WorldWideScience

Sample records for cells integrated networks

  1. Accurate path integration in continuous attractor network models of grid cells.

    Science.gov (United States)

    Burak, Yoram; Fiete, Ila R

    2009-02-01

    Grid cells in the rat entorhinal cortex display strikingly regular firing responses to the animal's position in 2-D space and have been hypothesized to form the neural substrate for dead-reckoning. However, errors accumulate rapidly when velocity inputs are integrated in existing models of grid cell activity. To produce grid-cell-like responses, these models would require frequent resets triggered by external sensory cues. Such inadequacies, shared by various models, cast doubt on the dead-reckoning potential of the grid cell system. Here we focus on the question of accurate path integration, specifically in continuous attractor models of grid cell activity. We show, in contrast to previous models, that continuous attractor models can generate regular triangular grid responses, based on inputs that encode only the rat's velocity and heading direction. We consider the role of the network boundary in the integration performance of the network and show that both periodic and aperiodic networks are capable of accurate path integration, despite important differences in their attractor manifolds. We quantify the rate at which errors in the velocity integration accumulate as a function of network size and intrinsic noise within the network. With a plausible range of parameters and the inclusion of spike variability, our model networks can accurately integrate velocity inputs over a maximum of approximately 10-100 meters and approximately 1-10 minutes. These findings form a proof-of-concept that continuous attractor dynamics may underlie velocity integration in the dorsolateral medial entorhinal cortex. The simulations also generate pertinent upper bounds on the accuracy of integration that may be achieved by continuous attractor dynamics in the grid cell network. We suggest experiments to test the continuous attractor model and differentiate it from models in which single cells establish their responses independently of each other.

  2. Synaptic integration of transplanted interneuron progenitor cells into native cortical networks.

    Science.gov (United States)

    Howard, MacKenzie A; Baraban, Scott C

    2016-08-01

    Interneuron-based cell transplantation is a powerful method to modify network function in a variety of neurological disorders, including epilepsy. Whether new interneurons integrate into native neural networks in a subtype-specific manner is not well understood, and the therapeutic mechanisms underlying interneuron-based cell therapy, including the role of synaptic inhibition, are debated. In this study, we tested subtype-specific integration of transplanted interneurons using acute cortical brain slices and visualized patch-clamp recordings to measure excitatory synaptic inputs, intrinsic properties, and inhibitory synaptic outputs. Fluorescently labeled progenitor cells from the embryonic medial ganglionic eminence (MGE) were used for transplantation. At 5 wk after transplantation, MGE-derived parvalbumin-positive (PV+) interneurons received excitatory synaptic inputs, exhibited mature interneuron firing properties, and made functional synaptic inhibitory connections to native pyramidal cells that were comparable to those of native PV+ interneurons. These findings demonstrate that MGE-derived PV+ interneurons functionally integrate into subtype-appropriate physiological niches within host networks following transplantation. Copyright © 2016 the American Physiological Society.

  3. Functional Stem Cell Integration into Neural Networks Assessed by Organotypic Slice Cultures.

    Science.gov (United States)

    Forsberg, David; Thonabulsombat, Charoensri; Jäderstad, Johan; Jäderstad, Linda Maria; Olivius, Petri; Herlenius, Eric

    2017-08-14

    Re-formation or preservation of functional, electrically active neural networks has been proffered as one of the goals of stem cell-mediated neural therapeutics. A primary issue for a cell therapy approach is the formation of functional contacts between the implanted cells and the host tissue. Therefore, it is of fundamental interest to establish protocols that allow us to delineate a detailed time course of grafted stem cell survival, migration, differentiation, integration, and functional interaction with the host. One option for in vitro studies is to examine the integration of exogenous stem cells into an existing active neural network in ex vivo organotypic cultures. Organotypic cultures leave the structural integrity essentially intact while still allowing the microenvironment to be carefully controlled. This allows detailed studies over time of cellular responses and cell-cell interactions, which are not readily performed in vivo. This unit describes procedures for using organotypic slice cultures as ex vivo model systems for studying neural stem cell and embryonic stem cell engraftment and communication with CNS host tissue. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  4. The hematopoietic chemokine CXCL12 promotes integration of human endothelial colony forming cell-derived cells into immature vessel networks.

    Science.gov (United States)

    Newey, Sarah E; Tsaknakis, Grigorios; Khoo, Cheen P; Athanassopoulos, Thanassi; Camicia, Rosalba; Zhang, Youyi; Grabowska, Rita; Harris, Adrian L; Roubelakis, Maria G; Watt, Suzanne M

    2014-11-15

    Proangiogenic factors, vascular endothelial growth factor (VEGF), and fibroblast growth factor-2 (FGF-2) prime endothelial cells to respond to "hematopoietic" chemokines and cytokines by inducing/upregulating expression of the respective chemokine/cytokine receptors. Coculture of human endothelial colony forming cell (ECFC)-derived cells with human stromal cells in the presence of VEGF and FGF-2 for 14 days resulted in upregulation of the "hematopoietic" chemokine CXCL12 and its CXCR4 receptor by day 3 of coculture. Chronic exposure to the CXCR4 antagonist AMD3100 in this vasculo/angiogenesis assay significantly reduced vascular tubule formation, an observation recapitulated by delayed AMD3100 addition. While AMD3100 did not affect ECFC-derived cell proliferation, it did demonstrate a dual action. First, over the later stages of the 14-day cocultures, AMD3100 delayed tubule organization into maturing vessel networks, resulting in enhanced endothelial cell retraction and loss of complexity as defined by live cell imaging. Second, at earlier stages of cocultures, we observed that AMD3100 significantly inhibited the integration of exogenous ECFC-derived cells into established, but immature, vascular networks. Comparative proteome profiler array analyses of ECFC-derived cells treated with AMD3100 identified changes in expression of potential candidate molecules involved in adhesion and/or migration. Blocking antibodies to CD31, but not CD146 or CD166, reduced the ECFC-derived cell integration into these extant vascular networks. Thus, CXCL12 plays a key role not only in endothelial cell sensing and guidance, but also in promoting the integration of ECFC-derived cells into developing vascular networks.

  5. The Genome-Scale Integrated Networks in Microorganisms

    Directory of Open Access Journals (Sweden)

    Tong Hao

    2018-02-01

    Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

  6. Load balancing in integrated optical wireless networks

    DEFF Research Database (Denmark)

    Yan, Ying; Dittmann, Lars; Wong, S-W.

    2010-01-01

    In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....

  7. Modeling integrated cellular machinery using hybrid Petri-Boolean networks.

    Directory of Open Access Journals (Sweden)

    Natalie Berestovsky

    Full Text Available The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has generally enabled taming computational complexity dealing with the entire system, allowed for using modeling techniques that are specific to each of the components, and achieved separation of the different time scales at which reactions in each of the three networks occur. Nonetheless, with this division comes loss of information and power needed to elucidate certain cellular phenomena. Within the cell, these three types of networks work in tandem, and each produces signals and/or substances that are used by the others to process information and operate normally. Therefore, computational techniques for modeling integrated cellular machinery are needed. In this work, we propose an integrated hybrid model (IHM that combines Petri nets and Boolean networks to model integrated cellular networks. Coupled with a stochastic simulation mechanism, the model simulates the dynamics of the integrated network, and can be perturbed to generate testable hypotheses. Our model is qualitative and is mostly built upon knowledge from the literature and requires fine-tuning of very few parameters. We validated our model on two systems: the transcriptional regulation of glucose metabolism in human cells, and cellular osmoregulation in S. cerevisiae. The model produced results that are in very good agreement with experimental data, and produces valid hypotheses. The abstract nature of our model and the ease of its construction makes it a very good candidate for modeling integrated networks from qualitative data. The results it produces can guide the practitioner to zoom into components and interconnections and investigate them

  8. Reconstruction of biological networks based on life science data integration.

    Science.gov (United States)

    Kormeier, Benjamin; Hippe, Klaus; Arrigo, Patrizio; Töpel, Thoralf; Janowski, Sebastian; Hofestädt, Ralf

    2010-10-27

    For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH--an integration toolkit for building life science data warehouses, CardioVINEdb--a information system for biological data in cardiovascular-disease and VANESA--a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

  9. An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells

    Directory of Open Access Journals (Sweden)

    Nam Seungyoon

    2012-12-01

    Full Text Available Abstract Background A major goal of the field of systems biology is to translate genome-wide profiling data (e.g., mRNAs, miRNAs into interpretable functional networks. However, employing a systems biology approach to better understand the complexities underlying drug resistance phenotypes in cancer continues to represent a significant challenge to the field. Previously, we derived two drug-resistant breast cancer sublines (tamoxifen- and fulvestrant-resistant cell lines from the MCF7 breast cancer cell line and performed genome-wide mRNA and microRNA profiling to identify differential molecular pathways underlying acquired resistance to these important antiestrogens. In the current study, to further define molecular characteristics of acquired antiestrogen resistance we constructed an “integrative network”. We combined joint miRNA-mRNA expression profiles, cancer contexts, miRNA-target mRNA relationships, and miRNA upstream regulators. In particular, to reduce the probability of false positive connections in the network, experimentally validated, rather than prediction-oriented, databases were utilized to obtain connectivity. Also, to improve biological interpretation, cancer contexts were incorporated into the network connectivity. Results Based on the integrative network, we extracted “substructures” (network clusters representing the drug resistant states (tamoxifen- or fulvestrant-resistance cells compared to drug sensitive state (parental MCF7 cells. We identified un-described network clusters that contribute to antiestrogen resistance consisting of miR-146a, -27a, -145, -21, -155, -15a, -125b, and let-7s, in addition to the previously described miR-221/222. Conclusions By integrating miRNA-related network, gene/miRNA expression and text-mining, the current study provides a computational-based systems biology approach for further investigating the molecular mechanism underlying antiestrogen resistance in breast cancer cells. In

  10. Self-organizing path integration using a linked continuous attractor and competitive network: path integration of head direction.

    Science.gov (United States)

    Stringer, Simon M; Rolls, Edmund T

    2006-12-01

    A key issue is how networks in the brain learn to perform path integration, that is update a represented position using a velocity signal. Using head direction cells as an example, we show that a competitive network could self-organize to learn to respond to combinations of head direction and angular head rotation velocity. These combination cells can then be used to drive a continuous attractor network to the next head direction based on the incoming rotation signal. An associative synaptic modification rule with a short term memory trace enables preceding combination cell activity during training to be associated with the next position in the continuous attractor network. The network accounts for the presence of neurons found in the brain that respond to combinations of head direction and angular head rotation velocity. Analogous networks in the hippocampal system could self-organize to perform path integration of place and spatial view representations.

  11. Reconstruction of biological networks based on life science data integration

    Directory of Open Access Journals (Sweden)

    Kormeier Benjamin

    2010-06-01

    Full Text Available For the implementation of the virtual cell, the fundamental question is how to model and simulate complex biological networks. Therefore, based on relevant molecular database and information systems, biological data integration is an essential step in constructing biological networks. In this paper, we will motivate the applications BioDWH - an integration toolkit for building life science data warehouses, CardioVINEdb - a information system for biological data in cardiovascular-disease and VANESA- a network editor for modeling and simulation of biological networks. Based on this integration process, the system supports the generation of biological network models. A case study of a cardiovascular-disease related gene-regulated biological network is also presented.

  12. NASA Integrated Network COOP

    Science.gov (United States)

    Anderson, Michael L.; Wright, Nathaniel; Tai, Wallace

    2012-01-01

    Natural disasters, terrorist attacks, civil unrest, and other events have the potential of disrupting mission-essential operations in any space communications network. NASA's Space Communications and Navigation office (SCaN) is in the process of studying options for integrating the three existing NASA network elements, the Deep Space Network, the Near Earth Network, and the Space Network, into a single integrated network with common services and interfaces. The need to maintain Continuity of Operations (COOP) after a disastrous event has a direct impact on the future network design and operations concepts. The SCaN Integrated Network will provide support to a variety of user missions. The missions have diverse requirements and include anything from earth based platforms to planetary missions and rovers. It is presumed that an integrated network, with common interfaces and processes, provides an inherent advantage to COOP in that multiple elements and networks can provide cross-support in a seamless manner. The results of trade studies support this assumption but also show that centralization as a means of achieving integration can result in single points of failure that must be mitigated. The cost to provide this mitigation can be substantial. In support of this effort, the team evaluated the current approaches to COOP, developed multiple potential approaches to COOP in a future integrated network, evaluated the interdependencies of the various approaches to the various network control and operations options, and did a best value assessment of the options. The paper will describe the trade space, the study methods, and results of the study.

  13. Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things.

    Science.gov (United States)

    Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

    2015-09-18

    With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified.

  14. BiologicalNetworks 2.0 - an integrative view of genome biology data

    Directory of Open Access Journals (Sweden)

    Ponomarenko Julia

    2010-12-01

    Full Text Available Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other and their relations (interactions, co-expression, co-citations, and other. The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.

  15. Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things

    Science.gov (United States)

    Wang, Lusheng; Wang, Yamei; Ding, Zhizhong; Wang, Xiumin

    2015-01-01

    With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs) tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS) game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI). In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG), forming a congestion game with ICI (CGI) and a congestion game with capacity (CGC). For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE). Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell) is profoundly revealed, and the collapse points are identified. PMID:26393617

  16. Cell Selection Game for Densely-Deployed Sensor and Mobile Devices In 5G Networks Integrating Heterogeneous Cells and the Internet of Things

    Directory of Open Access Journals (Sweden)

    Lusheng Wang

    2015-09-01

    Full Text Available With the rapid development of wireless networking technologies, the Internet of Things and heterogeneous cellular networks (HCNs tend to be integrated to form a promising wireless network paradigm for 5G. Hyper-dense sensor and mobile devices will be deployed under the coverage of heterogeneous cells, so that each of them could freely select any available cell covering it and compete for resource with others selecting the same cell, forming a cell selection (CS game between these devices. Since different types of cells usually share the same portion of the spectrum, devices selecting overlapped cells can experience severe inter-cell interference (ICI. In this article, we study the CS game among a large amount of densely-deployed sensor and mobile devices for their uplink transmissions in a two-tier HCN. ICI is embedded with the traditional congestion game (TCG, forming a congestion game with ICI (CGI and a congestion game with capacity (CGC. For the three games above, we theoretically find the circular boundaries between the devices selecting the macrocell and those selecting the picocells, indicated by the pure strategy Nash equilibria (PSNE. Meanwhile, through a number of simulations with different picocell radii and different path loss exponents, the collapse of the PSNE impacted by severe ICI (i.e., a large number of picocell devices change their CS preferences to the macrocell is profoundly revealed, and the collapse points are identified.

  17. TNF-α inhibits trophoblast integration into endothelial cellular networks.

    Science.gov (United States)

    Xu, B; Nakhla, S; Makris, A; Hennessy, A

    2011-03-01

    Preeclampsia has been linked to shallow trophoblast invasion and failure of uterine spiral artery transformation. Interaction between trophoblast cells and maternal uterine endothelium is critically important for this remodelling. The aim of our study was to investigate the effect of TNF-α on the interactions of trophoblast-derived JEG-3 cells into capillary-like cellular networks. We have employed an in vitro trophoblast-endothelial cell co-culture model to quantify trophoblast integration into endothelial cellular networks and to investigate the effects of TNF-α. Controlled co-cultures were also treated with anti-TNF-α antibody (5 μg/ml) to specifically block the effect of TNF-α. The invasion was evaluated by performing quantitative PCR (Q-PCR) to analyse gene expression of matrix metalloproteinases-2 (MMP-2), MMP-9, tissue inhibitor of matrix metalloproteinase (TIMP)-1, integrins (α(1)β(1) and α(6)β(4)), plasminogen activator inhibitor (PAI)-1, E-cadherin and VE-cadherin. JEG-3 cell integration into endothelial networks was significantly inhibited by exogenous TNF-α. The inhibition was observed in the range of 0.2-5 ng/ml, to a maximum 56% inhibition at the highest concentration. This inhibition was reversed by anti-TNF-α antibody. Q-PCR analysis showed that mRNA expression of integrins α(1)β(1) and MMP-2 was significantly decreased. VE-cadherin mRNA expression was significantly up-regulated (32-80%, p integration into maternal endothelial cellular networks, and this process involves the inhibition of MMP-2 and a failure of integrins switch from α(6)β(4) to α(1)β(1.) These molecular correlations reflect the changes identified in human preeclampsia. Copyright © 2011 Elsevier Ltd. All rights reserved.

  18. Increasing cellular coverage within integrated terrestrial/satellite mobile networks

    Science.gov (United States)

    Castro, Jonathan P.

    1995-01-01

    When applying the hierarchical cellular concept, the satellite acts as giant umbrella cell covering a region with some terrestrial cells. If a mobile terminal traversing the region arrives to the border-line or limits of a regular cellular ground service, network transition occurs and the satellite system continues the mobile coverage. To adequately assess the boundaries of service of a mobile satellite system an a cellular network within an integrated environment, this paper provides an optimized scheme to predict when a network transition may be necessary. Under the assumption of a classified propagation phenomenon and Lognormal shadowing, the study applies an analytical approach to estimate the location of a mobile terminal based on a reception of the signal strength emitted by a base station.

  19. Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.

    Directory of Open Access Journals (Sweden)

    Katrina M Waters

    Full Text Available To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

  20. Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

    Energy Technology Data Exchange (ETDEWEB)

    Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

    2012-03-29

    To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

  1. Experimental and computational tools for analysis of signaling networks in primary cells

    DEFF Research Database (Denmark)

    Schoof, Erwin M; Linding, Rune

    2014-01-01

    Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis, or differ......Cellular information processing in signaling networks forms the basis of responses to environmental stimuli. At any given time, cells receive multiple simultaneous input cues, which are processed and integrated to determine cellular responses such as migration, proliferation, apoptosis......; this information is critical when trying to elucidate key proteins involved in specific cellular responses. Here, methods to generate high-quality quantitative phosphorylation data from cell lysates originating from primary cells, and how to analyze the generated data to construct quantitative signaling network...

  2. Integration of donor mesenchymal stem cell-derived neuron-like cells into host neural network after rat spinal cord transection.

    Science.gov (United States)

    Zeng, Xiang; Qiu, Xue-Cheng; Ma, Yuan-Huan; Duan, Jing-Jing; Chen, Yuan-Feng; Gu, Huai-Yu; Wang, Jun-Mei; Ling, Eng-Ang; Wu, Jin-Lang; Wu, Wutian; Zeng, Yuan-Shan

    2015-06-01

    Functional deficits following spinal cord injury (SCI) primarily attribute to loss of neural connectivity. We therefore tested if novel tissue engineering approaches could enable neural network repair that facilitates functional recovery after spinal cord transection (SCT). Rat bone marrow-derived mesenchymal stem cells (MSCs), genetically engineered to overexpress TrkC, receptor of neurotrophin-3 (NT-3), were pre-differentiated into cells carrying neuronal features via co-culture with NT-3 overproducing Schwann cells in 3-dimensional gelatin sponge (GS) scaffold for 14 days in vitro. Intra-GS formation of MSC assemblies emulating neural network (MSC-GS) were verified morphologically via electron microscopy (EM) and functionally by whole-cell patch clamp recording of spontaneous post-synaptic currents. The differentiated MSCs still partially maintained prototypic property with the expression of some mesodermal cytokines. MSC-GS or GS was then grafted acutely into a 2 mm-wide transection gap in the T9-T10 spinal cord segments of adult rats. Eight weeks later, hindlimb function of the MSC-GS-treated SCT rats was significantly improved relative to controls receiving the GS or lesion only as indicated by BBB score. The MSC-GS transplantation also significantly recovered cortical motor evoked potential (CMEP). Histologically, MSC-derived neuron-like cells maintained their synapse-like structures in vivo; they additionally formed similar connections with host neurites (i.e., mostly serotonergic fibers plus a few corticospinal axons; validated by double-labeled immuno-EM). Moreover, motor cortex electrical stimulation triggered c-fos expression in the grafted and lumbar spinal cord cells of the treated rats only. Our data suggest that MSC-derived neuron-like cells resulting from NT-3-TrkC-induced differentiation can partially integrate into transected spinal cord and this strategy should be further investigated for reconstructing disrupted neural circuits. Copyright

  3. Cell-type-specific predictive network yields novel insights into mouse embryonic stem cell self-renewal and cell fate.

    Directory of Open Access Journals (Sweden)

    Karen G Dowell

    Full Text Available Self-renewal, the ability of a stem cell to divide repeatedly while maintaining an undifferentiated state, is a defining characteristic of all stem cells. Here, we clarify the molecular foundations of mouse embryonic stem cell (mESC self-renewal by applying a proven Bayesian network machine learning approach to integrate high-throughput data for protein function discovery. By focusing on a single stem-cell system, at a specific developmental stage, within the context of well-defined biological processes known to be active in that cell type, we produce a consensus predictive network that reflects biological reality more closely than those made by prior efforts using more generalized, context-independent methods. In addition, we show how machine learning efforts may be misled if the tissue specific role of mammalian proteins is not defined in the training set and circumscribed in the evidential data. For this study, we assembled an extensive compendium of mESC data: ∼2.2 million data points, collected from 60 different studies, under 992 conditions. We then integrated these data into a consensus mESC functional relationship network focused on biological processes associated with embryonic stem cell self-renewal and cell fate determination. Computational evaluations, literature validation, and analyses of predicted functional linkages show that our results are highly accurate and biologically relevant. Our mESC network predicts many novel players involved in self-renewal and serves as the foundation for future pluripotent stem cell studies. This network can be used by stem cell researchers (at http://StemSight.org to explore hypotheses about gene function in the context of self-renewal and to prioritize genes of interest for experimental validation.

  4. The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations.

    Science.gov (United States)

    Keenan, Alexandra B; Jenkins, Sherry L; Jagodnik, Kathleen M; Koplev, Simon; He, Edward; Torre, Denis; Wang, Zichen; Dohlman, Anders B; Silverstein, Moshe C; Lachmann, Alexander; Kuleshov, Maxim V; Ma'ayan, Avi; Stathias, Vasileios; Terryn, Raymond; Cooper, Daniel; Forlin, Michele; Koleti, Amar; Vidovic, Dusica; Chung, Caty; Schürer, Stephan C; Vasiliauskas, Jouzas; Pilarczyk, Marcin; Shamsaei, Behrouz; Fazel, Mehdi; Ren, Yan; Niu, Wen; Clark, Nicholas A; White, Shana; Mahi, Naim; Zhang, Lixia; Kouril, Michal; Reichard, John F; Sivaganesan, Siva; Medvedovic, Mario; Meller, Jaroslaw; Koch, Rick J; Birtwistle, Marc R; Iyengar, Ravi; Sobie, Eric A; Azeloglu, Evren U; Kaye, Julia; Osterloh, Jeannette; Haston, Kelly; Kalra, Jaslin; Finkbiener, Steve; Li, Jonathan; Milani, Pamela; Adam, Miriam; Escalante-Chong, Renan; Sachs, Karen; Lenail, Alex; Ramamoorthy, Divya; Fraenkel, Ernest; Daigle, Gavin; Hussain, Uzma; Coye, Alyssa; Rothstein, Jeffrey; Sareen, Dhruv; Ornelas, Loren; Banuelos, Maria; Mandefro, Berhan; Ho, Ritchie; Svendsen, Clive N; Lim, Ryan G; Stocksdale, Jennifer; Casale, Malcolm S; Thompson, Terri G; Wu, Jie; Thompson, Leslie M; Dardov, Victoria; Venkatraman, Vidya; Matlock, Andrea; Van Eyk, Jennifer E; Jaffe, Jacob D; Papanastasiou, Malvina; Subramanian, Aravind; Golub, Todd R; Erickson, Sean D; Fallahi-Sichani, Mohammad; Hafner, Marc; Gray, Nathanael S; Lin, Jia-Ren; Mills, Caitlin E; Muhlich, Jeremy L; Niepel, Mario; Shamu, Caroline E; Williams, Elizabeth H; Wrobel, David; Sorger, Peter K; Heiser, Laura M; Gray, Joe W; Korkola, James E; Mills, Gordon B; LaBarge, Mark; Feiler, Heidi S; Dane, Mark A; Bucher, Elmar; Nederlof, Michel; Sudar, Damir; Gross, Sean; Kilburn, David F; Smith, Rebecca; Devlin, Kaylyn; Margolis, Ron; Derr, Leslie; Lee, Albert; Pillai, Ajay

    2018-01-24

    The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH Common Fund program that catalogs how human cells globally respond to chemical, genetic, and disease perturbations. Resources generated by LINCS include experimental and computational methods, visualization tools, molecular and imaging data, and signatures. By assembling an integrated picture of the range of responses of human cells exposed to many perturbations, the LINCS program aims to better understand human disease and to advance the development of new therapies. Perturbations under study include drugs, genetic perturbations, tissue micro-environments, antibodies, and disease-causing mutations. Responses to perturbations are measured by transcript profiling, mass spectrometry, cell imaging, and biochemical methods, among other assays. The LINCS program focuses on cellular physiology shared among tissues and cell types relevant to an array of diseases, including cancer, heart disease, and neurodegenerative disorders. This Perspective describes LINCS technologies, datasets, tools, and approaches to data accessibility and reusability. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

    Directory of Open Access Journals (Sweden)

    Joseph A. Wayman

    2015-03-01

    Full Text Available Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to consider, transient metabolic measurements are easier to obtain, and we no longer have to consider cell growth. Thus, cell-free operation holds several significant advantages for model development, identification and validation. Theoretically, genome-scale cell-free kinetic models may be possible for industrially important organisms, such as E. coli, if a simple, tractable framework for integrating allosteric regulation with enzyme kinetics can be formulated. Toward this unmet need, we present an effective biochemical network modeling framework for building dynamic cell-free metabolic models. The key innovation of our approach is the integration of simple effective rules encoding complex allosteric regulation with traditional kinetic pathway modeling. We tested our approach by modeling the time evolution of several hypothetical cell-free metabolic networks. We found that simple effective rules, when integrated with traditional enzyme kinetic expressions, captured complex allosteric patterns such as ultrasensitivity or non-competitive inhibition in the absence of mechanistic information. Second, when integrated into network models, these rules captured classic regulatory patterns such as product-induced feedback inhibition. Lastly, we showed, at least for the network architectures considered here, that we could simultaneously estimate kinetic parameters and allosteric connectivity from synthetic data starting from an unbiased collection of possible allosteric structures using particle swarm optimization. However, when starting with an initial population that was heavily enriched with incorrect structures, our particle swarm approach could converge

  6. Integration of Plant Metabolomics Data with Metabolic Networks: Progresses and Challenges.

    Science.gov (United States)

    Töpfer, Nadine; Seaver, Samuel M D; Aharoni, Asaph

    2018-01-01

    In the last decade, plant genome-scale modeling has developed rapidly and modeling efforts have advanced from representing metabolic behavior of plant heterotrophic cell suspensions to studying the complex interplay of cell types, tissues, and organs. A crucial driving force for such developments is the availability and integration of "omics" data (e.g., transcriptomics, proteomics, and metabolomics) which enable the reconstruction, extraction, and application of context-specific metabolic networks. In this chapter, we demonstrate a workflow to integrate gas chromatography coupled to mass spectrometry (GC-MS)-based metabolomics data of tomato fruit pericarp (flesh) tissue, at five developmental stages, with a genome-scale reconstruction of tomato metabolism. This method allows for the extraction of context-specific networks reflecting changing activities of metabolic pathways throughout fruit development and maturation.

  7. Challenges of Integrating NASA's Space Communications Networks

    Science.gov (United States)

    Reinert, Jessica; Barnes, Patrick

    2013-01-01

    The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

  8. Challenges of Integrating NASAs Space Communication Networks

    Science.gov (United States)

    Reinert, Jessica M.; Barnes, Patrick

    2013-01-01

    The transition to new technology, innovative ideas, and resistance to change is something that every industry experiences. Recent examples of this shift are changing to using robots in the assembly line construction of automobiles or the increasing use of robotics for medical procedures. Most often this is done with cost-reduction in mind, though ease of use for the customer is also a driver. All industries experience the push to increase efficiency of their systems; National Aeronautics and Space Administration (NASA) and the commercial space industry are no different. NASA space communication services are provided by three separately designed, developed, maintained, and operated communications networks known as the Deep Space Network (DSN), Near Earth Network (NEN) and Space Network (SN). The Space Communications and Navigation (SCaN) Program is pursuing integration of these networks and has performed a variety of architecture trade studies to determine what integration options would be the most effective in achieving a unified user mission support organization, and increase the use of common operational equipment and processes. The integration of multiple, legacy organizations and existing systems has challenges ranging from technical to cultural. The existing networks are the progeny of the very first communication and tracking capabilities implemented by NASA and the Jet Propulsion Laboratory (JPL) more than 50 years ago and have been customized to the needs of their respective user mission base. The technical challenges to integrating the networks are many, though not impossible to overcome. The three distinct networks provide the same types of services, with customizable data rates, bandwidth, frequencies, and so forth. The differences across the networks have occurred in effort to satisfy their user missions' needs. Each new requirement has made the networks more unique and harder to integrate. The cultural challenges, however, have proven to be a

  9. Integration of RFID and Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    Miodrag; Bolic; Amiya; Nayak; Ivan; Stojmenovi.

    2007-01-01

    Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN) are two important wireless technologies that have wide variety of applications and provide limitless future potentials. However,RFID and sensor networks almost are under development in parallel way. Integration of RFID and wireless sensor networks attracts little attention from research community. This paper first presents a brief introduction on RFID,and then investigates recent research works,new products/patents and applications that integrate RFID with sensor networks. Four types of integration are discussed. They are integrating tags with sensors,integrating tags with wireless sensor nodes,integrating readers with wireless sensor nodes and wire-less devices,and mix of RFID and sensors. New challenges and future works are discussed in the end.

