National Natural Science Foundation of China under Grant Nos 61377070, 61090391 and 61675196, and the National High-Technology Research and Development Program of China under Grant No 2013AA014203.

  17. A General Bayesian Network Approach to Analyzing Online Game Item Values and Its Influence on Consumer Satisfaction and Purchase Intention

    Science.gov (United States)

    Lee, Kun Chang; Park, Bong-Won

    Many online game users purchase game items with which to play free-to-play games. Because of a lack of research into which there is no specified framework for categorizing the values of game items, this study proposes four types of online game item values based on an analysis of literature regarding online game characteristics. It then proposes to investigate how online game users perceive satisfaction and purchase intention from the proposed four types of online game item values. Though regression analysis has been used frequently to answer this kind of research question, we propose a new approach, a General Bayesian Network (GBN), which can be performed in an understandable way without sacrificing predictive accuracy. Conventional techniques, such as regression analysis, do not provide significant explanation for this kind of problem because they are fixed to a linear structure and are limited in explaining why customers are likely to purchase game items and if they are satisfied with their purchases. In contrast, the proposed GBN provides a flexible underlying structure based on questionnaire survey data and offers robust decision support on this kind of research question by identifying its causal relationships. To illustrate the validity of GBN in solving the research question in this study, 327 valid questionnaires were analyzed using GBN with what-if and goal-seeking approaches. The experimental results were promising and meaningful in comparison with regression analysis results.

  18. Heterogeneous interactome between Litopenaeus vannamei plasma proteins and Vibrio parahaemolyticus outer membrane proteins.

    Science.gov (United States)

    Liu, Xiang; She, Xin-Tao; Zhu, Qing-Feng; Li, Hui; Peng, Xuan-Xian

    2013-01-01

    A great loss has been suffered by microbial infectious diseases under intensive shrimp farming in recent years. In this background, the understanding of shrimp innate immunity becomes an importantly scientific issue, but little is known about the heterogeneous protein-protein interaction between pathogenic cells and hosts, which is a key step for the invading microbes to infect internet organs through bloodstream. In the present study, bacterial outer membrane (OM) protein array and pull-down approaches are used to isolate both Vibrio parahaemolyticus OM proteins that bind to shrimp serum proteins and the shrimp serum proteins that interact with bacterial cells, respectively. Three interacting shrimp serum proteins, hemocyanin, β-1,3-glucan binding protein and LV_HP_RA36F08r and thirty interacting OM proteins were determined. They form 63 heterogeneous protein-protein interactions. Nine out of the 30 OM proteins were randomly demonstrated to be up-regulated or down-regulated when bacterial cells were cultured with shrimp sera, indicating the biological significance of the network. The interesting findings uncover the complexity of struggle between host immunity and bacterial infection. Compared with our previous report on heterogeneous interactome between fish grill and bacterial OM proteins, the present study further extends the investigation from lower vertebrates to invertebrates and develops a bacterial OM protein array to identify the OM proteins bound with shrimp serum proteins, which elevates the frequencies of the bound OM proteins. Our results highlight the way to determine and understand the heterogeneous interaction between hosts and microbes.

  19. An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis.

    Science.gov (United States)

    Vashisht, Shikha; Bagler, Ganesh

    2012-01-01

    Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC) is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.

  20. An approach for the identification of targets specific to bone metastasis using cancer genes interactome and gene ontology analysis.

    Directory of Open Access Journals (Sweden)

    Shikha Vashisht

    Full Text Available Metastasis is one of the most enigmatic aspects of cancer pathogenesis and is a major cause of cancer-associated mortality. Secondary bone cancer (SBC is a complex disease caused by metastasis of tumor cells from their primary site and is characterized by intricate interplay of molecular interactions. Identification of targets for multifactorial diseases such as SBC, the most frequent complication of breast and prostate cancers, is a challenge. Towards achieving our aim of identification of targets specific to SBC, we constructed a 'Cancer Genes Network', a representative protein interactome of cancer genes. Using graph theoretical methods, we obtained a set of key genes that are relevant for generic mechanisms of cancers and have a role in biological essentiality. We also compiled a curated dataset of 391 SBC genes from published literature which serves as a basis of ontological correlates of secondary bone cancer. Building on these results, we implement a strategy based on generic cancer genes, SBC genes and gene ontology enrichment method, to obtain a set of targets that are specific to bone metastasis. Through this study, we present an approach for probing one of the major complications in cancers, namely, metastasis. The results on genes that play generic roles in cancer phenotype, obtained by network analysis of 'Cancer Genes Network', have broader implications in understanding the role of molecular regulators in mechanisms of cancers. Specifically, our study provides a set of potential targets that are of ontological and regulatory relevance to secondary bone cancer.

  1. Who do you know? Developing and Analyzing Entrepreneur Networks: An Analysis of the Tech Entrepreneurial Environment of Six African Cities

    Science.gov (United States)

    2015-01-01

    2013, 2014, 2015) Greve, A. and Salaff, J. W. (2003), Social Networks and Entrepreneurship . Entrepreneurship Theory and Practice, 28: 1–22. doi...8. Religious Leader- A local minister or other religious member who can assist with access to the required resource. 9. Someone in Social Network...Someone beyond an immediate family member, in network of friends, or a connection on social media who can assist with access to the required

  2. Who Do You Know? Developing and Analyzing Entrepreneur Networks: Data Collection in the Tech Entrepreneurial Environment of Six African Cities

    Science.gov (United States)

    2015-01-01

    Social Networks and Entrepreneurship . Entrepreneurship Theory and Practice, 28: 1–22. doi: 10.1111/1540-8520.00029... Social capital: Advances in research, Oxford University Press (2008). Witt, P. (2004) Entrepreneurs’ networks and the success of start-ups. Entrepreneurship and Regional Development. 16:391–412. ...accurately measure social capital and circumvents the massive effort of mapping an individual’s social network before locating the social resources in

  3. Dissection of protein interactomics highlights microRNA synergy.

    Directory of Open Access Journals (Sweden)

    Wenliang Zhu

    Full Text Available Despite a large amount of microRNAs (miRNAs have been validated to play crucial roles in human biology and disease, there is little systematic insight into the nature and scale of the potential synergistic interactions executed by miRNAs themselves. Here we established an integrated parameter synergy score to determine miRNA synergy, by combining the two mechanisms for miRNA-miRNA interactions, miRNA-mediated gene co-regulation and functional association between target gene products, into one single parameter. Receiver operating characteristic (ROC analysis indicated that synergy score accurately identified the gene ontology-defined miRNA synergy (AUC = 0.9415, p<0.001. Only a very small portion of the random miRNA-miRNA combinations generated potent synergy, implying poor expectancy of widespread synergy. However, targeting more key genes made two miRNAs more likely to act synergistically. Compared to other miRNAs, miR-21 was a highly exceptional case due to frequent appearance in the top synergistic miRNA pairs. This result highlighted its essential role in coordinating or strengthening physiological and pathological functions of other miRNAs. The synergistic effect of miR-21 and miR-1 were functionally validated for their significant influences on myocardial apoptosis, cardiac hypertrophy and fibrosis. The novel approach established in this study enables easy and effective identification of condition-restricted potent miRNA synergy simply by concentrating the available protein interactomics and miRNA-target interaction data into a single parameter synergy score. Our results may be important for understanding synergistic gene regulation by miRNAs and may have significant implications for miRNA combination therapy of cardiovascular disease.

  4. Properties of grain boundary networks in the NEEM ice core analyzed by combined transmission and reflection optical microscopy

    Science.gov (United States)

    Binder, Tobias; Weikusat, Ilka; Garbe, Christoph; Svensson, Anders; Kipfstuhl, Sepp

    2014-05-01

    Microstructure analysis of ice cores is vital to understand the processes controlling the flow of ice on the microscale. To quantify the microstructural variability (and thus occurring processes) on centimeter, meter and kilometer scale along deep polar ice cores, a large number of sections has to be analyzed. In the last decade, two different methods have been applied: On the one hand, transmission optical microscopy of thin sections between crossed polarizers yields information on the distribution of crystal c-axes. On the other hand, reflection optical microscopy of polished and controlled sublimated section surfaces allows to characterize the high resolution properties of a single grain boundary, e.g. its length, shape or curvature (further developed by [1]). Along the entire NEEM ice core (North-West Greenland, 2537 m length) drilled in 2008-2011 we applied both methods to the same set of vertical sections. The data set comprises series of six consecutive 6 x 9 cm2 sections in steps of 20 m - in total about 800 images. A dedicated method for automatic processing and matching both image types has recently been developed [2]. The high resolution properties of the grain boundary network are analyzed. Furthermore, the automatic assignment of c-axis misorientations to visible sublimation grooves enables us to quantify the degree of similarity between the microstructure revealed by both analysis techniques. The reliability to extract grain boundaries from both image types as well as the appearance of sublimation groove patterns exhibiting low misorientations is investigated. X-ray Laue diffraction measurements (yielding full crystallographic orientation) have validated the sensitivity of the surface sublimation method for sub-grain boundaries [3]. We introduce an approach for automatic extraction of sub-grain structures from sublimation grooves. A systematic analysis of sub-grain boundary densities indicates a possible influence of high impurity contents (amongst

  5. Utilizing Social Networks in Times of Crisis: Understanding, Exploring and Analyzing Critical Incident Management at Institutions of Higher Education

    Science.gov (United States)

    Asselin, Martha Jo

    2012-01-01

    With the rising number of major crises on college campuses today (Security on Campus Inc., 2009), institutions of higher education can benefit from understanding of how social networks may be used in times of emergency. What is currently known about the usage of social networks is not integral to the current practices of crisis management that are…

  6. Analyzing Video Streaming Quality by Using Various Error Correction Methods on Mobile Ad hoc Networks in NS2

    Directory of Open Access Journals (Sweden)

    Norrozila Sulaiman

    2014-10-01

    Full Text Available Transmission video over ad hoc networks has become one of the most important and interesting subjects of study for researchers and programmers because of the strong relationship between video applications and frequent users of various mobile devices, such as laptops, PDAs, and mobile phones in all aspects of life. However, many challenges, such as packet loss, congestion (i.e., impairments at the network layer, multipath fading (i.e., impairments at the physical layer [1], and link failure, exist in transferring video over ad hoc networks; these challenges negatively affect the quality of the perceived video [2].This study has investigated video transfer over ad hoc networks. The main challenges of transferring video over ad hoc networks as well as types of errors that may occur during video transmission, various types of video mechanisms, error correction methods, and different Quality of Service (QoS parameters that affect the quality of the received video are also investigated.

  7. ∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis.

    Science.gov (United States)

    Pankow, Sandra; Bamberger, Casimir; Calzolari, Diego; Martínez-Bartolomé, Salvador; Lavallée-Adam, Mathieu; Balch, William E; Yates, John R

    2015-12-24

    Deletion of phenylalanine 508 of the cystic fibrosis transmembrane conductance regulator (∆F508 CFTR) is the major cause of cystic fibrosis, one of the most common inherited childhood diseases. The mutated CFTR anion channel is not fully glycosylated and shows minimal activity in bronchial epithelial cells of patients with cystic fibrosis. Low temperature or inhibition of histone deacetylases can partly rescue ∆F508 CFTR cellular processing defects and function. A favourable change of ∆F508 CFTR protein-protein interactions was proposed as a mechanism of rescue; however, CFTR interactome dynamics during temperature shift and inhibition of histone deacetylases are unknown. Here we report the first comprehensive analysis of the CFTR and ∆F508 CFTR interactome and its dynamics during temperature shift and inhibition of histone deacetylases. By using a novel deep proteomic analysis method, we identify 638 individual high-confidence CFTR interactors and discover a ∆F508 deletion-specific interactome, which is extensively remodelled upon rescue. Detailed analysis of the interactome remodelling identifies key novel interactors, whose loss promote ∆F508 CFTR channel function in primary cystic fibrosis epithelia or which are critical for CFTR biogenesis. Our results demonstrate that global remodelling of ∆F508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of cystic fibrosis caused by deletion of F508.

  8. Magnetostatics and dynamics of ion irradiatied NiFe/Ta multilayer films studied by vector network analyzer ferromagnetic resonance

    Energy Technology Data Exchange (ETDEWEB)

    Marko, Daniel

    2010-11-25

    In the present work, the implications of ion irradiation on the magnetostatic and dynamic properties of soft magnetic Py/Ta (Py=Permalloy: Ni{sub 80}Fe{sub 20}) single and multilayer films have been investigated with the main objective of finding a way to determine their saturation magnetization. Both polar magneto-optical Kerr effect (MOKE) and vector network analyzer ferromagnetic resonance (VNA-FMR) measurements have proven to be suitable methods to determine {mu}{sub 0}M{sub S}, circumventing the problem of the unknown effective magnetic volume that causes conventional techniques such as SQUID or VSM to fail. Provided there is no perpendicular anisotropy contribution in the samples, the saturation magnetization can be determined even in the case of strong interfacial mixing due to an inherently high number of Py/Ta interfaces and/or ion irradiation with high fluences. Another integral part of this work has been to construct a VNA-FMR spectrometer capable of performing both azimuthal and polar angle-dependent measurements using a magnet strong enough to saturate samples containing iron. Starting from scratch, this comprised numerous steps such as developing a suitable coplanar waveguide design, and writing the control, evaluation, and fitting software. With both increasing ion fluence and number of Py/Ta interfaces, a decrease of saturation magnetization has been observed. In the case of the 10 x Py samples, an immediate decrease of {mu}{sub 0}M{sub S} already sets in at small ion fluences. However, for the 1 x Py and 5 x Py samples, the saturation magnetization remains constant up to a certain ion fluence, but then starts to rapidly decrease. Ne ion irradiation causes a mixing and broadening of the interfaces. Thus, the Py/Ta stacks undergo a transition from being polycrystalline to amorphous at a critical fluence depending on the number of interfaces. The saturation magnetization is found to vanish at a Ta concentration of about 10-15 at.% in the Py layers

  9. Letting the managers manage: analyzing capacity to conserve biodiversity in a cross-border protected area network

    Directory of Open Access Journals (Sweden)

    Sarah Clement

    2016-09-01

    Full Text Available Biodiversity loss is one of the most significant drivers of ecosystem change and is projected to continue at a rapid rate. While protected areas, such as national parks, are seen as important refuges for biodiversity, their effectiveness in stemming biodiversity decline has been questioned. Public agencies have a critical role in the governance of many such areas, but there are tensions between the need for these agencies to be more "adaptive" and their current operating environment. Our aim is to analyze how institutions enable or constrain capacity to conserve biodiversity in a globally significant cross-border network of protected areas, the Australian Alps. Using a novel conceptual framework for diagnosing biodiversity institutions, our research examined institutional adaptive capacity and more general capacity for conserving biodiversity. Several intertwined issues limit public agencies' capacity to fulfill their conservation responsibilities. Narrowly defined accountability measures constrain adaptive capacity and divert attention away from addressing key biodiversity outcomes. Implications for learning were also evident, with protected area agencies demonstrating successful learning for on-ground issues but less success in applying this learning to deeper policy change. Poor capacity to buffer political and community influences in managing significant cross-border drivers of biodiversity decline signals poor fit with the institutional context and has implications for functional fit. While cooperative federalism provides potential benefits for buffering through diversity, it also means protected area agencies have restricted authority to address cross-border threats. Restrictions on staff authority and discretion, as public servants, have further implications for deploying capacity. This analysis, particularly the possibility of fostering "ambidexterity" - creatively responding to political pressures in a way that also achieves a desirable

  10. Analyzing the role of social networks in mapping knowledge flows: A case of a pharmaceutical company in India

    Directory of Open Access Journals (Sweden)

    V. Murale

    2014-03-01

    Full Text Available Knowledge Management literature lays emphasis on the fact that a major chunk of knowledge dissemination occurs through the various forms of social networks that exist within the organizations. A social network is a simple structure comprising of set of actors or nodes that may have relationships ties with one another. The social network analysis (SNA will help in mapping and measuring formal and informal relationships to understand what facilitates or impedes the knowledge flows that bind interacting units. This paper aims at studying the knowledge flows that happen through the social networks. It first, provides a conceptual framework and review of literature on the recent research and application of knowledge mapping and SNA, followed by a discussion on application of SNA for mapping knowledge flows in a pharmaceutical firm. In the last part, Knowledge maps are presented to illustrate the actual knowledge flow in firm.

  11. Modeling and analyzing gene co-expression in hepatocellular carcinoma using actor-semiotic networks and centrality signatures.

    Science.gov (United States)

    Fung, David C Y

    2008-01-01

    Primary hepatocellular carcinoma (HCC) is currently the fifth most common malignancy and the third most common cause of cancer mortality worldwide. Because of its high prevalence in developing nations, there have been numerous efforts made in the molecular characterization of primary HCC. However, a better understanding into the pathology of HCC required software-assisted network modeling and analysis. In this paper, the author presented his first attempt in exploring the biological implication of gene co-expression in HCC using actor-semiotic network modeling and analysis. The network was first constructed by integrating inter-actor relationships, e.g. gene co-expression, microRNA-to-gene, and protein interactions, with semiotic relationships, e.g. gene-to-Gene Ontology Process. Topological features that are highly discriminative of the HCC phenotype were identified by visual inspection. Finally, the author devised a graph signature-based analysis method to supplement the network exploration.

  12. Modeling and Analyzing Gene Co-Expression in Hepatocellular Carcinoma Using Actor-Semiotic Networks and Centrality Signatures

    Directory of Open Access Journals (Sweden)

    David C.Y. Fung

    2008-01-01

    Full Text Available Primary hepatocellular carcinoma (HCC is currently the fifth most common malignancy and the third most common cause of cancer mortality worldwide. Because of its high prevalence in developing nations, there have been numerous efforts made in the molecular characterization of primary HCC. However, a better understanding into the pathology of HCC required software-assisted network modeling and analysis. In this paper, the author presented his first attempt in exploring the biological implication of gene co-expression in HCC using actor-semiotic network modeling and analysis. The network was first constructed by integrating inter-actor relationships, e.g. gene co-expression, microRNA-to-gene, and protein interactions, with semiotic relationships, e.g. gene-to-Gene Ontology Process. Topological features that are highly discriminative of the HCC phenotype were identified by visual inspection. Finally, the author devised a graph signature- based analysis method to supplement the network exploration.

  13. Who do you know? Developing and Analyzing Entrepreneur Networks: An Analysis of the Entrepreneurial Environment of Kampala, Uganda

    Science.gov (United States)

    2013-11-04

    Social Networks and Entrepreneurship . Entrepreneurship Theory and Practice, 28: 1–22. doi: 10.1111/1540-8520.00029 Lin, N. and Dumin, M. (1986...entrepreneur lives and operates. In order to develop this model, we have adapted a technique used in sociology to measure social capital called the Position...Generator (Lin & Dumin, 1986; Lin et Al, 2001). This technique circumvents the massive effort of mapping an individual’s social network before

  14. Who Do You Know? Developing and Analyzing Entrepreneur Networks: An Analysis of the Entrepreneurial Environment of Addis Ababa, Ethiopia

    Science.gov (United States)

    2013-11-01

    845.938.0804 References Greve, A., Salaff, J., 2003. Social networks and entrepreneurship . Entrepreneurship Theory and Practice 28 (1), 1–22. Lin, Nan...adapted a technique used in sociology to measure social capital called the Position Generator (Lin & Dumin, 1986; Lin et Al, 2001). This technique...circumvents the massive effort of mapping an individual’s social network before locating the social resources in it. By approaching the entrepreneur’s

  15. Analyzing Collaborative Governance Through Social Network Analysis: A Case Study of River Management Along the Waal River in The Netherlands

    Science.gov (United States)

    Fliervoet, J. M.; Geerling, G. W.; Mostert, E.; Smits, A. J. M.

    2016-02-01

    Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.

  16. Analyzing Collaborative Governance Through Social Network Analysis: A Case Study of River Management Along the Waal River in The Netherlands.

    Science.gov (United States)

    Fliervoet, J M; Geerling, G W; Mostert, E; Smits, A J M

    2016-02-01

    Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.

  17. A New Approach to Analyzing Patterns of Collaboration in Co-authorship Networks - Mesoscopic Analysis and Interpretation

    CERN Document Server

    Velden, Theresa A; Lagoze, Carl J

    2009-01-01

    This paper focuses on methods to study patterns of collaboration in co-authorship networks at the mesocopic level. We combine qualitative methods (participant interviews) with quantitative methods (network analysis) and demonstrate the value of our approach in a case study comparing three research fields in chemistry. A mesoscopic level of analysis means that in addition to the basic analytic unit of the individual researcher as node in a co-author network, we analyse the clustering of authors into groups that we interpret as basic collective units of knowledge production in a research specialty. We find a variety of structural types of these clusters that point to potential variations in the underlying social configurations and collaborative working modes of the collective units in the respective research specialties. We further identify two types of co-authorship relations between clusters of authors based on linkage patterns. One type corresponds to extensive inter-group collaboration and the other type to...

  18. M-ARRAY QUADRATURE AMPLITUDE MODULATION WIRELESS SENSOR NETWORK MODULATOR RELIABILITY AND ACCURACY ANALYZE IN CIVIL SHM

    Directory of Open Access Journals (Sweden)

    Mohammud Ershadul Haque

    2013-01-01

    Full Text Available Wireless Sensor Network (WSN is the new invention applying for assessment the damage of the historical or high rise civil building structural health. Technical challenges affecting deployment of wireless sensor network including the range of the transmission problem, low data transmission rate of the existing SHM strategies. The most vital factor of SHM wireless sensor systems is the modulator accuracy and reliability that qualify the wireless communication system to assess large building structure health Information. The objective of this article is to provide solution to measure both reliability and accuracy of the wireless sensor network modulator. we computed M-array QAM modulator BER and compare the simulation result with theoretical to find out optimum modulation technique for transmission System with considering maximum data rate, AWGN channel and also measured modulator accuracy based on ZigBee by computing M-array modulator Error Vector Magnitude (EVM to quantify the transmitter quality.

  19. Fracture network evaluation program (FraNEP): A software for analyzing 2D fracture trace-line maps

    Science.gov (United States)

    Zeeb, Conny; Gomez-Rivas, Enrique; Bons, Paul D.; Virgo, Simon; Blum, Philipp

    2013-10-01

    Fractures, such as joints, faults and veins, strongly influence the transport of fluids through rocks by either enhancing or inhibiting flow. Techniques used for the automatic detection of lineaments from satellite images and aerial photographs, LIDAR technologies and borehole televiewers significantly enhanced data acquisition. The analysis of such data is often performed manually or with different analysis software. Here we present a novel program for the analysis of 2D fracture networks called FraNEP (Fracture Network Evaluation Program). The program was developed using Visual Basic for Applications in Microsoft Excel™ and combines features from different existing software and characterization techniques. The main novelty of FraNEP is the possibility to analyse trace-line maps of fracture networks applying the (1) scanline sampling, (2) window sampling or (3) circular scanline and window method, without the need of switching programs. Additionally, binning problems are avoided by using cumulative distributions, rather than probability density functions. FraNEP is a time-efficient tool for the characterisation of fracture network parameters, such as density, intensity and mean length. Furthermore, fracture strikes can be visualized using rose diagrams and a fitting routine evaluates the distribution of fracture lengths. As an example of its application, we use FraNEP to analyse a case study of lineament data from a satellite image of the Oman Mountains.

  20. Livelihood Diversification in Tropical Coastal Communities: A Network-Based Approach to Analyzing ‘Livelihood Landscapes’

    Science.gov (United States)

    Cinner, Joshua E.; Bodin, Örjan

    2010-01-01

    Background Diverse livelihood portfolios are frequently viewed as a critical component of household economies in developing countries. Within the context of natural resources governance in particular, the capacity of individual households to engage in multiple occupations has been shown to influence important issues such as whether fishers would exit a declining fishery, how people react to policy, the types of resource management systems that may be applicable, and other decisions about natural resource use. Methodology/Principal Findings This paper uses network analysis to provide a novel methodological framework for detailed systemic analysis of household livelihood portfolios. Paying particular attention to the role of natural resource-based occupations such as fisheries, we use network analyses to map occupations and their interrelationships- what we refer to as ‘livelihood landscapes’. This network approach allows for the visualization of complex information about dependence on natural resources that can be aggregated at different scales. We then examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities in 5 western Indian Ocean countries. Network statistics, including in- and out-degree centrality, the density of the network, and the level of network centralization are compared along a multivariate index of community-level socioeconomic development and a gradient of human population density. The combination of network analyses suggests an increase in household-level specialization with development for most occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified. Conclusions/Significance The novel modeling approach introduced here provides for various types of livelihood portfolio analyses at different scales of social aggregation. Our livelihood landscapes approach provides insights into communities

  1. MitProNet: A knowledgebase and analysis platform of proteome, interactome and diseases for mammalian mitochondria.

    Directory of Open Access Journals (Sweden)

    Jiabin Wang

    Full Text Available Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of

  2. Analyze to Network Bank Fraud Cases and Prevention%网银诈骗案件的分析及防范

    Institute of Scientific and Technical Information of China (English)

    纪芳; 薛亮

    2011-01-01

    本文通过介绍几起典型的网银诈骗案件,分析网银诈骗的过程,最后提出一些防范措施与建议,以此提高警惕,保护好个人财产。%This paper describes several typical Network Bank fraud cases,analyzes the process of Network Bank fraud,and finally proposes some preventive measures and recommendations,as alert and protection for personal property.

  3. Analyzing subsurface drain network performance in an agricultural monitoring site with a three-dimensional hydrological model

    Science.gov (United States)

    Nousiainen, Riikka; Warsta, Lassi; Turunen, Mika; Huitu, Hanna; Koivusalo, Harri; Pesonen, Liisa

    2015-10-01

    Effectiveness of a subsurface drainage system decreases with time, leading to a need to restore the drainage efficiency by installing new drain pipes in problem areas. The drainage performance of the resulting system varies spatially and complicates runoff and nutrient load generation within the fields. We presented a method to estimate the drainage performance of a heterogeneous subsurface drainage system by simulating the area with the three-dimensional hydrological FLUSH model. A GIS analysis was used to delineate the surface runoff contributing area in the field. We applied the method to reproduce the water balance and to investigate the effectiveness of a subsurface drainage network of a clayey field located in southern Finland. The subsurface drainage system was originally installed in the area in 1971 and the drainage efficiency was improved in 1995 and 2005 by installing new drains. FLUSH was calibrated against total runoff and drain discharge data from 2010 to 2011 and validated against total runoff in 2012. The model supported quantification of runoff fractions via the three installed drainage networks. Model realisations were produced to investigate the extent of the runoff contributing areas and the effect of the drainage parameters on subsurface drain discharge. The analysis showed that better model performance was achieved when the efficiency of the oldest drainage network (installed in 1971) was decreased. Our analysis method can reveal the drainage system performance but not the reason for the deterioration of the drainage performance. Tillage layer runoff from the field was originally computed by subtracting drain discharge from the total runoff. The drains installed in 1995 bypass the measurement system, which renders the tillage layer runoff calculation procedure invalid after 1995. Therefore, this article suggests use of a local correction coefficient based on the simulations for further research utilizing data from the study area.

  4. Proteomics, metabolomics, and protein interactomics in the characterization of the molecular features of major depressive disorder.

    Science.gov (United States)

    Martins-de-Souza, Daniel

    2014-03-01

    Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types-prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples.

  5. Serum Amyloid P Component (SAP) Interactome in Human Plasma Containing Physiological Calcium Levels.

    Science.gov (United States)

    Poulsen, Ebbe Toftgaard; Pedersen, Kata Wolff; Marzeda, Anna Maria; Enghild, Jan J

    2017-02-14

    The pentraxin serum amyloid P component (SAP) is secreted by the liver and found in plasma at a concentration of approximately 30 mg/L. SAP is a 25 kDa homopentamer known to bind both protein and nonprotein ligands, all in a calcium-dependent manner. The function of SAP is unclear but likely involves the humoral innate immune system spanning the complement system, inflammation, and coagulation. Also, SAP is known to bind to the generic structure of amyloid deposits and possibly to protect them against proteolysis. In this study, we have characterized the SAP interactome in human plasma containing the physiological Ca(2+) concentration using SAP affinity pull-down and co-immunoprecipitation experiments followed by mass spectrometry analyses. The analyses resulted in the identification of 33 proteins, of which 24 were direct or indirect interaction partners not previously reported. The SAP interactome can be divided into categories that include apolipoproteins, the complement system, coagulation, and proteolytic regulation.

  6. A systems level strategy for analyzing the cell death network: implication in exploring the apoptosis/autophagy connection.

    Science.gov (United States)

    Zalckvar, E; Yosef, N; Reef, S; Ber, Y; Rubinstein, A D; Mor, I; Sharan, R; Ruppin, E; Kimchi, A

    2010-08-01

    The mammalian cell death network comprises three distinct functional modules: apoptosis, autophagy and programmed necrosis. Currently, the field lacks systems level approaches to assess the extent to which the intermodular connectivity affects cell death performance. Here, we developed a platform that is based on single and double sets of RNAi-mediated perturbations targeting combinations of apoptotic and autophagic genes. The outcome of perturbations is measured both at the level of the overall cell death responses, using an unbiased quantitative reporter, and by assessing the molecular responses within the different functional modules. Epistatic analyses determine whether seemingly unrelated pairs of proteins are genetically linked. The initial running of this platform in etoposide-treated cells, using a few single and double perturbations, identified several levels of connectivity between apoptosis and autophagy. The knock down of caspase3 turned on a switch toward autophagic cell death, which requires Atg5 or Beclin-1. In addition, a reciprocal connection between these two autophagic genes and apoptosis was identified. By applying computational tools that are based on mining the protein-protein interaction database, a novel biochemical pathway connecting between Atg5 and caspase3 is suggested. Scaling up this platform into hundreds of perturbations potentially has a wide, general scope of applicability, and will provide the basis for future modeling of the cell death network.

  7. Expression of DISC1-interactome members correlates with cognitive phenotypes related to schizophrenia.

    Directory of Open Access Journals (Sweden)

    Antonio Rampino

    Full Text Available Cognitive dysfunction is central to the schizophrenia phenotype. Genetic and functional studies have implicated Disrupted-in-Schizophrenia 1 (DISC1, a leading candidate gene for schizophrenia and related psychiatric conditions, in cognitive function. Altered expression of DISC1 and DISC1-interactors has been identified in schizophrenia. Dysregulated expression of DISC1-interactome genes might, therefore, contribute to schizophrenia susceptibility via disruption of molecular systems required for normal cognitive function. Here, the blood RNA expression levels of DISC1 and DISC1-interacting proteins were measured in 63 control subjects. Cognitive function was assessed using neuropsychiatric tests and functional magnetic resonance imaging was used to assess the activity of prefrontal cortical regions during the N-back working memory task, which is abnormal in schizophrenia. Pairwise correlations between gene expression levels and the relationship between gene expression levels and cognitive function and N-back-elicited brain activity were assessed. Finally, the expression levels of DISC1, AKAP9, FEZ1, NDEL1 and PCM1 were compared between 63 controls and 69 schizophrenic subjects. We found that DISC1-interactome genes showed correlated expression in the blood of healthy individuals. The expression levels of several interactome members were correlated with cognitive performance and N-back-elicited activity in the prefrontal cortex. In addition, DISC1 and NDEL1 showed decreased expression in schizophrenic subjects compared to healthy controls. Our findings highlight the importance of the coordinated expression of DISC1-interactome genes for normal cognitive function and suggest that dysregulated DISC1 and NDEL1 expression might, in part, contribute to susceptibility for schizophrenia via disruption of prefrontal cortex-dependent cognitive functions.

  8. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    ZHU MingZhu; GAO Lei; LI Xia; LIU ZhiCheng

    2009-01-01

    Proteins rarely function in isolation Inside and outside cells, but operate as part of a highly Intercon-nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action In terms of informatice. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac-tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins In the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem-onstrated to be drug-target proteins in the literature.

  9. Identifying drug-target proteins based on network features

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    Proteins rarely function in isolation inside and outside cells, but operate as part of a highly intercon- nected cellular network called the interaction network. Therefore, the analysis of the properties of drug-target proteins in the biological network is especially helpful for understanding the mechanism of drug action in terms of informatics. At present, no detailed characterization and description of the topological features of drug-target proteins have been available in the human protein-protein interac- tion network. In this work, by mapping the drug-targets in DrugBank onto the interaction network of human proteins, five topological indices of drug-targets were analyzed and compared with those of the whole protein interactome set and the non-drug-target set. The experimental results showed that drug-target proteins have higher connectivity and quicker communication with each other in the PPI network. Based on these features, all proteins in the interaction network were ranked. The results showed that, of the top 100 proteins, 48 are covered by DrugBank; of the remaining 52 proteins, 9 are drug-target proteins covered by the TTD, Matador and other databases, while others have been dem- onstrated to be drug-target proteins in the literature.

  10. A viral-human interactome based on structural motif-domain interactions captures the human infectome.

    Directory of Open Access Journals (Sweden)

    Aldo Segura-Cabrera

    Full Text Available Protein interactions between a pathogen and its host are fundamental in the establishment of the pathogen and underline the infection mechanism. In the present work, we developed a single predictive model for building a host-viral interactome based on the identification of structural descriptors from motif-domain interactions of protein complexes deposited in the Protein Data Bank (PDB. The structural descriptors were used for searching, in a database of protein sequences of human and five clinically important viruses; therefore, viral and human proteins sharing a descriptor were predicted as interacting proteins. The analysis of the host-viral interactome allowed to identify a set of new interactions that further explain molecular mechanism associated with viral infections and showed that it was able to capture human proteins already associated to viral infections (human infectome and non-infectious diseases (human diseasome. The analysis of human proteins targeted by viral proteins in the context of a human interactome showed that their neighbors are enriched in proteins reported with differential expression under infection and disease conditions. It is expected that the findings of this work will contribute to the development of systems biology for infectious diseases, and help guide the rational identification and prioritization of novel drug targets.

  11. Elucidation of epithelial-mesenchymal transition-related pathways in a triple-negative breast cancer cell line model by multi-omics interactome analysis.

    Science.gov (United States)

    Pauling, Josch K; Christensen, Anne G; Batra, Richa; Alcaraz, Nicolas; Barbosa, Eudes; Larsen, Martin R; Beck, Hans C; Leth-Larsen, Rikke; Azevedo, Vasco; Ditzel, Henrik J; Baumbach, Jan

    2014-11-01

    In life sciences, and particularly biomedical research, linking aberrant pathways exhibiting phenotype-specific alterations to the underlying physical condition or disease is an ongoing challenge. Computationally, a key approach for pathway identification is data enrichment, combined with generation of biological networks. This allows identification of intrinsic patterns in the data and their linkage to a specific context such as cellular compartments, diseases or functions. Identification of aberrant pathways by traditional approaches is often limited to biological networks based on either gene expression, protein expression or post-translational modifications. To overcome single omics analysis, we developed a set of computational methods that allow a combined analysis of data collections from multiple omics fields utilizing hybrid interactome networks. We apply these methods to data obtained from a triple-negative breast cancer cell line model, combining data sets of gene and protein expression as well as protein phosphorylation. We focus on alterations associated with the phenotypical differences arising from epithelial-mesenchymal transition in two breast cancer cell lines exhibiting epithelial-like and mesenchymal-like morphology, respectively. Here we identified altered protein signaling activity in a complex biologically relevant network, related to focal adhesion and migration of breast cancer cells. We found dysregulated functional network modules revealing altered phosphorylation-dependent activity in concordance with the phenotypic traits and migrating potential of the tested model. In addition, we identified Ser267 on zyxin, a protein coupled to actin filament polymerization, as a potential in vivo phosphorylation target of cyclin-dependent kinase 1.

  12. Photoisomerization Reaction Mechanisms of o-Nitrophenol Revealed by Analyzing Intersystem Crossing Network at the MRCI Level.

    Science.gov (United States)

    Xu, Chao; Yu, Le; Zhu, Chaoyuan; Yu, Jianguo

    2015-10-22

    6SA-CASSCF(10, 10) /6-31G (d, p) and MRCI/cc-pVDZ methods were performed to probe photoisomerization reaction mechanisms of o-nitrophenol. Two low-lying singlet electronic states (S0 and S1) and two low-lying triplet electronic states (T1 and T2) were found to weave an intersystem crossing network in which a dominant stepwise photoisomerization provides a very efficient reaction pathway; the reaction takes place in the wide region of crossing seam-surface woven by S1 and T1 states first, followed by T1 and S0 states. Both intersystem crossing regions show strong spin-orbital coupling in the order of 40 wavenumbers. All nitro and aci-nitro isomers and transition states on four electronic potential energy surfaces are calculated along with analysis of both dominant and subdominant relaxation pathways, especially weak spin-orbital coupling (∼10 wavenumbers) between T2 and S1 states and effective conical intersection between T2 and T1 states opening a new relaxation pathway S1 → T2→ T1.

  13. Comparative Pathway Analyzer--a web server for comparative analysis, clustering and visualization of metabolic networks in multiple organisms.

    Science.gov (United States)

    Oehm, Sebastian; Gilbert, David; Tauch, Andreas; Stoye, Jens; Goesmann, Alexander

    2008-07-01

    In order to understand the phenotype of any living system, it is essential to not only investigate its genes, but also the specific metabolic pathway variant of the organism of interest, ideally in comparison with other organisms. The Comparative Pathway Analyzer, CPA, calculates and displays the differences in metabolic reaction content between two sets of organisms. Because results are highly dependent on the distribution of organisms into these two sets and the appropriate definition of these sets often is not easy, we provide hierarchical clustering methods for the identification of significant groupings. CPA also visualizes the reaction content of several organisms simultaneously allowing easy comparison. Reaction annotation data and maps for visualizing the results are taken from the KEGG database. Additionally, users can upload their own annotation data. This website is free and open to all users and there is no login requirement. It is available at https://www.cebitec.uni-bielefeld.de/groups/brf/software/cpa/index.html.

  14. Analyzing the EEG Signals in Order to Estimate the Depth of Anesthesia using Wavelet and Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Mansour Esmaeilpour

    2016-12-01

    Full Text Available Estimating depth of Anesthesia in patients with the objective to administer the right dosage of drug has always attracted the attention of specialists. To study Anesthesia, researchers analyze brain waves since this is the place which is directly affected by the drug. This study aimed to estimate the depth of Anesthesia using electroencephalogram (EGG signals, wavelet transform, and adaptive Neuro Fuzzy inference system (ANFIS. ANFIS can estimate the depth of Anesthesia with high accuracy. A set of EEG signals regarding consciousness, moderate Anesthesia, deep Anesthesia, and iso-electric point were collected from the American Society of Anesthesiologists (ASA and PhysioNet. First, the extracted features were combined using wavelet and spectral analysis after which the target features were selected. Later, the features were classified into four categories. The results obtained revealed that the accuracy of the proposed method was 98.45%. Since the visual analysis of EEG signals is difficult, the proposed method can significantly help anesthesiologists estimate the depth of Anesthesia. Further, the results showed that ANFIS could significantly increase the accuracy of Anesthesia depth estimation. Finally, the system was deemed to be advantageous since it was also capable of updating in real-time situations as well.

  15. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET, a new method for plasmid reconstruction from whole genome sequences.

    Directory of Open Access Journals (Sweden)

    Val F Lanza

    2014-12-01

    Full Text Available Bacterial whole genome sequence (WGS methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage, comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC, comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

  16. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.

    Science.gov (United States)

    Lanza, Val F; de Toro, María; Garcillán-Barcia, M Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M; de la Cruz, Fernando

    2014-12-01

    Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

  17. Evaluation of clustering algorithms for protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    van Helden Jacques

    2006-11-01

    Full Text Available Abstract Background Protein interactions are crucial components of all cellular processes. Recently, high-throughput methods have been developed to obtain a global description of the interactome (the whole network of protein interactions for a given organism. In 2002, the yeast interactome was estimated to contain up to 80,000 potential interactions. This estimate is based on the integration of data sets obtained by various methods (mass spectrometry, two-hybrid methods, genetic studies. High-throughput methods are known, however, to yield a non-negligible rate of false positives, and to miss a fraction of existing interactions. The interactome can be represented as a graph where nodes correspond with proteins and edges with pairwise interactions. In recent years clustering methods have been developed and applied in order to extract relevant modules from such graphs. These algorithms require the specification of parameters that may drastically affect the results. In this paper we present a comparative assessment of four algorithms: Markov Clustering (MCL, Restricted Neighborhood Search Clustering (RNSC, Super Paramagnetic Clustering (SPC, and Molecular Complex Detection (MCODE. Results A test graph was built on the basis of 220 complexes annotated in the MIPS database. To evaluate the robustness to false positives and false negatives, we derived 41 altered graphs by randomly removing edges from or adding edges to the test graph in various proportions. Each clustering algorithm was applied to these graphs with various parameter settings, and the clusters were compared with the annotated complexes. We analyzed the sensitivity of the algorithms to the parameters and determined their optimal parameter values. We also evaluated their robustness to alterations of the test graph. We then applied the four algorithms to six graphs obtained from high-throughput experiments and compared the resulting clusters with the annotated complexes. Conclusion This

  18. Evidence of Probabilistic Behaviour in Protein Interaction Networks

    Science.gov (United States)

    2008-01-31

    cerevisiae by mass spectrometry. Nature 2002, 415(6868):180-183. 6. Zhu H, Bilgin M, Bangham R, Hall D, Casamayor A, Bertone P, Lan N, Jansen R, Bidlingmaier...Doucette-Stamm L, Gunsalus KC, Harper JW, Cusick ME, Roth FP , Hill DE, Vidal M: A map of the interactome network of the metazoan C. elegans

  19. The pain interactome: connecting pain-specific protein interactions.

    Science.gov (United States)

    Jamieson, Daniel G; Moss, Andrew; Kennedy, Michael; Jones, Sherrie; Nenadic, Goran; Robertson, David L; Sidders, Ben

    2014-11-01

    Understanding the molecular mechanisms associated with disease is a central goal of modern medical research. As such, many thousands of experiments have been published that detail individual molecular events that contribute to a disease. Here we use a semi-automated text mining approach to accurately and exhaustively curate the primary literature for chronic pain states. In so doing, we create a comprehensive network of 1,002 contextualized protein-protein interactions (PPIs) specifically associated with pain. The PPIs form a highly interconnected and coherent structure, and the resulting network provides an alternative to those derived from connecting genes associated with pain using interactions that have not been shown to occur in a painful state. We exploit the contextual data associated with our interactions to analyse subnetworks specific to inflammatory and neuropathic pain, and to various anatomical regions. Here, we identify potential targets for further study and several drug-repurposing opportunities. Finally, the network provides a framework for the interpretation of new data within the field of pain.

  20. Neuregulin 1-erbB4 pathway in schizophrenia: From genes to an interactome.

    Science.gov (United States)

    Banerjee, Anamika; Macdonald, Mathew L; Borgmann-Winter, Karin E; Hahn, Chang-Gyu

    2010-09-30

    Recently identified candidate susceptibility genes for schizophrenia are likely to play, important roles in the pathophysiology of the illness. It is also clear, however, that the etiologic, contribution of these genes is not only via their own functions but also through interactions with other, genes and environmental factors. Genetic, transgenic and postmortem brain studies support a, potential role for NRG1-erbB4 signaling in schizophrenia. Embedded in the results of these studies, however, are clues to the notion that NRG1-erbB4 signaling does not act alone but in conjunction with, other pathways. This article aims to re-evaluate the evidence for the role of neuregulin 1 (NRG1)-erbB4 signaling in schizophrenia by focusing on its interactions with other candidate susceptibility, pathways. In addition, we consider molecular substrates upon which the NRG1-erbB4 and other, candidate pathways converge contributing to susceptibility for the illness (schizophrenia interactome). Glutamatergic signaling can be an interesting candidate for schizophrenia interactome. Schizophrenia is associated with NMDA receptor hypofunction and moreover, several susceptibility genes for, schizophrenia converge on NMDA receptor signaling. These candidate genes influence NMDA receptor, signaling via diverse mechanisms, yet all eventually impact on protein composition of NMDA receptor, complexes. Likewise, the protein associations in the receptor complexes can themselves modulate, signaling molecules of candidate genes and their pathways. Therefore, protein-protein interactions in the NMDA receptor complexes can mediate reciprocal interactions between NMDA receptor function, and susceptibility candidate pathways including NRG1-erbB4 signaling and thus can be a, schizophrenia interactome.

  1. Revealing missing parts of the interactome via link prediction.

    Directory of Open Access Journals (Sweden)

    Yuriy Hulovatyy

    Full Text Available Protein interaction networks (PINs are often used to "learn" new biological function from their topology. Since current PINs are noisy, their computational de-noising via link prediction (LP could improve the learning accuracy. LP uses the existing PIN topology to predict missing and spurious links. Many of existing LP methods rely on shared immediate neighborhoods of the nodes to be linked. As such, they have limitations. Thus, in order to comprehensively study what are the topological properties of nodes in PINs that dictate whether the nodes should be linked, we introduce novel sensitive LP measures that are expected to overcome the limitations of the existing methods. We systematically evaluate the new and existing LP measures by introducing "synthetic" noise into PINs and measuring how accurate the measures are in reconstructing the original PINs. Also, we use the LP measures to de-noise the original PINs, and we measure biological correctness of the de-noised PINs with respect to functional enrichment of the predicted interactions. Our main findings are: 1 LP measures that favor nodes which are both "topologically similar" and have large shared extended neighborhoods are superior; 2 using more network topology often though not always improves LP accuracy; and 3 LP improves biological correctness of the PINs, plus we validate a significant portion of the predicted interactions in independent, external PIN data sources. Ultimately, we are less focused on identifying a superior method but more on showing that LP improves biological correctness of PINs, which is its ultimate goal in computational biology. But we note that our new methods outperform each of the existing ones with respect to at least one evaluation criterion. Alarmingly, we find that the different criteria often disagree in identifying the best method(s, which has important implications for LP communities in any domain, including social networks.

  2. The Serum Amyloid p Component (SAP) Interactome in Human Plasma Containing Physiological Calcium Levels

    DEFF Research Database (Denmark)

    Poulsen, Ebbe Toftgaard; Pedersen, Kata Wolff; Marzeda, Anna Maria

    2017-01-01

    containing the physiological Ca2+ concentration using SAP affinity pull-down and co-immunoprecipitation experiments followed by mass spectrometry analyses. The analyses resulted in the identification of 33 proteins of which 24 were direct or indirect integration partners not previously reported. The SAP...... involves the humoral innate immune system spanning the complement system, inflammation, and coagulation. Also, SAP is known to binding to the generic structure of amyloid deposits and possibly to protect these against proteolysis. In this study, we have characterized the SAP interactome in human plasma...

  3. Evolution after whole-genome duplication: a network perspective.

    Science.gov (United States)

    Zhu, Yun; Lin, Zhenguo; Nakhleh, Luay

    2013-11-06

    Gene duplication plays an important role in the evolution of genomes and interactomes. Elucidating how evolution after gene duplication interplays at the sequence and network level is of great interest. In this work, we analyze a data set of gene pairs that arose through whole-genome duplication (WGD) in yeast. All these pairs have the same duplication time, making them ideal for evolutionary investigation. We investigated the interplay between evolution after WGD at the sequence and network levels and correlated these two levels of divergence with gene expression and fitness data. We find that molecular interactions involving WGD genes evolve at rates that are three orders of magnitude slower than the rates of evolution of the corresponding sequences. Furthermore, we find that divergence of WGD pairs correlates strongly with gene expression and fitness data. Because of the role of gene duplication in determining redundancy in biological systems and particularly at the network level, we investigated the role of interaction networks in elucidating the evolutionary fate of duplicated genes. We find that gene neighborhoods in interaction networks provide a mechanism for inferring these fates, and we developed an algorithm for achieving this task. Further epistasis analysis of WGD pairs categorized by their inferred evolutionary fates demonstrated the utility of these techniques. Finally, we find that WGD pairs and other pairs of paralogous genes of small-scale duplication origin share similar properties, giving good support for generalizing our results from WGD pairs to evolution after gene duplication in general.

  4. An Interactome-Centered Protein Discovery Approach Reveals Novel Components Involved in Mitosome Function and Homeostasis in Giardia lamblia

    Science.gov (United States)

    Rout, Samuel; Zumthor, Jon Paulin; Schraner, Elisabeth M.

    2016-01-01

    Protozoan parasites of the genus Giardia are highly prevalent globally, and infect a wide range of vertebrate hosts including humans, with proliferation and pathology restricted to the small intestine. This narrow ecological specialization entailed extensive structural and functional adaptations during host-parasite co-evolution. An example is the streamlined mitosomal proteome with iron-sulphur protein maturation as the only biochemical pathway clearly associated with this organelle. Here, we applied techniques in microscopy and protein biochemistry to investigate the mitosomal membrane proteome in association to mitosome homeostasis. Live cell imaging revealed a highly immobilized array of 30–40 physically distinct mitosome organelles in trophozoites. We provide direct evidence for the single giardial dynamin-related protein as a contributor to mitosomal morphogenesis and homeostasis. To overcome inherent limitations that have hitherto severely hampered the characterization of these unique organelles we applied a novel interaction-based proteome discovery strategy using forward and reverse protein co-immunoprecipitation. This allowed generation of organelle proteome data strictly in a protein-protein interaction context. We built an initial Tom40-centered outer membrane interactome by co-immunoprecipitation experiments, identifying small GTPases, factors with dual mitosome and endoplasmic reticulum (ER) distribution, as well as novel matrix proteins. Through iterative expansion of this protein-protein interaction network, we were able to i) significantly extend this interaction-based mitosomal proteome to include other membrane-associated proteins with possible roles in mitosome morphogenesis and connection to other subcellular compartments, and ii) identify novel matrix proteins which may shed light on mitosome-associated metabolic functions other than Fe-S cluster biogenesis. Functional analysis also revealed conceptual conservation of protein translocation

  5. An Interactome-Centered Protein Discovery Approach Reveals Novel Components Involved in Mitosome Function and Homeostasis in Giardia lamblia.

    Science.gov (United States)

    Rout, Samuel; Zumthor, Jon Paulin; Schraner, Elisabeth M; Faso, Carmen; Hehl, Adrian B

    2016-12-01

    Protozoan parasites of the genus Giardia are highly prevalent globally, and infect a wide range of vertebrate hosts including humans, with proliferation and pathology restricted to the small intestine. This narrow ecological specialization entailed extensive structural and functional adaptations during host-parasite co-evolution. An example is the streamlined mitosomal proteome with iron-sulphur protein maturation as the only biochemical pathway clearly associated with this organelle. Here, we applied techniques in microscopy and protein biochemistry to investigate the mitosomal membrane proteome in association to mitosome homeostasis. Live cell imaging revealed a highly immobilized array of 30-40 physically distinct mitosome organelles in trophozoites. We provide direct evidence for the single giardial dynamin-related protein as a contributor to mitosomal morphogenesis and homeostasis. To overcome inherent limitations that have hitherto severely hampered the characterization of these unique organelles we applied a novel interaction-based proteome discovery strategy using forward and reverse protein co-immunoprecipitation. This allowed generation of organelle proteome data strictly in a protein-protein interaction context. We built an initial Tom40-centered outer membrane interactome by co-immunoprecipitation experiments, identifying small GTPases, factors with dual mitosome and endoplasmic reticulum (ER) distribution, as well as novel matrix proteins. Through iterative expansion of this protein-protein interaction network, we were able to i) significantly extend this interaction-based mitosomal proteome to include other membrane-associated proteins with possible roles in mitosome morphogenesis and connection to other subcellular compartments, and ii) identify novel matrix proteins which may shed light on mitosome-associated metabolic functions other than Fe-S cluster biogenesis. Functional analysis also revealed conceptual conservation of protein translocation

  6. An Interactome-Centered Protein Discovery Approach Reveals Novel Components Involved in Mitosome Function and Homeostasis in Giardia lamblia.

    Directory of Open Access Journals (Sweden)

    Samuel Rout

    2016-12-01

    Full Text Available Protozoan parasites of the genus Giardia are highly prevalent globally, and infect a wide range of vertebrate hosts including humans, with proliferation and pathology restricted to the small intestine. This narrow ecological specialization entailed extensive structural and functional adaptations during host-parasite co-evolution. An example is the streamlined mitosomal proteome with iron-sulphur protein maturation as the only biochemical pathway clearly associated with this organelle. Here, we applied techniques in microscopy and protein biochemistry to investigate the mitosomal membrane proteome in association to mitosome homeostasis. Live cell imaging revealed a highly immobilized array of 30-40 physically distinct mitosome organelles in trophozoites. We provide direct evidence for the single giardial dynamin-related protein as a contributor to mitosomal morphogenesis and homeostasis. To overcome inherent limitations that have hitherto severely hampered the characterization of these unique organelles we applied a novel interaction-based proteome discovery strategy using forward and reverse protein co-immunoprecipitation. This allowed generation of organelle proteome data strictly in a protein-protein interaction context. We built an initial Tom40-centered outer membrane interactome by co-immunoprecipitation experiments, identifying small GTPases, factors with dual mitosome and endoplasmic reticulum (ER distribution, as well as novel matrix proteins. Through iterative expansion of this protein-protein interaction network, we were able to i significantly extend this interaction-based mitosomal proteome to include other membrane-associated proteins with possible roles in mitosome morphogenesis and connection to other subcellular compartments, and ii identify novel matrix proteins which may shed light on mitosome-associated metabolic functions other than Fe-S cluster biogenesis. Functional analysis also revealed conceptual conservation of protein

  7. Methods for Analyzing Pipe Networks

    DEFF Research Database (Denmark)

    Nielsen, Hans Bruun

    1989-01-01

    to formulate the flow equations in terms of pipe discharges than in terms of energy heads. The behavior of some iterative methods is compared in the initial phase with large errors. It is explained why the linear theory method oscillates when the iteration gets close to the solution, and it is further...

  8. Evolve: Analyzing Evolving Social Networks

    Science.gov (United States)

    2012-07-01

    interesting: the Enron email data set and the World-trade data set. These two data sets were interesting because we have some notion of what the...ground truth looks like based on historical facts (world trade: which countries have traded strongly with each other over the past 40 years; Enron : what...defined. The Enron email data is a stream (each email has a unique time-stamp), so we used one-month snapshots to get a fair amount of snapshots

  9. Targeted Interactomics in Plants Through Protein Complex Isolation

    Institute of Scientific and Technical Information of China (English)

    Geert De Jaeger

    2012-01-01

    TAPtag technology is the most widely applied tool to pick up in situ protein interactions in a proteome wide setting.Our research team has developed a versatile TAP technology platform for protein complex isolation from plants.We isolated complexes for hundreds of proteins and extensively demonstrated the power of our technology for protein discovery,functional analysis of proteins and protein complexes,and the modelling of protein networks.Complexes are purified from Arabidopsis cell suspension cultures or seedlings and we are currently translating the technology towards crop plants to bring complex purification in a developmental context.Besides protein complexes,we are deriving protocol variations to isolate chromatin complexes.

  10. Identifying the common interaction networks of amoeboid motility and cancer cell metastasis

    Directory of Open Access Journals (Sweden)

    Ahmed H. Zeitoun

    2012-06-01

    Full Text Available The recently analyzed genome of Naegleria gruberi, a free-living amoeboflagellate of the Heterolobosea clade, revealed a remarkably complex ancestral eukaryote with a rich repertoire of cytoskeletal-, motility- and signaling-genes. This protist, which diverged from other eukaryotic lineages over a billion years ago, possesses the ability for both amoeboid and flagellar motility. In a phylogenomic comparison of two free living eukaryotes with large proteomic datasets of three metastatic tumour entities (malignant melanoma, breast- and prostate-carcinoma, we find common proteins with potential importance for cell motility and cancer cell metastasis. To identify the underlying signaling modules, we constructed for each tumour type a protein-protein interaction network including these common proteins. The connectivity within this interactome revealed specific interactions and pathways which constitute prospective points of intervention for novel anti-metastatic tumour therapies.

  11. 生化网络的随机Petri网建模与分析%Modeling and analyzing biochemical networks using stochastic Petri nets

    Institute of Scientific and Technical Information of China (English)

    丁德武; 李文泽

    2012-01-01

    细胞的行为是随机性的,学习细胞中的随机性有助于理解细胞的组织,设计和进化.建立、确认和分析随机的生化网络模型是当前计算系统生物学领域的一个重要研究主题.当前,标准的Petri网模型已经成为生化网络模拟和定性分析的有力工具.尝试使用随机Petri网对生化网络进行建模与分析,简单描述了随机Petri网理论对标准Petri网的扩充,通过对二聚作用和肌动蛋白这两个典型例子的建模与演化模拟,介绍、论证了随机Petri网理论的新应用.%Cellular behavior is stochastic, and studying stochastic in the cell can help to understand the organization, design and evolution of the cell. Establishment, identification and analysis of stochastic biochemical network models is an important research topic in the field of computational systems biology. At present, the standard Petri net model has become a powerful tool for biochemical network modeling and qualitative analysis. This paper attempts to apply stochastic Petri nets to modeling and analyzing biochemical network, it briefly describes the expansion of the stochastic Petri net theory to standard Petri nets, then by modeling and evolution simulating two classic examples (dimerization and actin), it demonstrates new applications of stochastic Petri nets theory.

  12. Analyzing Peace Pedagogies

    Science.gov (United States)

    Haavelsrud, Magnus; Stenberg, Oddbjorn

    2012-01-01

    Eleven articles on peace education published in the first volume of the Journal of Peace Education are analyzed. This selection comprises peace education programs that have been planned or carried out in different contexts. In analyzing peace pedagogies as proposed in the 11 contributions, we have chosen network analysis as our method--enabling…

  13. Determination of electric field, magnetic field, and electric current distributions of infrared optical antennas: A nano-optical vector network analyzer

    CERN Document Server

    Olmon, Robert L; Krenz, Peter M; Lail, Brian A; Saraf, Laxmikant V; Boreman, Glenn D; Raschke, Markus B

    2010-01-01

    In addition to the electric field E(r), the associated magnetic field H(r) and current density J(r) characterize any electromagnetic device, providing insight into antenna coupling and mutual impedance. We demonstrate the optical analogue of the radio frequency vector network analyzer implemented in interferometric homodyne scattering-type scanning near-field optical microscopy (s-SNOM) for obtaining E(r), H(r), and J(r). The approach is generally applicable and demonstrated for the case of a linear coupled-dipole antenna in the mid-infrared. The determination of the underlying 3D vector electric near-field distribution E(r) with nanometer spatial resolution and full phase and amplitude information is enabled by the design of probe tips with selectivity with respect to E-parallel and E-perpendicular fabricated by focused ion-beam milling and nano-CVD.

  14. Vector network analyzer measurement of the amplitude of an electrically excited surface acoustic wave and validation by X-ray diffraction

    Science.gov (United States)

    Camara, I. S.; Croset, B.; Largeau, L.; Rovillain, P.; Thevenard, L.; Duquesne, J.-Y.

    2017-01-01

    Surface acoustic waves are used in magnetism to initiate magnetization switching, in microfluidics to control fluids and particles in lab-on-a-chip devices, and in quantum systems like two-dimensional electron gases, quantum dots, photonic cavities, and single carrier transport systems. For all these applications, an easy tool is highly needed to measure precisely the acoustic wave amplitude in order to understand the underlying physics and/or to optimize the device used to generate the acoustic waves. We present here a method to determine experimentally the amplitude of surface acoustic waves propagating on Gallium Arsenide generated by an interdigitated transducer. It relies on Vector Network Analyzer measurements of S parameters and modeling using the Coupling-Of-Modes theory. The displacements obtained are in excellent agreement with those measured by a very different method based on X-ray diffraction measurements.

  15. Caspofungin exposure alters the core septin AspB interactome of Aspergillus fumigatus.

    Science.gov (United States)

    Vargas-Muñiz, José M; Renshaw, Hilary; Waitt, Greg; Soderblom, Erik J; Moseley, M Arthur; Palmer, Jonathan M; Juvvadi, Praveen R; Keller, Nancy P; Steinbach, William J

    2017-04-01

    Aspergillus fumigatus, the main etiological agent of invasive aspergillosis, is a leading cause of death in immunocompromised patients. Septins, a conserved family of GTP-binding proteins, serve as scaffolding proteins to recruit enzymes and key regulators to different cellular compartments. Deletion of the A. fumigatus septin aspB increases susceptibility to the echinocandin antifungal caspofungin. However, how AspB mediates this response to caspofungin is unknown. Here, we characterized the AspB interactome under basal conditions and after exposure to a clinically relevant concentration of caspofungin. While A. fumigatus AspB interacted with 334 proteins, including kinases, cell cycle regulators, and cell wall synthesis-related proteins under basal growth conditions, caspofungin exposure altered AspB interactions. A total of 69 of the basal interactants did not interact with AspB after exposure to caspofungin, and 54 new interactants were identified following caspofungin exposure. We generated A. fumigatus deletion strains for 3 proteins (ArpB, Cyp4, and PpoA) that only interacted with AspB following exposure to caspofungin that were previously annotated as induced after exposure to antifungal agents, yet only PpoA was implicated in the response to caspofungin. Taken together, we defined how the septin AspB interactome is altered in the presence of a clinically relevant antifungal.

  16. Improved microarray-based decision support with graph encoded interactome data.

    Directory of Open Access Journals (Sweden)

    Anneleen Daemen

    Full Text Available In the past, microarray studies have been criticized due to noise and the limited overlap between gene signatures. Prior biological knowledge should therefore be incorporated as side information in models based on gene expression data to improve the accuracy of diagnosis and prognosis in cancer. As prior knowledge, we investigated interaction and pathway information from the human interactome on different aspects of biological systems. By exploiting the properties of kernel methods, relations between genes with similar functions but active in alternative pathways could be incorporated in a support vector machine classifier based on spectral graph theory. Using 10 microarray data sets, we first reduced the number of data sources relevant for multiple cancer types and outcomes. Three sources on metabolic pathway information (KEGG, protein-protein interactions (OPHID and miRNA-gene targeting (microRNA.org outperformed the other sources with regard to the considered class of models. Both fixed and adaptive approaches were subsequently considered to combine the three corresponding classifiers. Averaging the predictions of these classifiers performed best and was significantly better than the model based on microarray data only. These results were confirmed on 6 validation microarray sets, with a significantly improved performance in 4 of them. Integrating interactome data thus improves classification of cancer outcome for the investigated microarray technologies and cancer types. Moreover, this strategy can be incorporated in any kernel method or non-linear version of a non-kernel method.

  17. Arabidopsis G-protein interactome reveals connections to cell wall carbohydrates and morphogenesis

    Energy Technology Data Exchange (ETDEWEB)

    Klopffleisch, Karsten [University of Cologne; Phan, Nguyen [University of North Carolina, Chapel Hill; Chen, Jay [ORNL; Panstruga, Ralph [Max-Planck Institute for Plant Breeding Research; Uhrig, Joachim [University of Cologne; Jones, Alan M [University of North Carolina, Chapel Hill

    2011-01-01

    The heterotrimeric G-protein complex is minimally composed of G{alpha}, G{beta}, and G{gamma} subunits. In the classic scenario, the G-protein complex is the nexus in signaling from the plasma membrane, where the heterotrimeric G-protein associates with heptahelical G-protein-coupled receptors (GPCRs), to cytoplasmic target proteins called effectors. Although a number of effectors are known in metazoans and fungi, none of these are predicted to exist in their canonical forms in plants. To identify ab initio plant G-protein effectors and scaffold proteins, we screened a set of proteins from the G-protein complex using two-hybrid complementation in yeast. After deep and exhaustive interrogation, we detected 544 interactions between 434 proteins, of which 68 highly interconnected proteins form the core G-protein interactome. Within this core, over half of the interactions comprising two-thirds of the nodes were retested and validated as genuine in planta. Co-expression analysis in combination with phenotyping of loss-of-function mutations in a set of core interactome genes revealed a novel role for G-proteins in regulating cell wall modification.