  10. Integrative modelling of the influence of MAPK network on cancer cell fate decision.

    Directory of Open Access Journals (Sweden)

    Luca Grieco

    2013-10-01

    Full Text Available The Mitogen-Activated Protein Kinase (MAPK network consists of tightly interconnected signalling pathways involved in diverse cellular processes, such as cell cycle, survival, apoptosis and differentiation. Although several studies reported the involvement of these signalling cascades in cancer deregulations, the precise mechanisms underlying their influence on the balance between cell proliferation and cell death (cell fate decision in pathological circumstances remain elusive. Based on an extensive analysis of published data, we have built a comprehensive and generic reaction map for the MAPK signalling network, using CellDesigner software. In order to explore the MAPK responses to different stimuli and better understand their contributions to cell fate decision, we have considered the most crucial components and interactions and encoded them into a logical model, using the software GINsim. Our logical model analysis particularly focuses on urinary bladder cancer, where MAPK network deregulations have often been associated with specific phenotypes. To cope with the combinatorial explosion of the number of states, we have applied novel algorithms for model reduction and for the compression of state transition graphs, both implemented into the software GINsim. The results of systematic simulations for different signal combinations and network perturbations were found globally coherent with published data. In silico experiments further enabled us to delineate the roles of specific components, cross-talks and regulatory feedbacks in cell fate decision. Finally, tentative proliferative or anti-proliferative mechanisms can be connected with established bladder cancer deregulations, namely Epidermal Growth Factor Receptor (EGFR over-expression and Fibroblast Growth Factor Receptor 3 (FGFR3 activating mutations.

  11. The genetic interaction network of CCW12, a Saccharomyces cerevisiae gene required for cell wall integrity during budding and formation of mating projections

    Science.gov (United States)

    2011-01-01

    Background Mannoproteins construct the outer cover of the fungal cell wall. The covalently linked cell wall protein Ccw12p is an abundant mannoprotein. It is considered as crucial structural cell wall component since in baker's yeast the lack of CCW12 results in severe cell wall damage and reduced mating efficiency. Results In order to explore the function of CCW12, we performed a Synthetic Genetic Analysis (SGA) and identified genes that are essential in the absence of CCW12. The resulting interaction network identified 21 genes involved in cell wall integrity, chitin synthesis, cell polarity, vesicular transport and endocytosis. Among those are PFD1, WHI3, SRN2, PAC10, FEN1 and YDR417C, which have not been related to cell wall integrity before. We correlated our results with genetic interaction networks of genes involved in glucan and chitin synthesis. A core of genes essential to maintain cell integrity in response to cell wall stress was identified. In addition, we performed a large-scale transcriptional analysis and compared the transcriptional changes observed in mutant ccw12Δ with transcriptomes from studies investigating responses to constitutive or acute cell wall damage. We identified a set of genes that are highly induced in the majority of the mutants/conditions and are directly related to the cell wall integrity pathway and cell wall compensatory responses. Among those are BCK1, CHS3, EDE1, PFD1, SLT2 and SLA1 that were also identified in the SGA. In contrast, a specific feature of mutant ccw12Δ is the transcriptional repression of genes involved in mating. Physiological experiments substantiate this finding. Further, we demonstrate that Ccw12p is present at the cell periphery and highly concentrated at the presumptive budding site, around the bud, at the septum and at the tip of the mating projection. Conclusions The combination of high throughput screenings, phenotypic analyses and localization studies provides new insight into the function of Ccw

  12. A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

    OpenAIRE

    Blanco, Bego; Taboada, Ianire; Fajardo, Jose Oscar; Liberal, Fidel

    2017-01-01

    In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-awa...

  13. Cell fate reprogramming by control of intracellular network dynamics

    Science.gov (United States)

    Zanudo, Jorge G. T.; Albert, Reka

    Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

  14. The genetic network controlling plasma cell differentiation.

    Science.gov (United States)

    Nutt, Stephen L; Taubenheim, Nadine; Hasbold, Jhagvaral; Corcoran, Lynn M; Hodgkin, Philip D

    2011-10-01

    Upon activation by antigen, mature B cells undergo immunoglobulin class switch recombination and differentiate into antibody-secreting plasma cells, the endpoint of the B cell developmental lineage. Careful quantitation of these processes, which are stochastic, independent and strongly linked to the division history of the cell, has revealed that populations of B cells behave in a highly predictable manner. Considerable progress has also been made in the last few years in understanding the gene regulatory network that controls the B cell to plasma cell transition. The mutually exclusive transcriptomes of B cells and plasma cells are maintained by the antagonistic influences of two groups of transcription factors, those that maintain the B cell program, including Pax5, Bach2 and Bcl6, and those that promote and facilitate plasma cell differentiation, notably Irf4, Blimp1 and Xbp1. In this review, we discuss progress in the definition of both the transcriptional and cellular events occurring during late B cell differentiation, as integrating these two approaches is crucial to defining a regulatory network that faithfully reflects the stochastic features and complexity of the humoral immune response. 2011 Elsevier Ltd. All rights reserved.

  15. European networks in structural integrity

    International Nuclear Information System (INIS)

    Crutzen, S.; Davies, M.; Hemsworth, B.; Hurst, R.; Kussmaul, K.

    1994-01-01

    Several institutions and electrical utilities in Europe, including the Joint Research Centre (JRC) have the capability to deal problems posed by the operation and ageing of structural components and with their structural integrity assessment. These institutions and the JRC have developed cooperative programmes now organised in networks. They include utilities, engineering companies, R and D laboratories and Regulatory Bodies. Networks are organised and managed like the successful PISC programme: The Institute for Advanced Materials of JRC plays the role of Operating Agent and Manager of these networks: ENIQ, AMES, NESC, each of them dealing with a specific aspect of fitness for purpose of materials in structural components. There exist strong links between the networks and EC Working Groups on Structural Integrity Codes and Standards. (orig.)

  16. Integrated circuit and method of arbitration in a network on an integrated circuit.

    NARCIS (Netherlands)

    2011-01-01

    The invention relates to an integrated circuit and to a method of arbitration in a network on an integrated circuit. According to the invention, a method of arbitration in a network on an integrated circuit is provided, the network comprising a router unit, the router unit comprising a first input

  17. Direct Adaptive Aircraft Control Using Dynamic Cell Structure Neural Networks

    Science.gov (United States)

    Jorgensen, Charles C.

    1997-01-01

    A Dynamic Cell Structure (DCS) Neural Network was developed which learns topology representing networks (TRNS) of F-15 aircraft aerodynamic stability and control derivatives. The network is integrated into a direct adaptive tracking controller. The combination produces a robust adaptive architecture capable of handling multiple accident and off- nominal flight scenarios. This paper describes the DCS network and modifications to the parameter estimation procedure. The work represents one step towards an integrated real-time reconfiguration control architecture for rapid prototyping of new aircraft designs. Performance was evaluated using three off-line benchmarks and on-line nonlinear Virtual Reality simulation. Flight control was evaluated under scenarios including differential stabilator lock, soft sensor failure, control and stability derivative variations, and air turbulence.

  18. Building secure network by integrated technology

    International Nuclear Information System (INIS)

    An Dehai; Xu Rongsheng; Liu Baoxu

    2000-01-01

    The author introduces a method which can realize the most powerful network security prevention by the network security integrated technologies such as firewall, realtime monitor, network scanner, Web detection and security, etc

  19. Changes in the topology of gene expression networks by human immunodeficiency virus type 1 (HIV-1) integration in macrophages.

    Science.gov (United States)

    Soto-Girón, María Juliana; García-Vallejo, Felipe

    2012-01-01

    One key step of human immunodeficiency virus type 1 (HIV-1) infection is the integration of its viral cDNA. This process is mediated through complex networks of host-virus interactions that alter several normal cell functions of the host. To study the complexity of disturbances in cell gene expression networks by HIV-1 integration, we constructed a network of human macrophage genes located close to chromatin regions rich in proviruses. To perform the network analysis, we selected 28 genes previously identified as the target of cDNA integration and their transcriptional profiles were obtained from GEO Profiles (NCBI). A total of 2770 interactions among the 28 genes located around the HIV-1 proviruses in human macrophages formed a highly dense main network connected to five sub-networks. The overall network was significantly enriched by genes associated with signal transduction, cellular communication and regulatory processes. To simulate the effects of HIV-1 integration in infected macrophages, five genes with the most number of interaction in the normal network were turned off by putting in zero the correspondent expression values. The HIV-1 infected network showed changes in its topology and alteration in the macrophage functions reflected in a re-programming of biosynthetic and general metabolic process. Understanding the complex virus-host interactions that occur during HIV-1 integration, may provided valuable genomic information to develop new antiviral treatments focusing on the management of some specific gene expression networks associated with viral integration. This is the first gene network which describes the human macrophages genes interactions related with HIV-1 integration. Copyright © 2011 Elsevier B.V. All rights reserved.

  20. Cardiogenic induction of pluripotent stem cells streamlined through a conserved SDF-1/VEGF/BMP2 integrated network.

    Directory of Open Access Journals (Sweden)

    Anca Chiriac

    Full Text Available BACKGROUND: Pluripotent stem cells produce tissue-specific lineages through programmed acquisition of sequential gene expression patterns that function as a blueprint for organ formation. As embryonic stem cells respond concomitantly to diverse signaling pathways during differentiation, extraction of a pro-cardiogenic network would offer a roadmap to streamline cardiac progenitor output. METHODS AND RESULTS: To resolve gene ontology priorities within precursor transcriptomes, cardiogenic subpopulations were here generated according to either growth factor guidance or stage-specific biomarker sorting. Innate expression profiles were independently delineated through unbiased systems biology mapping, and cross-referenced to filter transcriptional noise unmasking a conserved progenitor motif (55 up- and 233 down-regulated genes. The streamlined pool of 288 genes organized into a core biological network that prioritized the "Cardiovascular Development" function. Recursive in silico deconvolution of the cardiogenic neighborhood and associated canonical signaling pathways identified a combination of integrated axes, CXCR4/SDF-1, Flk-1/VEGF and BMP2r/BMP2, predicted to synchronize cardiac specification. In vitro targeting of the resolved triad in embryoid bodies accelerated expression of Nkx2.5, Mef2C and cardiac-MHC, enhanced beating activity, and augmented cardiogenic yield. CONCLUSIONS: Transcriptome-wide dissection of a conserved progenitor profile thus revealed functional highways that coordinate cardiogenic maturation from a pluripotent ground state. Validating the bioinformatics algorithm established a strategy to rationally modulate cell fate, and optimize stem cell-derived cardiogenesis.

  1. Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

    Directory of Open Access Journals (Sweden)

    Christopher E Hart

    2006-12-01

    Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

  2. Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation.

    Directory of Open Access Journals (Sweden)

    Alexander Zhyvoloup

    2017-07-01

    Full Text Available HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation.

  3. Digoxin reveals a functional connection between HIV-1 integration preference and T-cell activation.

    Science.gov (United States)

    Zhyvoloup, Alexander; Melamed, Anat; Anderson, Ian; Planas, Delphine; Lee, Chen-Hsuin; Kriston-Vizi, Janos; Ketteler, Robin; Merritt, Andy; Routy, Jean-Pierre; Ancuta, Petronela; Bangham, Charles R M; Fassati, Ariberto

    2017-07-01

    HIV-1 integrates more frequently into transcribed genes, however the biological significance of HIV-1 integration targeting has remained elusive. Using a selective high-throughput chemical screen, we discovered that the cardiac glycoside digoxin inhibits wild-type HIV-1 infection more potently than HIV-1 bearing a single point mutation (N74D) in the capsid protein. We confirmed that digoxin repressed viral gene expression by targeting the cellular Na+/K+ ATPase, but this did not explain its selectivity. Parallel RNAseq and integration mapping in infected cells demonstrated that digoxin inhibited expression of genes involved in T-cell activation and cell metabolism. Analysis of >400,000 unique integration sites showed that WT virus integrated more frequently than N74D mutant within or near genes susceptible to repression by digoxin and involved in T-cell activation and cell metabolism. Two main gene networks down-regulated by the drug were CD40L and CD38. Blocking CD40L by neutralizing antibodies selectively inhibited WT virus infection, phenocopying digoxin. Thus the selectivity of digoxin depends on a combination of integration targeting and repression of specific gene networks. The drug unmasked a functional connection between HIV-1 integration and T-cell activation. Our results suggest that HIV-1 evolved integration site selection to couple its early gene expression with the status of target CD4+ T-cells, which may affect latency and viral reactivation.

  4. Intelligent sensor networks the integration of sensor networks, signal processing and machine learning

    CERN Document Server

    Hu, Fei

    2012-01-01

    Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl

  5. The plant cell wall integrity maintenance mechanism--a case study of a cell wall plasma membrane signaling network.

    Science.gov (United States)

    Hamann, Thorsten

    2015-04-01

    Some of the most important functions of plant cell walls are protection against biotic/abiotic stress and structural support during growth and development. A prerequisite for plant cell walls to perform these functions is the ability to perceive different types of stimuli in both qualitative and quantitative manners and initiate appropriate responses. The responses in turn involve adaptive changes in cellular and cell wall metabolism leading to modifications in the structures originally required for perception. While our knowledge about the underlying plant mechanisms is limited, results from Saccharomyces cerevisiae suggest the cell wall integrity maintenance mechanism represents an excellent example to illustrate how the molecular mechanisms responsible for stimulus perception, signal transduction and integration can function. Here I will review the available knowledge about the yeast cell wall integrity maintenance system for illustration purposes, summarize the limited knowledge available about the corresponding plant mechanism and discuss the relevance of the plant cell wall integrity maintenance mechanism in biotic stress responses. Copyright © 2014 Elsevier Ltd. All rights reserved.

  6. Combating Forest Corruption: the Forest Integrity Network

    NARCIS (Netherlands)

    Gupta, A.; Siebert, U.

    2004-01-01

    This article describes the strategies and activities of the Forest Integrity Network. One of the most important underlying causes of forest degradation is corruption and related illegal logging. The Forest Integrity Network is a timely new initiative to combat forest corruption. Its approach is to

  7. AN OVERVIEW OF UMTS AND WIMAX NETWORKS INTEGRATION

    Directory of Open Access Journals (Sweden)

    Dewi Wirastuti

    2010-12-01

    Full Text Available This paper gives an overview of the network integration of UMTS (Universal Mobile TelecommunicationSystem with WiMAX (Wordwide Interoperability of Microwave Access. A few proposed interworking solutionsand seamless integration of both networks are explained. The best architecture and key procedures that will enablethe integration both networks and handover mechanism for the seamless mobility are presented. Considering thetrend of the current network evolution, which is the convergence between the telecommunications and broadcastworlds, an integration of mobile WiMAX with present 2G, 2.5G or 3G accesses into a homogeneous architecturegoes a long way to achieve the reality of mobile broadband networks. With the advent of mobile WiMAX, a mobilebroadband wireless access solution and based on all-IP (Internet Protocol based OFDMA (Orthogonal FrequencyDivision Multiple Access technology, an UMTS-WiMAX

  8. Integrated control platform for converged optical and wireless networks

    DEFF Research Database (Denmark)

    Yan, Ying

    The next generation of broadband access networks is expected to be heterogeneous. Multiple wired and wireless systems can be integrated, in order to simultaneously provide seamless access with an appropriate Quality of Service (QoS). Wireless networks support ubiquitous connectivity yet low data...... rates, whereas optical networks can offer much higher data rates but only provide fixed connection structures. Their complementary characteristics make the integration of the two networks a promising trend for next generation networks. With combined strengths, the converged network will provide both...... the complementary characteristics of the optical networks and the wireless networks, addresses motivations for their interworking, discusses the current progress in hybrid network architectures as well as the functionalities of a control system, and identifies the achieved research contributions in the integrated...

  9. Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular.

    Science.gov (United States)

    Okasaka, Shozo; Weiler, Richard J; Keusgen, Wilhelm; Pudeyev, Andrey; Maltsev, Alexander; Karls, Ingolf; Sakaguchi, Kei

    2016-08-25

    The fifth-generation mobile networks (5G) will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave) spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet) architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP) and user plane (UP) will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC) was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access.

  10. Wellbore Integrity Network

    Energy Technology Data Exchange (ETDEWEB)

    Carey, James W. [Los Alamos National Laboratory; Bachu, Stefan [Alberta Innovates

    2012-06-21

    In this presentation, we review the current state of knowledge on wellbore integrity as developed in the IEA Greenhouse Gas Programme's Wellbore Integrity Network. Wells are one of the primary risks to the successful implementation of CO{sub 2} storage programs. Experimental studies show that wellbore materials react with CO{sub 2} (carbonation of cement and corrosion of steel) but the impact on zonal isolation is unclear. Field studies of wells in CO{sub 2}-bearing fields show that CO{sub 2} does migrate external to casing. However, rates and amounts of CO{sub 2} have not been quantified. At the decade time scale, wellbore integrity is driven by construction quality and geomechanical processes. Over longer time-scales (> 100 years), chemical processes (cement degradation and corrosion) become more important, but competing geomechanical processes may preserve wellbore integrity.

  11. A platform for rapid prototyping of synthetic gene networks in mammalian cells

    Science.gov (United States)

    Duportet, Xavier; Wroblewska, Liliana; Guye, Patrick; Li, Yinqing; Eyquem, Justin; Rieders, Julianne; Rimchala, Tharathorn; Batt, Gregory; Weiss, Ron

    2014-01-01

    Mammalian synthetic biology may provide novel therapeutic strategies, help decipher new paths for drug discovery and facilitate synthesis of valuable molecules. Yet, our capacity to genetically program cells is currently hampered by the lack of efficient approaches to streamline the design, construction and screening of synthetic gene networks. To address this problem, here we present a framework for modular and combinatorial assembly of functional (multi)gene expression vectors and their efficient and specific targeted integration into a well-defined chromosomal context in mammalian cells. We demonstrate the potential of this framework by assembling and integrating different functional mammalian regulatory networks including the largest gene circuit built and chromosomally integrated to date (6 transcription units, 27kb) encoding an inducible memory device. Using a library of 18 different circuits as a proof of concept, we also demonstrate that our method enables one-pot/single-flask chromosomal integration and screening of circuit libraries. This rapid and powerful prototyping platform is well suited for comparative studies of genetic regulatory elements, genes and multi-gene circuits as well as facile development of libraries of isogenic engineered cell lines. PMID:25378321

  12. Reverse-engineering of gene networks for regulating early blood development from single-cell measurements.

    Science.gov (United States)

    Wei, Jiangyong; Hu, Xiaohua; Zou, Xiufen; Tian, Tianhai

    2017-12-28

    Recent advances in omics technologies have raised great opportunities to study large-scale regulatory networks inside the cell. In addition, single-cell experiments have measured the gene and protein activities in a large number of cells under the same experimental conditions. However, a significant challenge in computational biology and bioinformatics is how to derive quantitative information from the single-cell observations and how to develop sophisticated mathematical models to describe the dynamic properties of regulatory networks using the derived quantitative information. This work designs an integrated approach to reverse-engineer gene networks for regulating early blood development based on singel-cell experimental observations. The wanderlust algorithm is initially used to develop the pseudo-trajectory for the activities of a number of genes. Since the gene expression data in the developed pseudo-trajectory show large fluctuations, we then use Gaussian process regression methods to smooth the gene express data in order to obtain pseudo-trajectories with much less fluctuations. The proposed integrated framework consists of both bioinformatics algorithms to reconstruct the regulatory network and mathematical models using differential equations to describe the dynamics of gene expression. The developed approach is applied to study the network regulating early blood cell development. A graphic model is constructed for a regulatory network with forty genes and a dynamic model using differential equations is developed for a network of nine genes. Numerical results suggests that the proposed model is able to match experimental data very well. We also examine the networks with more regulatory relations and numerical results show that more regulations may exist. We test the possibility of auto-regulation but numerical simulations do not support the positive auto-regulation. In addition, robustness is used as an importantly additional criterion to select candidate

  13. Meditation is associated with increased brain network integration.

    Science.gov (United States)

    van Lutterveld, Remko; van Dellen, Edwin; Pal, Prasanta; Yang, Hua; Stam, Cornelis Jan; Brewer, Judson

    2017-09-01

    This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration. Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4-8 Hz), alpha (8-13 Hz) and lower beta (13-20 Hz) frequency bands. Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands. These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using

  14. Cell cycle gene expression networks discovered using systems biology: Significance in carcinogenesis

    Science.gov (United States)

    Scott, RE; Ghule, PN; Stein, JL; Stein, GS

    2015-01-01

    The early stages of carcinogenesis are linked to defects in the cell cycle. A series of cell cycle checkpoints are involved in this process. The G1/S checkpoint that serves to integrate the control of cell proliferation and differentiation is linked to carcinogenesis and the mitotic spindle checkpoint with the development of chromosomal instability. This paper presents the outcome of systems biology studies designed to evaluate if networks of covariate cell cycle gene transcripts exist in proliferative mammalian tissues including mice, rats and humans. The GeneNetwork website that contains numerous gene expression datasets from different species, sexes and tissues represents the foundational resource for these studies (www.genenetwork.org). In addition, WebGestalt, a gene ontology tool, facilitated the identification of expression networks of genes that co-vary with key cell cycle targets, especially Cdc20 and Plk1 (www.bioinfo.vanderbilt.edu/webgestalt). Cell cycle expression networks of such covariate mRNAs exist in multiple proliferative tissues including liver, lung, pituitary, adipose and lymphoid tissues among others but not in brain or retina that have low proliferative potential. Sixty-three covariate cell cycle gene transcripts (mRNAs) compose the average cell cycle network with p = e−13 to e−36. Cell cycle expression networks show species, sex and tissue variability and they are enriched in mRNA transcripts associated with mitosis many of which are associated with chromosomal instability. PMID:25808367

  15. Measuring the degree of integration for an integrated service network

    Directory of Open Access Journals (Sweden)

    Chenglin Ye

    2012-09-01

    Full Text Available Background: Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies' perception and expectation. We propose a method for quantifying the agencies' service integration. Using the data from the Children's Treatment Network (CTN, we aimed to measure the degree of integration for the CTN agencies in York and Simcoe.  Theory and Methods: We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score.  Results: Most agencies' integration scores were less than 65%. As measured by the agreement between every other agency's perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39% - 49% and 52% (95% CI: 48% - 56%, respectively. The sensitivity analysis showed that the global scores were robust.  Conclusion: Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes.

  16. Measuring the degree of integration for an integrated service network

    Directory of Open Access Journals (Sweden)

    Chenglin Ye

    2012-09-01

    Full Text Available Background: Integration involves the coordination of services provided by autonomous agencies and improves the organization and delivery of multiple services for target patients. Current measures generally do not distinguish between agencies' perception and expectation. We propose a method for quantifying the agencies' service integration. Using the data from the Children's Treatment Network (CTN, we aimed to measure the degree of integration for the CTN agencies in York and Simcoe. Theory and Methods: We quantified the integration by the agreement between perceived and expected levels of involvement and calculated four scores from different perspectives for each agency. We used the average score to measure the global network integration and examined the sensitivity of the global score. Results: Most agencies' integration scores were less than 65%. As measured by the agreement between every other agency's perception and expectation, the overall integration of CTN in Simcoe and York was 44% (95% CI: 39% - 49% and 52% (95% CI: 48% - 56%, respectively. The sensitivity analysis showed that the global scores were robust. Conclusion: Our method extends existing measures of integration and possesses a good extent of validity. We can also apply the method in monitoring improvement and linking integration with other outcomes. 

  17. Functional Module Analysis for Gene Coexpression Networks with Network Integration.

    Science.gov (United States)

    Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

  18. Integrated Optoelectronic Networks for Application-Driven Multicore Computing

    Science.gov (United States)

    2017-05-08

    AFRL-AFOSR-VA-TR-2017-0102 Integrated Optoelectronic Networks for Application- Driven Multicore Computing Sudeep Pasricha COLORADO STATE UNIVERSITY...AND SUBTITLE Integrated Optoelectronic Networks for Application-Driven Multicore Computing 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA9550-13-1-0110 5c...and supportive materials with innovative architectural designs that integrate these components according to system-wide application needs. 15

  19. Proof-of-Concept of a Millimeter-Wave Integrated Heterogeneous Network for 5G Cellular

    Directory of Open Access Journals (Sweden)

    Shozo Okasaka

    2016-08-01

    Full Text Available The fifth-generation mobile networks (5G will not only enhance mobile broadband services, but also enable connectivity for a massive number of Internet-of-Things devices, such as wireless sensors, meters or actuators. Thus, 5G is expected to achieve a 1000-fold or more increase in capacity over 4G. The use of the millimeter-wave (mmWave spectrum is a key enabler to allowing 5G to achieve such enhancement in capacity. To fully utilize the mmWave spectrum, 5G is expected to adopt a heterogeneous network (HetNet architecture, wherein mmWave small cells are overlaid onto a conventional macro-cellular network. In the mmWave-integrated HetNet, splitting of the control plane (CP and user plane (UP will allow continuous connectivity and increase the capacity of the mmWave small cells. mmWave communication can be used not only for access linking, but also for wireless backhaul linking, which will facilitate the installation of mmWave small cells. In this study, a proof-of-concept (PoC was conducted to demonstrate the practicality of a prototype mmWave-integrated HetNet, using mmWave technologies for both backhaul and access.

  20. Transcriptomic and Proteomic Data Integration and Two-Dimensional Molecular Maps with Regulatory and Functional Linkages: Application to Cell Proliferation and Invasion Networks in Glioblastoma.

    Science.gov (United States)

    Gupta, Manoj Kumar; Jayaram, Savita; Reddy, Divijendra Natha; Polisetty, Ravindra Varma; Sirdeshmukh, Ravi

    2015-12-04

    Glioblastoma multiforme (GBM), the most aggressive primary brain tumor, is characterized by high rates of cell proliferation, migration, and invasion. New therapeutic strategies and targets are being continuously explored with the hope for better outcome. By overlaying transcriptomic and proteomic data from GBM clinical tissues, we identified 317 differentially expressed proteins to be concordant with the messenger RNAs (mRNAs). We used these entities to generate integrated regulatory information at the level of microRNAs (miRNAs) and their mRNA and protein targets using prediction programs or experimentally verified miRNA target mode in the miRWalk database. We observed 60% or even more of the miRNA-target pairs to be consistent with experimentally observed inverse expression of these molecules in GBM. The integrated view of these regulatory cascades in the contexts of cell proliferation and invasion networks revealed two-dimensional molecular interactions with regulatory and functional linkages (miRNAs and their mRNA-protein targets in one dimension; multiple miRNAs associated in a functional network in the second dimension). A total of 28 of the 35 differentially expressed concordant mRNA-protein entities represented in the proliferation network, and 51 of the 59 such entities represented in the invasion network, mapped to altered miRNAs from GBM and conformed to an inverse relationship in their expression. We believe the two-dimensional maps of gene expression changes enhance the strength of the discovery datasets derived from omics-based studies for their applications in GBM as well as tumors in general.

  1. Protein Signaling Networks from Single Cell Fluctuations and Information Theory Profiling

    Science.gov (United States)

    Shin, Young Shik; Remacle, F.; Fan, Rong; Hwang, Kiwook; Wei, Wei; Ahmad, Habib; Levine, R.D.; Heath, James R.

    2011-01-01

    Protein signaling networks among cells play critical roles in a host of pathophysiological processes, from inflammation to tumorigenesis. We report on an approach that integrates microfluidic cell handling, in situ protein secretion profiling, and information theory to determine an extracellular protein-signaling network and the role of perturbations. We assayed 12 proteins secreted from human macrophages that were subjected to lipopolysaccharide challenge, which emulates the macrophage-based innate immune responses against Gram-negative bacteria. We characterize the fluctuations in protein secretion of single cells, and of small cell colonies (n = 2, 3,···), as a function of colony size. Measuring the fluctuations permits a validation of the conditions required for the application of a quantitative version of the Le Chatelier's principle, as derived using information theory. This principle provides a quantitative prediction of the role of perturbations and allows a characterization of a protein-protein interaction network. PMID:21575571

  2. Integration of a network aware traffic generation device into a computer network emulation platform

    CSIR Research Space (South Africa)

    Von Solms, S

    2014-07-01

    Full Text Available Flexible, open source network emulation tools can provide network researchers with significant benefits regarding network behaviour and performance. The evaluation of these networks can benefit greatly from the integration of realistic, network...

  3. An emerging role of pectic rhamnogalacturonanII for cell wall integrity

    OpenAIRE

    Reboul, Rebecca; Tenhaken, Raimund

    2012-01-01

    The plant cell wall is a complex network of different polysaccharides and glycoproteins, showing high diversity in nature. The essential components, tethering cell wall are under debate, as novel mutants challenge established models. The mutant ugd2,3 with a reduced supply of the important wall precursor UDP-glucuronic acid reveals the critical role of the pectic compound rhamnogalacturonanII for cell wall stability. This polymer seems to be more important for cell wall integrity than the pre...

  4. European networks in industrial integrity

    International Nuclear Information System (INIS)

    Crutzen, S.

    1995-01-01

    Several institutions and electrical utilities in Europe, including the Joint Research Centre (JRC), have the capability to deal with several of the problems posed by the operation and aging of structural components and with their structural integrity assessment. These institutions and the JRC have developed cooperative programmes and organized themselves into networks. This article describes the structure and objective of the existing networks. 3 figs

  5. Integrating Social Networks in Teaching in Higher Education

    Science.gov (United States)

    Abousoliman, Onsy

    2017-01-01

    In response to the emerging and swiftly developing digital tools, this dissertation investigated integrating a specific category of these tools, social networks, in teaching in higher education. The study focused on exploring how social networks integration might impact the teaching/learning process and on investigating the challenges that could…

  6. Integrating neural network technology and noise analysis

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Oak Ridge National Lab., TN

    1995-01-01

    The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check values and bearings illustrate the usefulness of the methodology developed. (Author)

  7. Tools and Models for Integrating Multiple Cellular Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.

    2015-11-06

    In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

  8. Optimal Detection of a Localized Perturbation in Random Networks of Integrate-and-Fire Neurons

    Science.gov (United States)

    Bernardi, Davide; Lindner, Benjamin

    2017-06-01

    Experimental and theoretical studies suggest that cortical networks are chaotic and coding relies on averages over large populations. However, there is evidence that rats can respond to the short stimulation of a single cortical cell, a theoretically unexplained fact. We study effects of single-cell stimulation on a large recurrent network of integrate-and-fire neurons and propose a simple way to detect the perturbation. Detection rates obtained from simulations and analytical estimates are similar to experimental response rates if the readout is slightly biased towards specific neurons. Near-optimal detection is attained for a broad range of intermediate values of the mean coupling between neurons.