  18. Border control--a membrane-linked interactome of Arabidopsis.

    Science.gov (United States)

    Jones, Alexander M; Xuan, Yuanhu; Xu, Meng; Wang, Rui-Sheng; Ho, Cheng-Hsun; Lalonde, Sylvie; You, Chang Hun; Sardi, Maria I; Parsa, Saman A; Smith-Valle, Erika; Su, Tianying; Frazer, Keith A; Pilot, Guillaume; Pratelli, Réjane; Grossmann, Guido; Acharya, Biswa R; Hu, Heng-Cheng; Engineer, Cawas; Villiers, Florent; Ju, Chuanli; Takeda, Kouji; Su, Zhao; Dong, Qunfeng; Assmann, Sarah M; Chen, Jin; Kwak, June M; Schroeder, Julian I; Albert, Reka; Rhee, Seung Y; Frommer, Wolf B

    2014-05-16

    Cellular membranes act as signaling platforms and control solute transport. Membrane receptors, transporters, and enzymes communicate with intracellular processes through protein-protein interactions. Using a split-ubiquitin yeast two-hybrid screen that covers a test-space of 6.4 × 10(6) pairs, we identified 12,102 membrane/signaling protein interactions from Arabidopsis. Besides confirmation of expected interactions such as heterotrimeric G protein subunit interactions and aquaporin oligomerization, >99% of the interactions were previously unknown. Interactions were confirmed at a rate of 32% in orthogonal in planta split-green flourescent protein interaction assays, which was statistically indistinguishable from the confirmation rate for known interactions collected from literature (38%). Regulatory associations in membrane protein trafficking, turnover, and phosphorylation include regulation of potassium channel activity through abscisic acid signaling, transporter activity by a WNK kinase, and a brassinolide receptor kinase by trafficking-related proteins. These examples underscore the utility of the membrane/signaling protein interaction network for gene discovery and hypothesis generation in plants and other organisms. Copyright © 2014, American Association for the Advancement of Science.

  19. A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

    Directory of Open Access Journals (Sweden)

    Goyal Neeraj

    2010-01-01

    Full Text Available To compare the accuracy of artificial neural network (ANN analysis and multi-variate regression analysis (MVRA for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL. A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC (r2 . For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL.

  20. Complex Networks Approach for Analyzing the Correlation of Traditional Chinese Medicine Syndrome Evolvement and Cardiovascular Events in Patients with Stable Coronary Heart Disease

    Directory of Open Access Journals (Sweden)

    Zhuye Gao

    2015-01-01

    Full Text Available This is a multicenter prospective cohort study to analyze the correlation of traditional Chinese medicine (TCM syndrome evolvement and cardiovascular events in patients with stable coronary heart disease (CHD. The impact of syndrome evolvement on cardiovascular events during the 6-month and 12-month follow-up was analyzed using complex networks approach. Results of verification using Chi-square test showed that the occurrence of cardiovascular events was positively correlated with syndrome evolvement when it evolved from toxic syndrome to Qi deficiency, blood stasis, or sustained toxic syndrome, when it evolved from Qi deficiency to blood stasis, toxic syndrome, or sustained Qi deficiency, and when it evolved from blood stasis to Qi deficiency. Blood stasis, Qi deficiency, and toxic syndrome are important syndrome factors for stable CHD. There are positive correlations between cardiovascular events and syndrome evolution from toxic syndrome to Qi deficiency or blood stasis, from Qi deficiency to blood stasis, or toxic syndrome and from blood stasis to Qi deficiency. These results indicate that stable CHD patients with pathogenesis of toxin consuming Qi, toxin leading to blood stasis, and mutual transformation of Qi deficiency and blood stasis are prone to recurrent cardiovascular events.

  1. Analogies between the measurement of acoustic impedance via the reaction on the source method and the automatic microwave vector network analyzer technique

    Science.gov (United States)

    McLean, James; Sutton, Robert; Post, John

    2003-10-01

    One useful method of acoustic impedance measurement involves the measurement of the electrical impedance ``looking into'' the electrical port of a reciprocal electroacoustic transducer. This reaction on the source method greatly facilitates the measurement of acoustic impedance by borrowing highly refined techniques to measure electrical impedance. It is also well suited for in situ acoustic impedance measurements. In order to accurately determine acoustic impedance from the measured electrical impedance, the characteristics of the transducer must be accurately known, i.e., the characteristics of the transducer must be ``removed'' completely from the data. The measurement of acoustic impedance via the measurement of the reaction on the source is analogous to modern microwave measurements made with an automatic vector network analyzer. The action of the analyzer is described as de-embedding the desired data (such as acoustic impedance) from the raw data. Such measurements are fundamentally substitution measurements in that the transducer's characteristics are determined by measuring a set of reference standards. The reaction on the source method is extended to take advantage of improvements in microwave measurement techniques which allow calibration via imperfect standard loads. This removes one of the principal weaknesses of the method in that the requirement of high-quality reference standards is relaxed.

  2. Systems biology in the context of big data and networks.

    Science.gov (United States)

    Altaf-Ul-Amin, Md; Afendi, Farit Mochamad; Kiboi, Samuel Kuria; Kanaya, Shigehiko

    2014-01-01

    Science is going through two rapidly changing phenomena: one is the increasing capabilities of the computers and software tools from terabytes to petabytes and beyond, and the other is the advancement in high-throughput molecular biology producing piles of data related to genomes, transcriptomes, proteomes, metabolomes, interactomes, and so on. Biology has become a data intensive science and as a consequence biology and computer science have become complementary to each other bridged by other branches of science such as statistics, mathematics, physics, and chemistry. The combination of versatile knowledge has caused the advent of big-data biology, network biology, and other new branches of biology. Network biology for instance facilitates the system-level understanding of the cell or cellular components and subprocesses. It is often also referred to as systems biology. The purpose of this field is to understand organisms or cells as a whole at various levels of functions and mechanisms. Systems biology is now facing the challenges of analyzing big molecular biological data and huge biological networks. This review gives an overview of the progress in big-data biology, and data handling and also introduces some applications of networks and multivariate analysis in systems biology.

  3. Network analysis of human glaucomatous optic nerve head astrocytes

    Directory of Open Access Journals (Sweden)

    Bhattacharya Sanjoy K

    2009-05-01

    Full Text Available Abstract Background Astrocyte activation is a characteristic response to injury in the central nervous system, and can be either neurotoxic or neuroprotective, while the regulation of both roles remains elusive. Methods To decipher the regulatory elements controlling astrocyte-mediated neurotoxicity in glaucoma, we conducted a systems-level functional analysis of gene expression, proteomic and genetic data associated with reactive optic nerve head astrocytes (ONHAs. Results Our reconstruction of the molecular interactions affected by glaucoma revealed multi-domain biological networks controlling activation of ONHAs at the level of intercellular stimuli, intracellular signaling and core effectors. The analysis revealed that synergistic action of the transcription factors AP-1, vitamin D receptor and Nuclear Factor-kappaB in cross-activation of multiple pathways, including inflammatory cytokines, complement, clusterin, ephrins, and multiple metabolic pathways. We found that the products of over two thirds of genes linked to glaucoma by genetic analysis can be functionally interconnected into one epistatic network via experimentally-validated interactions. Finally, we built and analyzed an integrative disease pathology network from a combined set of genes revealed in genetic studies, genes differentially expressed in glaucoma and closely connected genes/proteins in the interactome. Conclusion Our results suggest several key biological network modules that are involved in regulating neurotoxicity of reactive astrocytes in glaucoma, and comprise potential targets for cell-based therapy.

  4. Application of Artificial Neural Network Modeling to the Analysis of the Automated Radioxenon Sampler-Analyzer State Of Health Sensors OF HEALTH SENSORS

    Energy Technology Data Exchange (ETDEWEB)

    Hayes, James C.; Doctor, Pam G.; Heimbigner, Tom R.; Hubbard, Charles W.; Kangas, Lars J.; Keller, Paul E.; McIntyre, Justin I.; Schrom, Brian T.; Suarez, Reynold

    2006-09-19

    The Automated Radioxenon Analyzer/Sampler (ARSA) is a radioxenon gas collection and analysis system operating autonomously under computer control. The ARSA systems are deployed as part of an international network of sensors, with individual stations feeding radioxenon concentration data to a central data center. Because the ARSA instrument is complex and is often deployed in remote areas, it requires constant self-monitoring to verify that it is operating according to specifications. System performance monitoring is accomplished by over 200 internal sensors, with some values reported to the data center. Several sensors are designated as safety sensors that can automatically shut down the ARSA when unsafe conditions arise. In this case, the data center is advised of the shutdown and the cause, so that repairs may be initiated. The other sensors, called state of health (SOH) sensors, also provide valuable information on the functioning of the ARSA and are particularly useful for detecting impending malfunctions before they occur to avoid unscheduled shutdowns. Any of the sensor readings can be displayed by an ARSA Data Viewer, but interpretation of the data is difficult without specialized technical knowledge not routinely available at the data center. Therefore it would be advantageous to have sensor data automatically evaluated for the precursors of malfunctions and the results transmitted to the data center. Artificial Neural Networks (ANN) are a class of data analysis methods that have shown wide application to monitoring systems with large numbers of information inputs, such as the ARSA. In this work supervised and unsupervised ANN methods were applied to ARSA SOH data recording during normal operation of the instrument, and the ability of ANN methods to predict system state is presented.

  5. Report for CS 698-95 ?Directed Research ? Performance Modeling:? Using Queueing Network Modeling to Analyze the University of San Francisco Keck Cluster Supercomputer

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, M L

    2005-09-28

    In today's world, the need for computing power is becoming more pressing daily. Our need to process, analyze, and store data is quickly exceeding the capabilities of small self-contained serial machines, such as the modern desktop PC. Initially, this gap was filled by the creation of supercomputers: large-scale self-contained parallel machines. However, current markets, as well as the costs to develop and maintain such machines, are quickly making such machines a rarity, used only in highly specialized environments. A third type of machine exists, however. This relatively new type of machine, known as a cluster, is built from common, and often inexpensive, commodity self-contained desktop machines. But how well do these clustered machines work? There have been many attempts to quantify the performance of clustered computers. One approach, Queueing Network Modeling (QNM), appears to be a potentially useful and rarely tried method of modeling such systems. QNM, which has its beginnings in the modeling of traffic patterns, has expanded, and is now used to model everything from CPU and disk services, to computer systems, to service rates in store checkout lines. This history of successful usage, as well as the correspondence of QNM components to commodity clusters, suggests that QNM can be a useful tool for both the cluster designer, interested in the best value for the cost, and the user of existing machines, interested in performance rates and time-to-solution. So, what is QNM? Queueing Network Modeling is an approach to computer system modeling where the computer is represented as a network of queues and evaluated analytically. How does this correspond to clusters? There is a neat one-to-one relationship between the components of a QNM model and a cluster. For example: A cluster is made from a combination of computational nodes and network switches. Both of these fit nicely with the QNM descriptions of service centers (delay, queueing, and load

  6. A human phenome-interactome network of protein complexes implicated in genetic disorders

    DEFF Research Database (Denmark)

    Hansen, Kasper Lage; Karlberg, Erik, Olof, Linnart; Størling, Zenia, Marian

    2007-01-01

    the known disease-causing protein as the top candidate, and in 870 intervals with no identified disease-causing gene, provides novel candidates implicated in disorders such as retinitis pigmentosa, epithelial ovarian cancer, inflammatory bowel disease, amyotrophic lateral sclerosis, Alzheimer disease, type...

  7. A network medicine approach to quantify distance between hereditary disease modules on the interactome

    Science.gov (United States)

    Caniza, Horacio; Romero, Alfonso E.; Paccanaro, Alberto

    2015-12-01

    We introduce a MeSH-based method that accurately quantifies similarity between heritable diseases at molecular level. This method effectively brings together the existing information about diseases that is scattered across the vast corpus of biomedical literature. We prove that sets of MeSH terms provide a highly descriptive representation of heritable disease and that the structure of MeSH provides a natural way of combining individual MeSH vocabularies. We show that our measure can be used effectively in the prediction of candidate disease genes. We developed a web application to query more than 28.5 million relationships between 7,574 hereditary diseases (96% of OMIM) based on our similarity measure.

  8. Interactome network analysis identifies multiple caspase-6 interactors involved in the pathogenesis of HD

    DEFF Research Database (Denmark)

    Riechers, Sean-Patrick; Butland, Stefanie; Deng, Yu

    2016-01-01

    Caspase-6 (CASP6) has emerged as an important player in Huntington disease (HD), Alzheimer disease (AD) and cerebral ischemia, where it is activated early in the disease process. CASP6 also plays a key role in axonal degeneration, further underscoring the importance of this protease in neurodegen...

  9. Preferential associations between co-regulated genes reveal a transcriptional interactome in erythroid cells.

    Science.gov (United States)

    Schoenfelder, Stefan; Sexton, Tom; Chakalova, Lyubomira; Cope, Nathan F; Horton, Alice; Andrews, Simon; Kurukuti, Sreenivasulu; Mitchell, Jennifer A; Umlauf, David; Dimitrova, Daniela S; Eskiw, Christopher H; Luo, Yanquan; Wei, Chia-Lin; Ruan, Yijun; Bieker, James J; Fraser, Peter

    2010-01-01

    The discovery of interchromosomal interactions in higher eukaryotes points to a functional interplay between genome architecture and gene expression, challenging the view of transcription as a one-dimensional process. However, the extent of interchromosomal interactions and the underlying mechanisms are unknown. Here we present the first genome-wide analysis of transcriptional interactions using the mouse globin genes in erythroid tissues. Our results show that the active globin genes associate with hundreds of other transcribed genes, revealing extensive and preferential intra- and interchromosomal transcription interactomes. We show that the transcription factor Klf1 mediates preferential co-associations of Klf1-regulated genes at a limited number of specialized transcription factories. Our results establish a new gene expression paradigm, implying that active co-regulated genes and their regulatory factors cooperate to create specialized nuclear hot spots optimized for efficient and coordinated transcriptional control.

  10. A Transporter Interactome Is Essential for the Acquisition of Antimicrobial Resistance to Antibiotics

    Science.gov (United States)

    Shuster, Yonatan; Steiner-Mordoch, Sonia; Alon Cudkowicz, Noemie; Schuldiner, Shimon

    2016-01-01

    Awareness of the problem of antimicrobial resistance (AMR) has escalated and drug-resistant infections are named among the most urgent problems facing clinicians today. Our experiments here identify a transporter interactome and portray its essential function in acquisition of antimicrobial resistance. By exposing E. coli cells to consecutive increasing concentrations of the fluoroquinolone norfloxacin we generated in the laboratory highly resistant strains that carry multiple mutations, most of them identical to those identified in clinical isolates. With this experimental paradigm, we show that the MDTs function in a coordinated mode to provide an essential first-line defense mechanism, preventing the drug reaching lethal concentrations, until a number of stable efficient alterations occur that allow survival. Single-component efflux transporters remove the toxic compounds from the cytoplasm to the periplasmic space where TolC-dependent transporters expel them from the cell. We postulate a close interaction between the two types of transporters to prevent rapid leak of the hydrophobic substrates back into the cell. The findings change the prevalent concept that in Gram-negative bacteria a single multidrug transporter, AcrAB-TolC type, is responsible for the resistance. The concept of a functional interactome, the process of identification of its members, the elucidation of the nature of the interactions and its role in cell physiology will change the existing paradigms in the field. We anticipate that our work will have an impact on the present strategy searching for inhibitors of AcrAB-TolC as adjuvants of existing antibiotics and provide novel targets for this urgent undertaking. PMID:27050393

  11. A Transporter Interactome Is Essential for the Acquisition of Antimicrobial Resistance to Antibiotics.

    Science.gov (United States)

    Shuster, Yonatan; Steiner-Mordoch, Sonia; Alon Cudkowicz, Noemie; Schuldiner, Shimon

    2016-01-01

    Awareness of the problem of antimicrobial resistance (AMR) has escalated and drug-resistant infections are named among the most urgent problems facing clinicians today. Our experiments here identify a transporter interactome and portray its essential function in acquisition of antimicrobial resistance. By exposing E. coli cells to consecutive increasing concentrations of the fluoroquinolone norfloxacin we generated in the laboratory highly resistant strains that carry multiple mutations, most of them identical to those identified in clinical isolates. With this experimental paradigm, we show that the MDTs function in a coordinated mode to provide an essential first-line defense mechanism, preventing the drug reaching lethal concentrations, until a number of stable efficient alterations occur that allow survival. Single-component efflux transporters remove the toxic compounds from the cytoplasm to the periplasmic space where TolC-dependent transporters expel them from the cell. We postulate a close interaction between the two types of transporters to prevent rapid leak of the hydrophobic substrates back into the cell. The findings change the prevalent concept that in Gram-negative bacteria a single multidrug transporter, AcrAB-TolC type, is responsible for the resistance. The concept of a functional interactome, the process of identification of its members, the elucidation of the nature of the interactions and its role in cell physiology will change the existing paradigms in the field. We anticipate that our work will have an impact on the present strategy searching for inhibitors of AcrAB-TolC as adjuvants of existing antibiotics and provide novel targets for this urgent undertaking.

  12. A Transporter Interactome Is Essential for the Acquisition of Antimicrobial Resistance to Antibiotics.

    Directory of Open Access Journals (Sweden)

    Yonatan Shuster

    Full Text Available Awareness of the problem of antimicrobial resistance (AMR has escalated and drug-resistant infections are named among the most urgent problems facing clinicians today. Our experiments here identify a transporter interactome and portray its essential function in acquisition of antimicrobial resistance. By exposing E. coli cells to consecutive increasing concentrations of the fluoroquinolone norfloxacin we generated in the laboratory highly resistant strains that carry multiple mutations, most of them identical to those identified in clinical isolates. With this experimental paradigm, we show that the MDTs function in a coordinated mode to provide an essential first-line defense mechanism, preventing the drug reaching lethal concentrations, until a number of stable efficient alterations occur that allow survival. Single-component efflux transporters remove the toxic compounds from the cytoplasm to the periplasmic space where TolC-dependent transporters expel them from the cell. We postulate a close interaction between the two types of transporters to prevent rapid leak of the hydrophobic substrates back into the cell. The findings change the prevalent concept that in Gram-negative bacteria a single multidrug transporter, AcrAB-TolC type, is responsible for the resistance. The concept of a functional interactome, the process of identification of its members, the elucidation of the nature of the interactions and its role in cell physiology will change the existing paradigms in the field. We anticipate that our work will have an impact on the present strategy searching for inhibitors of AcrAB-TolC as adjuvants of existing antibiotics and provide novel targets for this urgent undertaking.

  13. Analyzing Orientations

    Science.gov (United States)

    Ruggles, Clive L. N.

    Archaeoastronomical field survey typically involves the measurement of structural orientations (i.e., orientations along and between built structures) in relation to the visible landscape and particularly the surrounding horizon. This chapter focuses on the process of analyzing the astronomical potential of oriented structures, whether in the field or as a desktop appraisal, with the aim of establishing the archaeoastronomical "facts". It does not address questions of data selection (see instead Chap. 25, "Best Practice for Evaluating the Astronomical Significance of Archaeological Sites", 10.1007/978-1-4614-6141-8_25) or interpretation (see Chap. 24, "Nature and Analysis of Material Evidence Relevant to Archaeoastronomy", 10.1007/978-1-4614-6141-8_22). The main necessity is to determine the azimuth, horizon altitude, and declination in the direction "indicated" by any structural orientation. Normally, there are a range of possibilities, reflecting the various errors and uncertainties in estimating the intended (or, at least, the constructed) orientation, and in more formal approaches an attempt is made to assign a probability distribution extending over a spread of declinations. These probability distributions can then be cumulated in order to visualize and analyze the combined data from several orientations, so as to identify any consistent astronomical associations that can then be correlated with the declinations of particular astronomical objects or phenomena at any era in the past. The whole process raises various procedural and methodological issues and does not proceed in isolation from the consideration of corroborative data, which is essential in order to develop viable cultural interpretations.

  14. Synthesis of an inositol hexakisphosphate (IP6) affinity probe to study the interactome from a colon cancer cell line.

    Science.gov (United States)

    Yin, Meng-Xin; Catimel, Bruno; Gregory, Mark; Condron, Melanie; Kapp, Eugene; Holmes, Andrew B; Burgess, Antony W

    2016-03-14

    Inositol hexakisphosphate (InsP6 or IP6) is an important signalling molecule in vesicular trafficking, neurotransmission, immune responses, regulation of protein kinases and phosphatases, activation of ion channels, antioxidant functions and anticancer activities. An IP6 probe was synthesised from myo-inositol via a derivatised analogue, which was immobilised through a terminal amino group onto Dynabeads. Systematic analysis of the IP6 interactome has been performed using the IP6 affinity probe using cytosolic extracts from the LIM1215 colonic carcinoma cell line. LC/MS/MS analysis identified 77 proteins or protein complexes that bind to IP6 specifically, including AP-2 complex proteins and β-arrestins as well as a number of novel potential IP6 interacting proteins. Bioinformatic enrichment analysis of the IP6 interactome reinforced the concept that IP6 regulates a number of biological processes including cell cycle and division, signal transduction, intracellular protein transport, vesicle-mediated transport and RNA splicing.

  15. Modeling gene regulatory networks: A network simplification algorithm

    Science.gov (United States)

    Ferreira, Luiz Henrique O.; de Castro, Maria Clicia S.; da Silva, Fabricio A. B.

    2016-12-01

    Boolean networks have been used for some time to model Gene Regulatory Networks (GRNs), which describe cell functions. Those models can help biologists to make predictions, prognosis and even specialized treatment when some disturb on the GRN lead to a sick condition. However, the amount of information related to a GRN can be huge, making the task of inferring its boolean network representation quite a challenge. The method shown here takes into account information about the interactome to build a network, where each node represents a protein, and uses the entropy of each node as a key to reduce the size of the network, allowing the further inferring process to focus only on the main protein hubs, the ones with most potential to interfere in overall network behavior.

  16. Investigating and Analyzing of Retrieval Status in Network Meta-analysis%网状Meta分析检索实施情况调查分析

    Institute of Scientific and Technical Information of China (English)

    田金徽; 李伦; 葛龙; 张珺; 魏成; 刘爱萍; 张俊华

    2015-01-01

    Objective:To analyze the current situation of retrieval of network Meta-analysis ( NMA) .Methods: PubMed, EM-BASE.com, Web of Science and Cochrane library were used to find potential NMA , NMA were select based on the inclusion and exclu-sion criteria.Data were extracted by Excel software and analyses were performed using STATA 12.0 software.Results:391 NMA were in-cluded in this study.The most commonly retrieved databases were Medline/PubMed, EMBASE, CENTRAL in 383 NMA,at the same time,review,ongoing trials,published Meta-analysis, conference were also searched in small number of NMA .Medline/PubMed+CEN-TRAL was the high frequency combined resources , only 270 NMA searched Medline/PubMed+EMBASE+CENTRAL,at the same time, the database and published Meta-analysis have been searched in 38.12%NMA.Conclusion:The databases have not covered basic data-bases in included NMA , especially published Meta-analysis need to be strengthened .At the same time, we should pay attention to pub-lished Meta-analysis and basic databases in the future .%目的:调查网状Meta分析(network Meta-analysis,NMA)检索实施情况. 方法:检索PubMed、EMBASE.com、Web of Sci-ence和Cochrane library等数据库获取NMA,根据预先制定的纳入和排除标准纳入符合条件的NMA,提取检索实施方面的相关条目并输入Excel,采用STATA 12.0进行统计分析. 结果:最终纳入391 篇NMA,383 篇NMA检索频率较高的数据库依次为Medline/PubMed、EMBASE和CENTRAL,辅助检索频率较高的依次为追踪综述、检索在研试验、检索已经发表的Meta分析和追踪会议文献. 检索最高的数据库组合为Medline/PubMed+CENTRAL,而只有270篇NMA同时检索了Medline/PubMed+EM-BASE+CENTRAL,只有38.12%的NMA同时检索了数据库和已经发表的Meta分析. 结论:调查显示目前NMA检索对NMA制作基本数据库检索不够,辅助检索措施尤其是对已发表Meta分析的检索有待加强. 希望今后NMA撰写者同时检索基本数据

  17. 面向智能电网的物联网技术及应用分析%Analyzing of Smart Grid Networking Technology and Application

    Institute of Scientific and Technical Information of China (English)

    凌俊斌; 刘婷

    2014-01-01

    Networking technology for smart grid is the inevitable trend of development of this technology. This paper introduced the applications of networking technology in the smart grid, and the base application system construction situation for smart grid networking technology.%物联网技术应用于智能电网,是这一技术发展的必然趋势。简要介绍物联网技术在智能电网中的应用,以及面向智能电网的物联网技术的基础应用体系建设的具体情况。

  18. MyProteinNet: build up-to-date protein interaction networks for organisms, tissues and user-defined contexts.

    Science.gov (United States)

    Basha, Omer; Flom, Dvir; Barshir, Ruth; Smoly, Ilan; Tirman, Shoval; Yeger-Lotem, Esti

    2015-07-01

    The identification of the molecular pathways active in specific contexts, such as disease states or drug responses, often requires an extensive view of the potential interactions between a subset of proteins. This view is not easily obtained: it requires the integration of context-specific protein list or expression data with up-to-date data of protein interactions that are typically spread across multiple databases. The MyProteinNet web server allows users to easily create such context-sensitive protein interaction networks. Users can automatically gather and consolidate data from up to 11 different databases to create a generic protein interaction network (interactome). They can score the interactions based on reliability and filter them by user-defined contexts including molecular expression and protein annotation. The output of MyProteinNet includes the generic and filtered interactome files, together with a summary of their network attributes. MyProteinNet is particularly geared toward building human tissue interactomes, by maintaining tissue expression profiles from multiple resources. The ability of MyProteinNet to facilitate the construction of up-to-date, context-specific interactomes and its applicability to 11 different organisms and to tens of human tissues, make it a powerful tool in meaningful analysis of protein networks. MyProteinNet is available at http://netbio.bgu.ac.il/myproteinnet. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  19. Intranuclear interactomic inhibition of NF-κB suppresses LPS-induced severe sepsis

    Energy Technology Data Exchange (ETDEWEB)

    Park, Sung-Dong [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Cheon, So Yeong [Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 120-752 (Korea, Republic of); Park, Tae-Yoon; Shin, Bo-Young [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Oh, Hyunju; Ghosh, Sankar [Department of Microbiology and Immunology, College of Physicians and Surgeons, Columbia University, New York, NY 10032 (United States); Koo, Bon-Nyeo, E-mail: koobn@yuhs.ac [Department of Anesthesiology and Pain Medicine, Anesthesia and Pain Research Institute, Yonsei University College of Medicine, Seoul 120-752 (Korea, Republic of); Lee, Sang-Kyou, E-mail: sjrlee@yonsei.ac.kr [Translational Research Center for Protein Function Control, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of); Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul 120-749 (Korea, Republic of)

    2015-08-28

    Suppression of nuclear factor-κB (NF-κB) activation, which is best known as a major regulator of innate and adaptive immune responses, is a potent strategy for the treatment of endotoxic sepsis. To inhibit NF-κB functions, we designed the intra-nuclear transducible form of transcription modulation domain (TMD) of RelA (p65), called nt-p65-TMD, which can be delivered effectively into the nucleus without influencing the cell viability, and work as interactomic inhibitors via disruption of the endogenous p65-mediated transcription complex. nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines, including TNF-α, IL-1β, or IL-6 from BV2 microglia cells stimulated by lipopolysaccharide (LPS). nt-p65-TMD did not inhibit tyrosine phosphorylation of signaling mediators such as ZAP-70, p38, JNK, or ERK involved in T cell activation, but was capable of suppressing the transcriptional activity of NF-κB without the functional effect on that of NFAT upon T-cell receptor (TCR) stimulation. The transduced nt-p65-TMD in T cell did not affect the expression of CD69, however significantly inhibited the secretion of T cell-specific cytokines such as IL-2, IFN-γ, IL-4, IL-17A, or IL-10. Systemic administration of nt-p65-TMD showed a significant therapeutic effect on LPS-induced sepsis model by inhibiting pro-inflammatory cytokines secretion. Therefore, nt-p65-TMD can be a novel therapeutics for the treatment of various inflammatory diseases, including sepsis, where a transcription factor has a key role in pathogenesis, and further allows us to discover new functions of p65 under normal physiological condition without genetic alteration. - Highlights: • The nt-p65-TMD is intra-nuclear interactomic inhibitor of endogenous p65. • The nt-p65-TMD effectively inhibited the secretion of pro-inflammatory cytokines. • The excellent therapeutic potential of nt-p65-TMD was confirmed in sepsis model.

  20. IPv6 Protocol Analyzer

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    With the emerging of next generation Intemet protocol (IPv6), it is expected to replace the current version of Internet protocol (IPv4) that will be exhausted in the near future. Besides providing adequate address space, some other new features are included into the new 128 bits of IP such as IP auto configuration, quality of service, simple routing capability, security, mobility and multicasting. The current protocol analyzer will not be able to handle IPv6 packets. This paper will focus on developing protocol analyzer that decodes IPv6 packet. IPv6 protocol analyzer is an application module,which is able to decode the IPv6 packet and provide detail breakdown of the construction of the packet. It has to understand the detail construction of the IPv6, and provide a high level abstraction of bits and bytes of the IPv6 packet.Thus it increases network administrators' understanding of a network protocol,helps he/she in solving protocol related problem in a IPv6 network environment.

  1. 网银犯罪活动的现状分析及防范对策%Analyze to current situation of crime and countermeasures of Network Bank

    Institute of Scientific and Technical Information of China (English)

    赵晓松

    2011-01-01

    在网络银行业务日渐发展的同时,其安全性问题已经成为制约网银发展的主要因素.自2005年起,关于网络银行的安全问题严重性的报道和争执就有愈演愈烈的趋势.近几年,发生多起倍受关注的网银安全事件发生.多名网银客户发生网上资金被盗事件,涉及20多个省份.本文针对网络银行犯罪活动的现状进行了成因分析,从计算机技术角度提出了若干防范策略.最后,文章提出了制止网银犯罪的其他策略与方法,指出打击网银犯罪将是一个长期和艰巨的任务,有待各方面的力量集中统一起来.%With the network bank business development in the meantime, the growing security problem has already become the main factors restricting network bank development. Since 2005, about the network bank security problems of severity reports and dispute have intensified trend. In recent years, more people pay more attention to the occur of network bank's safety incident. Many network bank client happen online fund stolen events, involving more than 20 provinces. This paper in view of the network bank criminal activities on the current situation of genesis analysis, from computer technology Angle, puts forward some preventive strategy. Finally, this paper puts forward the other strategies and methods to stop network bank crime, and points out that the strike of network bank crime will be a long-term and arduous task, expect to all kinds of power to be centralized and unified.

  2. 3D structure prediction of replication factor C subunits (RFC and their interactome in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Mohamed Ragab Abdel Gawwad

    2013-06-01

    Full Text Available DNA stress can causes potentially spontaneous genome damage during DNA replication process. Proteins involved in this process are DNA-dependent ATPases, required for replication and repair. In this study the 3-D structure of RFC protein subunits in Arabidopsis thaliana: RFC1, RFC2, RFC3, RFC4 and RFC5 are predicted and confirmed by Ramachadran plot. The amino acid sequences are highly similar to the sequences of the homologous human RFC 140-, 37-, 36-, 40-, and 38 kDa subunits, respectively, and also show amino acid sequence similarity to functionally homologous proteins from E. coli. All five subunits show conserved regions characteristic of ATP/GTP-binding proteins and have significant degree of similarity among each other. The segments of conserved amino acid sequences that define a family of related proteins have been identified. RFC1 is identical to CDC44, a gene identified as a cell division cycle gene encoding a protein involved in DNA metabolism. Subcellular localization and interactions of each protein RFC protein subunit is determined. It subsequently became clear that RFC proteins and their interactome have functions in cell cycle regulation and/or DNA replication and repair processes. In addition, AtRFC subunits are controlling the biosynthesis of salicylic and salicylic acid-mediated defense responses in Arabidopsis.

  3. Efficient Prediction of Progesterone Receptor Interactome Using a Support Vector Machine Model

    Directory of Open Access Journals (Sweden)

    Ji-Long Liu

    2015-03-01

    Full Text Available Protein-protein interaction (PPI is essential for almost all cellular processes and identification of PPI is a crucial task for biomedical researchers. So far, most computational studies of PPI are intended for pair-wise prediction. Theoretically, predicting protein partners for a single protein is likely a simpler problem. Given enough data for a particular protein, the results can be more accurate than general PPI predictors. In the present study, we assessed the potential of using the support vector machine (SVM model with selected features centered on a particular protein for PPI prediction. As a proof-of-concept study, we applied this method to identify the interactome of progesterone receptor (PR, a protein which is essential for coordinating female reproduction in mammals by mediating the actions of ovarian progesterone. We achieved an accuracy of 91.9%, sensitivity of 92.8% and specificity of 91.2%. Our method is generally applicable to any other proteins and therefore may be of help in guiding biomedical experiments.

  4. Interactome of Radiation-Induced microRNA-Predicted Target Genes

    Directory of Open Access Journals (Sweden)

    Tenzin W. Lhakhang

    2012-01-01

    Full Text Available The microRNAs (miRNAs function as global negative regulators of gene expression and have been associated with a multitude of biological processes. The dysfunction of the microRNAome has been linked to various diseases including cancer. Our laboratory recently reported modulation in the expression of miRNA in a variety of cell types exposed to ionizing radiation (IR. To further understand miRNA role in IR-induced stress pathways, we catalogued a set of common miRNAs modulated in various irradiated cell lines and generated a list of predicted target genes. Using advanced bioinformatics tools we identified cellular pathways where miRNA predicted target genes function. The miRNA-targeted genes were found to play key roles in previously identified IR stress pathways such as cell cycle, p53 pathway, TGF-beta pathway, ubiquitin-mediated proteolysis, focal adhesion pathway, MAPK signaling, thyroid cancer pathway, adherens junction, insulin signaling pathway, oocyte meiosis, regulation of actin cytoskeleton, and renal cell carcinoma pathway. Interestingly, we were able to identify novel targeted pathways that have not been identified in cellular radiation response, such as aldosterone-regulated sodium reabsorption, long-term potentiation, and neutrotrophin signaling pathways. Our analysis indicates that the miRNA interactome in irradiated cells provides a platform for comprehensive modeling of the cellular stress response to IR exposure.

  5. Elucidation of the Cellular Interactome of Ebola Virus Nucleoprotein and Identification of Therapeutic Targets.

    Science.gov (United States)

    García-Dorival, Isabel; Wu, Weining; Armstrong, Stuart D; Barr, John N; Carroll, Miles W; Hewson, Roger; Hiscox, Julian A

    2016-12-02

    Ebola virus (EBOV) infection results in severe disease and in some cases lethal hemorrhagic fever. The infection is directed by seven viral genes that encode nine viral proteins. By definition, viruses are obligate intracellular parasites and require aspects of host cell biology in order to replicate their genetic material, assemble new virus particles, and subvert host cell antiviral responses. Currently licensed antivirals are targeted against viral proteins to inhibit their function. However, experience with treating HIV and influenza virus demonstrates that resistant viruses are soon selected. An emerging area in virology is to transiently target host cell proteins that play critical proviral roles in virus biology, especially for acute infections. This has the advantage that the protein being targeted is evolutionary removed from the genome of the virus. Proteomics can aid in discovery biology and identify cellular proteins that may be utilized by the virus to facilitate infection. This work focused on defining the interactome of the EBOV nucleoprotein and identified that cellular chaperones, including HSP70, associate with this protein to promote stability. Utilization of a mini-genome replication system based on a recent Makona isolate demonstrated that disrupting the stability of NP had an adverse effect on viral RNA synthesis.

  6. Comprehensive RNA Polymerase II Interactomes Reveal Distinct and Varied Roles for Each Phospho-CTD Residue

    Directory of Open Access Journals (Sweden)

    Kevin M. Harlen

    2016-06-01

    Full Text Available Transcription controls splicing and other gene regulatory processes, yet mechanisms remain obscure due to our fragmented knowledge of the molecular connections between the dynamically phosphorylated RNA polymerase II (Pol II C-terminal domain (CTD and regulatory factors. By systematically isolating phosphorylation states of the CTD heptapeptide repeat (Y1S2P3T4S5P6S7, we identify hundreds of protein factors that are differentially enriched, revealing unappreciated connections between the Pol II CTD and co-transcriptional processes. These data uncover a role for threonine-4 in 3′ end processing through control of the transition between cleavage and termination. Furthermore, serine-5 phosphorylation seeds spliceosomal assembly immediately downstream of 3′ splice sites through a direct interaction with spliceosomal subcomplex U1. Strikingly, threonine-4 phosphorylation also impacts splicing by serving as a mark of co-transcriptional spliceosome release and ensuring efficient post-transcriptional splicing genome-wide. Thus, comprehensive Pol II interactomes identify the complex and functional connections between transcription machinery and other gene regulatory complexes.

  7. Characterization of the Drosophila Atlastin Interactome Reveals VCP as a Functionally Related Interactor

    Institute of Scientific and Technical Information of China (English)

    Niamh C.O'Sullivan; Nina Dr(a)ger; Cahir J.O'Kane

    2013-01-01

    At least 25 genes,many involved in trafficking,localisation or shaping of membrane organelles,have been identified as causative genes for the neurodegenerative disorder hereditary spastic paraplegia (HSP).One of the most commonly mutated HSP genes,atlastin-1,encodes a dynamin-like GTPase that mediates homotypic fusion of endoplasmic reticulum (ER) membranes.However,the molecular mechanisms of atlastin-l-related membrane fusion and axonopathy remain unclear.To better understand its mode of action,we used affinity purification coupled with mass spectrometry to identify protein interactors of atlastin in Drosophila.Analysis of 72 identified proteins revealed that the atlastin interactome contains many proteins involved in protein processing and transport,in addition to proteins with roles in mRNA binding,metabolism and mitochondrial proteins.The highest confidence interactor from mass spectrometry analysis,the ubiquitin-selective AAA-ATPase valosin-containing protein (VCP),was validated as an atlastin-interacting protein,and VCP and atlastin showed overlapping subcellular distributions.Furthermore,VCP acted as a genetic modifier of atlastin:loss of VCP partially suppressed an eye phenotype caused by atlastin overexpression,whereas overexpression of VCP enhanced this phenotype.These interactions between atlastin and VCP suggest a functional relationship between these two proteins,and point to potential shared mechanisms between HSP and other forms of neurodegeneration.

  8. Influence of Slow Oscillation on Hippocampal Activity and Ripples Through Cortico-Hippocampal Synaptic Interactions, Analyzed by a Cortical-CA3-CA1 Network Model

    Directory of Open Access Journals (Sweden)

    Jiannis eTaxidis

    2013-02-01

    Full Text Available Hippocampal sharp wave-ripple complexes (SWRs involve the synchronous discharge of thousands of cells throughout the CA3-CA1-subiculum-entorhinal cortex axis. Their strong transient output affects cortical targets, rendering SWRs a possible means for memory transfer from the hippocampus to the neocortex for long-term storage. Neurophysiological observations of hippocampal activity modulation by the cortical slow oscillation (SO during deep sleep and anesthesia, and correlations between ripples and UP states, support the role of SWRs in memory consolidation through a cortico-hippocampal feedback loop. We couple a cortical network exhibiting SO with a hippocampal CA3-CA1 computational network model exhibiting SWRs, in order to model such cortico-hippocampal correlations and uncover important parameters and coupling mechanisms controlling them. The cortical oscillatory output entrains the CA3 network via connections representing the mossy fiber input, and the CA1 network via the temporoammonic pathway. The spiking activity in CA3 and CA1 is shown to depend on the excitation-to-inhibition ratio, induced by combining the two hippocampal inputs, with mossy fiber input controlling the UP-state correlation of CA3 population bursts and corresponding SWRs, whereas the temporoammonic input affects the overall CA1 spiking activity. Ripple characteristics and pyramidal spiking participation to SWRs are shaped by the strength of the Schaffer collateral drive. A set of in vivo recordings from the rat hippocampus confirms a model-predicted segregation of pyramidal cells into subgroups according to the SO state where they preferentially fire and their response to SWRs. These groups can potentially play distinct functional roles in the replay of spike sequences.

  9. Interactomes to Biological Phase Space: a call to begin thinking at a new level in computational biology.

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, George S.; Brown, William Michael

    2007-09-01

    Techniques for high throughput determinations of interactomes, together with high resolution protein collocalizations maps within organelles and through membranes will soon create a vast resource. With these data, biological descriptions, akin to the high dimensional phase spaces familiar to physicists, will become possible. These descriptions will capture sufficient information to make possible realistic, system-level models of cells. The descriptions and the computational models they enable will require powerful computing techniques. This report is offered as a call to the computational biology community to begin thinking at this scale and as a challenge to develop the required algorithms and codes to make use of the new data.3

  10. Identification of the dichotomous role of age-related LCK in calorie restriction revealed by integrative analysis of cDNA microarray and interactome.

    Science.gov (United States)

    Park, Daeui; Lee, Eun Kyeong; Jang, Eun Jee; Jeong, Hyoung Oh; Kim, Byoung-Chul; Ha, Young Mi; Hong, Seong Eui; Yu, Byung Pal; Chung, Hae Young

    2013-08-01

    Among the many experimental paradigms used for the investigation of aging, the calorie restriction (CR) model has been proven to be the most useful in gerontological research. Exploration of the mechanisms underlying CR has produced a wealth of data. To identify key molecules controlled by aging and CR, we integrated data from 84 mouse and rat cDNA microarrays with a protein-protein interaction network. On the basis of this integrative analysis, we selected three genes that are upregulated in aging but downregulated by CR and two genes that are downregulated in aging but upregulated by CR. One of these key molecules is lymphocyte-specific protein tyrosine kinase (LCK). To further confirm this result on LCK, we performed a series of experiments in vitro and in vivo using kidneys obtained from aged ad libitum-fed and CR rats. Our major significant findings are as follows: (1) identification of LCK as a key molecule using integrative analysis; (2) confirmation that the age-related increase in LCK was modulated by CR and that protein tyrosine kinase activity was decreased using a LCK-specific inhibitor; and (3) upregulation of LCK leads to NF-κB activation in a ONOO(-) generation-dependent manner, which is modulated by CR. These results indicate that LCK could be considered a target attenuated by the anti-aging effects of CR. Integrative analysis of cDNA microarray and interactome data are powerful tools for identifying target molecules that are involved in the aging process and modulated by CR.

  11. Harvesting candidate genes responsible for serious adverse drug reactions from a chemical-protein interactome.

    Directory of Open Access Journals (Sweden)

    Lun Yang

    2009-07-01

    Full Text Available Identifying genetic factors responsible for serious adverse drug reaction (SADR is of critical importance to personalized medicine. However, genome-wide association studies are hampered due to the lack of case-control samples, and the selection of candidate genes is limited by the lack of understanding of the underlying mechanisms of SADRs. We hypothesize that drugs causing the same type of SADR might share a common mechanism by targeting unexpectedly the same SADR-mediating protein. Hence we propose an approach of identifying the common SADR-targets through constructing and mining an in silico chemical-protein interactome (CPI, a matrix of binding strengths among 162 drug molecules known to cause at least one type of SADR and 845 proteins. Drugs sharing the same SADR outcome were also found to possess similarities in their CPI profiles towards this 845 protein set. This methodology identified the candidate gene of sulfonamide-induced toxic epidermal necrolysis (TEN: all nine sulfonamides that cause TEN were found to bind strongly to MHC I (Cw*4, whereas none of the 17 control drugs that do not cause TEN were found to bind to it. Through an insight into the CPI, we found the Y116S substitution of MHC I (B*5703 enhances the unexpected binding of abacavir to its antigen presentation groove, which explains why B*5701, not B*5703, is the risk allele of abacavir-induced hypersensitivity. In conclusion, SADR targets and the patient-specific off-targets could be identified through a systematic investigation of the CPI, generating important hypotheses for prospective experimental validation of the candidate genes.

  12. An affinity pull-down approach to identify the plant cyclic nucleotide interactome

    KAUST Repository

    Donaldson, Lara Elizabeth

    2013-09-03

    Cyclic nucleotides (CNs) are intracellular second messengers that play an important role in mediating physiological responses to environmental and developmental signals, in species ranging from bacteria to humans. In response to these signals, CNs are synthesized by nucleotidyl cyclases and then act by binding to and altering the activity of downstream target proteins known as cyclic nucleotide-binding proteins (CNBPs). A number of CNBPs have been identified across kingdoms including transcription factors, protein kinases, phosphodiesterases, and channels, all of which harbor conserved CN-binding domains. In plants however, few CNBPs have been identified as homology searches fail to return plant sequences with significant matches to known CNBPs. Recently, affinity pull-down techniques have been successfully used to identify CNBPs in animals and have provided new insights into CN signaling. The application of these techniques to plants has not yet been extensively explored and offers an alternative approach toward the unbiased discovery of novel CNBP candidates in plants. Here, an affinity pull-down technique for the identification of the plant CN interactome is presented. In summary, the method involves an extraction of plant proteins which is incubated with a CN-bait, followed by a series of increasingly stringent elutions that eliminates proteins in a sequential manner according to their affinity to the bait. The eluted and bait-bound proteins are separated by one-dimensional gel electrophoresis, excised, and digested with trypsin after which the resultant peptides are identified by mass spectrometry - techniques that are commonplace in proteomics experiments. The discovery of plant CNBPs promises to provide valuable insight into the mechanism of CN signal transduction in plants. © Springer Science+Business Media New York 2013.

  13. Analyzing Thiol-Dependent Redox Networks in the Presence of Methylene Blue and Other Antimalarial Agents with RT-PCR-Supported in silico Modeling

    Science.gov (United States)

    Zirkel, J.; Cecil, A.; Schäfer, F.; Rahlfs, S.; Ouedraogo, A.; Xiao, K.; Sawadogo, S.; Coulibaly, B.; Becker, K.; Dandekar, T.

    2012-01-01

    Background In the face of growing resistance in malaria parasites to drugs, pharmacological combination therapies are important. There is accumulating evidence that methylene blue (MB) is an effective drug against malaria. Here we explore the biological effects of both MB alone and in combination therapy using modeling and experimental data. Results We built a model of the central metabolic pathways in P. falciparum. Metabolic flux modes and their changes under MB were calculated by integrating experimental data (RT-PCR data on mRNAs for redox enzymes) as constraints and results from the YANA software package for metabolic pathway calculations. Several different lines of MB attack on Plasmodium redox defense were identified by analysis of the network effects. Next, chloroquine resistance based on pfmdr/and pfcrt transporters, as well as pyrimethamine/sulfadoxine resistance (by mutations in DHF/DHPS), were modeled in silico. Further modeling shows that MB has a favorable synergism on antimalarial network effects with these commonly used antimalarial drugs. Conclusions Theoretical and experimental results support that methylene blue should, because of its resistance-breaking potential, be further tested as a key component in drug combination therapy efforts in holoendemic areas. PMID:23236254

  14. Use of pruned computational neural networks for processing the response of oscillating chemical reactions with a view to analyzing nonlinear multicomponent mixtures.

    Science.gov (United States)

    Hervás, C; Toledo, R; Silva, M

    2001-01-01

    The suitability of pruned computational neural networks (CNNs) for resolving nonlinear multicomponent systems involving synergistic effects by use of oscillating chemical reaction-based methods implemented using the analyte pulse perturbation technique is demonstrated. The CNN input data used for this purpose are estimates provided by the Levenberg-Marquardt method in the form of a three-parameter Gaussian curve associated with the singular profile obtained when the oscillating system is perturbed by an analyte mixture. The performance of the proposed method was assessed by applying it to the resolution of mixtures of pyrogallol and gallic acid based on their perturbating effect on a classical oscillating chemical system, viz. the Belousov-Zhabotinskyi reaction. A straightforward network topology (3:3:2, with 18 connections after pruning) allowed the resolution of mixtures of the two analytes in concentration ratios from 1:7 to 6:2 with a standard error of prediction for the testing set of 4.01 and 8.98% for pyrogallol and gallic acid, respectively. The reduced dimensions of the selected CNN architecture allowed a mathematical transformation of the input vector into the output one that can be easily implemented via software. Finally, the suitability of response surface analysis as an alternative to CNNs was also tested. The results were poor (relative errors were high), which confirms that properly selected pruned CNNs are effective tools for solving the analytical problem addressed in this work.

  15. TFmiR: a web server for constructing and analyzing disease-specific transcription factor and miRNA co-regulatory networks.

    Science.gov (United States)

    Hamed, Mohamed; Spaniol, Christian; Nazarieh, Maryam; Helms, Volkhard

    2015-07-01

    TFmiR is a freely available web server for deep and integrative analysis of combinatorial regulatory interactions between transcription factors, microRNAs and target genes that are involved in disease pathogenesis. Since the inner workings of cells rely on the correct functioning of an enormously complex system of activating and repressing interactions that can be perturbed in many ways, TFmiR helps to better elucidate cellular mechanisms at the molecular level from a network perspective. The provided topological and functional analyses promote TFmiR as a reliable systems biology tool for researchers across the life science communities. TFmiR web server is accessible through the following URL: http://service.bioinformatik.uni-saarland.de/tfmir.

  16. Perturbation waves in proteins and protein networks: Applications of percolation and game theories in signaling and drug design

    CERN Document Server

    Antal, Miklos A; Csermely, Peter

    2008-01-01

    The network paradigm is increasingly used to describe the dynamics of complex systems. Here we review the current results and propose future development areas in the assessment of perturbation waves, i.e. propagating structural changes in amino acid networks building individual protein molecules and in protein-protein interaction networks (interactomes). We assess the possibilities and critically review the initial attempts for the application of game theory to the often rather complicated process, when two protein molecules approach each other, mutually adjust their conformations via multiple communication steps and finally, bind to each other. We also summarize available data on the application of percolation theory for the prediction of amino acid network- and interactome-dynamics. Furthermore, we give an overview of the dissection of signals and noise in the cellular context of various perturbations. Finally, we propose possible applications of the reviewed methodologies in drug design.

  17. Toxoplasmosis and Polygenic Disease Susceptibility Genes: Extensive Toxoplasma gondii Host/Pathogen Interactome Enrichment in Nine Psychiatric or Neurological Disorders

    Directory of Open Access Journals (Sweden)

    C. J. Carter

    2013-01-01

    Full Text Available Toxoplasma gondii is not only implicated in schizophrenia and related disorders, but also in Alzheimer's or Parkinson's disease, cancer, cardiac myopathies, and autoimmune disorders. During its life cycle, the pathogen interacts with ~3000 host genes or proteins. Susceptibility genes for multiple sclerosis, Alzheimer's disease, schizophrenia, bipolar disorder, depression, childhood obesity, Parkinson's disease, attention deficit hyperactivity disorder (multiple sclerosis, and autism (, but not anorexia or chronic fatigue are highly enriched in the human arm of this interactome and 18 (ADHD to 33% (MS of the susceptibility genes relate to it. The signalling pathways involved in the susceptibility gene/interactome overlaps are relatively specific and relevant to each disease suggesting a means whereby susceptibility genes could orient the attentions of a single pathogen towards disruption of the specific pathways that together contribute (positively or negatively to the endophenotypes of different diseases. Conditional protein knockdown, orchestrated by T. gondii proteins or antibodies binding to those of the host (pathogen derived autoimmunity and metabolite exchange, may contribute to this disruption. Susceptibility genes may thus be related to the causes and influencers of disease, rather than (and as well as to the disease itself.

  18. Comprehensively Characterizing the Thioredoxin Interactome In Vivo Highlights the Central Role Played by This Ubiquitous Oxidoreductase in Redox Control.

    Science.gov (United States)

    Arts, Isabelle S; Vertommen, Didier; Baldin, Francesca; Laloux, Géraldine; Collet, Jean-François

    2016-06-01

    Thioredoxin (Trx) is a ubiquitous oxidoreductase maintaining protein-bound cysteine residues in the reduced thiol state. Here, we combined a well-established method to trap Trx substrates with the power of bacterial genetics to comprehensively characterize the in vivo Trx redox interactome in the model bacterium Escherichia coli Using strains engineered to optimize trapping, we report the identification of a total 268 Trx substrates, including 201 that had never been reported to depend on Trx for reduction. The newly identified Trx substrates are involved in a variety of cellular processes, ranging from energy metabolism to amino acid synthesis and transcription. The interaction between Trx and two of its newly identified substrates, a protein required for the import of most carbohydrates, PtsI, and the bacterial actin homolog MreB was studied in detail. We provide direct evidence that PtsI and MreB contain cysteine residues that are susceptible to oxidation and that participate in the formation of an intermolecular disulfide with Trx. By considerably expanding the number of Trx targets, our work highlights the role played by this major oxidoreductase in a variety of cellular processes. Moreover, as the dependence on Trx for reduction is often conserved across species, it also provides insightful information on the interactome of Trx in organisms other than E. coli.

  19. FMGN, RENUMN, POLY, TRIPOLY: Suite of Programs for calculating and analyzing flow and transport in fracture networks embedded in porous matrix blocks

    Energy Technology Data Exchange (ETDEWEB)

    Birkhoelzer, J.; Karasaki, K.

    1996-09-01

    This report describes a suite of programs developed at the Ernest Orlando Lawrence Berkeley National Laboratory (Berkeley Lab) for simulating flow and solute transport in fracture networks embedded in porous matrix blocks. The codes FMGN, RENUMN and TRIPOLY are extensions of the older codes FMG, RENUM and TRINET developed at the Berkeley Lab, and references are made to previous Berkeley Lab reports which describe those codes. The first section of this report describes the general background of TRIPOLY and the theory of treating the fluid and solute exchange between fractures and rock. The second section is a user`s manual for the programs FMGN, RENUMN, POLY and TRIPOLY. Note that the description of FMGN and RENUMN is very short in this section. FMGN and RENUMN are relatively unchanged from the old codes FMG and RENUM, and only the differences between the old and new versions are listed in this report. For work with FMGN and RENUMN we refer to the detailed description of theory and design in BILLAUX et al. and the user`s manual in BILLAUX et al. respectively. For the other codes POLY (newly developed) and TRIPOLY (features major changes compared to the old program version TRINET) a detailed user`s manual is enclosed in this report. It provides the user with sufficient information to run the programs. The third section of this report comprises some sample problems as a tutorial.

  20. Application of analyzing a network by EPANET in renovation of water supply network for mine dust prevention%EPANET管网分析在矿井防尘供水管网改造中的应用

    Institute of Scientific and Technical Information of China (English)

    侯晓东

    2015-01-01

    为解决开滦集团崔家寨矿部分采掘工作面供水压力低, 导致防尘设施达不到预期防尘效果的问题,通过对实际矿井防尘供水管网进行合理简化处理,利用EPANET管网模型对防尘管网系统进行了水力分析,针对现有管网设计存在的问题,提出了改造设计方案,并对方案解决问题的有效性进行了验证.%The water supply pressure of some mining work faces in Cuijiazhai mine, Kailuan Group, is below the basic requirements. The ef-fect of dust removal by dustproof facilities in these work faces is not acceptable. To improve the effect of dust removal, the EPANET network model was used to do hydraulic calculation,the disadvantages of present water supply network were specified. The water supply network in Cuijiazhai mine was simplified firstly for network analysis by EPANET software. A renovation design of the water supply network is given. The effectiveness of the renovation is verified by EPANET hydraulic analysis.

  1. 基于 PCI-E 总线的智能变电站网络记录分析仪研制%Development of a Network Recording Analyzer in the Smart Substation Based on PCI-E Bus

    Institute of Scientific and Technical Information of China (English)

    檀永; 侯明国; 沈健

    2015-01-01

    The network recording analyzer is a device for recording,monitoring and analyzing network data in the smart substation,which can find weak links and the malfunction equipment of the communication network in advance,prevent failures in the electric power system,and restore the faulty waveform of the primary equipment of the power system as well as the records of the action and behavior of its secondary equipment in case of power system failures,thus facilitating analysis and quick trouble-shooting once an accident happens.Real-time acquisition,high-speed storage and efficient extraction of massive network data in the smart substation are the difficult points in the development of a network recording analyzer.Based on a deep analysis of PCI-E,this paper gives a details introduction of a hardware platform for the network recording analyzer of the smart substation based on PCI-E bus,and briefly describes the key points for the design of the driver software,thus providing a feasible implementation scheme for the acquisition and storage of massive network data in the network recording analyzer.%网络记录分析仪是智能变电站内的网络数据记录、监视、分析设备,它可提前发现通信网络的薄弱环节和故障设备,预防电力系统事故的发生,并在发生电力系统故障时,还原电力系统一次设备故障波形以及二次设备动作行为记录,便于事故发生后进行分析和快速查找故障原因。智能变电站内海量网络数据的实时采集、高速存储、高效提取是研制网络记录分析仪的难点。在深入分析第三代总线通信接口标准 PCI-E 总线的基础上,详细介绍了一种基于 PCI-E 总线的智能变电站网络记录分析仪硬件平台,同时简要概述了驱动软件的设计要点,为网络记录分析仪海量网络数据的采集、存储提供了一个切实可行的实现方案。

  2. Complex Systems Analysis of Cell Cycling Models in Carcinogenesis:II. Cell Genome and Interactome, Neoplastic Non-random Transformation Models in Topoi with Lukasiewicz-Logic and MV Algebras

    CERN Document Server

    Baianu, I C

    2004-01-01

    Quantitative Biology, abstract q-bio.OT/0406045 From: I.C. Baianu Dr. [view email] Date (v1): Thu, 24 Jun 2004 02:45:13 GMT (164kb) Date (revised v2): Fri, 2 Jul 2004 00:58:06 GMT (160kb) Complex Systems Analysis of Cell Cycling Models in Carcinogenesis: II. Authors: I.C. Baianu Comments: 23 pages, 1 Figure Report-no: CC04 Subj-class: Other Carcinogenesis is a complex process that involves dynamically inter-connected modular sub-networks that evolve under the influence of micro-environmentally induced perturbations, in non-random, pseudo-Markov chain processes. An appropriate n-stage model of carcinogenesis involves therefore n-valued Logic treatments of nonlinear dynamic transformations of complex functional genomes and cell interactomes. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous, Boolean or "fuzzy", logic models of genetic activities in vivo....

  3. A potential role for intragenic miRNAs on their hosts' interactome

    Directory of Open Access Journals (Sweden)

    Kuo Winston P

    2010-10-01

    feedback loops between intragenic miRNAs, host genes, and miRNA target genes. We describe, how higher-order miRNA feedback on hosts' interactomes may at least in part explain correlation patterns observed between expression of host genes and intragenic miRNA targets in healthy and tumor tissue.

  4. Analyzing viewpoint diversity in twitter

    OpenAIRE

    2013-01-01

    Information diversity has a long tradition in human history. Recently there have been claims that diversity is diminishing in information available in social networks. On the other hand, some studies suggest that diversity is actually quite high in social networks such as Twitter. However these studies only focus on the concept of source diversity and they only focus on American users. In this paper we analyze different dimensions of diversity. We also provide an experimental design in which ...

  5. Comparative interactomics for virus-human protein-protein interactions: DNA viruses versus RNA viruses.

    Science.gov (United States)

    Durmuş, Saliha; Ülgen, Kutlu Ö

    2017-01-01

    Viruses are obligatory intracellular pathogens and completely depend on their hosts for survival and reproduction. The strategies adopted by viruses to exploit host cell processes and to evade host immune systems during infections may differ largely with the type of the viral genetic material. An improved understanding of these viral infection mechanisms is only possible through a better understanding of the pathogen-host interactions (PHIs) that enable viruses to enter into the host cells and manipulate the cellular mechanisms to their own advantage. Experimentally-verified protein-protein interaction (PPI) data of pathogen-host systems only became available at large scale within the last decade. In this study, we comparatively analyzed the current PHI networks belonging to DNA and RNA viruses and their human host, to get insights into the infection strategies used by these viral groups. We investigated the functional properties of human proteins in the PHI networks, to observe and compare the attack strategies of DNA and RNA viruses. We observed that DNA viruses are able to attack both human cellular and metabolic processes simultaneously during infections. On the other hand, RNA viruses preferentially interact with human proteins functioning in specific cellular processes as well as in intracellular transport and localization within the cell. Observing virus-targeted human proteins, we propose heterogeneous nuclear ribonucleoproteins and transporter proteins as potential antiviral therapeutic targets. The observed common and specific infection mechanisms in terms of viral strategies to attack human proteins may provide crucial information for further design of broad and specific next-generation antiviral therapeutics.

  6. Automation models for analyzing the resource status of telecom networks based on large scale data%基于大量数据分析电信网络资源状况的自动化模型

    Institute of Scientific and Technical Information of China (English)

    谢璨

    2012-01-01

      Nowadays, the structure of telecom networks becomes complicated, and accordingly the cost on network operation and maintenance grows. In this rapidly changing and so highly competitive environment, to improve network quality and premium customer service and in the meantime to monitor the cost on network operation and maintenance, telecom companies need to enhance the automation and intellectualization of relevant work. Based on the large-scale data generated from customer’s usage of data business, we build automation models for analyzing the resource status of different businesses and make it possible to provide more objective support reflecting users’ perception to decision-making on network operation and optimization in real-time.%  在电信网络结构日趋复杂,运维工作日益繁多的情况下,运营商若想提高网络质量和服务水平,而且还要控制运维成本,最好的办法就是使很多工作高度自动化和智能化。本文基于用户使用数据业务产生的大量数据,建立了达到业务精度的分析电信网络资源状况的自动化模型,可以及时、客观、更能体现用户感知地为网络维护和网络优化提供决策信息。

  7. Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

    Science.gov (United States)

    Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

    2016-06-20

    A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

  8. Analyzing competition in intermodal freight transport networks

    NARCIS (Netherlands)

    Saeedi, Hamid; Wiegmans, Bart; Behdani, Behzad; Zuidwijk, Rob

    2017-01-01

    To cope with an intense and competitive environment, intermodal freight transport operators have increasingly adopted business practices —like horizontal and vertical business integration—which aim to reduce the operational costs, increase the profit margins, and improve their competitive position

  9. A second-generation protein-protein interaction network of Helicobacter pylori.

    Science.gov (United States)

    Häuser, Roman; Ceol, Arnaud; Rajagopala, Seesandra V; Mosca, Roberto; Siszler, Gabriella; Wermke, Nadja; Sikorski, Patricia; Schwarz, Frank; Schick, Matthias; Wuchty, Stefan; Aloy, Patrick; Uetz, Peter

    2014-05-01

    Helicobacter pylori infections cause gastric ulcers and play a major role in the development of gastric cancer. In 2001, the first protein interactome was published for this species, revealing over 1500 binary protein interactions resulting from 261 yeast two-hybrid screens. Here we roughly double the number of previously published interactions using an ORFeome-based, proteome-wide yeast two-hybrid screening strategy. We identified a total of 1515 protein-protein interactions, of which 1461 are new. The integration of all the interactions reported in H. pylori results in 3004 unique interactions that connect about 70% of its proteome. Excluding interactions of promiscuous proteins we derived from our new data a core network consisting of 908 interactions. We compared our data set to several other bacterial interactomes and experimentally benchmarked the conservation of interactions using 365 protein pairs (interologs) of E. coli of which one third turned out to be conserved in both species.

  10. Analyzing the Facebook Friendship Graph

    OpenAIRE

    Catanese, Salvatore; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo

    2010-01-01

    Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a significant sample of data reflecting relationships among subscribed users. Our goal is to extract, from this platform, relevant ...

  11. A mesoscale abscisic acid hormone interactome reveals a dynamic signaling landscape in Arabidopsis.

    Science.gov (United States)

    Lumba, Shelley; Toh, Shigeo; Handfield, Louis-François; Swan, Michael; Liu, Raymond; Youn, Ji-Young; Cutler, Sean R; Subramaniam, Rajagopal; Provart, Nicholas; Moses, Alan; Desveaux, Darrell; McCourt, Peter

    2014-05-12

    The sesquiterpenoid abscisic acid (ABA) mediates an assortment of responses across a variety of kingdoms including both higher plants and animals. In plants, where most is known, a linear core ABA signaling pathway has been identified. However, the complexity of ABA-dependent gene expression suggests that ABA functions through an intricate network. Here, using systems biology approaches that focused on genes transcriptionally regulated by ABA, we defined an ABA signaling network of over 500 interactions among 138 proteins. This map greatly expanded ABA core signaling but was still manageable for systematic analysis. For example, functional analysis was used to identify an ABA module centered on two sucrose nonfermenting (SNF)-like kinases. We also used coexpression analysis of interacting partners within the network to uncover dynamic subnetwork structures in response to different abiotic stresses. This comprehensive ABA resource allows for application of approaches to understanding ABA functions in higher plants. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online

    Directory of Open Access Journals (Sweden)

    Chen Chang-Han

    2007-02-01

    Full Text Available Abstract Background The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level. Results Here, we build an integrative platform, the Encyclopedia of Hepatocellular Carcinoma genes Online, dubbed EHCO http://ehco.iis.sinica.edu.tw, to systematically collect, organize and compare the pileup of unsorted HCC-related studies by using natural language processing and softbots. Among the eight gene set collections, ranging across PubMed, SAGE, microarray, and proteomics data, there are 2,906 genes in total; however, more than 77% genes are only included once, suggesting that tremendous efforts need to be exerted to characterize the relationship between HCC and these genes. Of these HCC inventories, protein binding represents the largest proportion (~25% from Gene Ontology analysis. In fact, many differentially expressed gene sets in EHCO could form interaction networks (e.g. HBV-associated HCC network by using available human protein-protein interaction datasets. To further highlight the potential new targets in the inferred network from EHCO, we combine comparative genomics and interactomics approaches to analyze 120 evolutionary conserved and overexpressed genes in HCC. 47 out of 120 queries can form a highly interactive network with 18 queries serving as hubs. Conclusion This architectural map may represent the first step toward the attempt to decipher the hepatocarcinogenesis at the systems level. Targeting hubs and/or disruption of the network formation might reveal novel strategy for HCC treatment.