  9. The integration of weighted human gene association networks based on link prediction.

    Science.gov (United States)

    Yang, Jian; Yang, Tinghong; Wu, Duzhi; Lin, Limei; Yang, Fan; Zhao, Jing

    2017-01-31

    Physical and functional interplays between genes or proteins have important biological meaning for cellular functions. Some efforts have been made to construct weighted gene association meta-networks by integrating multiple biological resources, where the weight indicates the confidence of the interaction. However, it is found that these existing human gene association networks share only quite limited overlapped interactions, suggesting their incompleteness and noise. Here we proposed a workflow to construct a weighted human gene association network using information of six existing networks, including two weighted specific PPI networks and four gene association meta-networks. We applied link prediction algorithm to predict possible missing links of the networks, cross-validation approach to refine each network and finally integrated the refined networks to get the final integrated network. The common information among the refined networks increases notably, suggesting their higher reliability. Our final integrated network owns much more links than most of the original networks, meanwhile its links still keep high functional relevance. Being used as background network in a case study of disease gene prediction, the final integrated network presents good performance, implying its reliability and application significance. Our workflow could be insightful for integrating and refining existing gene association data.

  10. Trends in Integrated Ship Control Networking

    DEFF Research Database (Denmark)

    Jørgensen, N.; Nielsen, Jens Frederik Dalsgaard

    1997-01-01

    Integrated Ship Control systems can be designed as robust, distributed, autonomous control systems. The EU funded ATOMOS and ATOMOS II projects involves both technical and non technical aspects of this process. A reference modelling concept giving an outline of a generic ISC system covering...... the network and the equipment connected to it, a framework for verification of network functionality and performance by simulation and a general distribution platform for ISC systems, The ATOMOS Network, are results of this work....

  11. Integration of protein phosphorylation, acetylation, and methylation data sets to outline lung cancer signaling networks.

    Science.gov (United States)

    Grimes, Mark; Hall, Benjamin; Foltz, Lauren; Levy, Tyler; Rikova, Klarisa; Gaiser, Jeremiah; Cook, William; Smirnova, Ekaterina; Wheeler, Travis; Clark, Neil R; Lachmann, Alexander; Zhang, Bin; Hornbeck, Peter; Ma'ayan, Avi; Comb, Michael

    2018-05-22

    Protein posttranslational modifications (PTMs) have typically been studied independently, yet many proteins are modified by more than one PTM type, and cell signaling pathways somehow integrate this information. We coupled immunoprecipitation using PTM-specific antibodies with tandem mass tag (TMT) mass spectrometry to simultaneously examine phosphorylation, methylation, and acetylation in 45 lung cancer cell lines compared to normal lung tissue and to cell lines treated with anticancer drugs. This simultaneous, large-scale, integrative analysis of these PTMs using a cluster-filtered network (CFN) approach revealed that cell signaling pathways were outlined by clustering patterns in PTMs. We used the t-distributed stochastic neighbor embedding (t-SNE) method to identify PTM clusters and then integrated each with known protein-protein interactions (PPIs) to elucidate functional cell signaling pathways. The CFN identified known and previously unknown cell signaling pathways in lung cancer cells that were not present in normal lung epithelial tissue. In various proteins modified by more than one type of PTM, the incidence of those PTMs exhibited inverse relationships, suggesting that molecular exclusive "OR" gates determine a large number of signal transduction events. We also showed that the acetyltransferase EP300 appears to be a hub in the network of pathways involving different PTMs. In addition, the data shed light on the mechanism of action of geldanamycin, an HSP90 inhibitor. Together, the findings reveal that cell signaling pathways mediated by acetylation, methylation, and phosphorylation regulate the cytoskeleton, membrane traffic, and RNA binding protein-mediated control of gene expression. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

  12. Dynamic assembly of ultrasoft colloidal networks enables cell invasion within restrictive fibrillar polymers

    Science.gov (United States)

    Douglas, Alison M.; Fragkopoulos, Alexandros A.; Gaines, Michelle K.; Lyon, L. Andrew; Fernandez-Nieves, Alberto; Barker, Thomas H.

    2017-01-01

    In regenerative medicine, natural protein-based polymers offer enhanced endogenous bioactivity and potential for seamless integration with tissue, yet form weak hydrogels that lack the physical robustness required for surgical manipulation, making them difficult to apply in practice. The use of higher concentrations of protein, exogenous cross-linkers, and blending synthetic polymers has all been applied to form more mechanically robust networks. Each relies on generating a smaller network mesh size, which increases the elastic modulus and robustness, but critically inhibits cell spreading and migration, hampering tissue regeneration. Here we report two unique observations; first, that colloidal suspensions, at sufficiently high volume fraction (ϕ), dynamically assemble into a fully percolated 3D network within high-concentration protein polymers. Second, cells appear capable of leveraging these unique domains for highly efficient cell migration throughout the composite construct. In contrast to porogens, the particles in our system remain embedded within the bulk polymer, creating a network of particle-filled tunnels. Whereas this would normally physically restrict cell motility, when the particulate network is created using ultralow cross-linked microgels, the colloidal suspension displays viscous behavior on the same timescale as cell spreading and migration and thus enables efficient cell infiltration of the construct through the colloidal-filled tunnels.

  13. Romanian network for structural integrity assessment of nuclear components

    International Nuclear Information System (INIS)

    Roth, Maria; Constantinescu, Dan Mihai; Brad, Sebastian; Ducu, Catalin

    2008-01-01

    Full text: Based of the Romanian option to develop and operate nuclear facilities, using as model the networks created at European level and taking into account the international importance of the structural integrity assessments for lifetime extension of the nuclear components, a national Project started since 2005 in the framework of the National Program 'Research of Excellence', Modulus I 2006-2008, managed by the Ministry of Education and Research. Entitled 'Integrated Network for Structural Integrity Monitoring of Critical Components in Nuclear Facilities', with the acronym RIMIS, the Project had two main objectives: - to elaborate a procedure applicable to the structural integrity assessment of the critical components used in Romanian nuclear facilities; - to integrate the national networking in a similar one, at European level, to enhance the scientific significance of Romanian R and D organizations as well as to increase the contribution to solving one of the major issue of the nuclear field. The paper aimed to present the activities performed in the Romanian institutes, involved in the Project, the final results obtained as part of the R and D activities, including experimental, theoretical and modeling ones regarding structural integrity assessment of nuclear components employed in CANDU type reactors. Also the activity carried out in the framework of the NULIFE network, created at European level of the FP6 Program and sustained by the RIMIS network will be described. (authors)

  14. Integrated topology optimisation of multi-energy networks

    NARCIS (Netherlands)

    Mazairac, L.A.J.; Salenbien, R.; Vanhoudt, D.; Desmedt, J.; Vries, de B.

    2015-01-01

    Multi-carrier hybrid energy distribution net- works provide flexibility in case of network malfunctions, energy shortages and price fluctuations through energy conversion and storage. Therefore hybrid networks can cope with large-scale integration of distributed and intermittent renewable energy

  15. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    KAUST Repository

    Onesto, Valentina; Cosentino, Carlo; Di Fabrizio, Enzo M.; Cesarelli, Mario; Amato, Francesco; Gentile, Francesco

    2016-01-01

    Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  16. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    KAUST Repository

    Onesto, Valentina

    2016-05-10

    Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  17. Information in a Network of Neuronal Cells: Effect of Cell Density and Short-Term Depression

    Directory of Open Access Journals (Sweden)

    Valentina Onesto

    2016-01-01

    Full Text Available Neurons are specialized, electrically excitable cells which use electrical to chemical signals to transmit and elaborate information. Understanding how the cooperation of a great many of neurons in a grid may modify and perhaps improve the information quality, in contrast to few neurons in isolation, is critical for the rational design of cell-materials interfaces for applications in regenerative medicine, tissue engineering, and personalized lab-on-a-chips. In the present paper, we couple an integrate-and-fire model with information theory variables to analyse the extent of information in a network of nerve cells. We provide an estimate of the information in the network in bits as a function of cell density and short-term depression time. In the model, neurons are connected through a Delaunay triangulation of not-intersecting edges; in doing so, the number of connecting synapses per neuron is approximately constant to reproduce the early time of network development in planar neural cell cultures. In simulations where the number of nodes is varied, we observe an optimal value of cell density for which information in the grid is maximized. In simulations in which the posttransmission latency time is varied, we observe that information increases as the latency time decreases and, for specific configurations of the grid, it is largely enhanced in a resonance effect.

  18. Modeling and Simulation of Handover Scheme in Integrated EPON-WiMAX Networks

    DEFF Research Database (Denmark)

    Yan, Ying; Dittmann, Lars

    2011-01-01

    In this paper, we tackle the seamless handover problem in integrated optical wireless networks. Our model applies for the convergence network of EPON and WiMAX and a mobilityaware signaling protocol is proposed. The proposed handover scheme, Integrated Mobility Management Scheme (IMMS), is assisted...... by enhancing the traditional MPCP signaling protocol, which cooperatively collects mobility information from the front-end wireless network and makes centralized bandwidth allocation decisions in the backhaul optical network. The integrated network architecture and the joint handover scheme are simulated using...... OPNET modeler. Results show validation of the protocol, i.e., integrated handover scheme gains better network performances....

  19. Estimating immunoregulatory gene networks in human herpesvirus type 6-infected T cells

    International Nuclear Information System (INIS)

    Takaku, Tomoiku; Ohyashiki, Junko H.; Zhang, Yu; Ohyashiki, Kazuma

    2005-01-01

    The immune response to viral infection involves complex network of dynamic gene and protein interactions. We present here the dynamic gene network of the host immune response during human herpesvirus type 6 (HHV-6) infection in an adult T-cell leukemia cell line. Using a pathway-focused oligonucleotide DNA microarray, we found a possible association between chemokine genes regulating Th1/Th2 balance and genes regulating T-cell proliferation during HHV-6B infection. Gene network analysis using an integrated comprehensive workbench, VoyaGene, revealed that a gene encoding a TEC-family kinase, ITK, might be a putative modulator in the host immune response against HHV-6B infection. We conclude that Th2-dominated inflammatory reaction in host cells may play an important role in HHV-6B-infected T cells, thereby suggesting the possibility that ITK might be a therapeutic target in diseases related to dysregulation of Th1/Th2 balance. This study describes a novel approach to find genes related with the complex host-virus interaction using microarray data employing the Bayesian statistical framework

  20. State-related functional integration and functional segregation brain networks in schizophrenia.

    Science.gov (United States)

    Yu, Qingbao; Sui, Jing; Kiehl, Kent A; Pearlson, Godfrey; Calhoun, Vince D

    2013-11-01

    Altered topological properties of brain connectivity networks have emerged as important features of schizophrenia. The aim of this study was to investigate how the state-related modulations to graph measures of functional integration and functional segregation brain networks are disrupted in schizophrenia. Firstly, resting state and auditory oddball discrimination (AOD) fMRI data of healthy controls (HCs) and schizophrenia patients (SZs) were decomposed into spatially independent components (ICs) by group independent component analysis (ICA). Then, weighted positive and negative functional integration (inter-component networks) and functional segregation (intra-component networks) brain networks were built in each subject. Subsequently, connectivity strength, clustering coefficient, and global efficiency of all brain networks were statistically compared between groups (HCs and SZs) in each state and between states (rest and AOD) within group. We found that graph measures of negative functional integration brain network and several positive functional segregation brain networks were altered in schizophrenia during AOD task. The metrics of positive functional integration brain network and one positive functional segregation brain network were higher during the resting state than during the AOD task only in HCs. These findings imply that state-related characteristics of both functional integration and functional segregation brain networks are impaired in schizophrenia which provides new insight into the altered brain performance in this brain disorder. © 2013.

  1. Integrating Data and Networks: Human Factors

    Science.gov (United States)

    Chen, R. S.

    2012-12-01

    The development of technical linkages and interoperability between scientific networks is a necessary but not sufficient step towards integrated use and application of networked data and information for scientific and societal benefit. A range of "human factors" must also be addressed to ensure the long-term integration, sustainability, and utility of both the interoperable networks themselves and the scientific data and information to which they provide access. These human factors encompass the behavior of both individual humans and human institutions, and include system governance, a common framework for intellectual property rights and data sharing, consensus on terminology, metadata, and quality control processes, agreement on key system metrics and milestones, the compatibility of "business models" in the short and long term, harmonization of incentives for cooperation, and minimization of disincentives. Experience with several national and international initiatives and research programs such as the International Polar Year, the Group on Earth Observations, the NASA Earth Observing Data and Information System, the U.S. National Spatial Data Infrastructure, the Global Earthquake Model, and the United Nations Spatial Data Infrastructure provide a range of lessons regarding these human factors. Ongoing changes in science, technology, institutions, relationships, and even culture are creating both opportunities and challenges for expanded interoperability of scientific networks and significant improvement in data integration to advance science and the use of scientific data and information to achieve benefits for society as a whole.

  2. Functional brain networks underlying detection and integration of disconfirmatory evidence.

    Science.gov (United States)

    Lavigne, Katie M; Metzak, Paul D; Woodward, Todd S

    2015-05-15

    Processing evidence that disconfirms a prior interpretation is a fundamental aspect of belief revision, and has clear social and clinical relevance. This complex cognitive process requires (at minimum) an alerting stage and an integration stage, and in the current functional magnetic resonance imaging (fMRI) study, we used multivariate analysis methodology on two datasets in an attempt to separate these sequentially-activated cognitive stages and link them to distinct functional brain networks. Thirty-nine healthy participants completed one of two versions of an evidence integration experiment involving rating two consecutive animal images, both of which consisted of two intact images of animal faces morphed together at different ratios (e.g., 70/30 bird/dolphin followed by 10/90 bird/dolphin). The two versions of the experiment differed primarily in terms of stimulus presentation and timing, which facilitated functional interpretation of brain networks based on differences in the hemodynamic response shapes between versions. The data were analyzed using constrained principal component analysis for fMRI (fMRI-CPCA), which allows distinct, simultaneously active task-based networks to be separated, and these were interpreted using both temporal (task-based hemodynamic response shapes) and spatial (dominant brain regions) information. Three networks showed increased activity during integration of disconfirmatory relative to confirmatory evidence: (1) a network involved in alerting to the requirement to revise an interpretation, identified as the salience network (dorsal anterior cingulate cortex and bilateral insula); (2) a sensorimotor response-related network (pre- and post-central gyri, supplementary motor area, and thalamus); and (3) an integration network involving rostral prefrontal, orbitofrontal and posterior parietal cortex. These three networks were staggered in their peak activity (alerting, responding, then integrating), but at certain time points (e

  3. Machine-to-Machine networks: integration of M2M networks into companies' administrative networks

    OpenAIRE

    Pointereau, Romain

    2013-01-01

    This analysis will address the technical, economic and regulatory aspects and will identify the position taken by the various market actors. Integration of M2M Networks into Companies' Administrative Networks. Integración de redes M2M en redes administrativas de las empresas. Integració de xarxes M2M en xarxes administratives de les empreses.

  4. Dynamic changes in protein functional linkage networks revealed by integration with gene expression data.

    Directory of Open Access Journals (Sweden)

    Shubhada R Hegde

    2008-11-01

    Full Text Available Response of cells to changing environmental conditions is governed by the dynamics of intricate biomolecular interactions. It may be reasonable to assume, proteins being the dominant macromolecules that carry out routine cellular functions, that understanding the dynamics of protein:protein interactions might yield useful insights into the cellular responses. The large-scale protein interaction data sets are, however, unable to capture the changes in the profile of protein:protein interactions. In order to understand how these interactions change dynamically, we have constructed conditional protein linkages for Escherichia coli by integrating functional linkages and gene expression information. As a case study, we have chosen to analyze UV exposure in wild-type and SOS deficient E. coli at 20 minutes post irradiation. The conditional networks exhibit similar topological properties. Although the global topological properties of the networks are similar, many subtle local changes are observed, which are suggestive of the cellular response to the perturbations. Some such changes correspond to differences in the path lengths among the nodes of carbohydrate metabolism correlating with its loss in efficiency in the UV treated cells. Similarly, expression of hubs under unique conditions reflects the importance of these genes. Various centrality measures applied to the networks indicate increased importance for replication, repair, and other stress proteins for the cells under UV treatment, as anticipated. We thus propose a novel approach for studying an organism at the systems level by integrating genome-wide functional linkages and the gene expression data.

  5. PP042. Anti-hypertensive drugs hydralazine, clonidine and labetalol improve trophoblast integration into endothelial cellular networks in vitro.

    Science.gov (United States)

    Xu, B; Charlton, F; Makris, A; Hennessy, A

    2012-07-01

    Preeclampsia is an exaggerated maternal inflammatory state with over-expression of placental soluble fms-like tyrosine kinase 1 (sFlt-1). It is also associated with shallow trophoblast invasion and inadequate transformation of uterine spiral arteries. Antihypertensive drugs administrated in preeclampsia to control blood pressure have been reported to regulate placental and circulating cytokine production from women with preeclampsia. Whether they could modulate the interaction between trophoblast and endothelial cells are not investigated. This study is to examine the effect of pharmacological dose of anti-hypertensive hydralazine, clonidine and labetalol on trophoblast cell integration into inflammatory TNF-a pre-exposed endothelial cellular networks. Human uterine myometrial microvascular endothelial cells (UtMVECs) were pre-incubated with (or without) low dose (0.5ng/ml) inflammatory TNF-a or TNF-a plus sFlt-1 (100ng/ml) for 24hours. These cells were labelled with red fluorescence and seeded on a 24-well culture plate coated with Matrigel. Endothelial tubular structures appeared within 4hours. Green fluorescent-labelled HTR-8/SVneo trophoblast cells were then co-cultured with endothelial cells, with (or without) hydralazine (10μg/ml), clonidine (1.0μg/ml) or labetalol (0.5μg/ml). Red and green fluorescent images were captured after 24hours. Drug effect on HTR-8 cells integration into endothelial cellular networks was quantified by Image Analysis software. The conditioned media were also collected to measure concentrations of free VEGF, PLGF and sFlt-1 by ELISA. When HTR-8/SVneo trophoblast cells were co-cultured with TNF-a pre-incubated endothelial cells, hydralazine and clonidine can significantly increase the trophoblast integration into endothelial cellular networks. This increase was not seen if co-cultured with normal endothelial cells (without TNF-a pre-incubation) or with TNF-a plus sFlt-1 treated endothelial cells. Labetalol could increase the HTR-8

  6. Integration of gene expression and methylation to unravel biological networks in glioblastoma patients.

    Science.gov (United States)

    Gadaleta, Francesco; Bessonov, Kyrylo; Van Steen, Kristel

    2017-02-01

    The vast amount of heterogeneous omics data, encompassing a broad range of biomolecular information, requires novel methods of analysis, including those that integrate the available levels of information. In this work, we describe Regression2Net, a computational approach that is able to integrate gene expression and genomic or methylation data in two steps. First, penalized regressions are used to build Expression-Expression (EEnet) and Expression-Genomic or Expression-Methylation (EMnet) networks. Second, network theory is used to highlight important communities of genes. When applying our approach, Regression2Net to gene expression and methylation profiles for individuals with glioblastoma multiforme, we identified, respectively, 284 and 447 potentially interesting genes in relation to glioblastoma pathology. These genes showed at least one connection in the integrated networks ANDnet and XORnet derived from aforementioned EEnet and EMnet networks. Although the edges in ANDnet occur in both EEnet and EMnet, the edges in XORnet occur in EMnet but not in EEnet. In-depth biological analysis of connected genes in ANDnet and XORnet revealed genes that are related to energy metabolism, cell cycle control (AATF), immune system response, and several cancer types. Importantly, we observed significant overrepresentation of cancer-related pathways including glioma, especially in the XORnet network, suggesting a nonignorable role of methylation in glioblastoma multiforma. In the ANDnet, we furthermore identified potential glioma suppressor genes ACCN3 and ACCN4 linked to the NBPF1 neuroblastoma breakpoint family, as well as numerous ABC transporter genes (ABCA1, ABCB1) suggesting drug resistance of glioblastoma tumors. © 2016 WILEY PERIODICALS, INC.

  7. A study of integration for I and C network prototype of KNGR

    International Nuclear Information System (INIS)

    Yang, S. K; Park, H. S.; Jeong, H. Y.

    1999-01-01

    Full digitization of instrumentation and control system (I and C) based on the network is one of the distinguished design characteristics of Korean Next Generation Reactor (KNGR). However, as the reliability of digital I and C system tends to depend on the reliability of software and network, developing of integrated I and C network prototype is required to verify system integrity. To achieve this goal, some prototypes of I and C systems were already developed during KNGR(II). Also, during the period of KNGR(III), integrated I and C network prototypes will be designed by prototypes developed at the stage of KNGR(II). In this paper, it will be considered to develop prototypes of plant major system and to detail the characteristics of architecture for integrated I and C network. Also, the major role of gate-way (Information Gate-Way) and backbone network will be considered too. Through this, the integrity of network design of KNGR will be achieved

  8. Different cell fates from cell-cell interactions: core architectures of two-cell bistable networks.

    Science.gov (United States)

    Rouault, Hervé; Hakim, Vincent

    2012-02-08

    The acquisition of different fates by cells that are initially in the same state is central to development. Here, we investigate the possible structures of bistable genetic networks that can allow two identical cells to acquire different fates through cell-cell interactions. Cell-autonomous bistable networks have been previously sampled using an evolutionary algorithm. We extend this evolutionary procedure to take into account interactions between cells. We obtain a variety of simple bistable networks that we classify into major subtypes. Some have long been proposed in the context of lateral inhibition through the Notch-Delta pathway, some have been more recently considered and others appear to be new and based on mechanisms not previously considered. The results highlight the role of posttranscriptional interactions and particularly of protein complexation and sequestration, which can replace cooperativity in transcriptional interactions. Some bistable networks are entirely based on posttranscriptional interactions and the simplest of these is found to lead, upon a single parameter change, to oscillations in the two cells with opposite phases. We provide qualitative explanations as well as mathematical analyses of the dynamical behaviors of various created networks. The results should help to identify and understand genetic structures implicated in cell-cell interactions and differentiation. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  9. The integration of weighted gene association networks based on information entropy.

    Science.gov (United States)

    Yang, Fan; Wu, Duzhi; Lin, Limei; Yang, Jian; Yang, Tinghong; Zhao, Jing

    2017-01-01

    Constructing genome scale weighted gene association networks (WGAN) from multiple data sources is one of research hot spots in systems biology. In this paper, we employ information entropy to describe the uncertain degree of gene-gene links and propose a strategy for data integration of weighted networks. We use this method to integrate four existing human weighted gene association networks and construct a much larger WGAN, which includes richer biology information while still keeps high functional relevance between linked gene pairs. The new WGAN shows satisfactory performance in disease gene prediction, which suggests the reliability of our integration strategy. Compared with existing integration methods, our method takes the advantage of the inherent characteristics of the component networks and pays less attention to the biology background of the data. It can make full use of existing biological networks with low computational effort.

  10. T-SDN architecture for space and ground integrated optical transport network

    Science.gov (United States)

    Nie, Kunkun; Hu, Wenjing; Gao, Shenghua; Chang, Chengwu

    2015-11-01

    Integrated optical transport network is the development trend of the future space information backbone network. The space and ground integrated optical transport network(SGIOTN) may contain a variety of equipment and systems. Changing the network or meeting some innovation missions in the network will be an expensive implement. Software Defined Network(SDN) provides a good solution to flexibly adding process logic, timely control states and resources of the whole network, as well as shielding the differences of heterogeneous equipment and so on. According to the characteristics of SGIOTN, we propose an transport SDN architecture for it, with hierarchical control plane and data plane composed of packet networks and optical transport networks.

  11. Integration Strategy Is a Key Step in Network-Based Analysis and Dramatically Affects Network Topological Properties and Inferring Outcomes

    Science.gov (United States)

    Jin, Nana; Wu, Deng; Gong, Yonghui; Bi, Xiaoman; Jiang, Hong; Li, Kongning; Wang, Qianghu

    2014-01-01

    An increasing number of experiments have been designed to detect intracellular and intercellular molecular interactions. Based on these molecular interactions (especially protein interactions), molecular networks have been built for using in several typical applications, such as the discovery of new disease genes and the identification of drug targets and molecular complexes. Because the data are incomplete and a considerable number of false-positive interactions exist, protein interactions from different sources are commonly integrated in network analyses to build a stable molecular network. Although various types of integration strategies are being applied in current studies, the topological properties of the networks from these different integration strategies, especially typical applications based on these network integration strategies, have not been rigorously evaluated. In this paper, systematic analyses were performed to evaluate 11 frequently used methods using two types of integration strategies: empirical and machine learning methods. The topological properties of the networks of these different integration strategies were found to significantly differ. Moreover, these networks were found to dramatically affect the outcomes of typical applications, such as disease gene predictions, drug target detections, and molecular complex identifications. The analysis presented in this paper could provide an important basis for future network-based biological researches. PMID:25243127

  12. Global phosphoproteome profiling reveals unanticipated networks responsive to cisplatin treatment of embryonic stem cells

    DEFF Research Database (Denmark)

    Pines, Alex; Kelstrup, Christian D; Vrouwe, Mischa G

    2011-01-01

    (stable isotope labeling by amino acids in cell culture)-labeled murine embryonic stem cells with the anticancer drug cisplatin. Network and pathway analyses indicated that processes related to the DNA damage response and cytoskeleton organization were significantly affected. Although the ATM (ataxia...... rearrangements. Integration of transcriptomic and proteomic data revealed a poor correlation between changes in the relative levels of transcripts and their corresponding proteins, but a large overlap in affected pathways at the levels of mRNA, protein, and phosphoprotein. This study provides an integrated view...

  13. Integration and the performance of healthcare networks: do integration strategies enhance efficiency, profitability, and image?

    Directory of Open Access Journals (Sweden)

    Thomas T.H. Wan

    2001-06-01

    Full Text Available Purpose: This study examines the integration effects on efficiency and financial viability of the top 100 integrated healthcare networks (IHNs in the United States. Theory: A contingency- strategic theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. Methods: The lists of the top 100 IHNs ranked in two years, 1998 and 1999, by the SMG Marketing Group were merged to create a database for the study. Multiple indicators were used to examine the relationship between IHNs' characteristics and their performance in efficiency and financial viability. A path analytical model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' images, represented by attaining ranking among the top 100 in two consecutive years, were analysed. Results and conclusion: No positive associations were found between integration and network performance in efficiency or profits. Longitudinal data are needed to investigate the effect of integration on healthcare networks' financial performance.

  14. Semantic web for integrated network analysis in biomedicine.

    Science.gov (United States)

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  15. A data integration approach for cell cycle analysis oriented to model simulation in systems biology

    Directory of Open Access Journals (Sweden)

    Mosca Ettore

    2007-08-01

    Full Text Available Abstract Background The cell cycle is one of the biological processes most frequently investigated in systems biology studies and it involves the knowledge of a large number of genes and networks of protein interactions. A deep knowledge of the molecular aspect of this biological process can contribute to making cancer research more accurate and innovative. In this context the mathematical modelling of the cell cycle has a relevant role to quantify the behaviour of each component of the systems. The mathematical modelling of a biological process such as the cell cycle allows a systemic description that helps to highlight some features such as emergent properties which could be hidden when the analysis is performed only from a reductionism point of view. Moreover, in modelling complex systems, a complete annotation of all the components is equally important to understand the interaction mechanism inside the network: for this reason data integration of the model components has high relevance in systems biology studies. Description In this work, we present a resource, the Cell Cycle Database, intended to support systems biology analysis on the Cell Cycle process, based on two organisms, yeast and mammalian. The database integrates information about genes and proteins involved in the cell cycle process, stores complete models of the interaction networks and allows the mathematical simulation over time of the quantitative behaviour of each component. To accomplish this task, we developed, a web interface for browsing information related to cell cycle genes, proteins and mathematical models. In this framework, we have implemented a pipeline which allows users to deal with the mathematical part of the models, in order to solve, using different variables, the ordinary differential equation systems that describe the biological process. Conclusion This integrated system is freely available in order to support systems biology research on the cell cycle and

  16. Differential neural network configuration during human path integration

    Science.gov (United States)

    Arnold, Aiden E. G. F; Burles, Ford; Bray, Signe; Levy, Richard M.; Iaria, Giuseppe

    2014-01-01

    Path integration is a fundamental skill for navigation in both humans and animals. Despite recent advances in unraveling the neural basis of path integration in animal models, relatively little is known about how path integration operates at a neural level in humans. Previous attempts to characterize the neural mechanisms used by humans to visually path integrate have suggested a central role of the hippocampus in allowing accurate performance, broadly resembling results from animal data. However, in recent years both the central role of the hippocampus and the perspective that animals and humans share similar neural mechanisms for path integration has come into question. The present study uses a data driven analysis to investigate the neural systems engaged during visual path integration in humans, allowing for an unbiased estimate of neural activity across the entire brain. Our results suggest that humans employ common task control, attention and spatial working memory systems across a frontoparietal network during path integration. However, individuals differed in how these systems are configured into functional networks. High performing individuals were found to more broadly express spatial working memory systems in prefrontal cortex, while low performing individuals engaged an allocentric memory system based primarily in the medial occipito-temporal region. These findings suggest that visual path integration in humans over short distances can operate through a spatial working memory system engaging primarily the prefrontal cortex and that the differential configuration of memory systems recruited by task control networks may help explain individual biases in spatial learning strategies. PMID:24808849

  17. Phenotypic stability and plasticity in GMP-derived cells as determined by their underlying regulatory network.

    Science.gov (United States)

    Ramírez, Carlos; Mendoza, Luis

    2018-04-01

    Blood cell formation has been recognized as a suitable system to study celular differentiation mainly because of its experimental accessibility, and because it shows characteristics such as hierarchical and gradual bifurcated patterns of commitment, which are present in several developmental processes. Although hematopoiesis has been extensively studied and there is a wealth of molecular and cellular data about it, it is not clear how the underlying molecular regulatory networks define or restrict cellular differentiation processes. Here, we infer the molecular regulatory network that controls the differentiation of a blood cell subpopulation derived from the granulocyte-monocyte precursor (GMP), comprising monocytes, neutrophils, eosinophils, basophils and mast cells. We integrate published qualitative experimental data into a model to describe temporal expression patterns observed in GMP-derived cells. The model is implemented as a Boolean network, and its dynamical behavior is studied. Steady states of the network can be clearly identified with the expression profiles of monocytes, mast cells, neutrophils, basophils, and eosinophils, under wild-type and mutant backgrounds. All scripts are publicly available at https://github.com/caramirezal/RegulatoryNetworkGMPModel. lmendoza@biomedicas.unam.mx. Supplementary data are available at Bioinformatics online.

  18. Integration of genomic information with biological networks using Cytoscape.

    Science.gov (United States)

    Bauer-Mehren, Anna

    2013-01-01

    Cytoscape is an open-source software for visualizing, analyzing, and modeling biological networks. This chapter explains how to use Cytoscape to analyze the functional effect of sequence variations in the context of biological networks such as protein-protein interaction networks and signaling pathways. The chapter is divided into five parts: (1) obtaining information about the functional effect of sequence variation in a Cytoscape readable format, (2) loading and displaying different types of biological networks in Cytoscape, (3) integrating the genomic information (SNPs and mutations) with the biological networks, and (4) analyzing the effect of the genomic perturbation onto the network structure using Cytoscape built-in functions. Finally, we briefly outline how the integrated data can help in building mathematical network models for analyzing the effect of the sequence variation onto the dynamics of the biological system. Each part is illustrated by step-by-step instructions on an example use case and visualized by many screenshots and figures.

  19. Bioinformatic Integration of Molecular Networks and Major Pathways Involved in Mice Cochlear and Vestibular Supporting Cells.

    Science.gov (United States)

    Requena, Teresa; Gallego-Martinez, Alvaro; Lopez-Escamez, Jose A

    2018-01-01

    Background : Cochlear and vestibular epithelial non-hair cells (ENHCs) are the supporting elements of the cellular architecture in the organ of Corti and the vestibular neuroepithelium in the inner ear. Intercellular and cell-extracellular matrix interactions are essential to prevent an abnormal ion redistribution leading to hearing and vestibular loss. The aim of this study is to define the main pathways and molecular networks in the mouse ENHCs. Methods : We retrieved microarray and RNA-seq datasets from mouse epithelial sensory and non-sensory cells from gEAR portal (http://umgear.org/index.html) and obtained gene expression fold-change between ENHCs and non-epithelial cells (NECs) against HCs for each gene. Differentially expressed genes (DEG) with a log2 fold change between 1 and -1 were discarded. The remaining genes were selected to search for interactions using Ingenuity Pathway Analysis and STRING platform. Specific molecular networks for ENHCs in the cochlea and the vestibular organs were generated and significant pathways were identified. Results : Between 1723 and 1559 DEG were found in the mouse cochlear and vestibular tissues, respectively. Six main pathways showed enrichment in the supporting cells in both tissues: (1) "Inhibition of Matrix Metalloproteases"; (2) "Calcium Transport I"; (3) "Calcium Signaling"; (4) "Leukocyte Extravasation Signaling"; (5) "Signaling by Rho Family GTPases"; and (6) "Axonal Guidance Si". In the mouse cochlea, ENHCs showed a significant enrichment in 18 pathways highlighting "axonal guidance signaling (AGS)" ( p = 4.37 × 10 -8 ) and "RhoGDI Signaling" ( p = 3.31 × 10 -8 ). In the vestibular dataset, there were 20 enriched pathways in ENHCs, the most significant being "Leukocyte Extravasation Signaling" ( p = 8.71 × 10 -6 ), "Signaling by Rho Family GTPases" ( p = 1.20 × 10 -5 ) and "Calcium Signaling" ( p = 1.20 × 10 -5 ). Among the top ranked networks, the most biologically significant network contained the

  20. A Method to Design Synthetic Cell-Cycle Networks

    International Nuclear Information System (INIS)

    Ke-Ke, Miao

    2009-01-01

    The interactions among proteins, DNA and RNA in an organism form elaborate cell-cycle networks which govern cell growth and proliferation. Understanding the common structure of cell-cycle networks will be of great benefit to science research. Here, inspired by the importance of the cell-cycle regulatory network of yeast which has been studied intensively, we focus on small networks with 11 nodes, equivalent to that of the cell-cycle regulatory network used by Li et al. [Proc. Natl. Acad. Sci. USA 101(2004)4781] Using a Boolean model, we study the correlation between structure and function, and a possible common structure. It is found that cascade-like networks with a great number of interactions between nodes are stable. Based on these findings, we are able to construct synthetic networks that have the same functions as the cell-cycle regulatory network. (condensed matter: structure, mechanical and thermal properties)

  1. A Robust Optimization Based Energy-Aware Virtual Network Function Placement Proposal for Small Cell 5G Networks with Mobile Edge Computing Capabilities

    Directory of Open Access Journals (Sweden)

    Bego Blanco

    2017-01-01

    Full Text Available In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.

  2. Predicting Protein Function via Semantic Integration of Multiple Networks.

    Science.gov (United States)

    Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

    2016-01-01

    Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

  3. Network signatures of cellular immortalization in human lymphoblastoid cell lines

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Sung-Mi; Jung, So-Young; Nam, Hye-Young; Kim, Hye-Ryun; Lee, Mee-Hee; Kim, Jun-Woo; Han, Bok-Ghee [National Biobank of Korea, Center for Genome Science, Korea National Institute of Health, Osong 363-951 (Korea, Republic of); Jeon, Jae-Pil, E-mail: jaepiljeon@hanmail.net [Division of Brain Diseases, Center for Biomedical Science, Korea National Institute of Health, Osong 363-951 (Korea, Republic of)

    2013-11-15

    Highlights: •We identified network signatures of LCL immortalization from transcriptomic profiles. •More than 41% of DEGs are possibly regulated by miRNAs in LCLs. •MicroRNA target genes in LCLs are involved in apoptosis and immune-related functions. •This approach is useful to find functional miRNA targets in specific cell conditions. -- Abstract: Human lymphoblastoid cell line (LCL) has been used as an in vitro cell model in genetic and pharmacogenomic studies, as well as a good model for studying gene expression regulatory machinery using integrated genomic analyses. In this study, we aimed to identify biological networks of LCL immortalization from transcriptomic profiles of microRNAs and their target genes in LCLs. We first selected differentially expressed genes (DEGs) and microRNAs (DEmiRs) between early passage LCLs (eLCLs) and terminally differentiated late passage LCLs (tLCLs). The in silico and correlation analysis of these DEGs and DEmiRs revealed that 1098 DEG–DEmiR pairs were found to be positively (n = 591 pairs) or negatively (n = 507 pairs) correlated with each other. More than 41% of DEGs are possibly regulated by miRNAs in LCL immortalizations. The target DEGs of DEmiRs were enriched for cellular functions associated with apoptosis, immune response, cell death, JAK–STAT cascade and lymphocyte activation while non-miRNA target DEGs were over-represented for basic cell metabolisms. The target DEGs correlated negatively with miR-548a-3p and miR-219-5p were significantly associated with protein kinase cascade, and the lymphocyte proliferation and apoptosis, respectively. In addition, the miR-106a and miR-424 clusters located in the X chromosome were enriched in DEmiR–mRNA pairs for LCL immortalization. In this study, the integrated transcriptomic analysis of LCLs could identify functional networks of biologically active microRNAs and their target genes involved in LCL immortalization.

  4. Integration versus Outsourcing in Stable Industry Equilibrium with Communication Networks

    OpenAIRE

    Okamoto, Yusuke

    2006-01-01

    For the selection of a firm's structure between vertical integration and arm's-length outsourcing, the importance of the thickness of the market had been emphasized in the previous literature. Here we take account of communication networks such as telephone, telex, fax, and the Internet. By doing so, we could illustrate the relationship between communication networks and the make-or-buy decision. With communication network technology differing in each type of firm, both vertically integrated ...

  5. Classification Method in Integrated Information Network Using Vector Image Comparison

    Directory of Open Access Journals (Sweden)

    Zhou Yuan

    2014-05-01

    Full Text Available Wireless Integrated Information Network (WMN consists of integrated information that can get data from its surrounding, such as image, voice. To transmit information, large resource is required which decreases the service time of the network. In this paper we present a Classification Approach based on Vector Image Comparison (VIC for WMN that improve the service time of the network. The available methods for sub-region selection and conversion are also proposed.

  6. Integrated network for structural integrity monitoring of critical components in nuclear facilities, RIMIS

    International Nuclear Information System (INIS)

    Roth, Maria; Constantinescu, Dan Mihai; Brad, Sebastian; Ducu, Catalin; Malinovschi, Viorel

    2008-01-01

    The round table aims to join specialists working in the research area of the Romanian R and D Institutes and Universities involved in structural integrity assessment of materials, especially those working in the nuclear field, together with the representatives of the end user, the Cernavoda NPP. This scientific event will offer the opportunity to disseminate the theoretical, experimental and modelling activities, carried out to date, in the framework of the National Program 'Research of Excellence', Module I 2006-2008, managed by the National Authority for Scientific Research. Entitled 'Integrated Network for Structural Integrity Monitoring of Critical Components in Nuclear Facilities, RIMIS, the project has two main objectives: 1. - to elaborate a procedure applicable to the structural integrity assessment of critical components used in Romanian nuclear facilities (CANDU type Reactor, Hydrogen Isotopes Separation installations); 2. - to integrate the national networking into a similar one of European level, and to enhance the scientific significance of Romanian R and D organisations as well as to increase the contribution in solving major issues of the nuclear field. The topics of the round table will be focused on: 1. Development of a Structural Integrity Assessment Methodology applicable to the nuclear facilities components; 2. Experimental investigation methods and procedures; 3. Numeric simulation of nuclear components behaviour; 4. Further activities to finalize the assessment procedure. Also participations and contributions to sustain the activity in the European Network NULIFE, FP6 will be discussed. (authors)

  7. Ubiquitous Integrity via Network Integration and Parallelism—Sustaining Pedestrian/Bike Urbanism

    Directory of Open Access Journals (Sweden)

    Li-Yen Hsu

    2013-08-01

    Full Text Available Nowadays, due to the concern regarding environmental issues, establishing pedestrian/bike friendly urbanism is widely encouraged. To promote safety-assured, mobile communication environments, efficient, reliable maintenance, and information integrity need to be designed, especially in highly possibly interfered places. For busy traffic areas, regular degree-3 dedicated short range communication (DSRC networks are safety and information featured with availability, reliability, and maintainability in paths of multi-lanes. For sparsely populated areas, probes of wireless sensors are rational, especially if sensor nodes can be organized to enhance security, reliability, and flexibility. Applying alternative network topologies, such as spider-webs, generalized honeycomb tori, and cube-connected cycles, for comparing and analyzing is proposed in DSRC and cellular communications to enhance integrity in communications.

  8. Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

    Directory of Open Access Journals (Sweden)

    Sriram Chandrasekaran

    2017-12-01

    Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

  9. Integrated computer network high-speed parallel interface

    International Nuclear Information System (INIS)

    Frank, R.B.

    1979-03-01

    As the number and variety of computers within Los Alamos Scientific Laboratory's Central Computer Facility grows, the need for a standard, high-speed intercomputer interface has become more apparent. This report details the development of a High-Speed Parallel Interface from conceptual through implementation stages to meet current and future needs for large-scle network computing within the Integrated Computer Network. 4 figures

  10. Seamless integrated network system for wireless communication systems

    NARCIS (Netherlands)

    Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

    2006-01-01

    To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

  11. Seamless integrated network system for wireless communication systems

    NARCIS (Netherlands)

    Wu, Gang; Mizuno, Mitsuhiko; Hase, Yoshihiro; Havinga, Paul J.M.

    2002-01-01

    To create a network that connects a plurality of wireless communication systems to create optimal systems for various environments, and that seamlessly integrates the resulting systems together in order to provide more efficient and advanced service in general. A network system that can seamlessly

  12. Construction of functional linkage gene networks by data integration.

    Science.gov (United States)

    Linghu, Bolan; Franzosa, Eric A; Xia, Yu

    2013-01-01

    Networks of functional associations between genes have recently been successfully used for gene function and disease-related research. A typical approach for constructing such functional linkage gene networks (FLNs) is based on the integration of diverse high-throughput functional genomics datasets. Data integration is a nontrivial task due to the heterogeneous nature of the different data sources and their variable accuracy and completeness. The presence of correlations between data sources also adds another layer of complexity to the integration process. In this chapter we discuss an approach for constructing a human FLN from data integration and a subsequent application of the FLN to novel disease gene discovery. Similar approaches can be applied to nonhuman species and other discovery tasks.

  13. Network architectures and protocols for the integration of ACTS and ISDN

    Science.gov (United States)

    Chitre, D. M.; Lowry, P. A.

    1992-01-01

    A close integration of satellite networks and the integrated services digital network (ISDN) is essential for satellite networks to carry ISDN traffic effectively. This also shows how a given (pre-ISDN) satellite network architecture can be enhanced to handle ISDN signaling and provide ISDN services. It also describes the functional architecture and high-level protocols that could be implemented in the NASA Advanced Communications Technology Satellite (ACTS) low burst rate communications system to provide ISDN services.

  14. Integrated Job Scheduling and Network Routing

    DEFF Research Database (Denmark)

    Gamst, Mette; Pisinger, David

    2013-01-01

    We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number of resou...... indicate that the algorithm can be used as an actual scheduling algorithm in the Grid or as a tool for analyzing Grid performance when adding extra machines or jobs. © 2012 Wiley Periodicals, Inc.......We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number...... of resources which must be sent to the executing machine through a network with limited capacity. A job cannot start before all of its resources have arrived at the machine. The scheduling problem is formulated as a Mixed Integer Program (MIP) and proved to be NP-hard. An exact solution approach using Dantzig...

  15. Integration of a laterally acquired gene into a cell network important for growth in a strain of Vibrio rotiferianus

    Directory of Open Access Journals (Sweden)

    Labbate Maurizio

    2011-11-01

    Full Text Available Abstract Background Lateral Gene Transfer (LGT is a major contributor to bacterial evolution and up to 25% of a bacterium's genome may have been acquired by this process over evolutionary periods of time. Successful LGT requires both the physical transfer of DNA and its successful incorporation into the host cell. One system that contributes to this latter step by site-specific recombination is the integron. Integrons are found in many diverse bacterial Genera and is a genetic system ubiquitous in vibrios that captures mobile DNA at a dedicated site. The presence of integron-associated genes, contained within units of mobile DNA called gene cassettes makes up a substantial component of the vibrio genome (1-3%. Little is known about the role of this system since the vast majority of genes in vibrio arrays are highly novel and functions cannot be ascribed. It is generally regarded that strain-specific mobile genes cannot be readily integrated into the cellular machinery since any perturbation of core metabolism is likely to result in a loss of fitness. Results In this study, at least one mobile gene contained within the Vibrio rotiferianus strain DAT722, but lacking close relatives elsewhere, is shown to greatly reduce host fitness when deleted and tested in growth assays. The precise role of the mobile gene product is unknown but impacts on the regulation of outermembrane porins. This demonstrates that strain specific laterally acquired mobile DNA can be integrated rapidly into bacterial networks such that it becomes advantageous for survival and adaptation in changing environments. Conclusions Mobile genes that are highly strain specific are generally believed to act in isolation. This is because perturbation of existing cell machinery by the acquisition of a new gene by LGT is highly likely to lower fitness. In contrast, we show here that at least one mobile gene, apparently unique to a strain, encodes a product that has integrated into central

  16. Automated quantification of neuronal networks and single-cell calcium dynamics using calcium imaging.

    Science.gov (United States)

    Patel, Tapan P; Man, Karen; Firestein, Bonnie L; Meaney, David F

    2015-03-30

    Recent advances in genetically engineered calcium and membrane potential indicators provide the potential to estimate the activation dynamics of individual neurons within larger, mesoscale networks (100s-1000+neurons). However, a fully integrated automated workflow for the analysis and visualization of neural microcircuits from high speed fluorescence imaging data is lacking. Here we introduce FluoroSNNAP, Fluorescence Single Neuron and Network Analysis Package. FluoroSNNAP is an open-source, interactive software developed in MATLAB for automated quantification of numerous biologically relevant features of both the calcium dynamics of single-cells and network activity patterns. FluoroSNNAP integrates and improves upon existing tools for spike detection, synchronization analysis, and inference of functional connectivity, making it most useful to experimentalists with little or no programming knowledge. We apply FluoroSNNAP to characterize the activity patterns of neuronal microcircuits undergoing developmental maturation in vitro. Separately, we highlight the utility of single-cell analysis for phenotyping a mixed population of neurons expressing a human mutant variant of the microtubule associated protein tau and wild-type tau. We show the performance of semi-automated cell segmentation using spatiotemporal independent component analysis and significant improvement in detecting calcium transients using a template-based algorithm in comparison to peak-based or wavelet-based detection methods. Our software further enables automated analysis of microcircuits, which is an improvement over existing methods. We expect the dissemination of this software will facilitate a comprehensive analysis of neuronal networks, promoting the rapid interrogation of circuits in health and disease. Copyright © 2015. Published by Elsevier B.V.

  17. Small cell networks deployment, management, and optimization

    CERN Document Server

    Claussen, Holger; Ho, Lester; Razavi, Rouzbeh; Kucera, Stepan

    2018-01-01

    Small Cell Networks: Deployment, Management, and Optimization addresses key problems of the cellular network evolution towards HetNets. It focuses on the latest developments in heterogeneous and small cell networks, as well as their deployment, operation, and maintenance. It also covers the full spectrum of the topic, from academic, research, and business to the practice of HetNets in a coherent manner. Additionally, it provides complete and practical guidelines to vendors and operators interested in deploying small cells. The first comprehensive book written by well-known researchers and engineers from Nokia Bell Labs, Small Cell Networks begins with an introduction to the subject--offering chapters on capacity scaling and key requirements of future networks. It then moves on to sections on coverage and capacity optimization, and interference management. From there, the book covers mobility management, energy efficiency, and small cell deployment, ending with a section devoted to future trends and applicat...

  18. Multi-attribute integrated measurement of node importance in complex networks.

    Science.gov (United States)

    Wang, Shibo; Zhao, Jinlou

    2015-11-01

    The measure of node importance in complex networks is very important to the research of networks stability and robustness; it also can ensure the security of the whole network. Most researchers have used a single indicator to measure the networks node importance, so that the obtained measurement results only reflect certain aspects of the networks with a loss of information. Meanwhile, because of the difference of networks topology, the nodes' importance should be described by combining the character of the networks topology. Most of the existing evaluation algorithms cannot completely reflect the circumstances of complex networks, so this paper takes into account the degree of centrality, the relative closeness centrality, clustering coefficient, and topology potential and raises an integrated measuring method to measure the nodes' importance. This method can reflect nodes' internal and outside attributes and eliminate the influence of network structure on the node importance. The experiments of karate network and dolphin network show that networks topology structure integrated measure has smaller range of metrical result than a single indicator and more universal. Experiments show that attacking the North American power grid and the Internet network with the method has a faster convergence speed than other methods.

  19. Discrete dynamic modeling of T cell survival signaling networks

    Science.gov (United States)

    Zhang, Ranran

    2009-03-01

    Biochemistry-based frameworks are often not applicable for the modeling of heterogeneous regulatory systems that are sparsely documented in terms of quantitative information. As an alternative, qualitative models assuming a small set of discrete states are gaining acceptance. This talk will present a discrete dynamic model of the signaling network responsible for the survival and long-term competence of cytotoxic T cells in the blood cancer T-LGL leukemia. We integrated the signaling pathways involved in normal T cell activation and the known deregulations of survival signaling in leukemic T-LGL, and formulated the regulation of each network element as a Boolean (logic) rule. Our model suggests that the persistence of two signals is sufficient to reproduce all known deregulations in leukemic T-LGL. It also indicates the nodes whose inactivity is necessary and sufficient for the reversal of the T-LGL state. We have experimentally validated several model predictions, including: (i) Inhibiting PDGF signaling induces apoptosis in leukemic T-LGL. (ii) Sphingosine kinase 1 and NFκB are essential for the long-term survival of T cells in T-LGL leukemia. (iii) T box expressed in T cells (T-bet) is constitutively activated in the T-LGL state. The model has identified potential therapeutic targets for T-LGL leukemia and can be used for generating long-term competent CTL necessary for tumor and cancer vaccine development. The success of this model, and of other discrete dynamic models, suggests that the organization of signaling networks has an determining role in their dynamics. Reference: R. Zhang, M. V. Shah, J. Yang, S. B. Nyland, X. Liu, J. K. Yun, R. Albert, T. P. Loughran, Jr., Network Model of Survival Signaling in LGL Leukemia, PNAS 105, 16308-16313 (2008).

  20. End-to-End Traffic Flow Modeling of the Integrated SCaN Network

    Science.gov (United States)

    Cheung, K.-M.; Abraham, D. S.

    2012-05-01

    In this article, we describe the analysis and simulation effort of the end-to-end traffic flow for the Integrated Space Communications and Navigation (SCaN) Network. Using the network traffic derived for the 30-day period of July 2018 from the Space Communications Mission Model (SCMM), we generate the wide-area network (WAN) bandwidths of the ground links for different architecture options of the Integrated SCaN Network. We also develop a new analytical scheme to model the traffic flow and buffering mechanism of a store-and-forward network. It is found that the WAN bandwidth of the Integrated SCaN Network is an important differentiator of different architecture options, as the recurring circuit costs of certain architecture options can be prohibitively high.

  1. Networks in Cell Biology

    Science.gov (United States)

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

    2010-05-01

    Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

  2. Correct integration of compressors and expanders in above ambient heat exchanger networks

    International Nuclear Information System (INIS)

    Fu, Chao; Gundersen, Truls

    2016-01-01

    The Appropriate Placement concept (also referred to as Correct Integration) is fundamental in Pinch Analysis. The placement of reactors, distillation columns, evaporators, heat pumps and heat engines in heat exchanger networks is well established. The placement of pressure changing equipment such as compressors and expanders is complex and less discussed in literature. A major difficulty is that both heat and work (not only heat) are involved. The integration of compressors and expanders separately into heat exchanger networks was recently investigated. A set of theorems were proposed for assisting the design. The problem is even more complex when both compressors and expanders are to be integrated. An important concern is about the sequence of integration with compressors and expanders, i.e. should compressors or expanders be implemented first. This problem is studied and a new theorem is formulated related to the Correct Integration of both compressors and expanders in above ambient heat exchanger networks. The objective is to minimize exergy consumption for the integrated processes. A graphical design methodology is developed for the integration of compressors and expanders into heat exchanger networks above ambient temperature. - Highlights: • The correct integration of compressors and expanders in heat exchanger networks is studied. • A theorem is proposed for heat integration between compressors and expanders. • The total exergy consumption is minimized.

  3. Maximizing performance of fuel cell using artificial neural network approach for smart grid applications

    International Nuclear Information System (INIS)

    Bicer, Y.; Dincer, I.; Aydin, M.

    2016-01-01

    This paper presents an artificial neural network (ANN) approach of a smart grid integrated proton exchange membrane (PEM) fuel cell and proposes a neural network model of a 6 kW PEM fuel cell. The data required to train the neural network model are generated by a model of 6 kW PEM fuel cell. After the model is trained and validated, it is used to analyze the dynamic behavior of the PEM fuel cell. The study results demonstrate that the model based on neural network approach is appropriate for predicting the outlet parameters. Various types of training methods, sample numbers and sample distribution methods are utilized to compare the results. The fuel cell stack efficiency considerably varies between 20% and 60%, according to input variables and models. The rapid changes in the input variables can be recovered within a short time period, such as 10 s. The obtained response graphs point out the load tracking features of ANN model and the projected changes in the input variables are controlled quickly in the study. - Highlights: • An ANN approach of a proton exchange membrane (PEM) fuel cell is proposed. • Dynamic behavior of the PEM fuel cell is analyzed. • The effects of various variables on model accuracy are investigated. • Response curves indicate the load following characteristics of the model.

  4. Networks of Cells and Petri Nets

    OpenAIRE

    Bernardini, Francesco; Gheorgue, Marian; Margenstern, Maurice; Verlan, Sergey

    2007-01-01

    We introduce a new class of P systems, called networks of cells, with rules allowing several cells to simultaneously interact with each other in order to produce some new objects inside some other output cells. We define different types of behavior for networks of cells by considering alternative strategies for the application of the rules: sequential application, free parallelism, maximal parallelism, locally-maximal parallelism and minimal parallelism. We devise a way for tra...

  5. The Contribution of Network Organization and Integration to the Development of Cognitive Control.

    Science.gov (United States)

    Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N; Luna, Beatriz

    2015-12-01

    Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

  6. The Contribution of Network Organization and Integration to the Development of Cognitive Control

    Science.gov (United States)

    Marek, Scott; Hwang, Kai; Foran, William; Hallquist, Michael N.; Luna, Beatriz

    2015-01-01

    Abstract Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI), graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10–26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control. PMID:26713863

  7. The Contribution of Network Organization and Integration to the Development of Cognitive Control.

    Directory of Open Access Journals (Sweden)

    Scott Marek

    2015-12-01

    Full Text Available Cognitive control, which continues to mature throughout adolescence, is supported by the ability for well-defined organized brain networks to flexibly integrate information. However, the development of intrinsic brain network organization and its relationship to observed improvements in cognitive control are not well understood. In the present study, we used resting state functional magnetic resonance imaging (RS-fMRI, graph theory, the antisaccade task, and rigorous head motion control to characterize and relate developmental changes in network organization, connectivity strength, and integration to inhibitory control development. Subjects were 192 10-26-y-olds who were imaged during 5 min of rest. In contrast to initial studies, our results indicate that network organization is stable throughout adolescence. However, cross-network integration, predominantly of the cingulo-opercular/salience network, increased with age. Importantly, this increased integration of the cingulo-opercular/salience network significantly moderated the robust effect of age on the latency to initiate a correct inhibitory control response. These results provide compelling evidence that the transition to adult-level inhibitory control is dependent upon the refinement and strengthening of integration between specialized networks. Our findings support a novel, two-stage model of neural development, in which networks stabilize prior to adolescence and subsequently increase their integration to support the cross-domain incorporation of information processing critical for mature cognitive control.

  8. Single-cell axotomy of cultured hippocampal neurons integrated in neuronal circuits.

    Science.gov (United States)

    Gomis-Rüth, Susana; Stiess, Michael; Wierenga, Corette J; Meyn, Liane; Bradke, Frank

    2014-05-01

    An understanding of the molecular mechanisms of axon regeneration after injury is key for the development of potential therapies. Single-cell axotomy of dissociated neurons enables the study of the intrinsic regenerative capacities of injured axons. This protocol describes how to perform single-cell axotomy on dissociated hippocampal neurons containing synapses. Furthermore, to axotomize hippocampal neurons integrated in neuronal circuits, we describe how to set up coculture with a few fluorescently labeled neurons. This approach allows axotomy of single cells in a complex neuronal network and the observation of morphological and molecular changes during axon regeneration. Thus, single-cell axotomy of mature neurons is a valuable tool for gaining insights into cell intrinsic axon regeneration and the plasticity of neuronal polarity of mature neurons. Dissociation of the hippocampus and plating of hippocampal neurons takes ∼2 h. Neurons are then left to grow for 2 weeks, during which time they integrate into neuronal circuits. Subsequent axotomy takes 10 min per neuron and further imaging takes 10 min per neuron.

  9. A novel network integrating a miRNA-203/SNAI1 feedback loop which regulates epithelial to mesenchymal transition.

    Directory of Open Access Journals (Sweden)

    Michèle Moes

    Full Text Available BACKGROUND: The majority of human cancer deaths are caused by metastasis. The metastatic dissemination is initiated by the breakdown of epithelial cell homeostasis. During this phenomenon, referred to as epithelial to mesenchymal transition (EMT, cells change their genetic and trancriptomic program leading to phenotypic and functional alterations. The challenge of understanding this dynamic process resides in unraveling regulatory networks involving master transcription factors (e.g. SNAI1/2, ZEB1/2 and TWIST1 and microRNAs. Here we investigated microRNAs regulated by SNAI1 and their potential role in the regulatory networks underlying epithelial plasticity. RESULTS: By a large-scale analysis on epithelial plasticity, we highlighted miR-203 and its molecular link with SNAI1 and the miR-200 family, key regulators of epithelial homeostasis. During SNAI1-induced EMT in MCF7 breast cancer cells, miR-203 and miR-200 family members were repressed in a timely correlated manner. Importantly, miR-203 repressed endogenous SNAI1, forming a double negative miR203/SNAI1 feedback loop. We integrated this novel miR203/SNAI1 with the known miR200/ZEB feedback loops to construct an a priori EMT core network. Dynamic simulations revealed stable epithelial and mesenchymal states, and underscored the crucial role of the miR203/SNAI1 feedback loop in state transitions underlying epithelial plasticity. CONCLUSION: By combining computational biology and experimental approaches, we propose a novel EMT core network integrating two fundamental negative feedback loops, miR203/SNAI1 and miR200/ZEB. Altogether our analysis implies that this novel EMT core network could function as a switch controlling epithelial cell plasticity during differentiation and cancer progression.

  10. Integrating wireless sensor network for monitoring subsidence phenomena

    Science.gov (United States)

    Marturià, Jordi; Lopez, Ferran; Gigli, Giovanni; Intrieri, Emanuele; Mucchi, Lorenzo; Fornaciai, Alessandro

    2016-04-01

    An innovative wireless sensor network (WSN) for the 3D superficial monitoring of deformations (such as landslides and subsidence) is being developed in the frame of the Wi-GIM project (Wireless sensor network for Ground Instability Monitoring - LIFE12 ENV/IT/001033). The surface movement is detected acquiring the position (x, y and z) by integrating large bandwidth technology able to detect the 3D coordinates of the sensor with a sub-meter error, with continuous wave radar, which allows decreasing the error down to sub-cm. The Estació neighborhood in Sallent is located over the old potassium mine Enrique. This zone has been affected by a subsidence process over more than twenty years. The implementation of a wide network for ground auscultation has allowed monitoring the process of subsidence since 1997. This network consists of: i) a high-precision topographic leveling network to control the subsidence in surface; ii) a rod extensometers network to monitor subsurface deformation; iii) an automatic Leica TCA Total Station to monitor building movements; iv) an inclinometers network to measure the horizontal displacements on subsurface and v) a piezometer to measure the water level. Those networks were implemented within an alert system for an organized an efficient response of the civil protection authorities in case of an emergency. On 23rd December 2008, an acceleration of subsoil movements (of approx. 12-18 cm/year) provoked the activation of the emergency plan by the Catalan Civil Protection. This implied the preventive and scheduled evacuation of the neighbours (January 2009) located in the area with a higher risk of collapse: around 120 residents of 43 homes. As a consequence, the administration implemented a compensation plan for the evacuation of the whole neighbourhood residents and the demolition of 405 properties. In this work, the adaptation and integration process of Wi-GIM system with those conventional monitoring network are presented for its testing

  11. Finding influential nodes for integration in brain networks using optimal percolation theory.

    Science.gov (United States)

    Del Ferraro, Gino; Moreno, Andrea; Min, Byungjoon; Morone, Flaviano; Pérez-Ramírez, Úrsula; Pérez-Cervera, Laura; Parra, Lucas C; Holodny, Andrei; Canals, Santiago; Makse, Hernán A

    2018-06-11

    Global integration of information in the brain results from complex interactions of segregated brain networks. Identifying the most influential neuronal populations that efficiently bind these networks is a fundamental problem of systems neuroscience. Here, we apply optimal percolation theory and pharmacogenetic interventions in vivo to predict and subsequently target nodes that are essential for global integration of a memory network in rodents. The theory predicts that integration in the memory network is mediated by a set of low-degree nodes located in the nucleus accumbens. This result is confirmed with pharmacogenetic inactivation of the nucleus accumbens, which eliminates the formation of the memory network, while inactivations of other brain areas leave the network intact. Thus, optimal percolation theory predicts essential nodes in brain networks. This could be used to identify targets of interventions to modulate brain function.