  13. An Algorithm-MILDDC and its Applying in Airplane Modular Production Networks Analyzing%MILDDC算法及其在飞机模块化生产网络分析中的应用

    Institute of Scientific and Technical Information of China (English)

    戴爱明; 肖灵机

    2013-01-01

      在中心度、节点最近邻和局部社团链接度最小增量有效融合的基础上,提出了一种基于中心度的最小链接度增量社团结构探测算法(Minimal Increment of Link Degree Based on Degree Centrality, MILDDC),并将MILDDC算法应用于某型飞机模块化生产网络并进行社团结构分析,计算结果说明,该算法具有一定的适用性,时间复杂度约为线性时间,并且对包含噪声、孤立点以及异形状的网络社团结构探测具有较强的鲁棒性。%  Based on effective integration of central degree, node nearest neighbor and minimum local community link degree increments, the thesis proposes Detecting Community Structure Algorithm by Minimal Increment of Link Degree Based on Degree Centrality (MILDDC),applies the algorithm in a type of airplane modular production network and analyzing its community structure, the result of calculation proves that the algorithm is applicable. Time complexity of MILDDC is about linear time, and the algorithm has a strong robustness on community structure mining including noise, isolated point and different shape networks.

  14. “Stop Ne(c)king around”: How interactomics contributes to functionally characterize Nek family kinases

    Institute of Scientific and Technical Information of China (English)

    Gabriela; Vaz; Meirelles; Arina; Marina; Perez; Edmárcia; Elisa; de; Souza; Ferna; Luisa; Basei; Priscila; Ferreira; Papa; Talita; Diniz; Melo; Hanchuk; Vanessa; Bomfim; Cardoso; Jrg; Kobarg

    2014-01-01

    Aside from Polo and Aurora, a third but less studied kinase family involved in mitosis regulation is the never in mitosis-gene A(NIMA)-related kinases(Neks). The founding member of this family is the sole member NIMA of Aspergillus nidulans, which is crucial for the initiation of mitosis in that organism. All 11 human Neks have been functionally assigned to one of the three core functions established for this family in mammals:(1) centrioles/mitosis;(2) primary ciliary function/ciliopathies; and(3) DNA damage response(DDR). Recent findings, especially on Nek 1 and 8, showed however, that several Neks participate in parallel in at least two of these contexts: primary ciliary function and DDR. In the core section of this in-depth review, we report the current detailed functional knowledge on each of the 11 Neks. In the discussion, we return to the cross-connections among Neks and point out how our and other groups’ functional and interactomics studies revealed that most Neks interact with protein partners associated with two if not all three of the functional contexts. We then raise the hypothesis that Neks may be the connecting regulatory elements that allow the cell to fine tune and synchronize the cellular events associated with these three core functions. The new and exciting findings on the Nek family open new perspectives and should allow the Neks to finally claim the attention they deserve in the field of kinases and cell cycle biology.

  15. Protein-mRNA interactome capture: cartography of the mRNP landscape [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Sean P. Ryder

    2016-11-01

    Full Text Available RNA-binding proteins play a variety of roles in cellular physiology. Some regulate mRNA processing, mRNA abundance, and translation efficiency. Some fight off invader RNA through small RNA-driven silencing pathways. Others sense foreign sequences in the form of double-stranded RNA and activate the innate immune response. Yet others, for example cytoplasmic aconitase, act as bi-functional proteins, processing metabolites in one conformation and regulating metabolic gene expression in another. Not all are involved in gene regulation. Some play structural roles, for example, connecting the translational machinery to the endoplasmic reticulum outer membrane. Despite their pervasive role and relative importance, it has remained difficult to identify new RNA-binding proteins in a systematic, unbiased way. A recent body of literature from several independent labs has defined robust, easily adaptable protocols for mRNA interactome discovery. In this review, I summarize the methods and review some of the intriguing findings from their application to a wide variety of biological systems.

  16. Magnetic nanoparticles to recover cellular organelles and study the time resolved nanoparticle-cell interactome throughout uptake.

    Science.gov (United States)

    Bertoli, Filippo; Davies, Gemma-Louise; Monopoli, Marco P; Moloney, Micheal; Gun'ko, Yurii K; Salvati, Anna; Dawson, Kenneth A

    2014-08-27

    Nanoparticles in contact with cells and living organisms generate quite novel interactions at the interface between the nanoparticle surface and the surrounding biological environment. However, a detailed time resolved molecular level description of the evolving interactions as nanoparticles are internalized and trafficked within the cellular environment is still missing and will certainly be required for the emerging arena of nanoparticle-cell interactions to mature. In this paper promising methodologies to map out the time resolved nanoparticle-cell interactome for nanoparticle uptake are discussed. Thus silica coated magnetite nanoparticles are presented to cells and their magnetic properties used to isolate, in a time resolved manner, the organelles containing the nanoparticles. Characterization of the recovered fractions shows that different cell compartments are isolated at different times, in agreement with imaging results on nanoparticle intracellular location. Subsequently the internalized nanoparticles can be further isolated from the recovered organelles, allowing the study of the most tightly nanoparticle-bound biomolecules, analogous to the 'hard corona' that so far has mostly been characterized in extracellular environments. Preliminary data on the recovered nanoparticles suggest that significant portion of the original corona (derived from the serum in which particles are presented to the cells) is preserved as nanoparticles are trafficked through the cells.

  17. Sequence- and interactome-based prediction of viral protein hotspots targeting host proteins: a case study for HIV Nef.

    Directory of Open Access Journals (Sweden)

    Mahdi Sarmady

    Full Text Available Virus proteins alter protein pathways of the host toward the synthesis of viral particles by breaking and making edges via binding to host proteins. In this study, we developed a computational approach to predict viral sequence hotspots for binding to host proteins based on sequences of viral and host proteins and literature-curated virus-host protein interactome data. We use a motif discovery algorithm repeatedly on collections of sequences of viral proteins and immediate binding partners of their host targets and choose only those motifs that are conserved on viral sequences and highly statistically enriched among binding partners of virus protein targeted host proteins. Our results match experimental data on binding sites of Nef to host proteins such as MAPK1, VAV1, LCK, HCK, HLA-A, CD4, FYN, and GNB2L1 with high statistical significance but is a poor predictor of Nef binding sites on highly flexible, hoop-like regions. Predicted hotspots recapture CD8 cell epitopes of HIV Nef highlighting their importance in modulating virus-host interactions. Host proteins potentially targeted or outcompeted by Nef appear crowding the T cell receptor, natural killer cell mediated cytotoxicity, and neurotrophin signaling pathways. Scanning of HIV Nef motifs on multiple alignments of hepatitis C protein NS5A produces results consistent with literature, indicating the potential value of the hotspot discovery in advancing our understanding of virus-host crosstalk.

  18. Large-scale co-evolution analysis of protein structural interlogues using the global protein structural interactome map (PSIMAP).

    Science.gov (United States)

    Kim, Wan K; Bolser, Dan M; Park, Jong H

    2004-05-01

    Interacting pairs of proteins should co-evolve to maintain functional and structural complementarity. Consequently, such a pair of protein families shows similarity between their phylogenetic trees. Although the tendency of co-evolution has been known for various ligand-receptor pairs, it has not been studied systematically in the widest possible scope. We investigated the degree of co-evolution for more than 900 family pairs in a global protein structural interactome map (PSIMAP--a map of all the structural domain-domain interactions in the PDB). There was significant correlation in 45% of the total SCOPs Family level pairs, rising to 78% in 454 reliable family interactions. Expectedly, the intra-molecular interactions between protein families showed stronger co-evolution than inter-molecular interactions. However, both types of interaction have a fundamentally similar pattern of co-evolution except for cases where different interfaces are involved. These results validate the use of co-evolution analysis with predictive methods such as PSIMAP to improve the accuracy of prediction based on "homologous interaction". The tendency of co-evolution enabled a nearly 5-fold enrichment in the identification of true interactions among the potential interlogues in PSIMAP. The estimated sensitivity was 79.2%, and the specificity was 78.6%. The results of co-evolution analysis are available online at http://www.biointeraction.org

  19. Differences in AMPA and Kainate Receptor Interactomes Facilitate Identification of AMPA Receptor Auxiliary Subunit GSG1L

    Directory of Open Access Journals (Sweden)

    Natalie F. Shanks

    2012-06-01

    Full Text Available AMPA receptor (AMPA-R complexes consist of channel-forming subunits, GluA1-4, and auxiliary proteins, including TARPs, CNIHs, synDIG1, and CKAMP44, which can modulate AMPA-R function in specific ways. The combinatorial effects of four GluA subunits binding to various auxiliary subunits amplify the functional diversity of AMPA-Rs. The significance and magnitude of molecular diversity, however, remain elusive. To gain insight into the molecular complexity of AMPA and kainate receptors, we compared the proteins that copurify with each receptor type in the rat brain. This interactome study identified the majority of known interacting proteins and, more importantly, provides candidates for additional studies. We validate the claudin homolog GSG1L as a newly identified binding protein and unique modulator of AMPA-R gating, as determined by detailed molecular, cellular, electrophysiological, and biochemical experiments. GSG1L extends the functional variety of AMPA-R complexes, and further investigation of other candidates may reveal additional complexity of ionotropic glutamate receptor function.

  20. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  1. 基于模糊推理的配电网停电原因分析系统%Distribution Network Outage Cause Analyzing System Based on Fuzzy Inference

    Institute of Scientific and Technical Information of China (English)

    周志宇; 周静; 江东林; 艾欣

    2013-01-01

    针对配电网停电原因复杂、停电研判决策不易等问题,对停电原因进行了深入分析并开发了应用系统.基于停电后其他相关系统可提供的信息及电网自身特点,提出了分层求解方法,并采用模糊外展理论进行了停电原因分析,采用混合架构完成了系统设计与开发,并在生产指挥平台上完成了系统部署.通过在配电网生产抢修指挥中的应用,证明了该系统的有效性和实用性.%To tackle the outage cause identification problem and the difficulty in decision-making for power outage judgment of the distribution system,a distribution network outage cause analyzing system is proposed based on fuzzy inference,and its application system is developed.By drawing on the information provided by related systems and the characteristics of the distribution system itself,a hierarchical solving method and the fuzzy abduction theory are used to analyze the outage causes.The system is completed by using the hybrid architecture and the production is deployed on the production command platform.Application in the command of production and emergency repair shows the system proposed is effective and practical.

  2. Recent advances in large-scale protein interactome mapping [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Virja Mehta

    2016-04-01

    Full Text Available Protein-protein interactions (PPIs underlie most, if not all, cellular functions. The comprehensive mapping of these complex networks of stable and transient associations thus remains a key goal, both for systems biology-based initiatives (where it can be combined with other ‘omics’ data to gain a better understanding of functional pathways and networks and for focused biological studies. Despite the significant challenges of such an undertaking, major strides have been made over the past few years. They include improvements in the computation prediction of PPIs and the literature curation of low-throughput studies of specific protein complexes, but also an increase in the deposition of high-quality data from non-biased high-throughput experimental PPI mapping strategies into publicly available databases.

  3. Bridging HIV-1 cellular latency and clinical long-term non-progressor: an interactomic view.

    Directory of Open Access Journals (Sweden)

    Jin Yang

    Full Text Available Development of an effective HIV management is enticed by the fact that long-term non-progressors (LTNP restrict viral replication spontaneously, but is hindered by HIV-1 latency. Given that the most overlapping characteristics found between HIV-1 LTNP and latency, detailed analysis of the difference would disclose the essentials of latency. In this study, microarray data from our previous study was combined with HIV-1 latency and LTNP data obtained from NCBI GEO database. Principal variance component analysis and hierarchical clustering verified the removal of batch effect across platform. The analysis revealed a total of 456 differential expressed genes with >2-fold change and B-statistic >0. Bayesian inference was used to reconstitute the transcriptional network of HIV-1 latency or LTNP, respectively. Gene regulation was reprogrammed under different disease condition. By network interference, KPNA2 and ATP5G3 were identified as the hubs in latency network which mediate nuclear export and RNA processing. These data offer comparative insights into HIV-1 latency, which will facilitate the understanding of the genetic basis of HIV-1 latency in vivo and serve as a clue for future treatment dealing with key targets in HIV-1 latency.

  4. The binary protein interactome of Treponema pallidum--the syphilis spirochete.

    Directory of Open Access Journals (Sweden)

    Björn Titz

    Full Text Available Protein interaction networks shed light on the global organization of proteomes but can also place individual proteins into a functional context. If we know the function of bacterial proteins we will be able to understand how these species have adapted to diverse environments including many extreme habitats. Here we present the protein interaction network for the syphilis spirochete Treponema pallidum which encodes 1,039 proteins, 726 (or 70% of which interact via 3,649 interactions as revealed by systematic yeast two-hybrid screens. A high-confidence subset of 991 interactions links 576 proteins. To derive further biological insights from our data, we constructed an integrated network of proteins involved in DNA metabolism. Combining our data with additional evidences, we provide improved annotations for at least 18 proteins (including TP0004, TP0050, and TP0183 which are suggested to be involved in DNA metabolism. We estimate that this "minimal" bacterium contains on the order of 3,000 protein interactions. Profiles of functional interconnections indicate that bacterial proteins interact more promiscuously than eukaryotic proteins, reflecting the non-compartmentalized structure of the bacterial cell. Using our high-confidence interactions, we also predict 417,329 homologous interactions ("interologs" for 372 completely sequenced genomes and provide evidence that at least one third of them can be experimentally confirmed.

  5. Klinefelter syndrome comorbidities linked to increased X chromosome gene dosage and altered protein interactome activity

    DEFF Research Database (Denmark)

    Belling, Kirstine González-Izarzugaza; Russo, Francesco; Jensen, Anders Boeck

    2017-01-01

    Jak-STAT pathway, dysregulated genes important for disturbed immune system (IL4), energy balance (POMC and LEP) and erythropoietin signalling in KS. We present an extended epidemiological study that links KS comorbidities to the molecular level and identify potential causal players in the disease...... of co-expressed modules as well as central hubs and gene dosage perturbed protein complexes in a KS comorbidity network build from known disease proteins and their protein-protein interactions. The systems biology approaches together pointed to novel aspects of KS disease phenotypes including perturbed...

  6. Neuroplasticity pathways and protein-interaction networks are modulated by vortioxetine in rodents

    DEFF Research Database (Denmark)

    Waller, Jessica A.; Nygaard, Sara Holm; Li, Yan

    2017-01-01

    . A subsequent qPCR study examining the expression of targets in the protein-protein interactome space in response to chronic vortioxetine treatment over a range of doses provides further biological validation that vortioxetine engages neuroplasticity networks. Thus, the same biology is regulated in different...... species and sexes, different brain regions, and in response to distinct routes of administration and regimens. Conclusions: A recurring theme, based on the present study as well as previous findings, is that networks related to synaptic plasticity, synaptic transmission, signal transduction...

  7. WD40 proteins propel cellular networks.

    Science.gov (United States)

    Stirnimann, Christian U; Petsalaki, Evangelia; Russell, Robert B; Müller, Christoph W

    2010-10-01

    Recent findings indicate that WD40 domains play central roles in biological processes by acting as hubs in cellular networks; however, they have been studied less intensely than other common domains, such as the kinase, PDZ or SH3 domains. As suggested by various interactome studies, they are among the most promiscuous interactors. Structural studies suggest that this property stems from their ability, as scaffolds, to interact with diverse proteins, peptides or nucleic acids using multiple surfaces or modes of interaction. A general scaffolding role is supported by the fact that no WD40 domain has been found with intrinsic enzymatic activity despite often being part of large molecular machines. We discuss the WD40 domain distributions in protein networks and structures of WD40-containing assemblies to demonstrate their versatility in mediating critical cellular functions.

  8. Estimation of global network statistics from incomplete data.

    Directory of Open Access Journals (Sweden)

    Catherine A Bliss

    Full Text Available Complex networks underlie an enormous variety of social, biological, physical, and virtual systems. A profound complication for the science of complex networks is that in most cases, observing all nodes and all network interactions is impossible. Previous work addressing the impacts of partial network data is surprisingly limited, focuses primarily on missing nodes, and suggests that network statistics derived from subsampled data are not suitable estimators for the same network statistics describing the overall network topology. We generate scaling methods to predict true network statistics, including the degree distribution, from only partial knowledge of nodes, links, or weights. Our methods are transparent and do not assume a known generating process for the network, thus enabling prediction of network statistics for a wide variety of applications. We validate analytical results on four simulated network classes and empirical data sets of various sizes. We perform subsampling experiments by varying proportions of sampled data and demonstrate that our scaling methods can provide very good estimates of true network statistics while acknowledging limits. Lastly, we apply our techniques to a set of rich and evolving large-scale social networks, Twitter reply networks. Based on 100 million tweets, we use our scaling techniques to propose a statistical characterization of the Twitter Interactome from September 2008 to November 2008. Our treatment allows us to find support for Dunbar's hypothesis in detecting an upper threshold for the number of active social contacts that individuals maintain over the course of one week.

  9. Networks of ProteinProtein Interactions: From Uncertainty to Molecular Details.

    Science.gov (United States)

    Garcia-Garcia, Javier; Bonet, Jaume; Guney, Emre; Fornes, Oriol; Planas, Joan; Oliva, Baldo

    2012-05-01

    Proteins are the bricks and mortar of cells. The work of proteins is structural and functional, as they are the principal element of the organization of the cell architecture, but they also play a relevant role in its metabolism and regulation. To perform all these functions, proteins need to interact with each other and with other bio-molecules, either to form complexes or to recognize precise targets of their action. For instance, a particular transcription factor may activate one gene or another depending on its interactions with other proteins and not only with DNA. Hence, the ability of a protein to interact with other bio-molecules, and the partners they have at each particular time and location can be crucial to characterize the role of a protein. Proteins rarely act alone; they rather constitute a mingled network of physical interactions or other types of relationships (such as metabolic and regulatory) or signaling cascades. In this context, understanding the function of a protein implies to recognize the members of its neighborhood and to grasp how they associate, both at the systemic and atomic level. The network of physical interactions between the proteins of a system, cell or organism, is defined as the interactome. The purpose of this review is to deepen the description of interactomes at different levels of detail: from the molecular structure of complexes to the global topology of the network of interactions. The approaches and techniques applied experimentally and computationally to attain each level are depicted. The limits of each technique and its integration into a model network, the challenges and actual problems of completeness of an interactome, and the reliability of the interactions are reviewed and summarized. Finally, the application of the current knowledge of protein-protein interactions on modern network medicine and protein function annotation is also explored.

  10. Identifying candidate agents for lung adenocarcinoma by walking the human interactome

    Directory of Open Access Journals (Sweden)

    Sun Y

    2016-09-01

    Full Text Available Yajiao Sun,1 Ranran Zhang,2 Zhe Jiang,1 Rongyao Xia,1 Jingwen Zhang,1 Jing Liu,1 Fuhui Chen1 1Department of Respiratory, The Second Affiliated Hospital of Harbin Medical University, 2Department of Respiratory, Harbin First Hospital, Harbin, People’s Republic of China Abstract: Despite recent advances in therapeutic strategies for lung cancer, mortality is still increasing. Therefore, there is an urgent need to identify effective novel drugs. In the present study, we implement drug repositioning for lung adenocarcinoma (LUAD by a bioinformatics method followed by experimental validation. We first identified differentially expressed genes between LUAD tissues and nontumor tissues from RNA sequencing data obtained from The Cancer Genome Atlas database. Then, candidate small molecular drugs were ranked according to the effect of their targets on differentially expressed genes of LUAD by a random walk with restart algorithm in protein–protein interaction networks. Our method identified some potentially novel agents for LUAD besides those that had been previously reported (eg, hesperidin. Finally, we experimentally verified that atracurium, one of the potential agents, could induce A549 cells death in non-small-cell lung cancer-derived A549 cells by an MTT assay, acridine orange and ethidium bromide staining, and electron microscopy. Furthermore, Western blot assays demonstrated that atracurium upregulated the proapoptotic Bad and Bax proteins, downregulated the antiapoptotic p-Bad and Bcl-2 proteins, and enhanced caspase-3 activity. It could also reduce the expression of p53 and p21Cip1/Waf1 in A549 cells. In brief, the candidate agents identified by our approach may provide greater insights into improving the therapeutic status of LUAD. Keywords: lung adenocarcinoma, drug repositioning, bioinformatics, protein–protein interaction network, atracurium

  11. Network properties of complex human disease genes identified through genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Fredrik Barrenas

    Full Text Available BACKGROUND: Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs, thereby eliminating discovery bias. PRINCIPAL FINDINGS: We derived a network of complex diseases (n = 54 and complex disease genes (n = 349 to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. CONCLUSIONS: This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.

  12. Network properties of complex human disease genes identified through genome-wide association studies.

    Science.gov (United States)

    Barrenas, Fredrik; Chavali, Sreenivas; Holme, Petter; Mobini, Reza; Benson, Mikael

    2009-11-30

    Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias. We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.

  13. C2Analyzer:Co-target-Co-function Analyzer

    Institute of Scientific and Technical Information of China (English)

    Md Aftabuddin; Chittabrata Mal; Arindam Deb; Sudip Kundu

    2014-01-01

    MicroRNAs (miRNAs) interact with their target mRNAs and regulate biological pro-cesses at post-transcriptional level. While one miRNA can target many mRNAs, a single mRNA can also be targeted by a set of miRNAs. The targeted mRNAs may be involved in different bio-logical processes that are described by gene ontology (GO) terms. The major challenges involved in analyzing these multitude regulations include identification of the combinatorial regulation of miR-NAs as well as determination of the co-functionally-enriched miRNA pairs. The C2Analyzer:Co-target-Co-function Analyzer, is a Perl-based, versatile and user-friendly web tool with online instructions. Based on the hypergeometric analysis, this novel tool can determine whether given pairs of miRNAs are co-functionally enriched. For a given set of GO term(s), it can also identify the set of miRNAs whose targets are enriched in the given GO term(s). Moreover, C2Analyzer can also identify the co-targeting miRNA pairs, their targets and GO processes, which they are involved in. The miRNA-miRNA co-functional relationship can also be saved as a .txt file, which can be used to further visualize the co-functional network by using other software like Cytoscape. C2Analyzer is freely available at www.bioinformatics.org/c2analyzer.

  14. Fly-DPI: database of protein interactomes for D. melanogaster in the approach of systems biology

    Directory of Open Access Journals (Sweden)

    Lin Chieh-Hua

    2006-12-01

    Full Text Available Abstract Background Proteins control and mediate many biological activities of cells by interacting with other protein partners. This work presents a statistical model to predict protein interaction networks of Drosophila melanogaster based on insight into domain interactions. Results Three high-throughput yeast two-hybrid experiments and the collection in FlyBase were used as our starting datasets. The co-occurrences of domains in these interactive events are converted into a probability score of domain-domain interaction. These scores are used to infer putative interaction among all available open reading frames (ORFs of fruit fly. Additionally, the likelihood function is used to estimate all potential protein-protein interactions. All parameters are successfully iterated and MLE is obtained for each pair of domains. Additionally, the maximized likelihood reaches its converged criteria and maintains the probability stable. The hybrid model achieves a high specificity with a loss of sensitivity, suggesting that the model may possess major features of protein-protein interactions. Several putative interactions predicted by the proposed hybrid model are supported by literatures, while experimental data with a low probability score indicate an uncertain reliability and require further proof of interaction. Fly-DPI is the online database used to present this work. It is an integrated proteomics tool with comprehensive protein annotation information from major databases as well as an effective means of predicting protein-protein interactions. As a novel search strategy, the ping-pong search is a naïve path map between two chosen proteins based on pre-computed shortest paths. Adopting effective filtering strategies will facilitate researchers in depicting the bird's eye view of the network of interest. Fly-DPI can be accessed at http://flydpi.nhri.org.tw. Conclusion This work provides two reference systems, statistical and biological, to evaluate

  15. The Intermodulation Lockin Analyzer

    CERN Document Server

    Tholen, Erik A; Forchheimer, Daniel; Schuler, Vivien; Tholen, Mats O; Hutter, Carsten; Haviland, David B

    2011-01-01

    Nonlinear systems can be probed by driving them with two or more pure tones while measuring the intermodulation products of the drive tones in the response. We describe a digital lock-in analyzer which is designed explicitly for this purpose. The analyzer is implemented on a field-programmable gate array, providing speed in analysis, real-time feedback and stability in operation. The use of the analyzer is demonstrated for Intermodulation Atomic Force Microscopy. A generalization of the intermodulation spectral technique to arbitrary drive waveforms is discussed.

  16. Analyzing in the present

    DEFF Research Database (Denmark)

    Revsbæk, Line; Tanggaard, Lene

    2015-01-01

    The article presents a notion of “analyzing in the present” as a source of inspiration in analyzing qualitative research materials. The term emerged from extensive listening to interview recordings during everyday commuting to university campus. Paying attention to the way different parts...... the interdependency between researcher and researched. On this basis, we advocate an explicit “open-state-of mind” listening as a key aspect of analyzing qualitative material, often described only as a matter of reading transcribed empirical materials, reading theory, and writing. The article contributes...

  17. Transcriptomic Analysis of the Claudin Interactome in Malignant Pleural Mesothelioma: Evaluation of the Effect of Disease Phenotype, Asbestos Exposure, and CDKN2A Deletion Status

    Science.gov (United States)

    Rouka, Erasmia; Vavougios, Georgios D.; Solenov, Evgeniy I.; Gourgoulianis, Konstantinos I.; Hatzoglou, Chrissi; Zarogiannis, Sotirios G.

    2017-01-01

    Malignant pleural mesothelioma (MPM) is a highly aggressive tumor primarily associated with asbestos exposure. Early detection of MPM is restricted by the long latency period until clinical presentation, the ineffectiveness of imaging techniques in early stage detection and the lack of non-invasive biomarkers with high sensitivity and specificity. In this study we used transcriptome data mining in order to determine which CLAUDIN (CLDN) genes are differentially expressed in MPM as compared to controls. Using the same approach we identified the interactome of the differentially expressed CLDN genes and assessed their expression profile. Subsequently, we evaluated the effect of tumor histology, asbestos exposure, CDKN2A deletion status, and gender on the gene expression level of the claudin interactome. We found that 5 out of 15 studied CLDNs (4, 5, 8, 10, 15) and 4 out of 27 available interactors (S100B, SHBG, CDH5, CXCL8) were differentially expressed in MPM specimens vs. healthy tissues. The genes encoding the CLDN-15 and S100B proteins present differences in their expression profile between the three histological subtypes of MPM. Moreover, CLDN-15 is significantly under-expressed in the cohort of patients with previous history of asbestos exposure. CLDN-15 was also found significantly underexpressed in patients lacking the CDKN2A gene. These results warrant the detailed in vitro investigation of the role of CDLN-15 in the pathobiology of MPM. PMID:28377727

  18. Chronically dysregulated NOTCH1 interactome in the dentate gyrus after traumatic brain injury

    Science.gov (United States)

    Puhakka, Noora; Bot, Anna Maria; Vuokila, Niina; Debski, Konrad Jozef; Lukasiuk, Katarzyna; Pitkänen, Asla

    2017-01-01

    Traumatic brain injury (TBI) can result in several dentate gyrus-regulated disabilities. Almost nothing is known about the chronic molecular changes after TBI, and their potential as treatment targets. We hypothesized that chronic transcriptional alterations after TBI are under microRNA (miRNA) control. Expression of miRNAs and their targets in the dentate gyrus was analyzed using microarrays at 3 months after experimental TBI. Of 305 miRNAs present on the miRNA-array, 12 were downregulated (pdentate gyrus pathology-related morbidities. PMID:28273100

  19. A microtubule interactome: complexes with roles in cell cycle and mitosis.

    Directory of Open Access Journals (Sweden)

    Julian R Hughes

    2008-04-01

    Full Text Available The microtubule (MT cytoskeleton is required for many aspects of cell function, including the transport of intracellular materials, the maintenance of cell polarity, and the regulation of mitosis. These functions are coordinated by MT-associated proteins (MAPs, which work in concert with each other, binding MTs and altering their properties. We have used a MT cosedimentation assay, combined with 1D and 2D PAGE and mass spectrometry, to identify over 250 MAPs from early Drosophila embryos. We have taken two complementary approaches to analyse the cellular function of novel MAPs isolated using this approach. First, we have carried out an RNA interference (RNAi screen, identifying 21 previously uncharacterised genes involved in MT organisation. Second, we have undertaken a bioinformatics analysis based on binary protein interaction data to produce putative interaction networks of MAPs. By combining both approaches, we have identified and validated MAP complexes with potentially important roles in cell cycle regulation and mitosis. This study therefore demonstrates that biologically relevant data can be harvested using such a multidisciplinary approach, and identifies new MAPs, many of which appear to be important in cell division.

  20. Analyzing binding data.

    Science.gov (United States)

    Motulsky, Harvey J; Neubig, Richard R

    2010-07-01

    Measuring the rate and extent of radioligand binding provides information on the number of binding sites, and their affinity and accessibility of these binding sites for various drugs. This unit explains how to design and analyze such experiments.

  1. Analog multivariate counting analyzers

    CERN Document Server

    Nikitin, A V; Armstrong, T P

    2003-01-01

    Characterizing rates of occurrence of various features of a signal is of great importance in numerous types of physical measurements. Such signal features can be defined as certain discrete coincidence events, e.g. crossings of a signal with a given threshold, or occurrence of extrema of a certain amplitude. We describe measuring rates of such events by means of analog multivariate counting analyzers. Given a continuous scalar or multicomponent (vector) input signal, an analog counting analyzer outputs a continuous signal with the instantaneous magnitude equal to the rate of occurrence of certain coincidence events. The analog nature of the proposed analyzers allows us to reformulate many problems of the traditional counting measurements, and cast them in a form which is readily addressed by methods of differential calculus rather than by algebraic or logical means of digital signal processing. Analog counting analyzers can be easily implemented in discrete or integrated electronic circuits, do not suffer fro...

  2. Miniature mass analyzer

    CERN Document Server

    Cuna, C; Lupsa, N; Cuna, S; Tuzson, B

    2003-01-01

    The paper presents the concept of different mass analyzers that were specifically designed as small dimension instruments able to detect with great sensitivity and accuracy the main environmental pollutants. The mass spectrometers are very suited instrument for chemical and isotopic analysis, needed in environmental surveillance. Usually, this is done by sampling the soil, air or water followed by laboratory analysis. To avoid drawbacks caused by sample alteration during the sampling process and transport, the 'in situ' analysis is preferred. Theoretically, any type of mass analyzer can be miniaturized, but some are more appropriate than others. Quadrupole mass filter and trap, magnetic sector, time-of-flight and ion cyclotron mass analyzers can be successfully shrunk, for each of them some performances being sacrificed but we must know which parameters are necessary to be kept unchanged. To satisfy the miniaturization criteria of the analyzer, it is necessary to use asymmetrical geometries, with ion beam obl...

  3. Analyzing Microarray Data.

    Science.gov (United States)

    Hung, Jui-Hung; Weng, Zhiping

    2017-03-01

    Because there is no widely used software for analyzing RNA-seq data that has a graphical user interface, this protocol provides an example of analyzing microarray data using Babelomics. This analysis entails performing quantile normalization and then detecting differentially expressed genes associated with the transgenesis of a human oncogene c-Myc in mice. Finally, hierarchical clustering is performed on the differentially expressed genes using the Cluster program, and the results are visualized using TreeView.

  4. Extracellular vesicles – biomarkers and effectors of the cellular interactome in cancer

    Directory of Open Access Journals (Sweden)

    Janusz eRak

    2013-03-01

    Full Text Available In multicellular organisms both health and disease are defined by patterns of communications between the constituent cells. In addition to networks of soluble mediators, cells are also programmed to exchange complex messages pre-assembled as multimolecular cargo of membraneous structures known extracellular vesicles (EV. Several biogenetic pathways produce EVs with different properties and known as exosomes, ectosomes and apoptotic bodies. In cancer, EVs carry molecular signatures and effectors of the disease, such as mutant oncoproteins, oncogenic transcripts, microRNA and DNA sequences. Intercellular trafficking of such EVs (oncosomes may contribute to horizontal cellular transformation, phenotypic reprogramming and functional re-education of recipient cells, both locally and systemically. The EV-mediated, reciprocal molecular exchange also includes tumor suppressors, phosphoproteins, proteases, growth factors and bioactive lipids, all of which participate in the functional integration of multiple cells and their collective involved in tumor angiogenesis, inflammation, immunity, coagulopathy, mobilization of bone marrow derived effectors, metastasis, drug resistance or cellular stemness. In cases where the EV involvement is rate limiting their production and uptake may represent and unexplored anticancer therapy target. Moreover, oncosomes circulating in biofluids of cancer patients offer an unprecedented, remote and non-invasive access to crucial molecular information about cancer cells, including their driver mutations, classifiers, molecular subtypes, therapeutic targets and biomarkers of drug resistance. New nanotechnologies are being developed to exploit this unique biomarker platform. Indeed, embracing the notion that human cancers are defined not only by processes occurring within cancer cells, but also between them, and amidst the altered tumor and systemic microenvironment may open new diagnostic and therapeutic opportunities.

  5. A Systems Biology Approach to Reveal Putative Host-Derived Biomarkers of Periodontitis by Network Topology Characterization of MMP-REDOX/NO and Apoptosis Integrated Pathways.

    Science.gov (United States)

    Zeidán-Chuliá, Fares; Gürsoy, Mervi; Neves de Oliveira, Ben-Hur; Özdemir, Vural; Könönen, Eija; Gürsoy, Ulvi K

    2015-01-01

    Periodontitis, a formidable global health burden, is a common chronic disease that destroys tooth-supporting tissues. Biomarkers of the early phase of this progressive disease are of utmost importance for global health. In this context, saliva represents a non-invasive biosample. By using systems biology tools, we aimed to (1) identify an integrated interactome between matrix metalloproteinase (MMP)-REDOX/nitric oxide (NO) and apoptosis upstream pathways of periodontal inflammation, and (2) characterize the attendant topological network properties to uncover putative biomarkers to be tested in saliva from patients with periodontitis. Hence, we first generated a protein-protein network model of interactions ("BIOMARK" interactome) by using the STRING 10 database, a search tool for the retrieval of interacting genes/proteins, with "Experiments" and "Databases" as input options and a confidence score of 0.400. Second, we determined the centrality values (closeness, stress, degree or connectivity, and betweenness) for the "BIOMARK" members by using the Cytoscape software. We found Ubiquitin C (UBC), Jun proto-oncogene (JUN), and matrix metalloproteinase-14 (MMP14) as the most central hub- and non-hub-bottlenecks among the 211 genes/proteins of the whole interactome. We conclude that UBC, JUN, and MMP14 are likely an optimal candidate group of host-derived biomarkers, in combination with oral pathogenic bacteria-derived proteins, for detecting periodontitis at its early phase by using salivary samples from patients. These findings therefore have broader relevance for systems medicine in global health as well.

  6. Total organic carbon analyzer

    Science.gov (United States)

    Godec, Richard G.; Kosenka, Paul P.; Smith, Brian D.; Hutte, Richard S.; Webb, Johanna V.; Sauer, Richard L.

    The development and testing of a breadboard version of a highly sensitive total-organic-carbon (TOC) analyzer are reported. Attention is given to the system components including the CO2 sensor, oxidation reactor, acidification module, and the sample-inlet system. Research is reported for an experimental reagentless oxidation reactor, and good results are reported for linearity, sensitivity, and selectivity in the CO2 sensor. The TOC analyzer is developed with gravity-independent components and is designed for minimal additions of chemical reagents. The reagentless oxidation reactor is based on electrolysis and UV photolysis and is shown to be potentially useful. The stability of the breadboard instrument is shown to be good on a day-to-day basis, and the analyzer is capable of 5 sample analyses per day for a period of about 80 days. The instrument can provide accurate TOC and TIC measurements over a concentration range of 20 ppb to 50 ppm C.

  7. Analyzing radioligand binding data.

    Science.gov (United States)

    Motulsky, Harvey; Neubig, Richard

    2002-08-01

    Radioligand binding experiments are easy to perform, and provide useful data in many fields. They can be used to study receptor regulation, discover new drugs by screening for compounds that compete with high affinity for radioligand binding to a particular receptor, investigate receptor localization in different organs or regions using autoradiography, categorize receptor subtypes, and probe mechanisms of receptor signaling, via measurements of agonist binding and its regulation by ions, nucleotides, and other allosteric modulators. This unit reviews the theory of receptor binding and explains how to analyze experimental data. Since binding data are usually best analyzed using nonlinear regression, this unit also explains the principles of curve fitting with nonlinear regression.

  8. Advances in hematology analyzers.

    Science.gov (United States)

    DeNicola, Dennis B

    2011-05-01

    The complete blood count is one of the basic building blocks of the minimum database in veterinary medicine. Over the past 20 years, there has been a tremendous advancement in the technology of hematology analyzers and their availability to the general practitioner. There are 4 basic methodologies that can be used to generate data for a complete blood count: manual methods, quantitative buffy coat analysis, automated impedance analysis, and flow cytometric analysis. This article will review the principles of these methodologies, discuss some of their advantages and disadvantages, and describe some of the hematology analyzers that are available for the in-house veterinary laboratory.

  9. Sulfur Dioxide Analyzer Instrument Handbook

    Energy Technology Data Exchange (ETDEWEB)

    Springston, Stephen R [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-05-01

    The Sulfur Dioxide Analyzer measures sulfur dioxide based on absorbance of UV light at one wavelength by SO2 molecules which then decay to a lower energy state by emitting UV light at a longer wavelength. Specifically, SO2 + hυ1 →SO2 *→SO2 + hυ2 The emitted light is proportional to the concentration of SO2 in the optical cell. External communication with the analyzer is available through an Ethernet port configured through the instrument network of the AOS systems. The Model 43i-TLE is part of the i-series of Thermo Scientific instruments. The i-series instruments are designed to interface with external computers through the proprietary Thermo Scientific iPort Software. However, this software is somewhat cumbersome and inflexible. Brookhaven National Laboratory (BNL) has written an interface program in National Instruments LabView that both controls the Model 43i-TLE Analyzer AND queries the unit for all measurement and housekeeping data. The LabView vi (the software program written by BNL) ingests all raw data from the instrument and outputs raw data files in a uniform data format similar to other instruments in the AOS and described more fully in Section 6.0 below.

  10. Analyzing Stereotypes in Media.

    Science.gov (United States)

    Baker, Jackie

    1996-01-01

    A high school film teacher studied how students recognized messages in film, examining how film education could help students identify and analyze racial and gender stereotypes. Comparison of students' attitudes before and after the film course found that the course was successful in raising students' consciousness. (SM)

  11. Analyzing Workforce Education. Monograph.

    Science.gov (United States)

    Texas Community & Technical Coll. Workforce Education Consortium.

    This monograph examines the issue of task analysis as used in workplace literacy programs, debating the need for it and how to perform it in a rapidly changing environment. Based on experiences of community colleges in Texas, the report analyzes ways that task analysis can be done and how to implement work force education programs more quickly.…

  12. [Analyzed the molecular interaction network of tumor suppressor gene 14-3-3 sigma in lung cancer cell based on stable isotope labeling by amino acids in cell culture technology].

    Science.gov (United States)

    Xiao, Ting; Mi, Wei; Li, Min; Cao, Bang-rong; Feng, Lin; Cheng, Shu-jun; Gao, Yan-ning

    2013-08-01

    To analysis the molecular interaction network of 14-3-3 sigma in non small cell lung cancer (NSCLC) cells. Established stable over-expressed 14-3-3 sigma protein PG cells, MTT assay was used to assess the growth rate of PG cells. Though stable isotope labeling by amino acids in cell culture (SILAC) and Mass spectrometry (MS) technology, to identify difference expressed proteins caused by over expressed 14-3-3 sigma. The protein expressed >2 or encyclopedia of genes and genomes (KEGG), established the molecular interaction network of tumor suppressor gene 14-3-3 sigma. The growth rate of over-expressed 14-3-3 sigma PG cell was obviously slower down compared to vector PG cells. A database including 147 differential protein was established. And a molecular interaction network of 14-3-3 sigma containing 26 protein was constructed.In this network, the expression of CSNK2A1 (casein kinase II subunit alpha), involved in numerous cellular processes, such as cell cycle progression, apoptosis and transcription, was the most significantly increased. A DNA repair protein, MEN1 (Menin) which functions as a transcriptional regulator was the most significantly decreased. After stable transfected with 14-3-3 sigma gene, growth rate of PG cells was inhibited, the proteins associated with cell cycle, DNA damage repair mechanisms were significantly changed, and constructed the molecular interaction network.

  13. Layer aggregation and reducibility of multilayer interconnected networks

    CERN Document Server

    De Domenico, M; Arenas, A; Latora, V

    2014-01-01

    Many complex systems can be represented as networks composed by distinct layers, interacting and depending on each others. For example, in biology, a good description of the full protein-protein interactome requires, for some organisms, up to seven distinct network layers, with thousands of protein-protein interactions each. A fundamental open question is then how much information is really necessary to accurately represent the structure of a multilayer complex system, and if and when some of the layers can indeed be aggregated. Here we introduce a method, based on information theory, to reduce the number of layers in multilayer networks, while minimizing information loss. We validate our approach on a set of synthetic benchmarks, and prove its applicability to an extended data set of protein-genetic interactions, showing cases where a strong reduction is possible and cases where it is not. Using this method we can describe complex systems with an optimal trade--off between accuracy and complexity.

  14. Analyzing Al Qaedaism

    Institute of Scientific and Technical Information of China (English)

    Yuan Hua

    2008-01-01

    Three major events are responsible for the rampancy today of Al Qaedaism, the doctrine of Al Qaeda, an Islam extremist organization. They are: the Anti-Soviet Afghanistan War for the birth of the group; the September 11 terrorist attacks for the spread of its extremist demagogy and the war on terror for its branches networking into alliances worldwide.Al Qaedaism aims at driving away Western forces on the Moslem lands, overthrowing local Pro-West regimes, destroying Israel and setting up a Caliphate empire. Its rampancy has resulted from a combination of diverse factors at work under specific historical conditions rather an inevitable outcome of the growth of the Islam religion.As an ideological weapon for launching Jihad to oust Western influence and topple local regimes, Al Qaedaism reflects an extremist portrayal of modern Islam society, politics, economy and culture.

  15. PhosphoSiteAnalyzer

    DEFF Research Database (Denmark)

    Bennetzen, Martin V; Cox, Jürgen; Mann, Matthias

    2012-01-01

    an algorithm to retrieve kinase predictions from the public NetworKIN webpage in a semiautomated way and applies hereafter advanced statistics to facilitate a user-tailored in-depth analysis of the phosphoproteomic data sets. The interface of the software provides a high degree of analytical flexibility...... and is designed to be intuitive for most users. PhosphoSiteAnalyzer is a freeware program available at http://phosphosite.sourceforge.net ....

  16. Magnetoresistive emulsion analyzer.

    Science.gov (United States)

    Lin, Gungun; Baraban, Larysa; Han, Luyang; Karnaushenko, Daniil; Makarov, Denys; Cuniberti, Gianaurelio; Schmidt, Oliver G

    2013-01-01

    We realize a magnetoresistive emulsion analyzer capable of detection, multiparametric analysis and sorting of ferrofluid-containing nanoliter-droplets. The operation of the device in a cytometric mode provides high throughput and quantitative information about the dimensions and magnetic content of the emulsion. Our method offers important complementarity to conventional optical approaches involving ferrofluids, and paves the way to the development of novel compact tools for diagnostics and nanomedicine including drug design and screening.

  17. Network neuroscience.

    Science.gov (United States)

    Bassett, Danielle S; Sporns, Olaf

    2017-02-23

    Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.

  18. Network-based association of hypoxia-responsive genes with cardiovascular diseases

    Science.gov (United States)

    Wang, Rui-Sheng; Oldham, William M.; Loscalzo, Joseph

    2014-10-01

    Molecular oxygen is indispensable for cellular viability and function. Hypoxia is a stress condition in which oxygen demand exceeds supply. Low cellular oxygen content induces a number of molecular changes to activate regulatory pathways responsible for increasing the oxygen supply and optimizing cellular metabolism under limited oxygen conditions. Hypoxia plays critical roles in the pathobiology of many diseases, such as cancer, heart failure, myocardial ischemia, stroke, and chronic lung diseases. Although the complicated associations between hypoxia and cardiovascular (and cerebrovascular) diseases (CVD) have been recognized for some time, there are few studies that investigate their biological link from a systems biology perspective. In this study, we integrate hypoxia genes, CVD genes, and the human protein interactome in order to explore the relationship between hypoxia and cardiovascular diseases at a systems level. We show that hypoxia genes are much closer to CVD genes in the human protein interactome than that expected by chance. We also find that hypoxia genes play significant bridging roles in connecting different cardiovascular diseases. We construct a hypoxia-CVD bipartite network and find several interesting hypoxia-CVD modules with significant gene ontology similarity. Finally, we show that hypoxia genes tend to have more CVD interactors in the human interactome than in random networks of matching topology. Based on these observations, we can predict novel genes that may be associated with CVD. This network-based association study gives us a broad view of the relationships between hypoxia and cardiovascular diseases and provides new insights into the role of hypoxia in cardiovascular biology.

  19. Triangular Alignment (TAME). A Tensor-based Approach for Higher-order Network Alignment

    Energy Technology Data Exchange (ETDEWEB)

    Mohammadi, Shahin [Purdue Univ., West Lafayette, IN (United States); Gleich, David F. [Purdue Univ., West Lafayette, IN (United States); Kolda, Tamara G. [Sandia National Laboratories (SNL-CA), Livermore, CA (United States); Grama, Ananth [Purdue Univ., West Lafayette, IN (United States)

    2015-11-01

    Network alignment is an important tool with extensive applications in comparative interactomics. Traditional approaches aim to simultaneously maximize the number of conserved edges and the underlying similarity of aligned entities. We propose a novel formulation of the network alignment problem that extends topological similarity to higher-order structures and provide a new objective function that maximizes the number of aligned substructures. This objective function corresponds to an integer programming problem, which is NP-hard. Consequently, we approximate this objective function as a surrogate function whose maximization results in a tensor eigenvalue problem. Based on this formulation, we present an algorithm called Triangular AlignMEnt (TAME), which attempts to maximize the number of aligned triangles across networks. We focus on alignment of triangles because of their enrichment in complex networks; however, our formulation and resulting algorithms can be applied to general motifs. Using a case study on the NAPABench dataset, we show that TAME is capable of producing alignments with up to 99% accuracy in terms of aligned nodes. We further evaluate our method by aligning yeast and human interactomes. Our results indicate that TAME outperforms the state-of-art alignment methods both in terms of biological and topological quality of the alignments.

  20. Analyzing Chinese Financial Reporting

    Institute of Scientific and Technical Information of China (English)

    SABRINA; ZHANG

    2008-01-01

    If the world’s capital markets could use a harmonized accounting framework it would not be necessary for a comparison between two or more sets of accounting standards. However,there is much to do before this becomes reality.This article aims to pres- ent a general overview of China’s General Accepted Accounting Principles(GAAP), U.S.General Accepted Accounting Principles and International Financial Reporting Standards(IFRS),and to analyze the differ- ences among IFRS,U.S.GAAP and China GAAP using fixed assets as an example.

  1. Mineral/Water Analyzer

    Science.gov (United States)

    1983-01-01

    An x-ray fluorescence spectrometer developed for the Viking Landers by Martin Marietta was modified for geological exploration, water quality monitoring, and aircraft engine maintenance. The aerospace system was highly miniaturized and used very little power. It irradiates the sample causing it to emit x-rays at various energies, then measures the energy levels for sample composition analysis. It was used in oceanographic applications and modified to identify element concentrations in ore samples, on site. The instrument can also analyze the chemical content of water, and detect the sudden development of excessive engine wear.

  2. Analyzing Aeroelasticity in Turbomachines

    Science.gov (United States)

    Reddy, T. S. R.; Srivastava, R.

    2003-01-01

    ASTROP2-LE is a computer program that predicts flutter and forced responses of blades, vanes, and other components of such turbomachines as fans, compressors, and turbines. ASTROP2-LE is based on the ASTROP2 program, developed previously for analysis of stability of turbomachinery components. In developing ASTROP2- LE, ASTROP2 was modified to include a capability for modeling forced responses. The program was also modified to add a capability for analysis of aeroelasticity with mistuning and unsteady aerodynamic solutions from another program, LINFLX2D, that solves the linearized Euler equations of unsteady two-dimensional flow. Using LINFLX2D to calculate unsteady aerodynamic loads, it is possible to analyze effects of transonic flow on flutter and forced response. ASTROP2-LE can be used to analyze subsonic, transonic, and supersonic aerodynamics and structural mistuning for rotors with blades of differing structural properties. It calculates the aerodynamic damping of a blade system operating in airflow so that stability can be assessed. The code also predicts the magnitudes and frequencies of the unsteady aerodynamic forces on the airfoils of a blade row from incoming wakes. This information can be used in high-cycle fatigue analysis to predict the fatigue lives of the blades.

  3. Field Deployable DNA analyzer

    Energy Technology Data Exchange (ETDEWEB)

    Wheeler, E; Christian, A; Marion, J; Sorensen, K; Arroyo, E; Vrankovich, G; Hara, C; Nguyen, C

    2005-02-09

    This report details the feasibility of a field deployable DNA analyzer. Steps for swabbing cells from surfaces and extracting DNA in an automatable way are presented. Since enzymatic amplification reactions are highly sensitive to environmental contamination, sample preparation is a crucial step to make an autonomous deployable instrument. We perform sample clean up and concentration in a flow through packed bed. For small initial samples, whole genome amplification is performed in the packed bed resulting in enough product for subsequent PCR amplification. In addition to DNA, which can be used to identify a subject, protein is also left behind, the analysis of which can be used to determine exposure to certain substances, such as radionuclides. Our preparative step for DNA analysis left behind the protein complement as a waste stream; we determined to learn if the proteins themselves could be analyzed in a fieldable device. We successfully developed a two-step lateral flow assay for protein analysis and demonstrate a proof of principle assay.

  4. Analyzing the platelet proteome.

    Science.gov (United States)

    García, Angel; Zitzmann, Nicole; Watson, Steve P

    2004-08-01

    During the last 10 years, mass spectrometry (MS) has become a key tool for protein analysis and has underpinned the emerging field of proteomics. Using high-throughput tandem MS/MS following protein separation, it is potentially possible to analyze hundreds to thousands of proteins in a sample at a time. This technology can be used to analyze the protein content (i.e., the proteome) of any cell or tissue and complements the powerful field of genomics. The technology is particularly suitable for platelets because of the absence of a nucleus. Cellular proteins can be separated by either gel-based methods such as two-dimensional gel electrophoresis or one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis followed by liquid chromatography (LC) -MS/MS or by multidimensional LC-MS/MS. Prefractionation techniques, such as subcellular fractionations or immunoprecipitations, can be used to improve the analysis. Each method has particular advantages and disadvantages. Proteomics can be used to compare the proteome of basal and diseased platelets, helping to reveal information on the molecular basis of the disease.

  5. Analyzing Pseudophosphatase Function.

    Science.gov (United States)

    Hinton, Shantá D

    2016-01-01

    Pseudophosphatases regulate signal transduction cascades, but their mechanisms of action remain enigmatic. Reflecting this mystery, the prototypical pseudophosphatase STYX (phospho-serine-threonine/tyrosine-binding protein) was named with allusion to the river of the dead in Greek mythology to emphasize that these molecules are "dead" phosphatases. Although proteins with STYX domains do not catalyze dephosphorylation, this in no way precludes their having other functions as integral elements of signaling networks. Thus, understanding their roles in signaling pathways may mark them as potential novel drug targets. This chapter outlines common strategies used to characterize the functions of pseudophosphatases, using as an example MK-STYX [mitogen-activated protein kinase (MAPK) phospho-serine-threonine/tyrosine binding], which has been linked to tumorigenesis, apoptosis, and neuronal differentiation. We start with the importance of "restoring" (when possible) phosphatase activity in a pseudophosphatase so that the active mutant may be used as a comparison control throughout immunoprecipitation and mass spectrometry analyses. To this end, we provide protocols for site-directed mutagenesis, mammalian cell transfection, co-immunoprecipitation, phosphatase activity assays, and immunoblotting that we have used to investigate MK-STYX and the active mutant MK-STYXactive. We also highlight the importance of utilizing RNA interference (RNAi) "knockdown" technology to determine a cellular phenotype in various cell lines. Therefore, we outline our protocols for introducing short hairpin RNA (shRNA) expression plasmids into mammalians cells and quantifying knockdown of gene expression with real-time quantitative PCR (qPCR). A combination of cellular, molecular, biochemical, and proteomic techniques has served as powerful tools in identifying novel functions of the pseudophosphatase MK-STYX. Likewise, the information provided here should be a helpful guide to elucidating the

  6. Structure, function and networks of transcription factors involved in abiotic stress responses

    DEFF Research Database (Denmark)

    Lindemose, Søren; O'Shea, Charlotte; Jensen, Michael Krogh

    2013-01-01

    and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based...... on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic...

  7. Analyzing business models

    DEFF Research Database (Denmark)

    Nielsen, Christian

    2014-01-01

    , because the costs of processing and analyzing it exceed the benefits indicating bounded rationality. Hutton (2002) concludes that the analyst community’s inability to raise important questions on quality of management and the viability of its business model inevitably led to the Enron debacle. There seems...... financial statement. Plumlee (2003) finds for instance that such information imposes significant costs on even expert users such as analysts and fund managers and reduces their use of it. Analysts’ ability to incorporate complex information in their analyses is a decreasing function of its complexity...... to be evidence of the fact that all types of corporate stakeholders from management to employees, owners, the media and politicians have grave difficulties in interpreting new forms of reporting. One hypothesis could be that if managements’ own understanding of value creation is disclosed to the other...

  8. Analyzing architecture articles

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    In the present study, we express the quality, function, and characteristics of architecture to help people comprehensively understand what architecture is. We also reveal the problems and conflict found in population, land, water resources, pollution, energy, and the organization systems in construction. China’s economy is transforming. We should focus on the cities, architectural environment, energy conservation, emission-reduction, and low-carbon output that will result in successful green development. We should macroscopically and microscopically analyze the development, from the natural environment to the artificial environment; from the relationship between human beings and nature to the combination of social ecology in cities, and farmlands. We must learn to develop and control them harmoniously and scientifically to provide a foundation for the methods used in architecture research.

  9. Analyzing geographic clustered response

    Energy Technology Data Exchange (ETDEWEB)

    Merrill, D.W.; Selvin, S.; Mohr, M.S.

    1991-08-01

    In the study of geographic disease clusters, an alternative to traditional methods based on rates is to analyze case locations on a transformed map in which population density is everywhere equal. Although the analyst's task is thereby simplified, the specification of the density equalizing map projection (DEMP) itself is not simple and continues to be the subject of considerable research. Here a new DEMP algorithm is described, which avoids some of the difficulties of earlier approaches. The new algorithm (a) avoids illegal overlapping of transformed polygons; (b) finds the unique solution that minimizes map distortion; (c) provides constant magnification over each map polygon; (d) defines a continuous transformation over the entire map domain; (e) defines an inverse transformation; (f) can accept optional constraints such as fixed boundaries; and (g) can use commercially supported minimization software. Work is continuing to improve computing efficiency and improve the algorithm. 21 refs., 15 figs., 2 tabs.

  10. GSM Trace Quality Analyzer (TQA) software

    OpenAIRE

    Blanchart Forne, Marc

    2016-01-01

    Connectivity is now the must-have service for enhancing passenger experience. To proof and also to show to the customers the quality of the connectivity system an user friendly mock-up has to be designed. A packet analyzer software designed to validate an existing SATCOM simulator and to improve future airline architecture networks.

  11. Analyzing the Information Economy: Tools and Techniques.

    Science.gov (United States)

    Robinson, Sherman

    1986-01-01

    Examines methodologies underlying studies which measure the information economy and considers their applicability and limitations for analyzing policy issues concerning libraries and library networks. Two studies provide major focus for discussion: Porat's "The Information Economy: Definition and Measurement" and Machlup's "Production and…

  12. Identifying and Analyzing Web Server Attacks

    Energy Technology Data Exchange (ETDEWEB)

    Seifert, Christian; Endicott-Popovsky, Barbara E.; Frincke, Deborah A.; Komisarczuk, Peter; Muschevici, Radu; Welch, Ian D.

    2008-08-29

    Abstract: Client honeypots can be used to identify malicious web servers that attack web browsers and push malware to client machines. Merely recording network traffic is insufficient to perform comprehensive forensic analyses of such attacks. Custom tools are required to access and analyze network protocol data. Moreover, specialized methods are required to perform a behavioral analysis of an attack, which helps determine exactly what transpired on the attacked system. This paper proposes a record/replay mechanism that enables forensic investigators to extract application data from recorded network streams and allows applications to interact with this data in order to conduct behavioral analyses. Implementations for the HTTP and DNS protocols are presented and their utility in network forensic investigations is demonstrated.

  13. PDA: Pooled DNA analyzer

    Directory of Open Access Journals (Sweden)

    Lin Chin-Yu

    2006-04-01

    Full Text Available Abstract Background Association mapping using abundant single nucleotide polymorphisms is a powerful tool for identifying disease susceptibility genes for complex traits and exploring possible genetic diversity. Genotyping large numbers of SNPs individually is performed routinely but is cost prohibitive for large-scale genetic studies. DNA pooling is a reliable and cost-saving alternative genotyping method. However, no software has been developed for complete pooled-DNA analyses, including data standardization, allele frequency estimation, and single/multipoint DNA pooling association tests. This motivated the development of the software, 'PDA' (Pooled DNA Analyzer, to analyze pooled DNA data. Results We develop the software, PDA, for the analysis of pooled-DNA data. PDA is originally implemented with the MATLAB® language, but it can also be executed on a Windows system without installing the MATLAB®. PDA provides estimates of the coefficient of preferential amplification and allele frequency. PDA considers an extended single-point association test, which can compare allele frequencies between two DNA pools constructed under different experimental conditions. Moreover, PDA also provides novel chromosome-wide multipoint association tests based on p-value combinations and a sliding-window concept. This new multipoint testing procedure overcomes a computational bottleneck of conventional haplotype-oriented multipoint methods in DNA pooling analyses and can handle data sets having a large pool size and/or large numbers of polymorphic markers. All of the PDA functions are illustrated in the four bona fide examples. Conclusion PDA is simple to operate and does not require that users have a strong statistical background. The software is available at http://www.ibms.sinica.edu.tw/%7Ecsjfann/first%20flow/pda.htm.

  14. Applications Analyzing of the P2P Network Technology for Smart Grid%P2P网络技术在智能电网中的应用分析

    Institute of Scientific and Technical Information of China (English)

    韩祺祎; 傅戈; 文红

    2013-01-01

    As a distributed network system, the smart grid network and P2P network have much in common. This paper analysis a distributed smart grid model based on the P2P file-sharing system. The analysis result shows that it is suitable for reliability, robustness, controllability, scalability and availability. But on security aspects, there are some shortages. So it is needed more study on security.%作为一个分布式的网络系统,智能电网与P2P网络有很多共同之处,本论文分析了P2P文件共享系统结构下的智能电网模型,对其可靠性、鲁棒性、可控性、可扩展性以及可用性等方面的适用性进行了分析,其均能满足需求,而安全性方面还有欠缺,仍需进一步的研究和改进。

  15. Open innovation in networks

    DEFF Research Database (Denmark)

    Hu, Yimei

    Open innovation in networks has been a popular topic for long, this paper rethinks the concepts of innovation network and network organization, and clarifies the differences between them based on the network perspective. Network perspective means that: network is the context of firms; market...... and hierarchy can be analyzed from a network approach. Within a network perspective, there are different levels of network, and a firm may not always has the power to “manage” innovation networks due to different levels of power. Based on the strength of a firm’s power, its role may varies from manager...

  16. The Mammalian Septin Interactome

    Science.gov (United States)

    Neubauer, Katharina; Zieger, Barbara

    2017-01-01

    Septins are GTP-binding and membrane-interacting proteins with a highly conserved domain structure involved in various cellular processes, including cytoskeleton organization, cytokinesis, and membrane dynamics. To date, 13 different septin genes have been identified in mammals (SEPT1 to SEPT12 and SEPT14), which can be classified into four distinct subgroups based on the sequence homology of their domain structure (SEPT2, SEPT3, SEPT6, and SEPT7 subgroup). The family members of these subgroups have a strong affinity for other septins and form apolar tri-, hexa-, or octameric complexes consisting of multiple septin polypeptides. The first characterized core complex is the hetero-trimer SEPT2-6-7. Within these complexes single septins can be exchanged in a subgroup-specific manner. Hexamers contain SEPT2 and SEPT6 subgroup members and SEPT7 in two copies each whereas the octamers additionally comprise two SEPT9 subgroup septins. The various isoforms seem to determine the function and regulation of the septin complex. Septins self-assemble into higher-order structures, including filaments and rings in orders, which are typical for different cell types. Misregulation of septins leads to human diseases such as neurodegenerative and bleeding disorders. In non-dividing cells such as neuronal tissue and platelets septins have been associated with exocytosis. However, many mechanistic details and roles attributed to septins are poorly understood. We describe here some important mammalian septin interactions with a special focus on the clinically relevant septin interactions. PMID:28224124

  17. Bios data analyzer.

    Science.gov (United States)

    Sabelli, H; Sugerman, A; Kovacevic, L; Kauffman, L; Carlson-Sabelli, L; Patel, M; Konecki, J

    2005-10-01

    The Bios Data Analyzer (BDA) is a set of computer programs (CD-ROM, in Sabelli et al., Bios. A Study of Creation, 2005) for new time series analyses that detects and measures creative phenomena, namely diversification, novelty, complexes, nonrandom complexity. We define a process as creative when its time series displays these properties. They are found in heartbeat interval series, the exemplar of bios .just as turbulence is the exemplar of chaos, in many other empirical series (galactic distributions, meteorological, economic and physiological series), in biotic series generated mathematically by the bipolar feedback, and in stochastic noise, but not in chaotic attractors. Differencing, consecutive recurrence and partial autocorrelation indicate nonrandom causation, thereby distinguishing chaos and bios from random and random walk. Embedding plots distinguish causal creative processes (e.g. bios) that include both simple and complex components of variation from stochastic processes (e.g. Brownian noise) that include only complex components, and from chaotic processes that decay from order to randomness as the number of dimensions is increased. Varying bin and dimensionality show that entropy measures symmetry and variety, and that complexity is associated with asymmetry. Trigonometric transformations measure coexisting opposites in time series and demonstrate bipolar, partial, and uncorrelated opposites in empirical processes and bios, supporting the hypothesis that bios is generated by bipolar feedback, a concept which is at variance with standard concepts of polar and complementary opposites.

  18. TEAMS Model Analyzer

    Science.gov (United States)

    Tijidjian, Raffi P.

    2010-01-01

    The TEAMS model analyzer is a supporting tool developed to work with models created with TEAMS (Testability, Engineering, and Maintenance System), which was developed by QSI. In an effort to reduce the time spent in the manual process that each TEAMS modeler must perform in the preparation of reporting for model reviews, a new tool has been developed as an aid to models developed in TEAMS. The software allows for the viewing, reporting, and checking of TEAMS models that are checked into the TEAMS model database. The software allows the user to selectively model in a hierarchical tree outline view that displays the components, failure modes, and ports. The reporting features allow the user to quickly gather statistics about the model, and generate an input/output report pertaining to all of the components. Rules can be automatically validated against the model, with a report generated containing resulting inconsistencies. In addition to reducing manual effort, this software also provides an automated process framework for the Verification and Validation (V&V) effort that will follow development of these models. The aid of such an automated tool would have a significant impact on the V&V process.

  19. Analyzing Teachers' Stories

    Directory of Open Access Journals (Sweden)

    Anat Kainan

    2002-09-01

    Full Text Available This article presents an integrated socio-literal approach as a way to analyze work stories. It uses a case of teachers' stories about the administration as an example. The stories focus on grumbles about various activities of members of the management of a school in a small town. The complaints appear in descriptions of the action, the characters, and, in particular, in the way the story is presented to the audience. The stories present a situation of two opposing groups-the administration and the teachers. The presentation of the stories creates a sense of togetherness among the veterans and new teachers in the staff room, and helps the integration of the new teachers into the staff. The veterans use the stories as an opportunity to express their anger at not having been assigned responsibilities on the one hand and their hopes of such promotion on the other. The stories act as a convenient medium to express criticism without entering into open hostilities. Behind them, a common principle can be discerned- the good of the school. The stories describe the infringement of various aspects of the school's social order, and it is possible to elicit from them what general pattern the teachers want to preserve in the school.