  12. Data-driven integration of genome-scale regulatory and metabolic network models

    Science.gov (United States)

    Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.

    2015-01-01

    Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934

  13. Universal Intelligent Small Cell (UnISCell for next generation cellular networks

    Directory of Open Access Journals (Sweden)

    Mohammad Patwary

    2016-11-01

    Full Text Available Exploring innovative cellular architectures to achieve enhanced system capacity and good coverage has become a critical issue towards realizing the next generation of wireless communications. In this context, this paper proposes a novel concept of Universal Intelligent Small Cell (UnISCell for enabling the densification of the next generation of cellular networks. The proposed novel concept envisions an integrated platform of providing a strong linkage between different stakeholders such as street lighting networks, landline telephone networks and future wireless networks, and is universal in nature being independent of the operating frequency bands and traffic types. The main motivating factors for the proposed small cell concept are the need of public infrastructure re-engineering, and the recent advances in several enabling technologies. First, we highlight the main concepts of the proposed UnISCell platform. Subsequently, we present two deployment scenarios for the proposed UnISCell concept considering infrastructure sharing and service sharing as important aspects. We then describe the key future technologies for enabling the proposed UnISCell concept and present a use case example with the help of numerical results. Finally, we conclude this article by providing some interesting future recommendations.

  14. TTEthernet for Integrated Spacecraft Networks

    Science.gov (United States)

    Loveless, Andrew

    2015-01-01

    Aerospace projects have traditionally employed federated avionics architectures, in which each computer system is designed to perform one specific function (e.g. navigation). There are obvious downsides to this approach, including excessive weight (from so much computing hardware), and inefficient processor utilization (since modern processors are capable of performing multiple tasks). There has therefore been a push for integrated modular avionics (IMA), in which common computing platforms can be leveraged for different purposes. This consolidation of multiple vehicle functions to shared computing platforms can significantly reduce spacecraft cost, weight, and design complexity. However, the application of IMA principles introduces significant challenges, as the data network must accommodate traffic of mixed criticality and performance levels - potentially all related to the same shared computer hardware. Because individual network technologies are rarely so competent, the development of truly integrated network architectures often proves unreasonable. Several different types of networks are utilized - each suited to support a specific vehicle function. Critical functions are typically driven by precise timing loops, requiring networks with strict guarantees regarding message latency (i.e. determinism) and fault-tolerance. Alternatively, non-critical systems generally employ data networks prioritizing flexibility and high performance over reliable operation. Switched Ethernet has seen widespread success filling this role in terrestrial applications. Its high speed, flexibility, and the availability of inexpensive commercial off-the-shelf (COTS) components make it desirable for inclusion in spacecraft platforms. Basic Ethernet configurations have been incorporated into several preexisting aerospace projects, including both the Space Shuttle and International Space Station (ISS). However, classical switched Ethernet cannot provide the high level of network

  15. Design of energy efficient optical networks with software enabled integrated control plane

    DEFF Research Database (Denmark)

    Wang, Jiayuan; Yan, Ying; Dittmann, Lars

    2015-01-01

    energy consumption by proposing a new integrated control plane structure utilising Software Defined Networking technologies. The integrated control plane increases the efficiencies of exchanging control information across different network domains, while introducing new possibilities to the routing...... methods and the control over quality of service (QoS). The structure is defined as an overlay generalised multi-protocol label switching (GMPLS) control model. With the defined structure, the integrated control plane is able to gather information from different domains (i.e. optical core network......'s) routing behaviours. With the flexibility of the routing structure, results show that the energy efficiency of the network can be improved without compromising the QoS for delay/blocking sensitive services....

  16. Molecular networks linked by Moesin drive remodeling of the cell cortex during mitosis

    Science.gov (United States)

    Roubinet, Chantal; Decelle, Barbara; Chicanne, Gaëtan; Dorn, Jonas F.; Payrastre, Bernard; Payre, François; Carreno, Sébastien

    2011-01-01

    The cortical mechanisms that drive the series of mitotic cell shape transformations remain elusive. In this paper, we identify two novel networks that collectively control the dynamic reorganization of the mitotic cortex. We demonstrate that Moesin, an actin/membrane linker, integrates these two networks to synergize the cortical forces that drive mitotic cell shape transformations. We find that the Pp1-87B phosphatase restricts high Moesin activity to early mitosis and down-regulates Moesin at the polar cortex, after anaphase onset. Overactivation of Moesin at the polar cortex impairs cell elongation and thus cytokinesis, whereas a transient recruitment of Moesin is required to retract polar blebs that allow cortical relaxation and dissipation of intracellular pressure. This fine balance of Moesin activity is further adjusted by Skittles and Pten, two enzymes that locally produce phosphoinositol 4,5-bisphosphate and thereby, regulate Moesin cortical association. These complementary pathways provide a spatiotemporal framework to explain how the cell cortex is remodeled throughout cell division. PMID:21969469

  17. Direct lifts of coupled cell networks

    Science.gov (United States)

    Dias, A. P. S.; Moreira, C. S.

    2018-04-01

    In networks of dynamical systems, there are spaces defined in terms of equalities of cell coordinates which are flow-invariant under any dynamical system that has a form consistent with the given underlying network structure—the network synchrony subspaces. Given a network and one of its synchrony subspaces, any system with a form consistent with the network, restricted to the synchrony subspace, defines a new system which is consistent with a smaller network, called the quotient network of the original network by the synchrony subspace. Moreover, any system associated with the quotient can be interpreted as the restriction to the synchrony subspace of a system associated with the original network. We call the larger network a lift of the smaller network, and a lift can be interpreted as a result of the cellular splitting of the smaller network. In this paper, we address the question of the uniqueness in this lifting process in terms of the networks’ topologies. A lift G of a given network Q is said to be direct when there are no intermediate lifts of Q between them. We provide necessary and sufficient conditions for a lift of a general network to be direct. Our results characterize direct lifts using the subnetworks of all splitting cells of Q and of all split cells of G. We show that G is a direct lift of Q if and only if either the split subnetwork is a direct lift or consists of two copies of the splitting subnetwork. These results are then applied to the class of regular uniform networks and to the special classes of ring networks and acyclic networks. We also illustrate that one of the applications of our results is to the lifting bifurcation problem.

  18. Cost-Based Vertical Handover Decision Algorithm for WWAN/WLAN Integrated Networks

    Directory of Open Access Journals (Sweden)

    Kim LaeYoung

    2009-01-01

    Full Text Available Abstract Next generation wireless communications are expected to rely on integrated networks consisting of multiple wireless technologies. Heterogeneous networks based on Wireless Local Area Networks (WLANs and Wireless Wide Area Networks (WWANs can combine their respective advantages on coverage and data rates, offering a high Quality of Service (QoS to mobile users. In such environment, multi-interface terminals should seamlessly switch from one network to another in order to obtain improved performance or at least to maintain a continuous wireless connection. Therefore, network selection algorithm is important in providing better performance to the multi-interface terminals in the integrated networks. In this paper, we propose a cost-based vertical handover decision algorithm that triggers the Vertical Handover (VHO based on a cost function for WWAN/WLAN integrated networks. For the cost function, we focus on developing an analytical model of the expected cost of WLAN for the mobile users that enter the double-coverage area while having a connection in the WWAN. Our simulation results show that the proposed scheme achieves better performance in terms of power consumption and throughput than typical approach where WLANs are always preferred whenever the WLAN access is available.

  19. Nano-topography Enhances Communication in Neural Cells Networks

    KAUST Repository

    Onesto, V.

    2017-08-23

    Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness Sa affects networks topology. In the low nano-meter range, S-a = 0-30 nm, information increases with Sa. Moreover, we found that energy density of a network of cells correlates to the topology of that network. This reinforces the view that information, energy and surface nano-topography are tightly inter-connected and should not be neglected when studying cell-cell interaction in neural tissue repair and regeneration.

  20. Dynamical Adaptation in Terrorist Cells/Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar; Ahmed, Zaki

    2010-01-01

    Typical terrorist cells/networks have dynamical structure as they evolve or adapt to changes which may occur due to capturing or killing of a member of the cell/network. Analytical measures in graph theory like degree centrality, betweenness and closeness centralities are very common and have long...

  1. A 40 GHz fully integrated circuit with a vector network analyzer and a coplanar-line-based detection area for circulating tumor cell analysis using 65 nm CMOS technology

    Science.gov (United States)

    Nakanishi, Taiki; Matsunaga, Maya; Kobayashi, Atsuki; Nakazato, Kazuo; Niitsu, Kiichi

    2018-03-01

    A 40-GHz fully integrated CMOS-based circuit for circulating tumor cells (CTC) analysis, consisting of an on-chip vector network analyzer (VNA) and a highly sensitive coplanar-line-based detection area is presented in this paper. In this work, we introduce a fully integrated architecture that eliminates unwanted parasitic effects. The proposed analyzer was designed using 65 nm CMOS technology, and SPICE and MWS simulations were used to validate its operation. The simulation confirmed that the proposed circuit can measure S-parameter shifts resulting from the addition of various types of tumor cells to the detection area, the data of which are provided in a previous study: the |S 21| values for HepG2, A549, and HEC-1-A cells are -0.683, -0.580, and -0.623 dB, respectively. Additionally, the measurement demonstrated an S-parameters reduction of -25.7% when a silicone resin was put on the circuit. Hence, the proposed system is expected to contribute to cancer diagnosis.

  2. Momentum integral network method for thermal-hydraulic transient analysis

    International Nuclear Information System (INIS)

    Van Tuyle, G.J.

    1983-01-01

    A new momentum integral network method has been developed, and tested in the MINET computer code. The method was developed in order to facilitate the transient analysis of complex fluid flow and heat transfer networks, such as those found in the balance of plant of power generating facilities. The method employed in the MINET code is a major extension of a momentum integral method reported by Meyer. Meyer integrated the momentum equation over several linked nodes, called a segment, and used a segment average pressure, evaluated from the pressures at both ends. Nodal mass and energy conservation determined nodal flows and enthalpies, accounting for fluid compression and thermal expansion

  3. Integration by cell algorithm for Slater integrals in a spline basis

    International Nuclear Information System (INIS)

    Qiu, Y.; Fischer, C.F.

    1999-01-01

    An algorithm for evaluating Slater integrals in a B-spline basis is introduced. Based on the piecewise property of the B-splines, the algorithm divides the two-dimensional (r 1 , r 2 ) region into a number of rectangular cells according to the chosen grid and implements the two-dimensional integration over each individual cell using Gaussian quadrature. Over the off-diagonal cells, the integrands are separable so that each two-dimensional cell-integral is reduced to a product of two one-dimensional integrals. Furthermore, the scaling invariance of the B-splines in the logarithmic region of the chosen grid is fully exploited such that only some of the cell integrations need to be implemented. The values of given Slater integrals are obtained by assembling the cell integrals. This algorithm significantly improves the efficiency and accuracy of the traditional method that relies on the solution of differential equations and renders the B-spline method more effective when applied to multi-electron atomic systems

  4. Iconic memory and parietofrontal network: fMRI study using temporal integration.

    Science.gov (United States)

    Saneyoshi, Ayako; Niimi, Ryosuke; Suetsugu, Tomoko; Kaminaga, Tatsuro; Yokosawa, Kazuhiko

    2011-08-03

    We investigated the neural basis of iconic memory using functional magnetic resonance imaging. The parietofrontal network of selective attention is reportedly relevant to readout from iconic memory. We adopted a temporal integration task that requires iconic memory but not selective attention. The results showed that the task activated the parietofrontal network, confirming that the network is involved in readout from iconic memory. We further tested a condition in which temporal integration was performed by visual short-term memory but not by iconic memory. However, no brain region revealed higher activation for temporal integration by iconic memory than for temporal integration by visual short-term memory. This result suggested that there is no localized brain region specialized for iconic memory per se.

  5. Human Systems Integration Assessment of Network Centric Command and Control

    National Research Council Canada - National Science Library

    Quashnock, Dee; Kelly, Richard T; Dunaway, John; Smillie, Robert J

    2004-01-01

    .... FORCEnet is the operational construct and architectural framework for Naval Network Centric Warfare in the information age that integrates warriors, sensors, networks, command and control, platforms...

  6. Unveiling network-based functional features through integration of gene expression into protein networks.

    Science.gov (United States)

    Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

    2018-06-01

    Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Diversity and plasticity of Th cell types predicted from regulatory network modelling.

    Directory of Open Access Journals (Sweden)

    Aurélien Naldi

    Full Text Available Alternative cell differentiation pathways are believed to arise from the concerted action of signalling pathways and transcriptional regulatory networks. However, the prediction of mammalian cell differentiation from the knowledge of the presence of specific signals and transcriptional factors is still a daunting challenge. In this respect, the vertebrate hematopoietic system, with its many branching differentiation pathways and cell types, is a compelling case study. In this paper, we propose an integrated, comprehensive model of the regulatory network and signalling pathways controlling Th cell differentiation. As most available data are qualitative, we rely on a logical formalism to perform extensive dynamical analyses. To cope with the size and complexity of the resulting network, we use an original model reduction approach together with a stable state identification algorithm. To assess the effects of heterogeneous environments on Th cell differentiation, we have performed a systematic series of simulations considering various prototypic environments. Consequently, we have identified stable states corresponding to canonical Th1, Th2, Th17 and Treg subtypes, but these were found to coexist with other transient hybrid cell types that co-express combinations of Th1, Th2, Treg and Th17 markers in an environment-dependent fashion. In the process, our logical analysis highlights the nature of these cell types and their relationships with canonical Th subtypes. Finally, our logical model can be used to explore novel differentiation pathways in silico.

  8. Observation and inverse problems in coupled cell networks

    International Nuclear Information System (INIS)

    Joly, Romain

    2012-01-01

    A coupled cell network is a model for many situations such as food webs in ecosystems, cellular metabolism and economic networks. It consists in a directed graph G, each node (or cell) representing an agent of the network and each directed arrow representing which agent acts on which. It yields a system of differential equations .x(t)=f(x(t)), where the component i of f depends only on the cells x j (t) for which the arrow j → i exists in G. In this paper, we investigate the observation problems in coupled cell networks: can one deduce the behaviour of the whole network (oscillations, stabilization, etc) by observing only one of the cells? We show that the natural observation properties hold for almost all the interactions f

  9. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  10. CellNet: Network Biology Applied to Stem Cell Engineering

    Science.gov (United States)

    Cahan, Patrick; Li, Hu; Morris, Samantha A.; da Rocha, Edroaldo Lummertz; Daley, George Q.; Collins, James J.

    2014-01-01

    SUMMARY Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population, and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. PMID:25126793

  11. CellNet: network biology applied to stem cell engineering.

    Science.gov (United States)

    Cahan, Patrick; Li, Hu; Morris, Samantha A; Lummertz da Rocha, Edroaldo; Daley, George Q; Collins, James J

    2014-08-14

    Somatic cell reprogramming, directed differentiation of pluripotent stem cells, and direct conversions between differentiated cell lineages represent powerful approaches to engineer cells for research and regenerative medicine. We have developed CellNet, a network biology platform that more accurately assesses the fidelity of cellular engineering than existing methodologies and generates hypotheses for improving cell derivations. Analyzing expression data from 56 published reports, we found that cells derived via directed differentiation more closely resemble their in vivo counterparts than products of direct conversion, as reflected by the establishment of target cell-type gene regulatory networks (GRNs). Furthermore, we discovered that directly converted cells fail to adequately silence expression programs of the starting population and that the establishment of unintended GRNs is common to virtually every cellular engineering paradigm. CellNet provides a platform for quantifying how closely engineered cell populations resemble their target cell type and a rational strategy to guide enhanced cellular engineering. Copyright © 2014 Elsevier Inc. All rights reserved.

  12. A joint classification method to integrate scientific and social networks

    NARCIS (Netherlands)

    Neshati, Mahmood; Asgari, Ehsaneddin; Hiemstra, Djoerd; Beigy, Hamid

    In this paper, we address the problem of scientific-social network integration to find a matching relationship between members of these networks. Utilizing several name similarity patterns and contextual properties of these networks, we design a focused crawler to find high probable matching pairs,

  13. Explicit integration of extremely stiff reaction networks: partial equilibrium methods

    International Nuclear Information System (INIS)

    Guidry, M W; Hix, W R; Billings, J J

    2013-01-01

    In two preceding papers (Guidry et al 2013 Comput. Sci. Disc. 6 015001 and Guidry and Harris 2013 Comput. Sci. Disc. 6 015002), we have shown that when reaction networks are well removed from equilibrium, explicit asymptotic and quasi-steady-state approximations can give algebraically stabilized integration schemes that rival standard implicit methods in accuracy and speed for extremely stiff systems. However, we also showed that these explicit methods remain accurate but are no longer competitive in speed as the network approaches equilibrium. In this paper, we analyze this failure and show that it is associated with the presence of fast equilibration timescales that neither asymptotic nor quasi-steady-state approximations are able to remove efficiently from the numerical integration. Based on this understanding, we develop a partial equilibrium method to deal effectively with the approach to equilibrium and show that explicit asymptotic methods, combined with the new partial equilibrium methods, give an integration scheme that can plausibly deal with the stiffest networks, even in the approach to equilibrium, with accuracy and speed competitive with that of implicit methods. Thus we demonstrate that such explicit methods may offer alternatives to implicit integration of even extremely stiff systems and that these methods may permit integration of much larger networks than have been possible before in a number of fields. (paper)

  14. Integrated healthcare networks' performance: a growth curve modeling approach.

    Science.gov (United States)

    Wan, Thomas T H; Wang, Bill B L

    2003-05-01

    This study examines the effects of integration on the performance ratings of the top 100 integrated healthcare networks (IHNs) in the United States. A strategic-contingency theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. To create a database for the panel study, the top 100 IHNs selected by the SMG Marketing Group in 1998 were followed up in 1999 and 2000. The data were merged with the Dorenfest data on information system integration. A growth curve model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' performance in 1998 and their subsequent rankings in the consecutive years were analyzed. IHNs' initial performance scores were positively influenced by network size, number of affiliated physicians and profit margin, and were negatively associated with average length of stay and technical efficiency. The continuing high performance, judged by maintaining higher performance scores, tended to be enhanced by the use of more managerial or executive decision-support systems. Future studies should include time-varying operational indicators to serve as predictors of network performance.

  15. A Critical Agency Network Model for Building an Integrated Outreach Program

    Science.gov (United States)

    Kiyama, Judy Marquez; Lee, Jenny J.; Rhoades, Gary

    2012-01-01

    This study considers a distinct case of a college outreach program that integrates student affairs staff, academic administrators, and faculty across campus. The authors find that social networks and critical agency help to understand the integration of these various professionals and offer a critical agency network model of enacting change.…

  16. Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

    Directory of Open Access Journals (Sweden)

    Xianjun Shen

    Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

  17. Structure-function relationships during segregated and integrated network states of human brain functional connectivity.

    Science.gov (United States)

    Fukushima, Makoto; Betzel, Richard F; He, Ye; van den Heuvel, Martijn P; Zuo, Xi-Nian; Sporns, Olaf

    2018-04-01

    Structural white matter connections are thought to facilitate integration of neural information across functionally segregated systems. Recent studies have demonstrated that changes in the balance between segregation and integration in brain networks can be tracked by time-resolved functional connectivity derived from resting-state functional magnetic resonance imaging (rs-fMRI) data and that fluctuations between segregated and integrated network states are related to human behavior. However, how these network states relate to structural connectivity is largely unknown. To obtain a better understanding of structural substrates for these network states, we investigated how the relationship between structural connectivity, derived from diffusion tractography, and functional connectivity, as measured by rs-fMRI, changes with fluctuations between segregated and integrated states in the human brain. We found that the similarity of edge weights between structural and functional connectivity was greater in the integrated state, especially at edges connecting the default mode and the dorsal attention networks. We also demonstrated that the similarity of network partitions, evaluated between structural and functional connectivity, increased and the density of direct structural connections within modules in functional networks was elevated during the integrated state. These results suggest that, when functional connectivity exhibited an integrated network topology, structural connectivity and functional connectivity were more closely linked to each other and direct structural connections mediated a larger proportion of neural communication within functional modules. Our findings point out the possibility of significant contributions of structural connections to integrative neural processes underlying human behavior.

  18. An Integrated Cell Purification and Genomics Strategy Reveals Multiple Regulators of Pancreas Development

    Science.gov (United States)

    Benitez, Cecil M.; Qu, Kun; Sugiyama, Takuya; Pauerstein, Philip T.; Liu, Yinghua; Tsai, Jennifer; Gu, Xueying; Ghodasara, Amar; Arda, H. Efsun; Zhang, Jiajing; Dekker, Joseph D.; Tucker, Haley O.; Chang, Howard Y.; Kim, Seung K.

    2014-01-01

    The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus. PMID:25330008

  19. An integrated cell purification and genomics strategy reveals multiple regulators of pancreas development.

    Directory of Open Access Journals (Sweden)

    Cecil M Benitez

    2014-10-01

    Full Text Available The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus.

  20. The integrated disease network.

    Science.gov (United States)

    Sun, Kai; Buchan, Natalie; Larminie, Chris; Pržulj, Nataša

    2014-11-01

    The growing body of transcriptomic, proteomic, metabolomic and genomic data generated from disease states provides a great opportunity to improve our current understanding of the molecular mechanisms driving diseases and shared between diseases. The use of both clinical and molecular phenotypes will lead to better disease understanding and classification. In this study, we set out to gain novel insights into diseases and their relationships by utilising knowledge gained from system-level molecular data. We integrated different types of biological data including genome-wide association studies data, disease-chemical associations, biological pathways and Gene Ontology annotations into an Integrated Disease Network (IDN), a heterogeneous network where nodes are bio-entities and edges between nodes represent their associations. We also introduced a novel disease similarity measure to infer disease-disease associations from the IDN. Our predicted associations were systemically evaluated against the Medical Subject Heading classification and a statistical measure of disease co-occurrence in PubMed. The strong correlation between our predictions and co-occurrence associations indicated the ability of our approach to recover known disease associations. Furthermore, we presented a case study of Crohn's disease. We demonstrated that our approach not only identified well-established connections between Crohn's disease and other diseases, but also revealed new, interesting connections consistent with emerging literature. Our approach also enabled ready access to the knowledge supporting these new connections, making this a powerful approach for exploring connections between diseases.

  1. A Temporal-Causal Modelling Approach to Integrated Contagion and Network Change in Social Networks

    NARCIS (Netherlands)

    Blankendaal, Romy; Parinussa, Sarah; Treur, Jan

    2016-01-01

    This paper introduces an integrated temporal-causal model for dynamics in social networks addressing the contagion principle by which states are affected mutually, and both the homophily principle and the more-becomes-more principle by which connections are adapted over time. The integrated model

  2. Capillary network formation from dispersed endothelial cells: Influence of cell traction, cell adhesion, and extracellular matrix rigidity

    Science.gov (United States)

    Ramos, João R. D.; Travasso, Rui; Carvalho, João

    2018-01-01

    The formation of a functional vascular network depends on biological, chemical, and physical processes being extremely well coordinated. Among them, the mechanical properties of the extracellular matrix and cell adhesion are fundamental to achieve a functional network of endothelial cells, able to fully cover a required domain. By the use of a Cellular Potts Model and Finite Element Method it is shown that there exists a range of values of endothelial traction forces, cell-cell adhesion, and matrix rigidities where the network can spontaneously be formed, and its properties are characterized. We obtain the analytical relation that the minimum traction force required for cell network formation must obey. This minimum value for the traction force is approximately independent on the considered cell number and cell-cell adhesion. We quantify how these two parameters influence the morphology of the resulting networks (size and number of meshes).

  3. Is functional integration of resting state brain networks an unspecific biomarker for working memory performance?

    Science.gov (United States)

    Alavash, Mohsen; Doebler, Philipp; Holling, Heinz; Thiel, Christiane M; Gießing, Carsten

    2015-03-01

    Is there one optimal topology of functional brain networks at rest from which our cognitive performance would profit? Previous studies suggest that functional integration of resting state brain networks is an important biomarker for cognitive performance. However, it is still unknown whether higher network integration is an unspecific predictor for good cognitive performance or, alternatively, whether specific network organization during rest predicts only specific cognitive abilities. Here, we investigated the relationship between network integration at rest and cognitive performance using two tasks that measured different aspects of working memory; one task assessed visual-spatial and the other numerical working memory. Network clustering, modularity and efficiency were computed to capture network integration on different levels of network organization, and to statistically compare their correlations with the performance in each working memory test. The results revealed that each working memory aspect profits from a different resting state topology, and the tests showed significantly different correlations with each of the measures of network integration. While higher global network integration and modularity predicted significantly better performance in visual-spatial working memory, both measures showed no significant correlation with numerical working memory performance. In contrast, numerical working memory was superior in subjects with highly clustered brain networks, predominantly in the intraparietal sulcus, a core brain region of the working memory network. Our findings suggest that a specific balance between local and global functional integration of resting state brain networks facilitates special aspects of cognitive performance. In the context of working memory, while visual-spatial performance is facilitated by globally integrated functional resting state brain networks, numerical working memory profits from increased capacities for local processing

  4. Electric Vehicle Integration into Modern Power Networks

    DEFF Research Database (Denmark)

    software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models......Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

  5. Electric Vehicle Integration into Modern Power Networks

    DEFF Research Database (Denmark)

    Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

  6. T-cell movement on the reticular network.

    Science.gov (United States)

    Donovan, Graham M; Lythe, Grant

    2012-02-21

    The idea that the apparently random motion of T cells in lymph nodes is a result of movement on a reticular network (RN) has received support from dynamic imaging experiments and theoretical studies. We present a mathematical representation of the RN consisting of edges connecting vertices that are randomly distributed in three-dimensional space, and models of lymphocyte movement on such networks including constant speed motion along edges and Brownian motion, not in three-dimensions, but only along edges. The simplest model, in which a cell moves with a constant speed along edges, is consistent with mean-squared displacement proportional to time over intervals long enough to include several changes of direction. A non-random distribution of turning angles is one consequence of motion on a preformed network. Confining cell movement to a network does not, in itself, increase the frequency of cell-cell encounters. Copyright © 2011 Elsevier Ltd. All rights reserved.

  7. Integrated resource management for Hybrid Optical Wireless (HOW) networks

    DEFF Research Database (Denmark)

    Yan, Ying; Yu, Hao; Wessing, Henrik

    2009-01-01

    Efficient utilization of available bandwidth over hybrid optical wireless networks is a critical issue, especially for multimedia applications with high data rates and stringent Quality of Service (QoS) requirements. In this paper, we propose an integrated resource management including an enhanced...... resource sharing scheme and an integrated admission control scheme for the hybrid optical wireless networks. It provides QoS guarantees for connections through both optical and wireless domain. Simulation results show that our proposed scheme improves QoS performances in terms of high throughput and low...

  8. Design mobile satellite system architecture as an integral part of the cellular access digital network

    Science.gov (United States)

    Chien, E. S. K.; Marinho, J. A.; Russell, J. E., Sr.

    1988-01-01

    The Cellular Access Digital Network (CADN) is the access vehicle through which cellular technology is brought into the mainstream of the evolving integrated telecommunications network. Beyond the integrated end-to-end digital access and per call network services provisioning of the Integrated Services Digital Network (ISDN), the CADN engenders the added capability of mobility freedom via wireless access. One key element of the CADN network architecture is the standard user to network interface that is independent of RF transmission technology. Since the Mobile Satellite System (MSS) is envisioned to not only complement but also enhance the capabilities of the terrestrial cellular telecommunications network, compatibility and interoperability between terrestrial cellular and mobile satellite systems are vitally important to provide an integrated moving telecommunications network of the future. From a network standpoint, there exist very strong commonalities between the terrestrial cellular system and the mobile satellite system. Therefore, the MSS architecture should be designed as an integral part of the CADN. This paper describes the concept of the CADN, the functional architecture of the MSS, and the user-network interface signaling protocols.

  9. Integration of Satellite and Terrestrial Networks at JPL

    Science.gov (United States)

    Pinck, D. S.

    1995-01-01

    This presentation focuses on the activities at JPL on the integration of satellite and terrestrial networks for mobile and personal communications. Activities fall into two categories: 1)advanced systems work, and 2)laboratory and field experimentation. Results of a workshop held at JPL on PCS integration and interoperability will be presented. Experiments will be described.

  10. Towards integrated crisis support of regional emergency networks.

    Science.gov (United States)

    Caro, D H

    1999-01-01

    Emergency and crisis management pose multidimensional information systems challenges for communities across North America. In the quest to reduce mortality and morbidity risks and to increase the level of crisis preparedness, regional emergency management networks have evolved. Integrated Crisis Support Systems (ICSS) are enabling information technologies that assist emergency managers by enhancing the ability to strategically manage and control these regional emergency networks efficiently and effectively. This article underscores the ICCS development, control and leadership issues and their promising implications for regional emergency management networks.

  11. Integrated Network Analysis and Effective Tools in Plant Systems Biology

    Directory of Open Access Journals (Sweden)

    Atsushi eFukushima

    2014-11-01

    Full Text Available One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1 network visualization tools, (2 pathway analyses, (3 genome-scale metabolic reconstruction, and (4 the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.