  20. Downhole Fluid Analyzer Development

    Energy Technology Data Exchange (ETDEWEB)

    Bill Turner

    2006-11-28

    A novel fiber optic downhole fluid analyzer has been developed for operation in production wells. This device will allow real-time determination of the oil, gas and water fractions of fluids from different zones in a multizone or multilateral completion environment. The device uses near infrared spectroscopy and induced fluorescence measurement to unambiguously determine the oil, water and gas concentrations at all but the highest water cuts. The only downhole components of the system are the fiber optic cable and windows. All of the active components--light sources, sensors, detection electronics and software--will be located at the surface, and will be able to operate multiple downhole probes. Laboratory testing has demonstrated that the sensor can accurately determine oil, water and gas fractions with a less than 5 percent standard error. Once installed in an intelligent completion, this sensor will give the operating company timely information about the fluids arising from various zones or multilaterals in a complex completion pattern, allowing informed decisions to be made on controlling production. The research and development tasks are discussed along with a market analysis.

  1. Analyzing Spacecraft Telecommunication Systems

    Science.gov (United States)

    Kordon, Mark; Hanks, David; Gladden, Roy; Wood, Eric

    2004-01-01

    Multi-Mission Telecom Analysis Tool (MMTAT) is a C-language computer program for analyzing proposed spacecraft telecommunication systems. MMTAT utilizes parameterized input and computational models that can be run on standard desktop computers to perform fast and accurate analyses of telecommunication links. MMTAT is easy to use and can easily be integrated with other software applications and run as part of almost any computational simulation. It is distributed as either a stand-alone application program with a graphical user interface or a linkable library with a well-defined set of application programming interface (API) calls. As a stand-alone program, MMTAT provides both textual and graphical output. The graphs make it possible to understand, quickly and easily, how telecommunication performance varies with variations in input parameters. A delimited text file that can be read by any spreadsheet program is generated at the end of each run. The API in the linkable-library form of MMTAT enables the user to control simulation software and to change parameters during a simulation run. Results can be retrieved either at the end of a run or by use of a function call at any time step.

  2. Digital Microfluidics Sample Analyzer

    Science.gov (United States)

    Pollack, Michael G.; Srinivasan, Vijay; Eckhardt, Allen; Paik, Philip Y.; Sudarsan, Arjun; Shenderov, Alex; Hua, Zhishan; Pamula, Vamsee K.

    2010-01-01

    Three innovations address the needs of the medical world with regard to microfluidic manipulation and testing of physiological samples in ways that can benefit point-of-care needs for patients such as premature infants, for which drawing of blood for continuous tests can be life-threatening in their own right, and for expedited results. A chip with sample injection elements, reservoirs (and waste), droplet formation structures, fluidic pathways, mixing areas, and optical detection sites, was fabricated to test the various components of the microfluidic platform, both individually and in integrated fashion. The droplet control system permits a user to control droplet microactuator system functions, such as droplet operations and detector operations. Also, the programming system allows a user to develop software routines for controlling droplet microactuator system functions, such as droplet operations and detector operations. A chip is incorporated into the system with a controller, a detector, input and output devices, and software. A novel filler fluid formulation is used for the transport of droplets with high protein concentrations. Novel assemblies for detection of photons from an on-chip droplet are present, as well as novel systems for conducting various assays, such as immunoassays and PCR (polymerase chain reaction). The lab-on-a-chip (a.k.a., lab-on-a-printed-circuit board) processes physiological samples and comprises a system for automated, multi-analyte measurements using sub-microliter samples of human serum. The invention also relates to a diagnostic chip and system including the chip that performs many of the routine operations of a central labbased chemistry analyzer, integrating, for example, colorimetric assays (e.g., for proteins), chemiluminescence/fluorescence assays (e.g., for enzymes, electrolytes, and gases), and/or conductometric assays (e.g., for hematocrit on plasma and whole blood) on a single chip platform.

  3. Soft Decision Analyzer

    Science.gov (United States)

    Steele, Glen; Lansdowne, Chatwin; Zucha, Joan; Schlensinger, Adam

    2013-01-01

    The Soft Decision Analyzer (SDA) is an instrument that combines hardware, firmware, and software to perform realtime closed-loop end-to-end statistical analysis of single- or dual- channel serial digital RF communications systems operating in very low signal-to-noise conditions. As an innovation, the unique SDA capabilities allow it to perform analysis of situations where the receiving communication system slips bits due to low signal-to-noise conditions or experiences constellation rotations resulting in channel polarity in versions or channel assignment swaps. SDA s closed-loop detection allows it to instrument a live system and correlate observations with frame, codeword, and packet losses, as well as Quality of Service (QoS) and Quality of Experience (QoE) events. The SDA s abilities are not confined to performing analysis in low signal-to-noise conditions. Its analysis provides in-depth insight of a communication system s receiver performance in a variety of operating conditions. The SDA incorporates two techniques for identifying slips. The first is an examination of content of the received data stream s relation to the transmitted data content and the second is a direct examination of the receiver s recovered clock signals relative to a reference. Both techniques provide benefits in different ways and allow the communication engineer evaluating test results increased confidence and understanding of receiver performance. Direct examination of data contents is performed by two different data techniques, power correlation or a modified Massey correlation, and can be applied to soft decision data widths 1 to 12 bits wide over a correlation depth ranging from 16 to 512 samples. The SDA detects receiver bit slips within a 4 bits window and can handle systems with up to four quadrants (QPSK, SQPSK, and BPSK systems). The SDA continuously monitors correlation results to characterize slips and quadrant change and is capable of performing analysis even when the

  4. Crew Activity Analyzer

    Science.gov (United States)

    Murray, James; Kirillov, Alexander

    2008-01-01

    The crew activity analyzer (CAA) is a system of electronic hardware and software for automatically identifying patterns of group activity among crew members working together in an office, cockpit, workshop, laboratory, or other enclosed space. The CAA synchronously records multiple streams of data from digital video cameras, wireless microphones, and position sensors, then plays back and processes the data to identify activity patterns specified by human analysts. The processing greatly reduces the amount of time that the analysts must spend in examining large amounts of data, enabling the analysts to concentrate on subsets of data that represent activities of interest. The CAA has potential for use in a variety of governmental and commercial applications, including planning for crews for future long space flights, designing facilities wherein humans must work in proximity for long times, improving crew training and measuring crew performance in military settings, human-factors and safety assessment, development of team procedures, and behavioral and ethnographic research. The data-acquisition hardware of the CAA (see figure) includes two video cameras: an overhead one aimed upward at a paraboloidal mirror on the ceiling and one mounted on a wall aimed in a downward slant toward the crew area. As many as four wireless microphones can be worn by crew members. The audio signals received from the microphones are digitized, then compressed in preparation for storage. Approximate locations of as many as four crew members are measured by use of a Cricket indoor location system. [The Cricket indoor location system includes ultrasonic/radio beacon and listener units. A Cricket beacon (in this case, worn by a crew member) simultaneously transmits a pulse of ultrasound and a radio signal that contains identifying information. Each Cricket listener unit measures the difference between the times of reception of the ultrasound and radio signals from an identified beacon

  5. Gibberellins and DELLAs: central nodes in growth regulatory networks.

    Science.gov (United States)

    Claeys, Hannes; De Bodt, Stefanie; Inzé, Dirk

    2014-04-01

    Gibberellins (GAs) are growth-promoting phytohormones that were crucial in breeding improved semi-dwarf varieties during the green revolution. However, the molecular basis for GA-induced growth stimulation is poorly understood. In this review, we use light-regulated hypocotyl elongation as a case study, combined with a meta-analysis of available transcriptome data, to discuss the role of GAs as central nodes in networks connecting environmental inputs to growth. These networks are highly tissue-specific, with dynamic and rapid regulation that mostly occurs at the protein level, directly affecting the activity and transcription of effectors. New systems biology approaches addressing the role of GAs in growth should take these properties into account, combining tissue-specific interactomics, transcriptomics and modeling, to provide essential knowledge to fuel a second green revolution.

  6. Viral perturbations of host networks reflect disease etiology.

    Directory of Open Access Journals (Sweden)

    Natali Gulbahce

    Full Text Available Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases, are also associated with viral infections (virally implicated diseases, either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV and human papillomavirus (HPV, we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.

  7. Grid and Data Analyzing and Security

    Directory of Open Access Journals (Sweden)

    Fatemeh SHOKRI

    2012-12-01

    Full Text Available This paper examines the importance of secure structures in the process of analyzing and distributing information with aid of Grid-based technologies. The advent of distributed network has provided many practical opportunities for detecting and recording the time of events, and made efforts to identify the events and solve problems of storing information such as being up-to-date and documented. In this regard, the data distribution systems in a network environment should be accurate. As a consequence, a series of continuous and updated data must be at hand. In this case, Grid is the best answer to use data and resource of organizations by common processing.

  8. Human Dopamine Receptors Interaction Network (DRIN): a systems biology perspective on topology, stability and functionality of the network.

    Science.gov (United States)

    Podder, Avijit; Jatana, Nidhi; Latha, N

    2014-09-21

    Dopamine receptors (DR) are one of the major neurotransmitter receptors present in human brain. Malfunctioning of these receptors is well established to trigger many neurological and psychiatric disorders. Taking into consideration that proteins function collectively in a network for most of the biological processes, the present study is aimed to depict the interactions between all dopamine receptors following a systems biology approach. To capture comprehensive interactions of candidate proteins associated with human dopamine receptors, we performed a protein-protein interaction network (PPIN) analysis of all five receptors and their protein partners by mapping them into human interactome and constructed a human Dopamine Receptors Interaction Network (DRIN). We explored the topology of dopamine receptors as molecular network, revealing their characteristics and the role of central network elements. More to the point, a sub-network analysis was done to determine major functional clusters in human DRIN that govern key neurological pathways. Besides, interacting proteins in a pathway were characterized and prioritized based on their affinity for utmost drug molecules. The vulnerability of different networks to the dysfunction of diverse combination of components was estimated under random and direct attack scenarios. To the best of our knowledge, the current study is unique to put all five dopamine receptors together in a common interaction network and to understand the functionality of interacting proteins collectively. Our study pinpointed distinctive topological and functional properties of human dopamine receptors that have helped in identifying potential therapeutic drug targets in the dopamine interaction network.

  9. New insights into schizophrenia disease genes interactome in the human brain: emerging targets and therapeutic implications in the postgenomics era.

    Science.gov (United States)

    Podder, Avijit; Latha, Narayanan

    2014-12-01

    Schizophrenia, a complex neurological disorder, is comprised of interactions between multiple genetic and environmental factors wherein each of the factors individually exhibits a small effect. In this regard a network-based strategy is best suited to capture the combined effect of multiple genes with their definite pattern of interactions. Given that schizophrenia affects multiple regions of the brain, we postulated that instead of any single specific tissue, a mutual set of interactions occurs between different regions of brain in a well-defined pattern responsible for the disease phenotype. To validate, we constructed and compared tissue specific co-expression networks of schizophrenia candidate genes in twenty diverse brain tissues. As predicted, we observed a common interaction network of certain genes in all the studied brain tissues. We examined fundamental network topologies of the common network to sequester essential common candidates for schizophrenia. We also performed a gene set analysis to identify the essential biological pathways enriched by the common candidates in the network. Finally, the candidate drug targets were prioritized and scored against known available schizophrenic drugs by molecular docking studies. We distinctively identified protein kinases as the top candidates in the network that can serve as probable drug targets for the disease. Conclusively, we propose that a comprehensive study of the connectivity amongst the disease genes themselves may turn out to be more informative to understand schizophrenia disease etiology and the underlying complexity.

  10. Dynamic Network Models

    CERN Document Server

    Armbruster, Benjamin

    2011-01-01

    We analyze random networks that change over time. First we analyze a dynamic Erdos-Renyi model, whose edges change over time. We describe its stationary distribution, its convergence thereto, and the SI contact process on the network, which has relevance for connectivity and the spread of infections. Second, we analyze the effect of node turnover, when nodes enter and leave the network, which has relevance for network models incorporating births, deaths, aging, and other demographic factors.

  11. Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

    Directory of Open Access Journals (Sweden)

    Pedamallu Chandra Sekhar

    2010-08-01

    Full Text Available Abstract Background Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible. Methods Here we report the development of a simple open source program module (OpenPPI_predictor that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism. Results Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans. Availability The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/.

  12. Uncovering Arabidopsis membrane protein interactome enriched in transporters using mating-based split ubiquitin assays and classification models

    Directory of Open Access Journals (Sweden)

    Jin eChen

    2012-06-01

    Full Text Available High-throughput data are a double-edged sword; for the benefit of large amount of data, there is an associated cost of noise. To increase reliability and scalability of high-throughput protein interaction data generation, we tested the efficacy of classification to enrich potential protein-protein interactions (pPPIs. We applied this method to identify interactions among Arabidopsis membrane proteins enriched in transporters. We validated our method with multiple retests. Classification improved the quality of the ensuing interaction network and was effective in reducing the search space and increasing true positive rate. The final network of 541 interactions among 239 proteins (of which 179 are transporters is the first protein interaction network enriched in membrane transporters reported for any organism. This network has similar topological attributes to other published protein interaction networks. It also extends and fills gaps in currently available biological networks in plants and allows building a number of hypotheses about processes and mechanisms involving signal-transduction and transport systems.

  13. Uncovering Arabidopsis Membrane Protein Interactome Enriched in Transporters Using Mating-Based Split Ubiquitin Assays and Classification Models

    Science.gov (United States)

    Chen, Jin; Lalonde, Sylvie; Obrdlik, Petr; Noorani Vatani, Azam; Parsa, Saman A.; Vilarino, Cristina; Revuelta, Jose Luis; Frommer, Wolf B.; Rhee, Seung Y.

    2012-01-01

    High-throughput data are a double-edged sword; for the benefit of large amount of data, there is an associated cost of noise. To increase reliability and scalability of high-throughput protein interaction data generation, we tested the efficacy of classification to enrich potential protein–protein interactions. We applied this method to identify interactions among Arabidopsis membrane proteins enriched in transporters. We validated our method with multiple retests. Classification improved the quality of the ensuing interaction network and was effective in reducing the search space and increasing true positive rate. The final network of 541 interactions among 239 proteins (of which 179 are transporters) is the first protein interaction network enriched in membrane transporters reported for any organism. This network has similar topological attributes to other published protein interaction networks. It also extends and fills gaps in currently available biological networks in plants and allows building a number of hypotheses about processes and mechanisms involving signal-transduction and transport systems. PMID:22737156

  14. Packet transport network in metro

    Science.gov (United States)

    Huang, Feng; Yi, Xiaobo; Zhang, Hanzheng; Gong, Ping

    2008-11-01

    IP packet based services such as high speed internet, IP voice and IP video will be widely deployed in telecom network, which make transport network evolution to packet transport network. Characteristics of transport network and requirements of packet transport network are analyzed, T-MPLS/MPLS-TP based PTN technology is given and it will be used in metro (access, aggregation and core) network.

  15. The Activation-Induced Assembly of an RNA/Protein Interactome Centered on the Splicing Factor U2AF2 Regulates Gene Expression in Human CD4 T Cells.

    Science.gov (United States)

    Whisenant, Thomas C; Peralta, Eigen R; Aarreberg, Lauren D; Gao, Nina J; Head, Steven R; Ordoukhanian, Phillip; Williamson, Jamie R; Salomon, Daniel R

    2015-01-01

    Activation of CD4 T cells is a reaction to challenges such as microbial pathogens, cancer and toxins that defines adaptive immune responses. The roles of T cell receptor crosslinking, intracellular signaling, and transcription factor activation are well described, but the importance of post-transcriptional regulation by RNA-binding proteins (RBPs) has not been considered in depth. We describe a new model expanding and activating primary human CD4 T cells and applied this to characterizing activation-induced assembly of splicing factors centered on U2AF2. We immunoprecipitated U2AF2 to identify what mRNA transcripts were bound as a function of activation by TCR crosslinking and costimulation. In parallel, mass spectrometry revealed the proteins incorporated into the U2AF2-centered RNA/protein interactome. Molecules that retained interaction with the U2AF2 complex after RNAse treatment were designated as "central" interactome members (CIMs). Mass spectrometry also identified a second class of activation-induced proteins, "peripheral" interactome members (PIMs), that bound to the same transcripts but were not in physical association with U2AF2 or its partners. siRNA knockdown of two CIMs and two PIMs caused changes in activation marker expression, cytokine secretion, and gene expression that were unique to each protein and mapped to pathways associated with key aspects of T cell activation. While knocking down the PIM, SYNCRIP, impacts a limited but immunologically important set of U2AF2-bound transcripts, knockdown of U2AF1 significantly impairs assembly of the majority of protein and mRNA components in the activation-induced interactome. These results demonstrated that CIMs and PIMs, either directly or indirectly through RNA, assembled into activation-induced U2AF2 complexes and play roles in post-transcriptional regulation of genes related to cytokine secretion. These data suggest an additional layer of regulation mediated by the activation-induced assembly of RNA

  16. From hub proteins to hub modules: the relationship between essentiality and centrality in the yeast interactome at different scales of organization.

    Directory of Open Access Journals (Sweden)

    Jimin Song

    Full Text Available Numerous studies have suggested that hub proteins in the S. cerevisiae physical interaction network are more likely to be essential than other proteins. The proposed reasons underlying this observed relationship between topology and functioning have been subject to some controversy, with recent work suggesting that it arises due to the participation of hub proteins in essential complexes and processes. However, do these essential modules themselves have distinct network characteristics, and how do their essential proteins differ in their topological properties from their non-essential proteins? We aimed to advance our understanding of protein essentiality by analyzing proteins, complexes and processes within their broader functional context and by considering physical interactions both within and across complexes and biological processes. In agreement with the view that essentiality is a modular property, we found that the number of intracomplex or intraprocess interactions that a protein has is a better indicator of its essentiality than its overall number of interactions. Moreover, we found that within an essential complex, its essential proteins have on average more interactions, especially intracomplex interactions, than its non-essential proteins. Finally, we built a module-level interaction network and found that essential complexes and processes tend to have higher interaction degrees in this network than non-essential complexes and processes; that is, they exhibit a larger amount of functional cross-talk than their non-essential counterparts.

  17. Coordinating, Scheduling, Processing and Analyzing IYA09

    Science.gov (United States)

    Gipson, John; Behrend, Dirk; Gordon, David; Himwich, Ed; MacMillan, Dan; Titus, Mike; Corey, Brian

    2010-01-01

    The IVS scheduled a special astrometric VLBI session for the International Year of Astronomy 2009 (IYA09) commemorating 400 years of optical astronomy and 40 years of VLBI. The IYA09 session is the most ambitious geodetic session to date in terms of network size, number of sources, and number of observations. We describe the process of designing, coordinating, scheduling, pre-session station checkout, correlating, and analyzing this session.

  18. On Random Linear Network Coding for Butterfly Network

    CERN Document Server

    Guang, Xuan

    2010-01-01

    Random linear network coding is a feasible encoding tool for network coding, specially for the non-coherent network, and its performance is important in theory and application. In this letter, we study the performance of random linear network coding for the well-known butterfly network by analyzing the failure probabilities. We determine the failure probabilities of random linear network coding for the well-known butterfly network and the butterfly network with channel failure probability p.

  19. Competing intramolecular N-H⋯O=C hydrogen bonds and extended intermolecular network in 1-(4-chlorobenzoyl)-3-(2-methyl-4-oxopentan-2-yl) thiourea analyzed by experimental and theoretical methods

    Energy Technology Data Exchange (ETDEWEB)

    Saeed, Aamer, E-mail: aamersaeed@yahoo.com [Department of Chemistry, Quaid-I-Azam University, Islamabad 45320 (Pakistan); Khurshid, Asma [Department of Chemistry, Quaid-I-Azam University, Islamabad 45320 (Pakistan); Jasinski, Jerry P. [Department of Chemistry, Keene State College, 229 Main Street Keene, NH 03435-2001 (United States); Pozzi, C. Gustavo; Fantoni, Adolfo C. [Instituto de Física La Plata, Departamento de Física, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, 49 y 115, La Plata, Buenos Aires (Argentina); Erben, Mauricio F., E-mail: erben@quimica.unlp.edu.ar [CEQUINOR (UNLP, CONICET-CCT La Plata), Departamento de Química, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, C.C. 962, (1900) La Plata, Buenos Aires (Argentina)

    2014-03-18

    Highlights: • Two distinct N-H⋯O=C intramolecular competing hydrogen bonds are feasible in the title molecule. • Crystal structures and vibrational properties were determined. • The C=O and C=S double bonds of the acyl-thiourea group are mutually oriented in opposite directions. • A strong hyperconjugative lpO1 → σ{sup ∗}(N2-H) remote interaction was detected. • Topological analysis reveals a Cl⋯N interaction playing a relevant role in crystal packing. - Abstract: The synthesis of a novel 1-acyl-thiourea species (C{sub 14}H{sub 17}N{sub 2}O{sub 2}SCl), has been tailored in such a way that two distinct N-H⋯O=C intramolecular competing hydrogen bonds are feasible. The X-ray structure analysis as well as the vibrational (FT-IR and FT-Raman) data reveal that the S conformation is preferred, with the C=O and C=S bonds of the acyl-thiourea group pointing in opposite directions. The preference for the intramolecular N-H⋯O=C hydrogen bond within the -C(O)NHC(S)NH- core is confirmed. The Natural Bond Orbital and the Atom in Molecule approaches demonstrate that a strong hyperconjugative lpO → σ{sup ∗}(N-H) remote interaction between the acyl and the thioamide N-H groups is responsible for the stabilization of the S conformation. Intermolecular interactions have been characterized in the periodic system electron density and the topological analysis reveals the presence of an extended intermolecular network in the crystal, including a Cl⋯N interaction playing a relevant role in crystal packing.

  20. MaxiK channel interactome reveals its interaction with GABA transporter 3 and heat shock protein 60 in the mammalian brain.

    Science.gov (United States)

    Singh, H; Li, M; Hall, L; Chen, S; Sukur, S; Lu, R; Caputo, A; Meredith, A L; Stefani, E; Toro, L

    2016-03-11

    Large conductance voltage and calcium-activated potassium (MaxiK) channels are activated by membrane depolarization and elevated cytosolic Ca(2+). In the brain, they localize to neurons and astrocytes, where they play roles such as resetting the membrane potential during an action potential, neurotransmitter release, and neurovascular coupling. MaxiK channels are known to associate with several modulatory proteins and accessory subunits, and each of these interactions can have distinct physiological consequences. To uncover new players in MaxiK channel brain physiology, we applied a directed proteomic approach and obtained MaxiK channel pore-forming α subunit brain interactome using specific antibodies. Controls included immunoprecipitations with rabbit immunoglobulin G (IgG) and with anti-MaxiK antibodies in wild type and MaxiK channel knockout mice (Kcnma1(-/-)), respectively. We have found known and unreported interactive partners that localize to the plasma membrane, extracellular space, cytosol and intracellular organelles including mitochondria, nucleus, endoplasmic reticulum and Golgi apparatus. Localization of MaxiK channel to mitochondria was further confirmed using purified brain mitochondria colabeled with MitoTracker. Independent proof of MaxiK channel interaction with previously unidentified partners is given for GABA transporter 3 (GAT3) and heat shock protein 60 (HSP60). In human embryonic kidney 293 cells containing SV40 T-antigen (HEK293T) cells, both GAT3 and HSP60 coimmunoprecipitated and colocalized with MaxiK channel; colabeling was observed mainly at the cell periphery with GAT3 and intracellularly with HSP60 with protein proximity indices of ∼ 0.6 and ∼ 0.4, respectively. In rat primary hippocampal neurons, colocalization index was identical for GAT3 (∼ 0.6) and slightly higher for HSP60 (∼ 0.5) association with MaxiK channel. The results of this study provide a complete interactome of MaxiK channel the mouse brain, further establish

  1. Systematic Determination of Human Cyclin Dependent Kinase (CDK)-9 Interactome Identifies Novel Functions in RNA Splicing Mediated by the DEAD Box (DDX)-5/17 RNA Helicases.

    Science.gov (United States)

    Yang, Jun; Zhao, Yingxin; Kalita, Mridul; Li, Xueling; Jamaluddin, Mohammad; Tian, Bing; Edeh, Chukwudi B; Wiktorowicz, John E; Kudlicki, Andrzej; Brasier, Allan R

    2015-10-01

    Inducible transcriptional elongation is a rapid, stereotypic mechanism for activating immediate early immune defense genes by the epithelium in response to viral pathogens. Here, the recruitment of a multifunctional complex containing the cyclin dependent kinase 9 (CDK9) triggers the process of transcriptional elongation activating resting RNA polymerase engaged with innate immune response (IIR) genes. To identify additional functional activity of the CDK9 complex, we conducted immunoprecipitation (IP) enrichment-stable isotope labeling LC-MS/MS of the CDK9 complex in unstimulated cells and from cells activated by a synthetic dsRNA, polyinosinic/polycytidylic acid [poly (I:C)]. 245 CDK9 interacting proteins were identified with high confidence in the basal state and 20 proteins in four functional classes were validated by IP-SRM-MS. These data identified that CDK9 interacts with DDX 5/17, a family of ATP-dependent RNA helicases, important in alternative RNA splicing of NFAT5, and mH2A1 mRNA two proteins controlling redox signaling. A direct comparison of the basal versus activated state was performed using stable isotope labeling and validated by IP-SRM-MS. Recruited into the CDK9 interactome in response to poly(I:C) stimulation are HSPB1, DNA dependent kinases, and cytoskeletal myosin proteins that exchange with 60S ribosomal structural proteins. An integrated human CDK9 interactome map was developed containing all known human CDK9- interacting proteins. These data were used to develop a probabilistic global map of CDK9-dependent target genes that predicted two functional states controlling distinct cellular functions, one important in immune and stress responses. The CDK9-DDX5/17 complex was shown to be functionally important by shRNA-mediated knockdown, where differential accumulation of alternatively spliced NFAT5 and mH2A1 transcripts and alterations in downstream redox signaling were seen. The requirement of CDK9 for DDX5 recruitment to NFAT5 and mH2A1

  2. Analyzing viewpoint diversity in twitter

    NARCIS (Netherlands)

    Bozdag, V.E.; Gao, Q.; Warnier, M.E.; Houben, G.J.P.M.

    2013-01-01

    Information diversity has a long tradition in human history. Recently there have been claims that diversity is diminishing in information available in social networks. On the other hand, some studies suggest that diversity is actually quite high in social networks such as Twitter. However these stud

  3. Reconstruction of the temporal signaling network in Salmonella-infected human cells

    Directory of Open Access Journals (Sweden)

    Gungor eBudak

    2015-07-01

    Full Text Available Salmonella enterica is a bacterial pathogen that usually infects its host through food sources. Translocation of the pathogen proteins into the host cells leads to changes in the signaling mechanism either by activating or inhibiting the host proteins. Using high-throughput ‘omic’ technologies, changes in the signaling components can be quantified at different levels; however, experimental hits are usually incomplete to represent the whole signaling system as some driver proteins stay hidden within the experimental data. Given that the bacterial infection modifies the response network of the host, more coherent view of the underlying biological processes and the signaling networks can be obtained by using a network modeling approach based on the reverse engineering principles in which a confident region from the protein interactome is found by inferring hits from the omic experiments. In this work, we have used a published temporal phosphoproteomic dataset of Salmonella-infected human cells and reconstructed the temporal signaling network of the human host by integrating the interactome and the phosphoproteomic datasets. We have combined two well-established network modeling frameworks, the Prize-collecting Steiner Forest (PCSF approach and the Integer Linear Programming (ILP based edge inference approach. The resulting network conserves the information on temporality, direction of interactions, while revealing hidden entities in the signaling, such as the SNARE binding, mTOR signaling, immune response, cytoskeleton organization, and apoptosis pathways. Targets of the Salmonella effectors in the host cells such as CDC42, RHOA, 14-3-3δ, Syntaxin family, Oxysterol-binding proteins were included in the reconstructed signaling network although they were not present in the initial phosphoproteomic data. We believe that integrated approaches have a high potential for the identification of clinical targets in infectious diseases, especially in the

  4. Assembly and interrogation of Alzheimer's disease genetic networks reveal novel regulators of progression.

    Directory of Open Access Journals (Sweden)

    Soline Aubry

    Full Text Available Alzheimer's disease (AD is a complex multifactorial disorder with poorly characterized pathogenesis. Our understanding of this disease would thus benefit from an approach that addresses this complexity by elucidating the regulatory networks that are dysregulated in the neural compartment of AD patients, across distinct brain regions. Here, we use a Systems Biology (SB approach, which has been highly successful in the dissection of cancer related phenotypes, to reverse engineer the transcriptional regulation layer of human neuronal cells and interrogate it to infer candidate Master Regulators (MRs responsible for disease progression. Analysis of gene expression profiles from laser-captured neurons from AD and controls subjects, using the Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe, yielded an interactome consisting of 488,353 transcription-factor/target interactions. Interrogation of this interactome, using the Master Regulator INference algorithm (MARINa, identified an unbiased set of candidate MRs causally responsible for regulating the transcriptional signature of AD progression. Experimental assays in autopsy-derived human brain tissue showed that three of the top candidate MRs (YY1, p300 and ZMYM3 are indeed biochemically and histopathologically dysregulated in AD brains compared to controls. Our results additionally implicate p53 and loss of acetylation homeostasis in the neurodegenerative process. This study suggests that an integrative, SB approach can be applied to AD and other neurodegenerative diseases, and provide significant novel insight on the disease progression.

  5. Protein interaction network of alternatively spliced isoforms from brain links genetic risk factors for autism.

    Science.gov (United States)

    Corominas, Roser; Yang, Xinping; Lin, Guan Ning; Kang, Shuli; Shen, Yun; Ghamsari, Lila; Broly, Martin; Rodriguez, Maria; Tam, Stanley; Trigg, Shelly A; Fan, Changyu; Yi, Song; Tasan, Murat; Lemmens, Irma; Kuang, Xingyan; Zhao, Nan; Malhotra, Dheeraj; Michaelson, Jacob J; Vacic, Vladimir; Calderwood, Michael A; Roth, Frederick P; Tavernier, Jan; Horvath, Steve; Salehi-Ashtiani, Kourosh; Korkin, Dmitry; Sebat, Jonathan; Hill, David E; Hao, Tong; Vidal, Marc; Iakoucheva, Lilia M

    2014-04-11

    Increased risk for autism spectrum disorders (ASD) is attributed to hundreds of genetic loci. The convergence of ASD variants have been investigated using various approaches, including protein interactions extracted from the published literature. However, these datasets are frequently incomplete, carry biases and are limited to interactions of a single splicing isoform, which may not be expressed in the disease-relevant tissue. Here we introduce a new interactome mapping approach by experimentally identifying interactions between brain-expressed alternatively spliced variants of ASD risk factors. The Autism Spliceform Interaction Network reveals that almost half of the detected interactions and about 30% of the newly identified interacting partners represent contribution from splicing variants, emphasizing the importance of isoform networks. Isoform interactions greatly contribute to establishing direct physical connections between proteins from the de novo autism CNVs. Our findings demonstrate the critical role of spliceform networks for translating genetic knowledge into a better understanding of human diseases.

  6. Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome--clozapine-induced agranulocytosis as a case study.

    Directory of Open Access Journals (Sweden)

    Lun Yang

    2011-03-01

    Full Text Available In the era of personalized medical practice, understanding the genetic basis of patient-specific adverse drug reaction (ADR is a major challenge. Clozapine provides effective treatments for schizophrenia but its usage is limited because of life-threatening agranulocytosis. A recent high impact study showed the necessity of moving clozapine to a first line drug, thus identifying the biomarkers for drug-induced agranulocytosis has become important. Here we report a methodology termed as antithesis chemical-protein interactome (CPI, which utilizes the docking method to mimic the differences in the drug-protein interactions across a panel of human proteins. Using this method, we identified HSPA1A, a known susceptibility gene for CIA, to be the off-target of clozapine. Furthermore, the mRNA expression of HSPA1A-related genes (off-target associated systems was also found to be differentially expressed in clozapine treated leukemia cell line. Apart from identifying the CIA causal genes we identified several novel candidate genes which could be responsible for agranulocytosis. Proteins related to reactive oxygen clearance system, such as oxidoreductases and glutathione metabolite enzymes, were significantly enriched in the antithesis CPI. This methodology conducted a multi-dimensional analysis of drugs' perturbation to the biological system, investigating both the off-targets and the associated off-systems to explore the molecular basis of an adverse event or the new uses for old drugs.