  12. Fabrication of microstamps and patterned cell network

    International Nuclear Information System (INIS)

    Seong, Nak Seon; Pak, James Jung Ho; Choi, Ju Hee; Ahn, Dong June; Hwang, Seong Min; Lee, Kyung J.

    2002-01-01

    Elastomeric stamps with micrometer-sized grids are fabricated for building biological cell networks by design. Polymerized polydimethyl-siloxane (PDMS) stamps are cast in a variety of different molds prepared by micro-electro mechanical systems (MEMS) technology. Micro square-grid patterns of 3-aminopropyl triethoxy silane (APS) are successfully imprinted on glass plates, and patterned networks of cardiac cells are obtained as designed. The resulting cellular networks clearly demonstrate that cell attachment and growth are greatly favored on APS-treated thin tracks. Here, we report the technical details related to the fabrication of microstamps, to the stamping procedure, and to the culture method. The potential applications of patterned cellular networks are also discussed

  13. Software-defined networking control plane for seamless integration of multiple silicon photonic switches in Datacom networks.

    Science.gov (United States)

    Shen, Yiwen; Hattink, Maarten H N; Samadi, Payman; Cheng, Qixiang; Hu, Ziyiz; Gazman, Alexander; Bergman, Keren

    2018-04-16

    Silicon photonics based switches offer an effective option for the delivery of dynamic bandwidth for future large-scale Datacom systems while maintaining scalable energy efficiency. The integration of a silicon photonics-based optical switching fabric within electronic Datacom architectures requires novel network topologies and arbitration strategies to effectively manage the active elements in the network. We present a scalable software-defined networking control plane to integrate silicon photonic based switches with conventional Ethernet or InfiniBand networks. Our software-defined control plane manages both electronic packet switches and multiple silicon photonic switches for simultaneous packet and circuit switching. We built an experimental Dragonfly network testbed with 16 electronic packet switches and 2 silicon photonic switches to evaluate our control plane. Observed latencies occupied by each step of the switching procedure demonstrate a total of 344 µs control plane latency for data-center and high performance computing platforms.

  14. Perspectives and limitations of QKD integration in metropolitan area networks.

    Science.gov (United States)

    Aleksic, Slavisa; Hipp, Florian; Winkler, Dominic; Poppe, Andreas; Schrenk, Bernhard; Franzl, Gerald

    2015-04-20

    Quantum key distribution (QKD) systems have already reached a reasonable level of maturity. However, a smooth integration and a wide adoption of commercial QKD systems in metropolitan area networks has still remained challenging because of technical and economical obstacles. Mainly the need for dedicated fibers and the strong dependence of the secret key rate on both loss budget and background noise in the quantum channel hinder a practical, flexible and robust implementation of QKD in current and next-generation optical metro networks. In this paper, we discuss these obstacles and present approaches to share existing fiber infrastructures among quantum and classical channels. Particularly, a proposal for a smooth integration of QKD in optical metro networks, which implies removing spurious background photons caused by optical transmitters, amplifiers and nonlinear effects in fibers, is presented and discussed. We determine and characterize impairments on quantum channels caused by many classical telecom channels at practically used power levels coexisting within the same fiber. Extensive experimental results are presented and indicate that a practical integration of QKD in conventional optical metro networks is possible.

  15. Designing optimal bioethanol networks with purification for integrated biorefineries

    International Nuclear Information System (INIS)

    Shenoy, Akshay U.; Shenoy, Uday V.

    2014-01-01

    Highlights: • An analytical method is devised for bioethanol network integration with purification. • Minimum fresh bioethanol flow and pinch are found by the Unified Targeting Algorithm. • Optimal bioethanol networks are then synthesized by the Nearest Neighbors Algorithm. • Continuous targets and networks are developed over the purifier inlet flowrate range. • Case study of a biorefinery producing bioethanol from wheat shows large savings. - Abstract: Bioethanol networks with purification for processing pathways in integrated biorefineries are targeted and designed in this work by an analytical approach not requiring graphical constructions. The approach is based on six fundamental equations involving eight variables: two balance equations for the stream flowrate and the bioethanol load over the total network system; one equation for the above-pinch bioethanol load being picked up by the minimum fresh resource and the purified stream; and three equations for the purification unit. A solution strategy is devised by specifying the two variables associated with the purifier inlet stream. Importantly, continuous targeting is then possible over the entire purifier inlet flowrate range on deriving elegant formulae for the remaining six variables. The Unified Targeting Algorithm (UTA) is utilized to establish the minimum fresh bioethanol resource flowrate and identify the pinch purity. The fresh bioethanol resource flowrate target is shown to decrease linearly with purifier inlet flowrate provided the pinch is held by the same point. The Nearest Neighbors Algorithm (NNA) is used to methodically synthesize optimal networks matching bioethanol demands and sources. A case study of a biorefinery producing bioethanol from wheat with arabinoxylan (AX) coproduction is presented. It illustrates the versatility of the approach in generating superior practical designs with up to nearly 94% savings for integrated bioethanol networks, both with and without process

  16. Social network extraction based on Web: 3. the integrated superficial method

    Science.gov (United States)

    Nasution, M. K. M.; Sitompul, O. S.; Noah, S. A.

    2018-03-01

    The Web as a source of information has become part of the social behavior information. Although, by involving only the limitation of information disclosed by search engines in the form of: hit counts, snippets, and URL addresses of web pages, the integrated extraction method produces a social network not only trusted but enriched. Unintegrated extraction methods may produce social networks without explanation, resulting in poor supplemental information, or resulting in a social network of durmise laden, consequently unrepresentative social structures. The integrated superficial method in addition to generating the core social network, also generates an expanded network so as to reach the scope of relation clues, or number of edges computationally almost similar to n(n - 1)/2 for n social actors.

  17. In Vivo Transplantation of Enteric Neural Crest Cells into Mouse Gut; Engraftment, Functional Integration and Long-Term Safety.

    Directory of Open Access Journals (Sweden)

    Julie E Cooper

    Full Text Available Enteric neuropathies are severe gastrointestinal disorders with unsatisfactory outcomes. We aimed to investigate the potential of enteric neural stem cell therapy approaches for such disorders by transplanting mouse enteric neural crest cells (ENCCs into ganglionic and aganglionic mouse gut in vivo and analysing functional integration and long-term safety.Neurospheres generated from yellow fluorescent protein (YFP expressing ENCCs selected from postnatal Wnt1-cre;R26R-YFP/YFP murine gut were transplanted into ganglionic hindgut of wild-type littermates or aganglionic hindgut of Ednrbtm1Ywa mice (lacking functional endothelin receptor type-B. Intestines were then assessed for ENCC integration and differentiation using immunohistochemistry, cell function using calcium imaging, and long-term safety using PCR to detect off-target YFP expression.YFP+ ENCCs engrafted, proliferated and differentiated into enteric neurons and glia within recipient ganglionic gut. Transplanted cells and their projections spread along the endogenous myenteric plexus to form branching networks. Electrical point stimulation of endogenous nerve fibres resulted in calcium transients (F/F0 = 1.16 ± 0.01;43 cells, n = 6 in YFP+ transplanted ENCCs (abolished with TTX. Long-term follow-up (24 months showed transplanted ENCCs did not give rise to tumours or spread to other organs (PCR negative in extraintestinal sites. In aganglionic gut ENCCs similarly spread and differentiated to form neuronal and glial networks with projections closely associated with endogenous neural networks of the transition zone.Transplanted ENCCs successfully engrafted into recipient ganglionic and aganglionic gut showing appropriate spread, localisation and, importantly, functional integration without any long-term safety issues. This study provides key support for the development and use of enteric neural stem cell therapies.

  18. Sensorimotor Functional and Structural Networks after Intracerebral Stem Cell Grafts in the Ischemic Mouse Brain.

    Science.gov (United States)

    Green, Claudia; Minassian, Anuka; Vogel, Stefanie; Diedenhofen, Michael; Beyrau, Andreas; Wiedermann, Dirk; Hoehn, Mathias

    2018-02-14

    Past investigations on stem cell-mediated recovery after stroke have limited their focus on the extent and morphological development of the ischemic lesion itself over time or on the integration capacity of the stem cell graft ex vivo However, an assessment of the long-term functional and structural improvement in vivo is essential to reliably quantify the regenerative capacity of cell implantation after stroke. We induced ischemic stroke in nude mice and implanted human neural stem cells (H9 derived) into the ipsilateral cortex in the acute phase. Functional and structural connectivity changes of the sensorimotor network were noninvasively monitored using magnetic resonance imaging for 3 months after stem cell implantation. A sharp decrease of the functional sensorimotor network extended even to the contralateral hemisphere, persisting for the whole 12 weeks of observation. In mice with stem cell implantation, functional networks were stabilized early on, pointing to a paracrine effect as an early supportive mechanism of the graft. This stabilization required the persistent vitality of the stem cells, monitored by bioluminescence imaging. Thus, we also observed deterioration of the early network stabilization upon vitality loss of the graft after a few weeks. Structural connectivity analysis showed fiber-density increases between the cortex and white matter regions occurring predominantly on the ischemic hemisphere. These fiber-density changes were nearly the same for both study groups. This motivated us to hypothesize that the stem cells can influence, via early paracrine effect, the functional networks, while observed structural changes are mainly stimulated by the ischemic event. SIGNIFICANCE STATEMENT In recent years, research on strokes has made a shift away from a focus on immediate ischemic effects and towards an emphasis on the long-range effects of the lesion on the whole brain. Outcome improvements in stem cell therapies also require the understanding of

  19. Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

    International Nuclear Information System (INIS)

    Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

    2007-11-01

    The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results

  20. Networks as integrated in research methodologies in PER

    DEFF Research Database (Denmark)

    Bruun, Jesper

    2016-01-01

    of using networks to create insightful maps of learning discussions. To conclude, I argue that conceptual blending is a powerful framework for constructing "mixed methods" methodologies that may integrate diverse theories and other methodologies with network methodologies.......In recent years a number of researchers within the PER community have started using network analysis as a new methodology to extend our understanding of teaching and learning physics by viewing these as complex systems. In this paper, I give examples of social, cognitive, and action mapping...... networks and how they can be analyzed. In so doing I show how a network can be methodologically described as a set of relations between a set of entities, and how a network can be characterized and analyzed as a mathematical object. Then, as an illustrative example, I discuss a relatively new example...

  1. Evaluating airline energy efficiency: An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure

    International Nuclear Information System (INIS)

    Xu, Xin; Cui, Qiang

    2017-01-01

    This paper focuses on evaluating airline energy efficiency, which is firstly divided into four stages: Operations Stage, Fleet Maintenance Stage, Services Stage and Sales Stage. The new four-stage network structure of airline energy efficiency is a modification of existing models. A new approach, integrated with Network Epsilon-based Measure and Network Slacks-based Measure, is applied to assess the overall energy efficiency and divisional efficiency of 19 international airlines from 2008 to 2014. The influencing factors of airline energy efficiency are analyzed through the regression analysis. The results indicate the followings: 1. The integrated model can identify the benchmarking airlines in the overall system and stages. 2. Most airlines' energy efficiencies keep steady during the period, except for some sharply fluctuations. The efficiency decreases mainly centralized in the year 2008–2011, affected by the financial crisis in the USA. 3. The average age of fleet is positively correlated with the overall energy efficiency, and each divisional efficiency has different significant influencing factors. - Highlights: • An integrated approach with Network Epsilon-based Measure and Network Slacks-based Measure is developed. • 19 airlines' energy efficiencies are evaluated. • Garuda Indonesia has the highest overall energy efficiency.

  2. Microbial network for waste activated sludge cascade utilization in an integrated system of microbial electrolysis and anaerobic fermentation

    DEFF Research Database (Denmark)

    Liu, Wenzong; He, Zhangwei; Yang, Chunxue

    2016-01-01

    in an integrated system of microbial electrolysis cell (MEC) and anaerobic digestion (AD) for waste activated sludge (WAS). Microbial communities in integrated system would build a thorough energetic and metabolic interaction network regarding fermentation communities and electrode respiring communities...... to Firmicutes (Acetoanaerobium, Acetobacterium, and Fusibacter) showed synergistic relationship with exoelectrogensin the degradation of complex organic matter or recycling of MEC products (H2). High protein and polysaccharide but low fatty acid content led to the dominance of Proteiniclasticum...... biofilm. The overall performance of WAS cascade utilization was substantially related to the microbial community structures, which in turn depended on the initial pretreatment to enhance WAS fermentation. It is worth noting that species in AD and MEC communities are able to build complex networks...

  3. Transparent Electrodes Based on Silver Nanowire Networks: From Physical Considerations towards Device Integration.

    Science.gov (United States)

    Bellet, Daniel; Lagrange, Mélanie; Sannicolo, Thomas; Aghazadehchors, Sara; Nguyen, Viet Huong; Langley, Daniel P; Muñoz-Rojas, David; Jiménez, Carmen; Bréchet, Yves; Nguyen, Ngoc Duy

    2017-05-24

    The past few years have seen a considerable amount of research devoted to nanostructured transparent conducting materials (TCM), which play a pivotal role in many modern devices such as solar cells, flexible light-emitting devices, touch screens, electromagnetic devices, and flexible transparent thin film heaters. Currently, the most commonly used TCM for such applications (ITO: Indium Tin oxide) suffers from two major drawbacks: brittleness and indium scarcity. Among emerging transparent electrodes, silver nanowire (AgNW) networks appear to be a promising substitute to ITO since such electrically percolating networks exhibit excellent properties with sheet resistance lower than 10 Ω/sq and optical transparency of 90%, fulfilling the requirements of most applications. In addition, AgNW networks also exhibit very good mechanical flexibility. The fabrication of these electrodes involves low-temperature processing steps and scalable methods, thus making them appropriate for future use as low-cost transparent electrodes in flexible electronic devices. This contribution aims to briefly present the main properties of AgNW based transparent electrodes as well as some considerations relating to their efficient integration in devices. The influence of network density, nanowire sizes, and post treatments on the properties of AgNW networks will also be evaluated. In addition to a general overview of AgNW networks, we focus on two important aspects: (i) network instabilities as well as an efficient Atomic Layer Deposition (ALD) coating which clearly enhances AgNW network stability and (ii) modelling to better understand the physical properties of these networks.

  4. CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

    Science.gov (United States)

    Heberle, Henry; Carazzolle, Marcelo Falsarella; Telles, Guilherme P; Meirelles, Gabriela Vaz; Minghim, Rosane

    2017-09-13

    The advent of "omics" science has brought new perspectives in contemporary biology through the high-throughput analyses of molecular interactions, providing new clues in protein/gene function and in the organization of biological pathways. Biomolecular interaction networks, or graphs, are simple abstract representations where the components of a cell (e.g. proteins, metabolites etc.) are represented by nodes and their interactions are represented by edges. An appropriate visualization of data is crucial for understanding such networks, since pathways are related to functions that occur in specific regions of the cell. The force-directed layout is an important and widely used technique to draw networks according to their topologies. Placing the networks into cellular compartments helps to quickly identify where network elements are located and, more specifically, concentrated. Currently, only a few tools provide the capability of visually organizing networks by cellular compartments. Most of them cannot handle large and dense networks. Even for small networks with hundreds of nodes the available tools are not able to reposition the network while the user is interacting, limiting the visual exploration capability. Here we propose CellNetVis, a web tool to easily display biological networks in a cell diagram employing a constrained force-directed layout algorithm. The tool is freely available and open-source. It was originally designed for networks generated by the Integrated Interactome System and can be used with networks from others databases, like InnateDB. CellNetVis has demonstrated to be applicable for dynamic investigation of complex networks over a consistent representation of a cell on the Web, with capabilities not matched elsewhere.

  5. From network structure to network reorganization: implications for adult neurogenesis

    International Nuclear Information System (INIS)

    Schneider-Mizell, Casey M; Zochowski, Michal R; Sander, Leonard M; Parent, Jack M; Ben-Jacob, Eshel

    2010-01-01

    Networks can be dynamical systems that undergo functional and structural reorganization. One example of such a process is adult hippocampal neurogenesis, in which new cells are continuously born and incorporate into the existing network of the dentate gyrus region of the hippocampus. Many of these introduced cells mature and become indistinguishable from established neurons, joining the existing network. Activity in the network environment is known to promote birth, survival and incorporation of new cells. However, after epileptogenic injury, changes to the connectivity structure around the neurogenic niche are known to correlate with aberrant neurogenesis. The possible role of network-level changes in the development of epilepsy is not well understood. In this paper, we use a computational model to investigate how the structural and functional outcomes of network reorganization, driven by addition of new cells during neurogenesis, depend on the original network structure. We find that there is a stable network topology that allows the network to incorporate new neurons in a manner that enhances activity of the persistently active region, but maintains global network properties. In networks having other connectivity structures, new cells can greatly alter the distribution of firing activity and destroy the initial activity patterns. We thus find that new cells are able to provide focused enhancement of network only for small-world networks with sufficient inhibition. Network-level deviations from this topology, such as those caused by epileptogenic injury, can set the network down a path that develops toward pathological dynamics and aberrant structural integration of new cells

  6. Integration of Self-Assembled Microvascular Networks with Microfabricated PEG-Based Hydrogels.

    Science.gov (United States)

    Cuchiara, Michael P; Gould, Daniel J; McHale, Melissa K; Dickinson, Mary E; West, Jennifer L

    2012-11-07

    Despite tremendous efforts, tissue engineered constructs are restricted to thin, simple tissues sustained only by diffusion. The most significant barrier in tissue engineering is insufficient vascularization to deliver nutrients and metabolites during development in vitro and to facilitate rapid vascular integration in vivo. Tissue engineered constructs can be greatly improved by developing perfusable microvascular networks in vitro in order to provide transport that mimics native vascular organization and function. Here a microfluidic hydrogel is integrated with a self-assembling pro-vasculogenic co-culture in a strategy to perfuse microvascular networks in vitro. This approach allows for control over microvascular network self-assembly and employs an anastomotic interface for integration of self-assembled micro-vascular networks with fabricated microchannels. As a result, transport within the system shifts from simple diffusion to vessel supported convective transport and extra-vessel diffusion, thus improving overall mass transport properties. This work impacts the development of perfusable prevascularized tissues in vitro and ultimately tissue engineering applications in vivo.

  7. Optimizing Groundwater Monitoring Networks Using Integrated Statistical and Geostatistical Approaches

    Directory of Open Access Journals (Sweden)

    Jay Krishna Thakur

    2015-08-01

    Full Text Available The aim of this work is to investigate new approaches using methods based on statistics and geo-statistics for spatio-temporal optimization of groundwater monitoring networks. The formulated and integrated methods were tested with the groundwater quality data set of Bitterfeld/Wolfen, Germany. Spatially, the monitoring network was optimized using geo-statistical methods. Temporal optimization of the monitoring network was carried out using Sen’s method (1968. For geostatistical network optimization, a geostatistical spatio-temporal algorithm was used to identify redundant wells in 2- and 2.5-D Quaternary and Tertiary aquifers. Influences of interpolation block width, dimension, contaminant association, groundwater flow direction and aquifer homogeneity on statistical and geostatistical methods for monitoring network optimization were analysed. The integrated approach shows 37% and 28% redundancies in the monitoring network in Quaternary aquifer and Tertiary aquifer respectively. The geostatistical method also recommends 41 and 22 new monitoring wells in the Quaternary and Tertiary aquifers respectively. In temporal optimization, an overall optimized sampling interval was recommended in terms of lower quartile (238 days, median quartile (317 days and upper quartile (401 days in the research area of Bitterfeld/Wolfen. Demonstrated methods for improving groundwater monitoring network can be used in real monitoring network optimization with due consideration given to influencing factors.

  8. Structural reliability calculation method based on the dual neural network and direct integration method.

    Science.gov (United States)

    Li, Haibin; He, Yun; Nie, Xiaobo

    2018-01-01

    Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

  9. Land Cover Change Detection using Neural Network and Grid Cells Techniques

    Science.gov (United States)

    Bagan, H.; Li, Z.; Tangud, T.; Yamagata, Y.

    2017-12-01

    In recent years, many advanced neural network methods have been applied in land cover classification, each of which has both strengths and limitations. In which, the self-organizing map (SOM) neural network method have been used to solve remote sensing data classification problems and have shown potential for efficient classification of remote sensing data. In SOM, both the distribution and the topology of features of the input layer are identified by using an unsupervised, competitive, neighborhood learning method. The high-dimensional data are then projected onto a low-dimensional map (competitive layer), usually as a two-dimensional map. The neurons (nodes) in the competitive layer are arranged by topological order in the input space. Spatio-temporal analyses of land cover change based on grid cells have demonstrated that gridded data are useful for obtaining spatial and temporal information about areas that are smaller than municipal scale and are uniform in size. Analysis based on grid cells has many advantages: grid cells all have the same size allowing for easy comparison; grids integrate easily with other scientific data; grids are stable over time and thus facilitate the modelling and analysis of very large multivariate spatial data sets. This study chose time-series MODIS and Landsat images as data sources, applied SOM neural network method to identify the land utilization in Inner Mongolia Autonomous Region of China. Then the results were integrated into grid cell to get the dynamic change maps. Land cover change using MODIS data in Inner Mongolia showed that urban area increased more than fivefold in recent 15 years, along with the growth of mining area. In terms of geographical distribution, the most obvious place of urban expansion is Ordos in southwest Inner Mongolia. The results using Landsat images from 1986 to 2014 in northeastern part of the Inner Mongolia show degradation in grassland from 1986 to 2014. Grid-cell-based spatial correlation

  10. The Segregation and Integration of Distinct Brain Networks and Their Relationship to Cognition.

    Science.gov (United States)

    Cohen, Jessica R; D'Esposito, Mark

    2016-11-30

    A critical feature of the human brain that gives rise to complex cognition is its ability to reconfigure its network structure dynamically and adaptively in response to the environment. Existing research probing task-related reconfiguration of brain network structure has concluded that, although there are many similarities in network structure during an intrinsic, resting state and during the performance of a variety of cognitive tasks, there are meaningful differences as well. In this study, we related intrinsic, resting state network organization to reconfigured network organization during the performance of two tasks: a sequence tapping task, which is thought to probe motor execution and likely engages a single brain network, and an n-back task, which is thought to probe working memory and likely requires coordination across multiple networks. We implemented graph theoretical analyses using functional connectivity data from fMRI scans to calculate whole-brain measures of network organization in healthy young adults. We focused on quantifying measures of network segregation (modularity, system segregation, local efficiency, number of provincial hub nodes) and measures of network integration (global efficiency, number of connector hub nodes). Using these measures, we found converging evidence that local, within-network communication is critical for motor execution, whereas integrative, between-network communication is critical for working memory. These results confirm that the human brain has the remarkable ability to reconfigure its large-scale organization dynamically in response to current cognitive demands and that interpreting reconfiguration in terms of network segregation and integration may shed light on the optimal network structures underlying successful cognition. The dynamic nature of the human brain gives rise to the wide range of behaviors and cognition of which humans are capable. We collected fMRI data from healthy young adults and measured large

  11. Fast mapping rapidly integrates information into existing memory networks.

    Science.gov (United States)

    Coutanche, Marc N; Thompson-Schill, Sharon L

    2014-12-01

    Successful learning involves integrating new material into existing memory networks. A learning procedure known as fast mapping (FM), thought to simulate the word-learning environment of children, has recently been linked to distinct neuroanatomical substrates in adults. This idea has suggested the (never-before tested) hypothesis that FM may promote rapid incorporation into cortical memory networks. We test this hypothesis here in 2 experiments. In our 1st experiment, we introduced 50 participants to 16 unfamiliar animals and names through FM or explicit encoding (EE) and tested participants on the training day, and again after sleep. Learning through EE produced strong declarative memories, without immediate lexical competition, as expected from slow-consolidation models. Learning through FM, however, led to almost immediate lexical competition, which continued to the next day. Additionally, the learned words began to prime related concepts on the day following FM (but not EE) training. In a 2nd experiment, we replicated the lexical integration results and determined that presenting an already-known item during learning was crucial for rapid integration through FM. The findings presented here indicate that learned items can be integrated into cortical memory networks at an accelerated rate through fast mapping. The retrieval of a related known concept, in order to infer the target of the FM question, is critical for this effect. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  12. Integrating Metal-Oxide-Decorated CNT Networks with a CMOS Readout in a Gas Sensor

    Directory of Open Access Journals (Sweden)

    Suhwan Kim

    2012-02-01

    Full Text Available We have implemented a tin-oxide-decorated carbon nanotube (CNT network gas sensor system on a single die. We have also demonstrated the deposition of metallic tin on the CNT network, its subsequent oxidation in air, and the improvement of the lifetime of the sensors. The fabricated array of CNT sensors contains 128 sensor cells for added redundancy and increased accuracy. The read-out integrated circuit (ROIC was combined with coarse and fine time-to-digital converters to extend its resolution in a power-efficient way. The ROIC is fabricated using a 0.35 µm CMOS process, and the whole sensor system consumes 30 mA at 5 V. The sensor system was successfully tested in the detection of ammonia gas at elevated temperatures.

  13. Large-scale modeling of condition-specific gene regulatory networks by information integration and inference.

    Science.gov (United States)

    Ellwanger, Daniel Christian; Leonhardt, Jörn Florian; Mewes, Hans-Werner

    2014-12-01

    Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE (http://mips.helmholtz-muenchen.de/cogere), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient η(2) (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  14. The EH network

    DEFF Research Database (Denmark)

    Santolini, E; Salcini, A E; Kay, B K

    1999-01-01

    . Moreover, a number of cellular ligands of the domain have been identified and demonstrated to define a complex network of protein-protein interactions in the eukaryotic cell. Interestingly, many of the EH-containing and EH-binding proteins display characteristics of endocytic "accessory" proteins......, suggesting that the principal function of the EH network is to regulate various steps in endocytosis. In addition, recent evidence suggests that the EH network might work as an "integrator" of signals controlling cellular pathways as diverse as endocytosis, nucleocytosolic export, and ultimately cell...

  15. Towards Integrated Marmara Strong Motion Network

    Science.gov (United States)

    Durukal, E.; Erdik, M.; Safak, E.; Ansal, A.; Ozel, O.; Alcik, H.; Mert, A.; Kafadar, N.; Korkmaz, A.; Kurtulus, A.

    2009-04-01

    Istanbul has a 65% chance of having a magnitude 7 or above earthquake within the next 30 years. As part of the preparations for the future earthquake, strong motion networks have been installed in and around Istanbul. The Marmara Strong Motion Network, operated by the Department of Earthquake Engineering of Kandilli Observatory and Earthquake Research Institute, encompasses permanent systems outlined below. It is envisaged that the networks will be run by a single entity responsible for technical management and maintanence, as well as for data management, archiving and dissemination through dedicated web-based interfaces. • Istanbul Earthquake Rapid Response and Early Warning System - IERREWS (one hundred 18-bit accelerometers for rapid response; ten 24-bit accelerometers for early warning) • IGDAŞ Gas Shutoff Network (100 accelerometers to be installed in 2010 and integrated with IERREWS) • Structural Monitoring Arrays - Fatih Sultan Mehmet Suspension Bridge (1200m-long suspension bridge across the Bosphorus, five 3-component accelerometers + GPS sensors) - Hagia Sophia Array (1500-year-old historical edifice, 9 accelerometers) - Süleymaniye Mosque Array (450-year-old historical edifice,9 accelerometers) - Fatih Mosque Array (237-year-old historical edifice, 9 accelerometers) - Kanyon Building Array (high-rise office building, 5 accelerometers) - Isbank Tower Array (high-rise office building, 5 accelerometers) - ENRON Array (power generation facility, 4 acelerometers) - Mihrimah Sultan Mosque Array (450-year-old historical edifice,9 accelerometers + tiltmeters, to be installed in 2009) - Sultanahmet Mosque Array, (390-year-old historical edifice, 9 accelerometers + tiltmeters, to be installed in 2009) • Special Arrays - Atakoy Vertical Array (four 3-component accelerometers at 25, 50, 75, and 150 m depths) - Marmara Tube Tunnel (1400 m long submerged tunnel, 128 ch. accelerometric data, 24 ch. strain data, to be installed in 2010) - Air-Force Academy

  16. Integrated network design and scheduling problems :

    Energy Technology Data Exchange (ETDEWEB)

    Nurre, Sarah G.; Carlson, Jeffrey J.

    2014-01-01

    We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

  17. Too Many Friends: Social Integration, Network Cohesion and Adolescent Depressive Symptoms

    Science.gov (United States)

    Falci, Christina; McNeely, Clea

    2009-01-01

    Using a nationally representative sample of adolescents, we examine associations among social integration (network size), network cohesion (alter-density), perceptions of social relationships (e.g., social support) and adolescent depressive symptoms. We find that adolescents with either too large or too small a network have higher levels of…

  18. Vertical integration and organizational networks in health care.

    Science.gov (United States)

    Robinson, J C; Casalino, L P

    1996-01-01

    This paper documents the growing linkages between primary care-centered medical groups and specialists and between physicians and hospitals under managed care. We evaluate the two alternative forms of organizational coordination: "vertical integration," based on unified ownership, and "virtual integration," based on contractual networks. Excess capacity and the need for investment capital are major short-term determinants of these vertical versus virtual integration decisions in health care. In the longer term, the principal determinants are economies of scale, risk-bearing ability, transaction costs, and the capacity for innovation in methods of managing care.

  19. Locally Integrated Energy Sectors supported by renewable network management within municipalities

    International Nuclear Information System (INIS)

    Kostevšek, Anja; Petek, Janez; Čuček, Lidija; Klemeš, Jiří Jaromír; Varbanov, Petar Sabev

    2015-01-01

    The decarbonisation of energy systems is one of the important issues of the present energy policies. One of the ways of achieving this is to focus on local energy systems, thus ensuring as much as possible their heat and power self-sufficiency by applying local renewable resource integration and transformation of the renewable energy. Increasing the share of renewables within the local energy balance could be accomplished by using a variety of approaches. One possibility is combining the Locally Integrated Energy Sectors' concept with the novel management and organisation of a renewables-based network. As a first priority, the proposed comprehensive approach focuses on increasing the energy efficiency of municipal heat and power systems using the Locally Integrated Energy Sectors' concept, which is followed by the integration of renewable energy sources with the establishment of a renewable-based network. The proposed approach is illustrated by a case study of district heating based on wood biomass for the municipality Ormož, Slovenia by integrating various end-users from different sectors. - Highlights: • The paper presents a new approach for accelerated inception of RES in municipalities. • LIES with RES network increases energy efficiency and accelerates RES integration. • A demonstration case of district heating on wood biomass within Ormož was performed.