  7. Interactomic analysis of REST/NRSF and implications of its functional links with the transcription suppressor TRIM28 during neuronal differentiation

    Science.gov (United States)

    Lee, Namgyu; Park, Sung Jin; Haddad, Ghazal; Kim, Dae-Kyum; Park, Seon-Min; Park, Sang Ki; Choi, Kwan Yong

    2016-01-01

    RE-1 silencing transcription factor (REST) is a transcriptional repressor that regulates gene expression by binding to repressor element 1. However, despite its critical function in physiology, little is known about its interaction proteins. Here we identified 204 REST-interacting proteins using affinity purification and mass spectrometry. The interactome included proteins associated with mRNA processing/splicing, chromatin organization, and transcription. The interactions of these REST-interacting proteins, which included TRIM28, were confirmed by co-immunoprecipitation and immunocytochemistry, respectively. Gene Ontology (GO) analysis revealed that neuronal differentiation-related GO terms were enriched among target genes that were co-regulated by REST and TRIM28, while the level of CTNND2 was increased by the knockdown of REST and TRIM28. Consistently, the level of CTNND2 increased while those of REST and TRIM28 decreased during neuronal differentiation in the primary neurons, suggesting that CTNND2 expression may be co-regulated by both. Furthermore, neurite outgrowth was increased by depletion of REST or TRIM28, implying that reduction of both REST and TRIM28 could promote neuronal differentiation via induction of CTNND2 expression. In conclusion, our study of REST reveals novel interacting proteins which could be a valuable resource for investigating unidentified functions of REST and also suggested functional links between REST and TRIM28 during neuronal development. PMID:27976729

  8. Elucidation of the Ebola virus VP24 cellular interactome and disruption of virus biology through targeted inhibition of host-cell protein function.

    Science.gov (United States)

    García-Dorival, Isabel; Wu, Weining; Dowall, Stuart; Armstrong, Stuart; Touzelet, Olivier; Wastling, Jonathan; Barr, John N; Matthews, David; Carroll, Miles; Hewson, Roger; Hiscox, Julian A

    2014-11-07

    Viral pathogenesis in the infected cell is a balance between antiviral responses and subversion of host-cell processes. Many viral proteins specifically interact with host-cell proteins to promote virus biology. Understanding these interactions can lead to knowledge gains about infection and provide potential targets for antiviral therapy. One such virus is Ebola, which has profound consequences for human health and causes viral hemorrhagic fever where case fatality rates can approach 90%. The Ebola virus VP24 protein plays a critical role in the evasion of the host immune response and is likely to interact with multiple cellular proteins. To map these interactions and better understand the potential functions of VP24, label-free quantitative proteomics was used to identify cellular proteins that had a high probability of forming the VP24 cellular interactome. Several known interactions were confirmed, thus placing confidence in the technique, but new interactions were also discovered including one with ATP1A1, which is involved in osmoregulation and cell signaling. Disrupting the activity of ATP1A1 in Ebola-virus-infected cells with a small molecule inhibitor resulted in a decrease in progeny virus, thus illustrating how quantitative proteomics can be used to identify potential therapeutic targets.

  9. 3D structure prediction of histone acetyltransferase (HAC proteins of the p300/CBP family and their interactome in Arabidopsis thaliana

    Directory of Open Access Journals (Sweden)

    Amar Cemanovic

    2014-09-01

    Full Text Available Histone acetylation is an important posttranslational modification correlated with gene activation. In Arabidopsis thaliana the histone acetyltransferase (HAC proteins of the CBP family are homologous to animal p300/CREB (cAMP-responsive element-binding proteins, which are important histone acetyltransferases participating in many physiological processes, including proliferation, differentiation, and apoptosis. In this study the 3-D structure of all HAC protein subunits in Arabidopsis thaliana: HAC1, HAC2, HAC4, HAC5 and HAC12 is predicted by homology modeling and confirmed by Ramachandran plot analysis. The amino acid sequences HAC family members are highly similar to the sequences of the homologous human p300/CREB protein. Conservation of p300/CBP domains among the HAC proteins was examined further by sequence alignment and pattern search. The domains of p300/CBP required for the HAC function, such as PHD, TAZ and ZZ domains, are conserved in all HAC proteins. Interactome analysis revealed that HAC1, HAC5 and HAC12 proteins interact with S-adenosylmethionine-dependent methyltransferase domaincontaining protein that shows methyltransferase activity, suggesting an additional function of the HAC proteins. Additionally, HAC5 has a strong interaction value for the putative c-myb-like transcription factor MYB3R-4, which suggests that it also may have a function in regulation of DNA replication.

  10. Complexity of Public Transport Networks

    Institute of Scientific and Technical Information of China (English)

    LU Huapu; SHI Ye

    2007-01-01

    The theory of complex networks was used to classify public transport networks into public transportation route networks, public transportation transfer networks, and bus station networks. The practical significance of the network parameters was then analyzed. The public transport networks in Langfang, Jining, and Dalian were then chosen as specific research cases. The results show that the public transportation networks have the characteristics of complex networks. In addition, the urban transportation network parameters all significantly affect the accessibility, convenience, and terrorist security capability of the urban public transportation network. The results link the findings with the actual situations to explore means to solve transportation system problems.

  11. Analyzing and Assessing Brain Structure with Graph Connectivity Measures

    Science.gov (United States)

    2014-05-09

    here. We implement several connectiv - ity measures used in previous studies which used networks to analyze brain structure in order to reproduce results... connectiv - ity measures. In response, we implemented a breadth first search algorithm which examined unconnected networks and found the largest

  12. Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

    Science.gov (United States)

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR-essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR-essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR-essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR-essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR-induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple organisms led

  13. Dissecting the gene network of dietary restriction to identify evolutionarily conserved pathways and new functional genes.

    Directory of Open Access Journals (Sweden)

    Daniel Wuttke

    Full Text Available Dietary restriction (DR, limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR-essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/. To dissect the interactions of DR-essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR-essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR-essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2 had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR-induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of

  14. Dissecting the Gene Network of Dietary Restriction to Identify Evolutionarily Conserved Pathways and New Functional Genes

    Science.gov (United States)

    Wuttke, Daniel; Connor, Richard; Vora, Chintan; Craig, Thomas; Li, Yang; Wood, Shona; Vasieva, Olga; Shmookler Reis, Robert; Tang, Fusheng; de Magalhães, João Pedro

    2012-01-01

    Dietary restriction (DR), limiting nutrient intake from diet without causing malnutrition, delays the aging process and extends lifespan in multiple organisms. The conserved life-extending effect of DR suggests the involvement of fundamental mechanisms, although these remain a subject of debate. To help decipher the life-extending mechanisms of DR, we first compiled a list of genes that if genetically altered disrupt or prevent the life-extending effects of DR. We called these DR–essential genes and identified more than 100 in model organisms such as yeast, worms, flies, and mice. In order for other researchers to benefit from this first curated list of genes essential for DR, we established an online database called GenDR (http://genomics.senescence.info/diet/). To dissect the interactions of DR–essential genes and discover the underlying lifespan-extending mechanisms, we then used a variety of network and systems biology approaches to analyze the gene network of DR. We show that DR–essential genes are more conserved at the molecular level and have more molecular interactions than expected by chance. Furthermore, we employed a guilt-by-association method to predict novel DR–essential genes. In budding yeast, we predicted nine genes related to vacuolar functions; we show experimentally that mutations deleting eight of those genes prevent the life-extending effects of DR. Three of these mutants (OPT2, FRE6, and RCR2) had extended lifespan under ad libitum, indicating that the lack of further longevity under DR is not caused by a general compromise of fitness. These results demonstrate how network analyses of DR using GenDR can be used to make phenotypically relevant predictions. Moreover, gene-regulatory circuits reveal that the DR–induced transcriptional signature in yeast involves nutrient-sensing, stress responses and meiotic transcription factors. Finally, comparing the influence of gene expression changes during DR on the interactomes of multiple

  15. Soft Decision Analyzer and Method

    Science.gov (United States)

    Steele, Glen F. (Inventor); Lansdowne, Chatwin (Inventor); Zucha, Joan P. (Inventor); Schlesinger, Adam M. (Inventor)

    2016-01-01

    A soft decision analyzer system is operable to interconnect soft decision communication equipment and analyze the operation thereof to detect symbol wise alignment between a test data stream and a reference data stream in a variety of operating conditions.

  16. Comparison of an expanded ataxia interactome with patient medical records reveals a relationship between macular degeneration and ataxia

    Science.gov (United States)

    Kahle, Juliette J.; Gulbahce, Natali; Shaw, Chad A.; Lim, Janghoo; Hill, David E.; Barabási, Albert-László; Zoghbi, Huda Y.

    2011-01-01

    Spinocerebellar ataxias 6 and 7 (SCA6 and SCA7) are neurodegenerative disorders caused by expansion of CAG repeats encoding polyglutamine (polyQ) tracts in CACNA1A, the alpha1A subunit of the P/Q-type calcium channel, and ataxin-7 (ATXN7), a component of a chromatin-remodeling complex, respectively. We hypothesized that finding new protein partners for ATXN7 and CACNA1A would provide insight into the biology of their respective diseases and their relationship to other ataxia-causing proteins. We identified 118 protein interactions for CACNA1A and ATXN7 linking them to other ataxia-causing proteins and the ataxia network. To begin to understand the biological relevance of these protein interactions within the ataxia network, we used OMIM to identify diseases associated with the expanded ataxia network. We then used Medicare patient records to determine if any of these diseases co-occur with hereditary ataxia. We found that patients with ataxia are at 3.03-fold greater risk of these diseases than Medicare patients overall. One of the diseases comorbid with ataxia is macular degeneration (MD). The ataxia network is significantly (P= 7.37 × 10−5) enriched for proteins that interact with known MD-causing proteins, forming a MD subnetwork. We found that at least two of the proteins in the MD subnetwork have altered expression in the retina of Ataxin-7266Q/+ mice suggesting an in vivo functional relationship with ATXN7. Together these data reveal novel protein interactions and suggest potential pathways that can contribute to the pathophysiology of ataxia, MD, and diseases comorbid with ataxia. PMID:21078624

  17. Fundamentals of Stochastic Networks

    CERN Document Server

    Ibe, Oliver C

    2011-01-01

    An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used. Combining techniques from stochastic processes and graph theory to analyze the behavior of networks, Fundamentals of Stochastic Networks provides an interdisciplinary approach by including practical applications of these stochastic networks in various fields of study, from engineering and operations management to communications and the physi

  18. VoIP Forensic Analyzer

    Directory of Open Access Journals (Sweden)

    M Mohemmed Sha

    2016-01-01

    Full Text Available People have been utilizing Voice over Internet Protocol (VoIP in most of the conventional communication facilities which has been of assistance in the enormous attenuation of operating costs, as well as the promotion of next- generation communication services-based IP. As an intimidating upshot, cyber criminals have correspondingly started interjecting the environment and creating new challenges for the law enforcement system in any Country. This paper presents an idea of a framework for the forensic analysis of the VoIP traffic over the network. This forensic activity includes spotting and scrutinizing the network patterns of VoIP-SIP stream, which is used to initiate a session for the communication, and regenerate the content from VoIP-RTP stream, which is employed to convey the data. Proposed network forensic investigation framework also accentuates on developing an efficient packet restructuring algorithm for tracing the depraved users involved in a conversation. Network forensics is the basis of proposed work, and performs packet level surveillance of VoIP followed by reconstruction of original malicious content or network session between users for their prosecution in the court.

  19. Network simulation experiments manual

    CERN Document Server

    Aboelela, Emad

    2011-01-01

    Network Simulation Experiments Manual, Third Edition, contains simulation-based experiments to help students and professionals learn about key concepts in computer networking. The simulation approach provides a virtual environment for a wide range of desirable features, such as modeling a network based on specified criteria and analyzing its performance under different scenarios. The experiments include the basics of using OPNET IT Guru Academic Edition; operation of the Ethernet network; partitioning of a physical network into separate logical networks using virtual local area networks (V

  20. PM 3655 PHILIPS Logic analyzer

    CERN Multimedia

    A logic analyzer is an electronic instrument that captures and displays multiple signals from a digital system or digital circuit. A logic analyzer may convert the captured data into timing diagrams, protocol decodes, state machine traces, assembly language, or may correlate assembly with source-level software. Logic Analyzers have advanced triggering capabilities, and are useful when a user needs to see the timing relationships between many signals in a digital system.

  1. High-throughput proteomic characterization of plasma rich in growth factors (PRGF-Endoret)-derived fibrin clot interactome.

    Science.gov (United States)

    Anitua, Eduardo; Prado, Roberto; Azkargorta, Mikel; Rodriguez-Suárez, Eva; Iloro, Ibon; Casado-Vela, Juan; Elortza, Felix; Orive, Gorka

    2015-11-01

    Plasma rich in growth factors (PRGF®-Endoret®) is an autologous technology that contains a set of proteins specifically addressed to wound healing and tissue regeneration. The scaffold formed by using this technology is a clot mainly composed of fibrin protein, forming a three-dimensional (3D) macroscopic network. This biomaterial is easily obtained by biotechnological means from blood and can be used in a range of situations to help wound healing and tissue regeneration. Although the main constituent of this clot is the fibrin scaffold, little is known about other proteins interacting in this clot that may act as adjuvants in the healing process. The aim of this study was to characterize the proteins enclosed by PRGF-Endoret scaffold, using a double-proteomic approach that combines 1D-SDS-PAGE approach followed by LC-MS/MS, and 2-DE followed by MALDI-TOF/TOF. The results presented here provide a description of the catalogue of key proteins in close contact with the fibrin scaffold. The obtained lists of proteins were grouped into families and networks according to gene ontology. Taken together, an enrichment of both proteins and protein families specifically involved in tissue regeneration and wound healing has been found.

  2. Analyzing and Modelling Energy Harvesting Wireless Sensor Networks

    OpenAIRE

    Ventura Jaume, Joan

    2011-01-01

    Projecte final de carrera fet en col.laboració amb Northeastern University. English: Energy harvesting is envisaged as an enabling technology to meet the growing energy demands of the 21st century. The current state of the art allows tapping into several physical and naturally existing sources, such as solar, wind, vibration, RF scavenging, among others. However, there is a lack of theoretical models that can predict future consumption and residual availability of energy in a sensor node e...

  3. The Mutational Landscape of Acute Promyelocytic Leukemia Reveals an Interacting Network of Co-Occurrences and Recurrent Mutations.

    Directory of Open Access Journals (Sweden)

    Mariam Ibáñez

    Full Text Available Preliminary Acute Promyelocytic Leukemia (APL whole exome sequencing (WES studies have identified a huge number of somatic mutations affecting more than a hundred different genes mainly in a non-recurrent manner, suggesting that APL is a heterogeneous disease with secondary relevant changes not yet defined. To extend our knowledge of subtle genetic alterations involved in APL that might cooperate with PML/RARA in the leukemogenic process, we performed a comprehensive analysis of somatic mutations in APL combining WES with sequencing of a custom panel of targeted genes by next-generation sequencing. To select a reduced subset of high confidence candidate driver genes, further in silico analysis were carried out. After prioritization and network analysis we found recurrent deleterious mutations in 8 individual genes (STAG2, U2AF1, SMC1A, USP9X, IKZF1, LYN, MYCBP2 and PTPN11 with a strong potential of being involved in APL pathogenesis. Our network analysis of multiple mutations provides a reliable approach to prioritize genes for additional analysis, improving our knowledge of the leukemogenesis interactome. Additionally, we have defined a functional module in the interactome of APL. The hypothesis is that the number, or the specific combinations, of mutations harbored in each patient might not be as important as the disturbance caused in biological key functions, triggered by several not necessarily recurrent mutations.

  4. The Mutational Landscape of Acute Promyelocytic Leukemia Reveals an Interacting Network of Co-Occurrences and Recurrent Mutations.

    Science.gov (United States)

    Ibáñez, Mariam; Carbonell-Caballero, José; García-Alonso, Luz; Such, Esperanza; Jiménez-Almazán, Jorge; Vidal, Enrique; Barragán, Eva; López-Pavía, María; LLop, Marta; Martín, Iván; Gómez-Seguí, Inés; Montesinos, Pau; Sanz, Miguel A; Dopazo, Joaquín; Cervera, José

    2016-01-01

    Preliminary Acute Promyelocytic Leukemia (APL) whole exome sequencing (WES) studies have identified a huge number of somatic mutations affecting more than a hundred different genes mainly in a non-recurrent manner, suggesting that APL is a heterogeneous disease with secondary relevant changes not yet defined. To extend our knowledge of subtle genetic alterations involved in APL that might cooperate with PML/RARA in the leukemogenic process, we performed a comprehensive analysis of somatic mutations in APL combining WES with sequencing of a custom panel of targeted genes by next-generation sequencing. To select a reduced subset of high confidence candidate driver genes, further in silico analysis were carried out. After prioritization and network analysis we found recurrent deleterious mutations in 8 individual genes (STAG2, U2AF1, SMC1A, USP9X, IKZF1, LYN, MYCBP2 and PTPN11) with a strong potential of being involved in APL pathogenesis. Our network analysis of multiple mutations provides a reliable approach to prioritize genes for additional analysis, improving our knowledge of the leukemogenesis interactome. Additionally, we have defined a functional module in the interactome of APL. The hypothesis is that the number, or the specific combinations, of mutations harbored in each patient might not be as important as the disturbance caused in biological key functions, triggered by several not necessarily recurrent mutations.

  5. Structure, Function and Networks of Transcription Factors Involved in Abiotic Stress Responses

    Directory of Open Access Journals (Sweden)

    Karen Skriver

    2013-03-01

    Full Text Available Transcription factors (TFs are master regulators of abiotic stress responses in plants. This review focuses on TFs from seven major TF families, known to play functional roles in response to abiotic stresses, including drought, high salinity, high osmolarity, temperature extremes and the phytohormone ABA. Although ectopic expression of several TFs has improved abiotic stress tolerance in plants, fine-tuning of TF expression and protein levels remains a challenge to avoid crop yield loss. To further our understanding of TFs in abiotic stress responses, emerging gene regulatory networks based on TFs and their direct targets genes are presented. These revealed components shared between ABA-dependent and independent signaling as well as abiotic and biotic stress signaling. Protein structure analysis suggested that TFs hubs of large interactomes have extended regions with protein intrinsic disorder (ID, referring to their lack of fixed tertiary structures. ID is now an emerging topic in plant science. Furthermore, the importance of the ubiquitin-proteasome protein degradation systems and modification by sumoylation is also apparent from the interactomes. Therefore; TF interaction partners such as E3 ubiquitin ligases and TF regions with ID represent future targets for engineering improved abiotic stress tolerance in crops.

  6. Analyzing data files in SWAN

    CERN Document Server

    Gajam, Niharika

    2016-01-01

    Traditionally analyzing data happens via batch-processing and interactive work on the terminal. The project aims to provide another way of analyzing data files: A cloud-based approach. It aims to make it a productive and interactive environment through the combination of FCC and SWAN software.

  7. Analyzing Valuation Practices through Contracts

    DEFF Research Database (Denmark)

    Tesnière, Germain; Labatut, Julie; Boxenbaum, Eva

    This paper seeks to analyze the most recent changes in how societies value animals. We analyze this topic through the prism of contracts between breeding companies and farmers. Focusing on new valuation practices and qualification of breeding animals, we question the evaluation of difficult...

  8. Label-free LC-MSe in tissue and serum reveals protein networks underlying differences between benign and malignant serous ovarian tumors.

    Directory of Open Access Journals (Sweden)

    Wouter Wegdam

    Full Text Available PURPOSE: To identify proteins and (molecular/biological pathways associated with differences between benign and malignant epithelial ovarian tumors. EXPERIMENTAL PROCEDURES: Serum of six patients with a serous adenocarcinoma of the ovary was collected before treatment, with a control group consisting of six matched patients with a serous cystadenoma. In addition to the serum, homogeneous regions of cells exhibiting uniform histology were isolated from benign and cancerous tissue by laser microdissection. We subsequently employed label-free liquid chromatography tandem mass spectrometry (LC-MSe to identify proteins in these serum and tissues samples. Analyses of differential expression between samples were performed using Bioconductor packages and in-house scripts in the statistical software package R. Hierarchical clustering and pathway enrichment analyses were performed, as well as network enrichment and interactome analysis using MetaCore. RESULTS: In total, we identified 20 and 71 proteins that were significantly differentially expressed between benign and malignant serum and tissue samples, respectively. The differentially expressed protein sets in serum and tissue largely differed with only 2 proteins in common. MetaCore network analysis, however inferred GCR-alpha and Sp1 as common transcriptional regulators. Interactome analysis highlighted 14-3-3 zeta/delta, 14-3-3 beta/alpha, Alpha-actinin 4, HSP60, and PCBP1 as critical proteins in the tumor proteome signature based on their relative overconnectivity. The data have been deposited to the ProteomeXchange with identifier PXD001084. DISCUSSION: Our analysis identified proteins with both novel and previously known associations to ovarian cancer biology. Despite the small overlap between differentially expressed protein sets in serum and tissue, APOA1 and Serotransferrin were significantly lower expressed in both serum and cancer tissue samples, suggesting a tissue-derived effect in serum

  9. Network analysis: a new approach to study endocrine disorders.

    Science.gov (United States)

    Stevens, A; De Leonibus, C; Hanson, D; Dowsey, A W; Whatmore, A; Meyer, S; Donn, R P; Chatelain, P; Banerjee, I; Cosgrove, K E; Clayton, P E; Dunne, M J

    2014-02-01

    Systems biology is the study of the interactions that occur between the components of individual cells - including genes, proteins, transcription factors, small molecules, and metabolites, and their relationships to complex physiological and pathological processes. The application of systems biology to medicine promises rapid advances in both our understanding of disease and the development of novel treatment options. Network biology has emerged as the primary tool for studying systems biology as it utilises the mathematical analysis of the relationships between connected objects in a biological system and allows the integration of varied 'omic' datasets (including genomics, metabolomics, proteomics, etc.). Analysis of network biology generates interactome models to infer and assess function; to understand mechanisms, and to prioritise candidates for further investigation. This review provides an overview of network methods used to support this research and an insight into current applications of network analysis applied to endocrinology. A wide spectrum of endocrine disorders are included ranging from congenital hyperinsulinism in infancy, through childhood developmental and growth disorders, to the development of metabolic diseases in early and late adulthood, such as obesity and obesity-related pathologies. In addition to providing a deeper understanding of diseases processes, network biology is also central to the development of personalised treatment strategies which will integrate pharmacogenomics with systems biology of the individual.

  10. Proteomic analyses of the SMYD family interactomes identify HSP90 as a novel target for SMYD2

    Institute of Scientific and Technical Information of China (English)

    Mohamed Abu-Farha; Sylvain Lanouette; Fred Elisma; Véronique Tremblay; Jeffery Butson; Daniel Figeys; Jean-Francois Couture

    2011-01-01

    The SMYD (SET and MYND domain) family of lysine methyltransferases (KMTs) plays pivotal roles in various cellular processes,including gene expression regulation and DNA damage response.Initially identified as genuine histone methyltransferases,specific members of this family have recently been shown to methylate non-histone proteins such as p53,VEGFR,and the retinoblastoma tumor suppressor (pRb).To gain further functional insights into this family of KMTs,we generated the protein interaction network for three different human SMYD proteins (SMYD2,SMYD3,and SMYDS).Characterization of each SMYD protein network revealed that they associate with both shared and unique sets of proteins.Among those,we found that HsP90 and several of its co-chaperones interact specifically with the tetratrico peptide repeat (TPR)-containing SMYD2 and SMYD3.Moreover,using proteomic and biochemical techniques,we provide evidence that SMYD2 methylates K209 and K615 on HSP90 nucleotide-binding and dimerization domains,respectively.In addition,we found that each methylation site displays unique reactivity in regard to the presence of HsP90 co-chaperones,pH,and demethylation by the lysine amine oxidase LSD1,suggesting that alternative mechanisms control HsP90 methylation by SMYD2.Altogether,this study highlights the ability of SMYD proteins to form unique protein complexes that may underlie their various biological functions and the SMYD2-mediated methylation of the key molecular chaperone HSP90.%The SMYD (SET and MYND domain) family of lysine methyltransferases (KMTs) plays pivotal roles in various cellular processes, including gene expression regulation and DNA damage response. Initially identified as genuine histone methyltransferases, specific members of this family have recently been shown to methylate non-histone proteins such as p53, VEGFR, and the retinoblastoma tumor suppressor (pRb). To gain further functional insights into this family of KMTs, we generated the protein interaction

  11. Sentiment Analyzer for Arabic Comments System

    Directory of Open Access Journals (Sweden)

    Alaa El-Dine Ali Hamouda

    2013-04-01

    Full Text Available Today, the number of users of social network is increasing. Millions of users share opinions on different aspects of life every day. Therefore social network are rich sources of data for opinion mining and sentiment analysis. Also users have become more interested in following news pages on Facebook. Several posts; political for example, have thousands of users’ comments that agree/disagree with the post content. Such comments can be a good indicator for the community opinion about the post content. For politicians, marketers, decision makers …, it is required to make sentiment analysis to know the percentage of users agree, disagree and neutral respect to a post. This raised the need to analyze theusers’ comments in Facebook. We focused on Arabic Facebook news pages for the task of sentiment analysis. We developed a corpus for sentiment analysis and opinion mining purposes. Then, we used different machine learning algorithms – decision tree, support vector machines, and naive bayes - to develop sentiment analyzer. The performance of the system using each technique was evaluated and compared with others.

  12. OFFgel-based multidimensional LC-MS/MS approach to the cataloguing of the human platelet proteome for an interactomic profile.

    Science.gov (United States)

    Krishnan, Shibu; Gaspari, Marco; Della Corte, Anna; Bianchi, Patrizia; Crescente, Marilena; Cerletti, Chiara; Torella, Daniele; Indolfi, Ciro; de Gaetano, Giovanni; Donati, Maria Benedetta; Rotilio, Domenico; Cuda, Giovanni

    2011-03-01

    The proteome of quiescent human platelets was analyzed by a shotgun proteomics approach consisting of enzymatic digestion, peptide separation based on isoelectric point by the use of OFFgel fractionation and, finally, RP nanoscale chromatography coupled to MS/MS detection (nano-LC-MS/MS). OFFgel fractionation in the first dimension was effective in providing an additional dimension of separation, orthogonal to RP nano-LC, thus generating an off-line multidimensional separation platform that proved to be robust and easy to set up. The analysis identified 1373 proteins with high confidence (false discovery rate<0.25%). The core set of 1373 human platelet proteins was investigated by Ingenuity Pathway Analysis software from which ten canonical pathways and eight networks have been validated, to suggest that platelets behave either as inflammatory or immune cells, and plasma membrane and cytoskeleton proteins play a fundamental role in their function. Moreover, toxicity pathway in agreement with network analysis, supports the concept that platelet life span is governed by an apoptotic mechanism.

  13. ANALYZE Users' Guide

    Energy Technology Data Exchange (ETDEWEB)

    Azevedo, S.

    1982-10-01

    This report is a reproduction of the visuals that were used in the ANALYZE Users' Guide lectures of the videotaped LLNL Continuing Education Course CE2018-H, State Space Lectures. The course was given in Spring 1982 through the EE Department Education Office. Since ANALYZE is menu-driven, interactive, and has self-explanatory questions (sort of), these visuals and the two 50-minute videotapes are the only documentation which comes with the code. More information about the algorithms contained in ANALYZE can be obtained from the IEEE book on Programs for Digital Signal Processing.

  14. Constrained Fisher Scoring for a Mixture of Factor Analyzers

    Science.gov (United States)

    2016-09-01

    global appearance model across the entire sensor network. constrained maximum likelihood estimation, mixture of factor analyzers, Newton’s method...ARL-TR-7836• SEP 2016 US Army Research Laboratory Constrained Fisher Scoring for a Mixture of Factor Analyzers by Gene T Whipps, Emre Ertin, and...TR-7836• SEP 2016 US Army Research Laboratory Constrained Fisher Scoring for a Mixture of Factor Analyzers by Gene T Whipps Sensors and Electron

  15. Robustness of Interdependent Networks

    Science.gov (United States)

    Havlin, Shlomo

    2011-03-01

    In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of many interdependent networks. We will present a framework for understanding the robustness of interacting networks subject to such cascading failures and provide a basic analytic approach that may be useful in future studies. We present exact analytical solutions for the critical fraction of nodes that upon removal will lead to a failure cascade and to a complete fragmentation of two interdependent networks in a first order transition. Surprisingly, analyzing complex systems as a set of interdependent networks may alter a basic assumption that network theory has relied on: while for a single network a broader degree distribution of the network nodes results in the network being more robust to random failures, for interdependent networks, the broader the distribution is, the more vulnerable the networks become to random failure. We also show that reducing the coupling between the networks leads to a change from a first order percolation phase transition to a second order percolation transition at a critical point. These findings pose a significant challenge to the future design of robust networks that need to consider the unique properties of interdependent networks.

  16. Improved cylindrical mirror energy analyzer

    Science.gov (United States)

    Baranova, L. A.

    2017-03-01

    A study has been carried out of the electron-optical properties of improved design of the cylindrical mirror energy analyzer. Both external and internal electrodes of the analyzer are divided into three isolated parts, whereby the potentials on the individual parts can be regulated independently from each other. In symmetric operating mode at identical potentials on the side parts of the electrodes, a significant increase has been obtained in resolving power and light-gathering power of the analyzer compared to the standard design of the cylindrical mirror. In asymmetric operating mode, which is implemented in a linear potential distribution on the external electrode, the conditions have been found under which the linear dispersion of the analyzer increases several times.

  17. Market study: Whole blood analyzer

    Science.gov (United States)

    1977-01-01

    A market survey was conducted to develop findings relative to the commercialization potential and key market factors of the whole blood analyzer which is being developed in conjunction with NASA's Space Shuttle Medical System.

  18. Data set of interactomes and metabolic pathways of proteins differentially expressed in brains with Alzheimer׳s disease

    Directory of Open Access Journals (Sweden)

    Benito Minjarez

    2016-06-01

    Full Text Available Alzheimer׳s disease is one of the main causes of dementia in the elderly and its frequency is on the rise worldwide. It is considered the result of complex interactions between genetic and environmental factors, being many of them unknown. Therefore, there is a dire necessity for the identification of novel molecular players for the understanding of this disease. In this data article we determined the protein expression profiles of whole protein extracts from cortex regions of brains from patients with Alzheimer׳s disease in comparison to a normal brain. We identified 721 iTRAQ-labeled polypeptides with more than 95% in confidence. We analyzed all proteins that changed in their expression level and located them in the KEGG metabolic pathways, as well as in the mitochondrial complexes of the electron transport chain and ATP synthase. In addition, we analyzed the over- and sub-expressed polypeptides through IPA software, specifically Core I and Biomarkers I modules. Data in this article is related to the research article “Identification of proteins that are differentially expressed in brains with Alzheimer’s disease using iTRAQ labeling and tandem mass spectrometry” (Minjarez et al., 2016 [1].

  19. Sentient networks

    Energy Technology Data Exchange (ETDEWEB)

    Chapline, G.

    1998-03-01

    The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A better idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.

  20. Network Transformations in Economy

    Directory of Open Access Journals (Sweden)

    Bolychev O.

    2014-09-01

    Full Text Available In the context of ever-increasing market competition, networked interactions play a special role in the economy. The network form of entrepreneurship is increasingly viewed as an effective organizational structure to create a market value embedded in innovative business solutions. The authors study the characteristics of a network as an economic category and emphasize certain similarities between Rus sian and international approaches to identifying interactions of economic systems based on the network principle. The paper focuses on the types of networks widely used in the economy. The authors analyze the transformation of business networks along two lines: from an intra- to an inter-firm network and from an inter-firm to an inter-organizational network. The possible forms of network formation are described depending on the strength of connections and the type of integration. The drivers and reasons behind process of transition from a hierarchical model of the organizational structure to a network type are identified. The authors analyze the advantages of creating inter-firm networks and discuss the features of inter-organizational networks as compares to inter-firm ones. The article summarizes the reasons for and advantages of participation in inter-rganizational networks and identifies the main barriers to the formation of inter-organizational network.