  20. Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

    Science.gov (United States)

    Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

    2003-01-01

    An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

  1. Inferring dynamic gene regulatory networks in cardiac differentiation through the integration of multi-dimensional data.

    Science.gov (United States)

    Gong, Wuming; Koyano-Nakagawa, Naoko; Li, Tongbin; Garry, Daniel J

    2015-03-07

    Decoding the temporal control of gene expression patterns is key to the understanding of the complex mechanisms that govern developmental decisions during heart development. High-throughput methods have been employed to systematically study the dynamic and coordinated nature of cardiac differentiation at the global level with multiple dimensions. Therefore, there is a pressing need to develop a systems approach to integrate these data from individual studies and infer the dynamic regulatory networks in an unbiased fashion. We developed a two-step strategy to integrate data from (1) temporal RNA-seq, (2) temporal histone modification ChIP-seq, (3) transcription factor (TF) ChIP-seq and (4) gene perturbation experiments to reconstruct the dynamic network during heart development. First, we trained a logistic regression model to predict the probability (LR score) of any base being bound by 543 TFs with known positional weight matrices. Second, four dimensions of data were combined using a time-varying dynamic Bayesian network model to infer the dynamic networks at four developmental stages in the mouse [mouse embryonic stem cells (ESCs), mesoderm (MES), cardiac progenitors (CP) and cardiomyocytes (CM)]. Our method not only infers the time-varying networks between different stages of heart development, but it also identifies the TF binding sites associated with promoter or enhancers of downstream genes. The LR scores of experimentally verified ESCs and heart enhancers were significantly higher than random regions (p network inference model identified a region with an elevated LR score approximately -9400 bp upstream of the transcriptional start site of Nkx2-5, which overlapped with a previously reported enhancer region (-9435 to -8922 bp). TFs such as Tead1, Gata4, Msx2, and Tgif1 were predicted to bind to this region and participate in the regulation of Nkx2-5 gene expression. Our model also predicted the key regulatory networks for the ESC-MES, MES-CP and CP

  2. CellNOptR: a flexible toolkit to train protein signaling networks to data using multiple logic formalisms.

    Science.gov (United States)

    Terfve, Camille; Cokelaer, Thomas; Henriques, David; MacNamara, Aidan; Goncalves, Emanuel; Morris, Melody K; van Iersel, Martijn; Lauffenburger, Douglas A; Saez-Rodriguez, Julio

    2012-10-18

    Cells process signals using complex and dynamic networks. Studying how this is performed in a context and cell type specific way is essential to understand signaling both in physiological and diseased situations. Context-specific medium/high throughput proteomic data measured upon perturbation is now relatively easy to obtain but formalisms that can take advantage of these features to build models of signaling are still comparatively scarce. Here we present CellNOptR, an open-source R software package for building predictive logic models of signaling networks by training networks derived from prior knowledge to signaling (typically phosphoproteomic) data. CellNOptR features different logic formalisms, from Boolean models to differential equations, in a common framework. These different logic model representations accommodate state and time values with increasing levels of detail. We provide in addition an interface via Cytoscape (CytoCopteR) to facilitate use and integration with Cytoscape network-based capabilities. Models generated with this pipeline have two key features. First, they are constrained by prior knowledge about the network but trained to data. They are therefore context and cell line specific, which results in enhanced predictive and mechanistic insights. Second, they can be built using different logic formalisms depending on the richness of the available data. Models built with CellNOptR are useful tools to understand how signals are processed by cells and how this is altered in disease. They can be used to predict the effect of perturbations (individual or in combinations), and potentially to engineer therapies that have differential effects/side effects depending on the cell type or context.

  3. [Comprehensive system integration and networking in operating rooms].

    Science.gov (United States)

    Feußner, H; Ostler, D; Kohn, N; Vogel, T; Wilhelm, D; Koller, S; Kranzfelder, M

    2016-12-01

    A comprehensive surveillance and control system integrating all devices and functions is a precondition for realization of the operating room of the future. Multiple proprietary integrated operation room systems are currently available with a central user interface; however, they only cover a relatively small part of all functionalities. Internationally, there are at least three different initiatives to promote a comprehensive systems integration and networking in the operating room: the Japanese smart cyber operating theater (SCOT), the American medical device plug-and-play interoperability program (MDPnP) and the German secure and dynamic networking in operating room and hospital (OR.NET) project supported by the Federal Ministry of Education and Research. Within the framework of the internationally advanced OR.NET project, prototype solution approaches were realized, which make short-term and mid-term comprehensive data retrieval systems probable. An active and even autonomous control of the medical devices by the surveillance and control system (closed loop) is expected only in the long run due to strict regulatory barriers.

  4. The governance of regional networks in the process of European integration

    OpenAIRE

    Cappellin, Riccardo

    2001-01-01

    The paper illustrates the model of territorial networks and it investigates the role of institutions in a bottom-up approach of economic and institutional integration aiming to tackle the negative impacts of the globalization process on the economic development. The first chapter illustrates in analytical terms the model of territorial networks and the multidimen-sional nature of the process of integration, in a regional and international setting and it contrasts it with the traditional neocl...

  5. Novel insights into embryonic stem cell self-renewal revealed through comparative human and mouse systems biology networks.

    Science.gov (United States)

    Dowell, Karen G; Simons, Allen K; Bai, Hao; Kell, Braden; Wang, Zack Z; Yun, Kyuson; Hibbs, Matthew A

    2014-05-01

    Embryonic stem cells (ESCs), characterized by their ability to both self-renew and differentiate into multiple cell lineages, are a powerful model for biomedical research and developmental biology. Human and mouse ESCs share many features, yet have distinctive aspects, including fundamental differences in the signaling pathways and cell cycle controls that support self-renewal. Here, we explore the molecular basis of human ESC self-renewal using Bayesian network machine learning to integrate cell-type-specific, high-throughput data for gene function discovery. We integrated high-throughput ESC data from 83 human studies (~1.8 million data points collected under 1,100 conditions) and 62 mouse studies (~2.4 million data points collected under 1,085 conditions) into separate human and mouse predictive networks focused on ESC self-renewal to analyze shared and distinct functional relationships among protein-coding gene orthologs. Computational evaluations show that these networks are highly accurate, literature validation confirms their biological relevance, and reverse transcriptase polymerase chain reaction (RT-PCR) validation supports our predictions. Our results reflect the importance of key regulatory genes known to be strongly associated with self-renewal and pluripotency in both species (e.g., POU5F1, SOX2, and NANOG), identify metabolic differences between species (e.g., threonine metabolism), clarify differences between human and mouse ESC developmental signaling pathways (e.g., leukemia inhibitory factor (LIF)-activated JAK/STAT in mouse; NODAL/ACTIVIN-A-activated fibroblast growth factor in human), and reveal many novel genes and pathways predicted to be functionally associated with self-renewal in each species. These interactive networks are available online at www.StemSight.org for stem cell researchers to develop new hypotheses, discover potential mechanisms involving sparsely annotated genes, and prioritize genes of interest for experimental validation

  6. Integration of expression data in genome-scale metabolic network reconstructions

    Directory of Open Access Journals (Sweden)

    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  7. Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis

    NARCIS (Netherlands)

    Dam, van J.C.J.; Schaap, P.J.; Martins dos Santos, V.A.P.; Suarez Diez, M.

    2014-01-01

    Background: Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each

  8. Photonic integrated multiwavelength transmitters for fiber-to-the-home networks

    NARCIS (Netherlands)

    Lawniczuk, K.; Smit, M.K.; Piramidowicz, P.; Szczepanski, P.; Leijtens, X.J.M.; Wale, M.J.

    2012-01-01

    In this paper we present measurement results of monolithically integrated photonic transmitters for application in the next generation Fiber-to-the-Home (FTTH) networks. 4- and 8-channel transmitters were integrated onto a single chip, using multiple lasers with distributed Bragg reflector (DBR)

  9. System-level Modeling of Wireless Integrated Sensor Networks

    DEFF Research Database (Denmark)

    Virk, Kashif M.; Hansen, Knud; Madsen, Jan

    2005-01-01

    Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

  10. Integrated multimedia information system on interactive CATV network

    Science.gov (United States)

    Lee, Meng-Huang; Chang, Shin-Hung

    1998-10-01

    In the current CATV system architectures, they provide one- way delivery of a common menu of entertainment to all the homes through the cable network. Through the technologies evolution, the interactive services (or two-way services) can be provided in the cable TV systems. They can supply customers with individualized programming and support real- time two-way communications. With a view to the service type changed from the one-way delivery systems to the two-way interactive systems, `on demand services' is a distinct feature of multimedia systems. In this paper, we present our work of building up an integrated multimedia system on interactive CATV network in Shih Chien University. Besides providing the traditional analog TV programming from the cable operator, we filter some channels to reserve them as our campus information channels. In addition to the analog broadcasting channel, the system also provides the interactive digital multimedia services, e.g. Video-On- Demand (VOD), Virtual Reality, BBS, World-Wide-Web, and Internet Radio Station. These two kinds of services are integrated in a CATV network by the separation of frequency allocation for the analog broadcasting service and the digital interactive services. Our ongoing work is to port our previous work of building up a VOD system conformed to DAVIC standard (for inter-operability concern) on Ethernet network into the current system.

  11. Integrating Space Communication Network Capabilities via Web Portal Technologies

    Science.gov (United States)

    Johnston, Mark D.; Lee, Carlyn-Ann; Lau, Chi-Wung; Cheung, Kar-Ming; Levesque, Michael; Carruth, Butch; Coffman, Adam; Wallace, Mike

    2014-01-01

    We have developed a service portal prototype as part of an investigation into the feasibility of using Java portlet technology as a means of providing integrated access to NASA communications network services. Portal servers provide an attractive platform for this role due to the various built-in collaboration applications they can provide, combined with the possibility to develop custom inter-operating portlets to extent their functionality while preserving common presentation and behavior. This paper describes various options for integration of network services related to planning and scheduling, and results based on use of a popular open-source portal framework. Plans are underway to develop an operational SCaN Service Portal, building on the experiences reported here.

  12. Using CORBA to integrate manufacturing cells to a virtual enterprise

    Science.gov (United States)

    Pancerella, Carmen M.; Whiteside, Robert A.

    1997-01-01

    It is critical in today's enterprises that manufacturing facilities are not isolated from design, planning, and other business activities and that information flows easily and bidirectionally between these activities. It is also important and cost-effective that COTS software, databases, and corporate legacy codes are well integrated in the information architecture. Further, much of the information generated during manufacturing must be dynamically accessible to engineering and business operations both in a restricted corporate intranet and on the internet. The software integration strategy in the Sandia Agile Manufacturing Testbed supports these enterprise requirements. We are developing a CORBA-based distributed object software system for manufacturing. Each physical machining device is a CORBA object and exports a common IDL interface to allow for rapid and dynamic insertion, deletion, and upgrading within the manufacturing cell. Cell management CORBA components access manufacturing devices without knowledge of any device-specific implementation. To support information flow from design to planning data is accessible to machinists on the shop floor. CORBA allows manufacturing components to be easily accessible to the enterprise. Dynamic clients can be created using web browsers and portable Java GUI's. A CORBA-OLE adapter allows integration to PC desktop applications. Other commercial software can access CORBA network objects in the information architecture through vendor API's.

  13. Analysis of Basic Transmission Networks for Integrated Ship Control Systems

    DEFF Research Database (Denmark)

    Hansen, T.N.; Granum-Jensen, M.

    1993-01-01

    Description of a computer network for Integrated Ship Control Systems which is going to be developed as part of an EC-project. Today equipment of different make are not able to communicate with each other because most often each supplier of ISC systems has got their own proprietary network.....

  14. Explicit integration with GPU acceleration for large kinetic networks

    International Nuclear Information System (INIS)

    Brock, Benjamin; Belt, Andrew; Billings, Jay Jay; Guidry, Mike

    2015-01-01

    We demonstrate the first implementation of recently-developed fast explicit kinetic integration algorithms on modern graphics processing unit (GPU) accelerators. Taking as a generic test case a Type Ia supernova explosion with an extremely stiff thermonuclear network having 150 isotopic species and 1604 reactions coupled to hydrodynamics using operator splitting, we demonstrate the capability to solve of order 100 realistic kinetic networks in parallel in the same time that standard implicit methods can solve a single such network on a CPU. This orders-of-magnitude decrease in computation time for solving systems of realistic kinetic networks implies that important coupled, multiphysics problems in various scientific and technical fields that were intractable, or could be simulated only with highly schematic kinetic networks, are now computationally feasible.

  15. Cell signaling heterogeneity is modulated by both cell-intrinsic and -extrinsic mechanisms: An integrated approach to understanding targeted therapy.

    Science.gov (United States)

    Kim, Eunjung; Kim, Jae-Young; Smith, Matthew A; Haura, Eric B; Anderson, Alexander R A

    2018-03-01

    During the last decade, our understanding of cancer cell signaling networks has significantly improved, leading to the development of various targeted therapies that have elicited profound but, unfortunately, short-lived responses. This is, in part, due to the fact that these targeted therapies ignore context and average out heterogeneity. Here, we present a mathematical framework that addresses the impact of signaling heterogeneity on targeted therapy outcomes. We employ a simplified oncogenic rat sarcoma (RAS)-driven mitogen-activated protein kinase (MAPK) and phosphoinositide 3-kinase-protein kinase B (PI3K-AKT) signaling pathway in lung cancer as an experimental model system and develop a network model of the pathway. We measure how inhibition of the pathway modulates protein phosphorylation as well as cell viability under different microenvironmental conditions. Training the model on this data using Monte Carlo simulation results in a suite of in silico cells whose relative protein activities and cell viability match experimental observation. The calibrated model predicts distributional responses to kinase inhibitors and suggests drug resistance mechanisms that can be exploited in drug combination strategies. The suggested combination strategies are validated using in vitro experimental data. The validated in silico cells are further interrogated through an unsupervised clustering analysis and then integrated into a mathematical model of tumor growth in a homogeneous and resource-limited microenvironment. We assess posttreatment heterogeneity and predict vast differences across treatments with similar efficacy, further emphasizing that heterogeneity should modulate treatment strategies. The signaling model is also integrated into a hybrid cellular automata (HCA) model of tumor growth in a spatially heterogeneous microenvironment. As a proof of concept, we simulate tumor responses to targeted therapies in a spatially segregated tissue structure containing tumor

  16. Signaling network of dendritic cells in response to pathogens: a community-input supported knowledgebase.

    Science.gov (United States)

    Patil, Sonali; Pincas, Hanna; Seto, Jeremy; Nudelman, German; Nudelman, Irina; Sealfon, Stuart C

    2010-10-07

    Dendritic cells are antigen-presenting cells that play an essential role in linking the innate and adaptive immune systems. Much research has focused on the signaling pathways triggered upon infection of dendritic cells by various pathogens. The high level of activity in the field makes it desirable to have a pathway-based resource to access the information in the literature. Current pathway diagrams lack either comprehensiveness, or an open-access editorial interface. Hence, there is a need for a dependable, expertly curated knowledgebase that integrates this information into a map of signaling networks. We have built a detailed diagram of the dendritic cell signaling network, with the goal of providing researchers with a valuable resource and a facile method for community input. Network construction has relied on comprehensive review of the literature and regular updates. The diagram includes detailed depictions of pathways activated downstream of different pathogen recognition receptors such as Toll-like receptors, retinoic acid-inducible gene-I-like receptors, C-type lectin receptors and nucleotide-binding oligomerization domain-like receptors. Initially assembled using CellDesigner software, it provides an annotated graphical representation of interactions stored in Systems Biology Mark-up Language. The network, which comprises 249 nodes and 213 edges, has been web-published through the Biological Pathway Publisher software suite. Nodes are annotated with PubMed references and gene-related information, and linked to a public wiki, providing a discussion forum for updates and corrections. To gain more insight into regulatory patterns of dendritic cell signaling, we analyzed the network using graph-theory methods: bifan, feedforward and multi-input convergence motifs were enriched. This emphasis on activating control mechanisms is consonant with a network that subserves persistent and coordinated responses to pathogen detection. This map represents a navigable

  17. Recurrent network models for perfect temporal integration of fluctuating correlated inputs.

    Directory of Open Access Journals (Sweden)

    Hiroshi Okamoto

    2009-06-01

    Full Text Available Temporal integration of input is essential to the accumulation of information in various cognitive and behavioral processes, and gradually increasing neuronal activity, typically occurring within a range of seconds, is considered to reflect such computation by the brain. Some psychological evidence suggests that temporal integration by the brain is nearly perfect, that is, the integration is non-leaky, and the output of a neural integrator is accurately proportional to the strength of input. Neural mechanisms of perfect temporal integration, however, remain largely unknown. Here, we propose a recurrent network model of cortical neurons that perfectly integrates partially correlated, irregular input spike trains. We demonstrate that the rate of this temporal integration changes proportionately to the probability of spike coincidences in synaptic inputs. We analytically prove that this highly accurate integration of synaptic inputs emerges from integration of the variance of the fluctuating synaptic inputs, when their mean component is kept constant. Highly irregular neuronal firing and spike coincidences are the major features of cortical activity, but they have been separately addressed so far. Our results suggest that the efficient protocol of information integration by cortical networks essentially requires both features and hence is heterotic.

  18. Predictive networks: a flexible, open source, web application for integration and analysis of human gene networks.

    Science.gov (United States)

    Haibe-Kains, Benjamin; Olsen, Catharina; Djebbari, Amira; Bontempi, Gianluca; Correll, Mick; Bouton, Christopher; Quackenbush, John

    2012-01-01

    Genomics provided us with an unprecedented quantity of data on the genes that are activated or repressed in a wide range of phenotypes. We have increasingly come to recognize that defining the networks and pathways underlying these phenotypes requires both the integration of multiple data types and the development of advanced computational methods to infer relationships between the genes and to estimate the predictive power of the networks through which they interact. To address these issues we have developed Predictive Networks (PN), a flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these 'known' interactions together with gene expression data to infer robust gene networks. The PN web application is accessible from http://predictivenetworks.org. The PN code base is freely available at https://sourceforge.net/projects/predictivenets/.

  19. Integrated circuit cell library

    Science.gov (United States)

    Whitaker, Sterling R. (Inventor); Miles, Lowell H. (Inventor)

    2005-01-01

    According to the invention, an ASIC cell library for use in creation of custom integrated circuits is disclosed. The ASIC cell library includes some first cells and some second cells. Each of the second cells includes two or more kernel cells. The ASIC cell library is at least 5% comprised of second cells. In various embodiments, the ASIC cell library could be 10% or more, 20% or more, 30% or more, 40% or more, 50% or more, 60% or more, 70% or more, 80% or more, 90% or more, or 95% or more comprised of second cells.

  20. Integration of Signaling Pathways with the Epigenetic Machinery in the Maintenance of Stem Cells

    Directory of Open Access Journals (Sweden)

    Luca Fagnocchi

    2016-01-01

    Full Text Available Stem cells balance their self-renewal and differentiation potential by integrating environmental signals with the transcriptional regulatory network. The maintenance of cell identity and/or cell lineage commitment relies on the interplay of multiple factors including signaling pathways, transcription factors, and the epigenetic machinery. These regulatory modules are strongly interconnected and they influence the pattern of gene expression of stem cells, thus guiding their cellular fate. Embryonic stem cells (ESCs represent an invaluable tool to study this interplay, being able to indefinitely self-renew and to differentiate towards all three embryonic germ layers in response to developmental cues. In this review, we highlight those mechanisms of signaling to chromatin, which regulate chromatin modifying enzymes, histone modifications, and nucleosome occupancy. In addition, we report the molecular mechanisms through which signaling pathways affect both the epigenetic and the transcriptional state of ESCs, thereby influencing their cell identity. We propose that the dynamic nature of oscillating signaling and the different regulatory network topologies through which those signals are encoded determine specific gene expression programs, leading to the fluctuation of ESCs among multiple pluripotent states or to the establishment of the necessary conditions to exit pluripotency.

  1. Integration of 100% Micro-Distributed Energy Resources in the Low Voltage Distribution Network

    DEFF Research Database (Denmark)

    You, Shi; Segerberg, Helena

    2014-01-01

    of heat pumps (HPs) and plug-in electric vehicles (PEVs) at 100% penetration level on a representative urban residential low voltage (LV) distribution network of Denmark are investigated by performing a steady-state load flow analysis through an integrated simulation setup. Three DERs integration...... oriented integration strategies, having 100% integration of DER in the provided LV network is feasible.......The existing electricity infrastructure may to a great extent limit a high penetration of the micro-sized Distributed Energy Resources (DERs), due to the physical bottlenecks, e.g. thermal capacitates of cables, transformers and the voltage limitations. In this study, the integration impacts...

  2. Integrated analysis of multiple data sources reveals modular structure of biological networks

    International Nuclear Information System (INIS)

    Lu Hongchao; Shi Baochen; Wu Gaowei; Zhang Yong; Zhu Xiaopeng; Zhang Zhihua; Liu Changning; Zhao, Yi; Wu Tao; Wang Jie; Chen Runsheng

    2006-01-01

    It has been a challenging task to integrate high-throughput data into investigations of the systematic and dynamic organization of biological networks. Here, we presented a simple hierarchical clustering algorithm that goes a long way to achieve this aim. Our method effectively reveals the modular structure of the yeast protein-protein interaction network and distinguishes protein complexes from functional modules by integrating high-throughput protein-protein interaction data with the added subcellular localization and expression profile data. Furthermore, we take advantage of the detected modules to provide a reliably functional context for the uncharacterized components within modules. On the other hand, the integration of various protein-protein association information makes our method robust to false-positives, especially for derived protein complexes. More importantly, this simple method can be extended naturally to other types of data fusion and provides a framework for the study of more comprehensive properties of the biological network and other forms of complex networks

  3. Neuronal Networks on Nanocellulose Scaffolds.

    Science.gov (United States)

    Jonsson, Malin; Brackmann, Christian; Puchades, Maja; Brattås, Karoline; Ewing, Andrew; Gatenholm, Paul; Enejder, Annika

    2015-11-01

    Proliferation, integration, and neurite extension of PC12 cells, a widely used culture model for cholinergic neurons, were studied in nanocellulose scaffolds biosynthesized by Gluconacetobacter xylinus to allow a three-dimensional (3D) extension of neurites better mimicking neuronal networks in tissue. The interaction with control scaffolds was compared with cationized nanocellulose (trimethyl ammonium betahydroxy propyl [TMAHP] cellulose) to investigate the impact of surface charges on the cell interaction mechanisms. Furthermore, coatings with extracellular matrix proteins (collagen, fibronectin, and laminin) were investigated to determine the importance of integrin-mediated cell attachment. Cell proliferation was evaluated by a cellular proliferation assay, while cell integration and neurite propagation were studied by simultaneous label-free Coherent anti-Stokes Raman Scattering and second harmonic generation microscopy, providing 3D images of PC12 cells and arrangement of nanocellulose fibrils, respectively. Cell attachment and proliferation were enhanced by TMAHP modification, but not by protein coating. Protein coating instead promoted active interaction between the cells and the scaffold, hence lateral cell migration and integration. Irrespective of surface modification, deepest cell integration measured was one to two cell layers, whereas neurites have a capacity to integrate deeper than the cell bodies in the scaffold due to their fine dimensions and amoeba-like migration pattern. Neurites with lengths of >50 μm were observed, successfully connecting individual cells and cell clusters. In conclusion, TMAHP-modified nanocellulose scaffolds promote initial cellular scaffold adhesion, which combined with additional cell-scaffold treatments enables further formation of 3D neuronal networks.

  4. Process and data fragmentation-oriented enterprise network integration with collaboration modelling and collaboration agents

    Science.gov (United States)

    Li, Qing; Wang, Ze-yuan; Cao, Zhi-chao; Du, Rui-yang; Luo, Hao

    2015-08-01

    With the process of globalisation and the development of management models and information technology, enterprise cooperation and collaboration has developed from intra-enterprise integration, outsourcing and inter-enterprise integration, and supply chain management, to virtual enterprises and enterprise networks. Some midfielder enterprises begin to serve for different supply chains. Therefore, they combine related supply chains into a complex enterprise network. The main challenges for enterprise network's integration and collaboration are business process and data fragmentation beyond organisational boundaries. This paper reviews the requirements of enterprise network's integration and collaboration, as well as the development of new information technologies. Based on service-oriented architecture (SOA), collaboration modelling and collaboration agents are introduced to solve problems of collaborative management for service convergence under the condition of process and data fragmentation. A model-driven methodology is developed to design and deploy the integrating framework. An industrial experiment is designed and implemented to illustrate the usage of developed technologies in this paper.

  5. Integrated Environment for Ubiquitous Healthcare and Mobile IPv6 Networks

    Science.gov (United States)

    Cagalaban, Giovanni; Kim, Seoksoo

    The development of Internet technologies based on the IPv6 protocol will allow real-time monitoring of people with health deficiencies and improve the independence of elderly people. This paper proposed a ubiquitous healthcare system for the personalized healthcare services with the support of mobile IPv6 networks. Specifically, this paper discusses the integration of ubiquitous healthcare and wireless networks and its functional requirements. This allow an integrated environment where heterogeneous devices such a mobile devices and body sensors can continuously monitor patient status and communicate remotely with healthcare servers, physicians, and family members to effectively deliver healthcare services.

  6. Nanosensors-Cellphone Integration for Extended Chemical Sensing Network

    Science.gov (United States)

    Li, Jing

    2011-01-01

    This poster is to present the development of a cellphone sensor network for extended chemical sensing. The nanosensors using carbon nanotubes and other nanostructures are used with low power and high sensitivity for chemical detection. The sensing module has been miniaturized to a small size that can plug in or clip on to a smartphone. The chemical information detected by the nanosensors are acquired by a smartphone and transmitted via cellphone 3g or WiFi network to an internet server. The whole integrated sensing system from sensor to cellphone to a cloud will provide an extended chemical sensing network that can cover nation wide and even cover global wide for early warning of a hazardous event.

  7. Development of a Deterministic Optimization Model for Design of an Integrated Utility and Hydrogen Supply Network

    International Nuclear Information System (INIS)

    Hwangbo, Soonho; Lee, In-Beum; Han, Jeehoon

    2014-01-01

    Lots of networks are constructed in a large scale industrial complex. Each network meet their demands through production or transportation of materials which are needed to companies in a network. Network directly produces materials for satisfying demands in a company or purchase form outside due to demand uncertainty, financial factor, and so on. Especially utility network and hydrogen network are typical and major networks in a large scale industrial complex. Many studies have been done mainly with focusing on minimizing the total cost or optimizing the network structure. But, few research tries to make an integrated network model by connecting utility network and hydrogen network. In this study, deterministic mixed integer linear programming model is developed for integrating utility network and hydrogen network. Steam Methane Reforming process is necessary for combining two networks. After producing hydrogen from Steam-Methane Reforming process whose raw material is steam vents from utility network, produced hydrogen go into hydrogen network and fulfill own needs. Proposed model can suggest optimized case in integrated network model, optimized blueprint, and calculate optimal total cost. The capability of the proposed model is tested by applying it to Yeosu industrial complex in Korea. Yeosu industrial complex has the one of the biggest petrochemical complex and various papers are based in data of Yeosu industrial complex. From a case study, the integrated network model suggests more optimal conclusions compared with previous results obtained by individually researching utility network and hydrogen network

  8. Monterey Bay National Marine Sanctuary: Sanctuary Integrated Monitoring Network (SIMoN)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Sanctuary Integrated Monitoring Network (SIMoN) is an integrated, long-term program that takes an ecosystem approach to identify and understand changes to the...

  9. Development of virtual private network for JT-60SA CAD integration

    International Nuclear Information System (INIS)

    Oshima, Takayuki; Fujita, Takaaki; Seki, Masami; Kawashima, Hisato; Hoshino, Katsumichi; Shibanuma, Kiyoshi; Verrecchia, M.; Teuchner, B.

    2010-01-01

    The CAD models will be exchanged and integrated at Naka for JT-60SA, a common computer network efficiently connected between Naka site and the Garching site is needed to be established. Virtual Private Network (VPN) was introduced with LAN on computer network physically-separated from JAEA intranet area and firewall. In July 2009, a new VPN connection between the Naka and Garching sites has been successfully demonstrated using IPSec-VPN technology with a commercial and cost-effective firewall/router for security. It was found that the introduction of the Wide Area File Service (WAFS) could solve the issue of the data transmission time and enhance the usability of the VPN for design integration in JT-60SA. (author)

  10. Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

    Science.gov (United States)

    van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

    2014-09-26

    Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different

  11. FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

    Directory of Open Access Journals (Sweden)

    A. A. Doudkin

    2015-01-01

    Full Text Available Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

  12. Hydrocarbons in Argentina: networks, territories, integration

    International Nuclear Information System (INIS)

    Carrizo, S.C.

    2003-12-01

    Argentinean hydrocarbons networks have lived a huge reorganizing the structure, after the State reform in the 90's. Activities deregulation and the privatization of YPF and Gas del Estado forced the sector re-concentration, since then dominated by foreign companies, leaded by Repsol YPF. The hydrocarbons federalization contributed to the weakening and un-capitalization loss of wealth of the State. These changes resulted in an increase of the hydrocarbons production allowing to achieve the self-supply. Nevertheless, the expansion of internal networks has not been large enough to ensure the coverage of new requirements. Besides, several infrastructures have been built up to join external markets. National networks are connected to those of near neighboring countries. This integration is an opportunity for the 'South Cone' countries to enhance their potentials. In the country, hydrocarbons territories undergo the reorganizing the structure effects (unemployment, loss of territorial identity, etc). With many difficulties and very different possibilities, those territories, like Comodoro Rivadavia, Ensenada et and Bahia Blanca, look for their re-invention. (author)

  13. Construction of Injectable Double-Network Hydrogels for Cell Delivery.

    Science.gov (United States)

    Yan, Yan; Li, Mengnan; Yang, Di; Wang, Qian; Liang, Fuxin; Qu, Xiaozhong; Qiu, Dong; Yang, Zhenzhong

    2017-07-10

    Herein we present a unique method of using dynamic cross-links, which are dynamic covalent bonding and ionic interaction, for the construction of injectable double-network (DN) hydrogels, with the objective of cell delivery for cartilage repair. Glycol chitosan and dibenzaldhyde capped poly(ethylene oxide) formed the first network, while calcium alginate formed the second one, and in the resultant DN hydrogel, either of the networks could be selectively removed. The moduli of the DN hydrogel were significantly improved compared to that of the parent single-network hydrogels and were tunable by changing the chemical components. In situ 3D cell encapsulation could be easily performed by mixing cell suspension to the polymer solutions and transferred through a syringe needle before sol-gel transition. Cell proliferation and mediated differentiation of mouse chondrogenic cells were achieved in the DN hydrogel extracellular matrix.

  14. Integration of biological networks and gene expression data using Cytoscape

    DEFF Research Database (Denmark)

    Cline, M.S.; Smoot, M.; Cerami, E.

    2007-01-01

    of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules......Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context...... and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape....

  15. The network perspective: an integration of attachment and family systems theories.

    Science.gov (United States)

    Kozlowska, Kasia; Hanney, Lesley

    2002-01-01

    In this article we discuss the network paradigm as a useful base from which to integrate attachment and family systems theories. The network perspective refers to the application of general systems theory to living systems, and provides a framework that conceptualizes the dyadic and family systems as simultaneously distinct and interconnected. Network thinking requires that the clinician holds multiple perspectives in mind, considers each system level as both a part and a whole, and shifts the focus of attention between levels as required. Key epistemological issues that have hindered the integration of the theories are discussed. These include inconsistencies within attachment theory itself and confusion surrounding the theoretical conceptualizations of the relationship between attachment and family systems theories. Detailed information about attachment categories is provided using the Dynamic Maturational model. Case vignettes illustrating work with young children and their families explore the clinical implications of integrating attachment data into family therapy practice.

  16. Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

    Science.gov (United States)

    He, Yongqun

    2014-07-01

    While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

  17. Outside-in control -Does plant cell wall integrity regulate cell cycle progression?

    Science.gov (United States)

    Gigli-Bisceglia, Nora; Hamann, Thorsten

    2018-04-13

    During recent years it has become accepted that plant cell walls are not inert objects surrounding all plant cells but are instead highly dynamic, plastic structures. They are involved in a large number of cell biological processes and contribute actively to plant growth, development and interaction with environment. Therefore, it is not surprising that cellular processes can control plant cell wall integrity while, simultaneously, cell wall integrity can influence cellular processes. In yeast and animal cells such a bi-directional relationship also exists between the yeast/animal extra-cellular matrices and the cell cycle. In yeast, the cell wall integrity maintenance mechanism and a dedicated plasmamembrane integrity checkpoint are mediating this relationship. Recent research has yielded insights into the mechanism controlling plant cell wall metabolism during cytokinesis. However, knowledge regarding putative regulatory pathways controlling adaptive modifications in plant cell cycle activity in response to changes in the state of the plant cell wall are not yet identified. In this review, we summarize similarities and differences in regulatory mechanisms coordinating extra cellular matrices and cell cycle activity in animal and yeast cells, discuss the available evidence supporting the existence of such a mechanism in plants and suggest that the plant cell wall integrity maintenance mechanism might also control cell cycle activity in plant cells. This article is protected by copyright. All rights reserved.

  18. Survivable integrated grooming in multi-granularity optical networks

    Science.gov (United States)

    Wu, Jingjing; Guo, Lei; Wei, Xuetao; Liu, Yejun

    2012-05-01

    Survivability is an important issue to ensure the service continuity in optical network. At the same time, with the granularity of traffic demands ranging from sub-wavelength-level to wavelength-level, traffic demands need to be aggregated and carried over the network in order to utilize resources effectively. Therefore, multi-granularity grooming is proposed to save the cost and reduce the number of switching ports in Optical-Cross Connects (OXCs). However, current works mostly addressed the survivable wavelength or waveband grooming. Therefore, in this paper, we propose three heuristic algorithms called Multi-granularity Dedicated Protection Grooming (MDPG), Multi-granularity Shared Protection Grooming (MSPG) and Multi-granularity Mixed Protection Grooming (MMPG), respectively. All of them are performed based on the Survivable Multi-granularity Integrated Auxiliary Graph (SMIAG) that includes one Wavelength Integrated Auxiliary Graph (WIAG) for wavelength protection and one waveBand Integrated Auxiliary Graph (BIAG) for waveband protection. Numerical results show that MMPG has the lowest average port-cost, the best resource utilization ratio and the lowest blocking probability among these three algorithms. Compared with MDPG, MSPG has lower average port-cost, better resource utilization ratio and lower blocking probability.

  19. MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

    Science.gov (United States)

    Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

    2016-03-18

    Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

  20. The cell envelope stress response of Bacillus subtilis: from static signaling devices to dynamic regulatory network.

    Science.gov (United States)

    Radeck, Jara; Fritz, Georg; Mascher, Thorsten

    2017-02-01

    The cell envelope stress response (CESR) encompasses all regulatory events that enable a cell to protect the integrity of its envelope, an essential structure of any bacterial cell. The underlying signaling network is particularly well understood in the Gram-positive model organism Bacillus subtilis. It consists of a number of two-component systems (2CS) and extracytoplasmic function σ factors that together regulate the production of both specific resistance determinants and general mechanisms to protect the envelope against antimicrobial peptides targeting the biogenesis of the cell wall. Here, we summarize the current picture of the B. subtilis CESR network, from the initial identification of the corresponding signaling devices to unraveling their interdependence and the underlying regulatory hierarchy within the network. In the course of detailed mechanistic studies, a number of novel signaling features could be described for the 2CSs involved in mediating CESR. This includes a novel class of so-called intramembrane-sensing histidine kinases (IM-HKs), which-instead of acting as stress sensors themselves-are activated via interprotein signal transfer. Some of these IM-HKs are involved in sensing the flux of antibiotic resistance transporters, a unique mechanism of responding to extracellular antibiotic challenge.

  1. A scored human protein-protein interaction network to catalyze genomic interpretation

    DEFF Research Database (Denmark)

    Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B

    2017-01-01

    Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (InWeb_InBioMap,......Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

  2. Integration and analysis of neighbor discovery and link quality estimation in wireless sensor networks.

    Science.gov (United States)

    Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

    2014-01-01

    Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  3. Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Marjan Radi

    2014-01-01

    Full Text Available Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications.

  4. An Integrated Intrusion Detection Model of Cluster-Based Wireless Sensor Network.

    Science.gov (United States)

    Sun, Xuemei; Yan, Bo; Zhang, Xinzhong; Rong, Chuitian

    2015-01-01

    Considering wireless sensor network characteristics, this paper combines anomaly and mis-use detection and proposes an integrated detection model of cluster-based wireless sensor network, aiming at enhancing detection rate and reducing false rate. Adaboost algorithm with hierarchical structures is used for anomaly detection of sensor nodes, cluster-head nodes and Sink nodes. Cultural-Algorithm and Artificial-Fish-Swarm-Algorithm optimized Back Propagation is applied to mis-use detection of Sink node. Plenty of simulation demonstrates that this integrated model has a strong performance of intrusion detection.

  5. Tensions in R&D networks : Implications for knowledge search and integration

    NARCIS (Netherlands)

    Ritala, Paavo; Huizingh, Eelko; Almpanopoulou, Argyro; Wijbenga, Paul

    R&D Networks comprise different actors with various goals and motivations. Thus, such networks are filled with tensions that emerge from simultaneously existing, competing or contradictory organizing elements and demands. In this study, we examine the knowledge search and integration behaviour of

  6. Implementation of Integrated Service Networks under the Quebec Mental Health Reform: Facilitators and Barriers associated with Different Territorial Profiles.

    Science.gov (United States)

    Fleury, Marie-Josée; Grenier, Guy; Vallée, Catherine; Aubé, Denise; Farand, Lambert

    2017-03-10

    This study evaluates implementation of the Quebec Mental Health Reform (2005-2015), which promoted the development of integrated service networks, in 11 local service networks organized into four territorial groups according to socio-demographic characteristics and mental health services offered. Data were collected from documents concerning networks; structured questionnaires completed by 90 managers and by 16 respondent-psychiatrists; and semi-structured interviews with 102 network stakeholders. Factors associated with implementation and integration were organized according to: 1) reform characteristics; 2) implementation context; 3) organizational characteristics; and 4) integration strategies. While local networks were in a process of development and expansion, none were fully integrated at the time of the study. Facilitators and barriers to implementation and integration were primarily associated with organizational characteristics. Integration was best achieved in larger networks including a general hospital with a psychiatric department, followed by networks with a psychiatric hospital. Formalized integration strategies such as service agreements, liaison officers, and joint training reduced some barriers to implementation in networks experiencing less favourable conditions. Strategies for the implementation of healthcare reform and integrated service networks should include sustained support and training in best-practices, adequate performance indicators and resources, formalized integration strategies to improve network coordination and suitable initiatives to promote staff retention.

  7. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks

    Science.gov (United States)

    Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E.; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A.; Kellis, Manolis

    2012-01-01

    Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein–protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level. PMID:22456606

  8. Predictive regulatory models in Drosophila melanogaster by integrative inference of transcriptional networks.

    Science.gov (United States)

    Marbach, Daniel; Roy, Sushmita; Ay, Ferhat; Meyer, Patrick E; Candeias, Rogerio; Kahveci, Tamer; Bristow, Christopher A; Kellis, Manolis

    2012-07-01

    Gaining insights on gene regulation from large-scale functional data sets is a grand challenge in systems biology. In this article, we develop and apply methods for transcriptional regulatory network inference from diverse functional genomics data sets and demonstrate their value for gene function and gene expression prediction. We formulate the network inference problem in a machine-learning framework and use both supervised and unsupervised methods to predict regulatory edges by integrating transcription factor (TF) binding, evolutionarily conserved sequence motifs, gene expression, and chromatin modification data sets as input features. Applying these methods to Drosophila melanogaster, we predict ∼300,000 regulatory edges in a network of ∼600 TFs and 12,000 target genes. We validate our predictions using known regulatory interactions, gene functional annotations, tissue-specific expression, protein-protein interactions, and three-dimensional maps of chromosome conformation. We use the inferred network to identify putative functions for hundreds of previously uncharacterized genes, including many in nervous system development, which are independently confirmed based on their tissue-specific expression patterns. Last, we use the regulatory network to predict target gene expression levels as a function of TF expression, and find significantly higher predictive power for integrative networks than for motif or ChIP-based networks. Our work reveals the complementarity between physical evidence of regulatory interactions (TF binding, motif conservation) and functional evidence (coordinated expression or chromatin patterns) and demonstrates the power of data integration for network inference and studies of gene regulation at the systems level.

  9. Integrative analysis for finding genes and networks involved in diabetes and other complex diseases

    DEFF Research Database (Denmark)

    Bergholdt, R.; Størling, Zenia, Marian; Hansen, Kasper Lage

    2007-01-01

    We have developed an integrative analysis method combining genetic interactions, identified using type 1 diabetes genome scan data, and a high-confidence human protein interaction network. Resulting networks were ranked by the significance of the enrichment of proteins from interacting regions. We...... identified a number of new protein network modules and novel candidate genes/proteins for type 1 diabetes. We propose this type of integrative analysis as a general method for the elucidation of genes and networks involved in diabetes and other complex diseases....

  10. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  11. atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

    Science.gov (United States)

    Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

    2012-07-20

    Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

  12. Control strategies for power distribution networks with electric vehicles integration

    DEFF Research Database (Denmark)

    Hu, Junjie

    of electrical energy. A smart grid can also be dened as an electricity network that can intelligently integrate the actions of all users connected to it - generators, consumers and those that do both - in order to eciently deliver sustainable, economic and secure electricity supplies. This thesis focuses...... of the ii market. To build a complete solution for integration of EVs into the distribution network, a price coordinated hierarchical scheduling system is proposed which can well characterize the involved actors in the smart grid. With this system, we demonstrate that it is possible to schedule the charging......Demand side resources, like electric vehicles (EVs), can become integral parts of a smart grids because instead of just consuming power they are capable of providing valuable services to power systems. EVs can be used to balance the intermittent renewable energy resources such as wind and solar...

  13. Integrative analysis of many weighted co-expression networks using tensor computation.

    Directory of Open Access Journals (Sweden)

    Wenyuan Li

    2011-06-01

    Full Text Available The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks.

  14. ICan: an integrated co-alteration network to identify ovarian cancer-related genes.

    Science.gov (United States)

    Zhou, Yuanshuai; Liu, Yongjing; Li, Kening; Zhang, Rui; Qiu, Fujun; Zhao, Ning; Xu, Yan

    2015-01-01

    Over the last decade, an increasing number of integrative studies on cancer-related genes have been published. Integrative analyses aim to overcome the limitation of a single data type, and provide a more complete view of carcinogenesis. The vast majority of these studies used sample-matched data of gene expression and copy number to investigate the impact of copy number alteration on gene expression, and to predict and prioritize candidate oncogenes and tumor suppressor genes. However, correlations between genes were neglected in these studies. Our work aimed to evaluate the co-alteration of copy number, methylation and expression, allowing us to identify cancer-related genes and essential functional modules in cancer. We built the Integrated Co-alteration network (ICan) based on multi-omics data, and analyzed the network to uncover cancer-related genes. After comparison with random networks, we identified 155 ovarian cancer-related genes, including well-known (TP53, BRCA1, RB1 and PTEN) and also novel cancer-related genes, such as PDPN and EphA2. We compared the results with a conventional method: CNAmet, and obtained a significantly better area under the curve value (ICan: 0.8179, CNAmet: 0.5183). In this paper, we describe a framework to find cancer-related genes based on an Integrated Co-alteration network. Our results proved that ICan could precisely identify candidate cancer genes and provide increased mechanistic understanding of carcinogenesis. This work suggested a new research direction for biological network analyses involving multi-omics data.

  15. Students' network integration vs. persistence in introductory physics courses

    Science.gov (United States)

    Zwolak, Justyna; Brewe, Eric

    2017-01-01

    Society is constantly in flux, which demands the continuous development of our educational system to meet new challenges and impart the appropriate knowledge/skills to students. In order to improve student learning, among other things, the way we are teaching has significantly changed over the past few decades. We are moving away from traditional, lecture-based teaching towards more interactive, engagement-based strategies. A current, major challenge for universities is to increase student retention. While students' academic and social integration into an institution seems to be vital for student retention, research on the effect of interpersonal interactions is rare. I use of network analysis to investigate academic and social experiences of students in and beyond the classroom. In particular, there is a compelling case that transformed physics classes, such as Modeling Instruction (MI), promote persistence by the creation of learning communities that support the integration of students into the university. I will discuss recent results on pattern development in networks of MI students' interactions throughout the semester, as well as the effect of students' position within the network on their persistence in physics.

  16. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    Science.gov (United States)

    Hjorth, Johannes J J; Dawitz, Julia; Kroon, Tim; Pires, Johny; Dassen, Valerie J; Berkhout, Janna A; Emperador Melero, Javier; Nadadhur, Aish G; Alevra, Mihai; Toonen, Ruud F; Heine, Vivi M; Mansvelder, Huibert D; Meredith, Rhiannon M

    2016-04-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell migration, to the refinement of synapses, topographic maps, and the mature composition of ion channels. These emergent activity patterns are not present in all cells simultaneously within the network and more immature "silent" cells, potentially correlated with the presence of silent synapses, are prominent in different networks during early developmental periods. Many current network analyses for detection of synchronous cellular activity utilize activity-based pixel correlations to identify cellular-based regions of interest (ROIs) and coincident cell activity. However, using activity-based correlations, these methods first underestimate or ignore the inactive silent cells within the developing network and second, are difficult to apply within cell-dense regions commonly found in developing brain networks. In addition, previous methods may ignore ROIs within a network that shows transient activity patterns comprising both inactive and active periods. We developed analysis software to semi-automatically detect cells within developing neuronal networks that were imaged using calcium-sensitive reporter dyes. Using an iterative threshold, modulation of activity was tracked within individual cells across the network. The distribution pattern of both inactive and active, including synchronous cells, could be determined based on distance measures to neighboring cells and according to different anatomical layers. © 2015 Wiley Periodicals, Inc.

  17. Cytoscape: a software environment for integrated models of biomolecular interaction networks.

    Science.gov (United States)

    Shannon, Paul; Markiel, Andrew; Ozier, Owen; Baliga, Nitin S; Wang, Jonathan T; Ramage, Daniel; Amin, Nada; Schwikowski, Benno; Ideker, Trey

    2003-11-01

    Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.

  18. Reduced integration and improved segregation of functional brain networks in Alzheimer's disease.

    Science.gov (United States)

    Kabbara, A; Eid, H; El Falou, W; Khalil, M; Wendling, F; Hassan, M

    2018-04-01

    Emerging evidence shows that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients' functional brain networks and their cognitive scores. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.

  19. Probabilistic Inference of Biological Networks via Data Integration

    Directory of Open Access Journals (Sweden)

    Mark F. Rogers

    2015-01-01

    Full Text Available There is significant interest in inferring the structure of subcellular networks of interaction. Here we consider supervised interactive network inference in which a reference set of known network links and nonlinks is used to train a classifier for predicting new links. Many types of data are relevant to inferring functional links between genes, motivating the use of data integration. We use pairwise kernels to predict novel links, along with multiple kernel learning to integrate distinct sources of data into a decision function. We evaluate various pairwise kernels to establish which are most informative and compare individual kernel accuracies with accuracies for weighted combinations. By associating a probability measure with classifier predictions, we enable cautious classification, which can increase accuracy by restricting predictions to high-confidence instances, and data cleaning that can mitigate the influence of mislabeled training instances. Although one pairwise kernel (the tensor product pairwise kernel appears to work best, different kernels may contribute complimentary information about interactions: experiments in S. cerevisiae (yeast reveal that a weighted combination of pairwise kernels applied to different types of data yields the highest predictive accuracy. Combined with cautious classification and data cleaning, we can achieve predictive accuracies of up to 99.6%.

  20. Dynamic Enhanced Inter-Cell Interference Coordination for Realistic Networks

    DEFF Research Database (Denmark)

    Pedersen, Klaus I.; Alvarez, Beatriz Soret; Barcos, Sonia

    2016-01-01

    Enhanced Inter-Cell Interference Coordination (eICIC) is a key ingredient to boost the performance of co-channel Heterogeneous Networks (HetNets). eICIC encompasses two main techniques: Almost Blank Subframes (ABS), during which the macro cell remains silent to reduce the interference, and biased...... and an opportunistic approach exploiting the varying cell conditions. Moreover, an autonomous fast distributed muting algorithm is presented, which is simple, robust, and well suited for irregular network deployments. Performance results for realistic network deployments show that the traditional semi-static e...

  1. Social networking in nursing education: integrative literature review.

    Science.gov (United States)

    Kakushi, Luciana Emi; Évora, Yolanda Dora Martinez

    2016-01-01

    to identify the use of social networking in nursing education. integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%), originating from the United States and United Kingdom (77.8%). It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning) and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%), Ning (28.5%), Twitter (21.4%) and MySpace (7.1%), by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process.

  2. Social networking in nursing education: integrative literature review

    Directory of Open Access Journals (Sweden)

    Luciana Emi Kakushi

    Full Text Available Abstract Objective: to identify the use of social networking in nursing education. Method: integrative literature review in the databases: LILACS, IBECS, Cochrane, BDENF, SciELO, CINAHL, Scopus, PubMed, CAPES Periodicals Portal and Web of Science, using the descriptors: social networking and nursing education and the keywords: social networking sites and nursing education, carried out in April 2015. Results: of the 489 articles found, only 14 met the inclusion and exclusion criteria. Most studies were published after 2013 (57%, originating from the United States and United Kingdom (77.8%. It was observed the use of social networking among nursing students, postgraduate students, mentors and nurses, in undergraduate programmes, hybrid education (blended-learning and in interprofessional education. The social networking sites used in the teaching and learning process were Facebook (42.8%, Ning (28.5%, Twitter (21.4% and MySpace (7.1%, by means of audios, videos, quizzes, animations, forums, guidance, support, discussions and research group. Conclusion: few experiences of the use of social networking in nursing education were found and their contributions show the numerous benefits and difficulties faced, providing resourses for the improvement and revaluation of their use in the teaching and learning process.

  3. Dynamics of the cell-cycle network under genome-rewiring perturbations

    International Nuclear Information System (INIS)

    Katzir, Yair; Elhanati, Yuval; Braun, Erez; Averbukh, Inna

    2013-01-01

    The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein–DNA and protein–protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited ‘resources’ and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes

  4. Cell proliferation along vascular islands during microvascular network growth

    Directory of Open Access Journals (Sweden)

    Kelly-Goss Molly R

    2012-06-01

    Full Text Available Abstract Background Observations in our laboratory provide evidence of vascular islands, defined as disconnected endothelial cell segments, in the adult microcirculation. The objective of this study was to determine if vascular islands are involved in angiogenesis during microvascular network growth. Results Mesenteric tissues, which allow visualization of entire microvascular networks at a single cell level, were harvested from unstimulated adult male Wistar rats and Wistar rats 3 and 10 days post angiogenesis stimulation by mast cell degranulation with compound 48/80. Tissues were immunolabeled for PECAM and BRDU. Identification of vessel lumens via injection of FITC-dextran confirmed that endothelial cell segments were disconnected from nearby patent networks. Stimulated networks displayed increases in vascular area, length density, and capillary sprouting. On day 3, the percentage of islands with at least one BRDU-positive cell increased compared to the unstimulated level and was equal to the percentage of capillary sprouts with at least one BRDU-positive cell. At day 10, the number of vascular islands per vascular area dramatically decreased compared to unstimulated and day 3 levels. Conclusions These results show that vascular islands have the ability to proliferate and suggest that they are able to incorporate into the microcirculation during the initial stages of microvascular network growth.

  5. On the area spectral efficiency improvement of heterogeneous network by exploiting the integration of macro-femto cellular networks

    KAUST Repository

    Shakir, Muhammad; Alouini, Mohamed-Slim

    2012-01-01

    . In this paper, we consider a Heterogeneous network where we complement the macrocell network with low-power low-cost user deployed nodes, such as femtocell base stations to increase the mean achievable capacity of the system. In this context, we integrate macro

  6. Neutral space analysis for a Boolean network model of the fission yeast cell cycle network

    Directory of Open Access Journals (Sweden)

    Gonzalo A Ruz

    2014-01-01

    Full Text Available BACKGROUND: Interactions between genes and their products give rise to complex circuits known as gene regulatory networks (GRN that enable cells to process information and respond to external stimuli. Several important processes for life, depend of an accurate and context-specific regulation of gene expression, such as the cell cycle, which can be analyzed through its GRN, where deregulation can lead to cancer in animals or a directed regulation could be applied for biotechnological processes using yeast. An approach to study the robustness of GRN is through the neutral space. In this paper, we explore the neutral space of a Schizosaccharomyces pombe (fission yeast cell cycle network through an evolution strategy to generate a neutral graph, composed of Boolean regulatory networks that share the same state sequences of the fission yeast cell cycle. RESULTS: Through simulations it was found that in the generated neutral graph, the functional networks that are not in the wildtype connected component have in general a Hamming distance more than 3 with the wildtype, and more than 10 between the other disconnected functional networks. Significant differences were found between the functional networks in the connected component of the wildtype network and the rest of the network, not only at a topological level, but also at the state space level, where significant differences in the distribution of the basin of attraction for the G1 fixed point was found for deterministic updating schemes. CONCLUSIONS: In general, functional networks in the wildtype network connected component, can mutate up to no more than 3 times, then they reach a point of no return where the networks leave the connected component of the wildtype. The proposed method to construct a neutral graph is general and can be used to explore the neutral space of other biologically interesting networks, and also formulate new biological hypotheses studying the functional networks in the

  7. Issues for the integration of satellite and terrestrial cellular networks for mobile communications

    Science.gov (United States)

    Delre, Enrico; Mistretta, Ignazio; Dellipriscoli, Francesco; Settimo, Franco

    1991-01-01

    Satellite and terrestrial cellular systems naturally complement each other for land mobile communications, even though present systems have been developed independently. The main advantages of the integrated system are a faster wide area coverage, a better management of overloading traffic conditions, an extension to geographical areas not covered by the terrestrial network and, in perspective, the provision of only one integrated system for all mobile communications (land, aeronautical, and maritime). To achieve these goals, as far as possible the same protocols of the terrestrial network should be used also for the satellite network. Discussed here are the main issues arising from the requirements of the main integrated system. Some results are illustrated, and possible future improvements due to technical solutions are presented.

  8. ISINA: INTEGRAL Source Identification Network Algorithm

    Science.gov (United States)

    Scaringi, S.; Bird, A. J.; Clark, D. J.; Dean, A. J.; Hill, A. B.; McBride, V. A.; Shaw, S. E.

    2008-11-01

    We give an overview of ISINA: INTEGRAL Source Identification Network Algorithm. This machine learning algorithm, using random forests, is applied to the IBIS/ISGRI data set in order to ease the production of unbiased future soft gamma-ray source catalogues. First, we introduce the data set and the problems encountered when dealing with images obtained using the coded mask technique. The initial step of source candidate searching is introduced and an initial candidate list is created. A description of the feature extraction on the initial candidate list is then performed together with feature merging for these candidates. Three training and testing sets are created in order to deal with the diverse time-scales encountered when dealing with the gamma-ray sky. Three independent random forests are built: one dealing with faint persistent source recognition, one dealing with strong persistent sources and a final one dealing with transients. For the latter, a new transient detection technique is introduced and described: the transient matrix. Finally the performance of the network is assessed and discussed using the testing set and some illustrative source examples. Based on observations with INTEGRAL, an ESA project with instruments and science data centre funded by ESA member states (especially the PI countries: Denmark, France, Germany, Italy, Spain), Czech Republic and Poland, and the participation of Russia and the USA. E-mail: simo@astro.soton.ac.uk

  9. The Eukaryotic Cell Originated in the Integration and Redistribution of Hyperstructures from Communities of Prokaryotic Cells Based on Molecular Complementarity

    Directory of Open Access Journals (Sweden)

    Vic Norris

    2009-06-01

    Full Text Available In the “ecosystems-first” approach to the origins of life, networks of non-covalent assemblies of molecules (composomes, rather than individual protocells, evolved under the constraints of molecular complementarity. Composomes evolved into the hyperstructures of modern bacteria. We extend the ecosystems-first approach to explain the origin of eukaryotic cells through the integration of mixed populations of bacteria. We suggest that mutualism and symbiosis resulted in cellular mergers entailing the loss of redundant hyperstructures, the uncoupling of transcription and translation, and the emergence of introns and multiple chromosomes. Molecular complementarity also facilitated integration of bacterial hyperstructures to perform cytoskeletal and movement functions.

  10. Identification of molecular candidates and interaction networks via integrative toxicogenomic analysis in a human cell line following low-dose exposure to the carcinogenic metals cadmium and nickel.

    Science.gov (United States)

    Kwon, Jee Young; Weon, Jong-Il; Koedrith, Preeyaporn; Park, Kang-Sik; Kim, Im Soon; Seo, Young Rok

    2013-09-01

    Cadmium and nickel have been classified as carcinogenic to humans by the World Health Organization's International Agency for Research on Cancer. Given their prevalence in the environment, the fact that cadmium and nickel may cause diseases including cancer even at low doses is a cause for concern. However, the exact mechanisms underlying the toxicological effects induced by low-dose exposure to cadmium and nickel remain to be elucidated. Furthermore, it has recently been recognized that integrative analysis of DNA, mRNA and proteins is required to discover biomarkers and signaling networks relevant to human toxicant exposure. In the present study, we examined the deleterious effects of chronic low-dose exposure of either cadmium or nickel on global profiling of DNA copy number variation, mRNA and proteins. Array comparative genomic hybridization, gene expression microarray and functional proteomics were conducted, and a bioinformatics tool, which predicted signaling pathways, was applied to integrate data for each heavy metal separately and together. We found distinctive signaling networks associated with subchronic low-dose exposure to cadmium and nickel, and identified pathways common to both. ACTB, HSP90AA1, HSPA5 and HSPA8, which are key mediators of pathways related to apoptosis, proliferation and neoplastic processes, were key mediators of the same pathways in low-dose nickel and cadmium exposure in particular. CASP-associated signaling pathways involving CASP3, CASP7 and CASP9 were observed in cadmium-exposed cells. We found that HSP90AA1, one of the main modulators, interacted with HIF1A, AR and BCL2 in nickel-exposed cells. Interestingly, we found that HSP90AA1 was involved in the BCL2-associated apoptotic pathway in the nickel-only data, whereas this gene interacted with several genes functioning in CASP-associated apoptotic signaling in the cadmium-only data. Additionally, JUN and FASN were main modulators in nickel-responsive signaling pathways. Our

  11. An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods

    Science.gov (United States)

    Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E.; Re, Matteo

    2014-01-01

    Objective In the context of “network medicine”, gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. Materials and methods We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. Results The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different “informativeness” embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Conclusions Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further

  12. Signaling network of dendritic cells in response to pathogens: a community-input supported knowledgebase

    Directory of Open Access Journals (Sweden)

    Nudelman Irina

    2010-10-01

    Full Text Available Abstract Background Dendritic cells are antigen-presenting cells that play an essential role in linking the innate and adaptive immune systems. Much research has focused on the signaling pathways triggered upon infection of dendritic cells by various pathogens. The high level of activity in the field makes it desirable to have a pathway-based resource to access the information in the literature. Current pathway diagrams lack either comprehensiveness, or an open-access editorial interface. Hence, there is a need for a dependable, expertly curated knowledgebase that integrates this information into a map of signaling networks. Description We have built a detailed diagram of the dendritic cell signaling network, with the goal of providing researchers with a valuable resource and a facile method for community input. Network construction has relied on comprehensive review of the literature and regular updates. The diagram includes detailed depictions of pathways activated downstream of different pathogen recognition receptors such as Toll-like receptors, retinoic acid-inducible gene-I-like receptors, C-type lectin receptors and nucleotide-binding oligomerization domain-like receptors. Initially assembled using CellDesigner software, it provides an annotated graphical representation of interactions stored in Systems Biology Mark-up Language. The network, which comprises 249 nodes and 213 edges, has been web-published through the Biological Pathway Publisher software suite. Nodes are annotated with PubMed references and gene-related information, and linked to a public wiki, providing a discussion forum for updates and corrections. To gain more insight into regulatory patterns of dendritic cell signaling, we analyzed the network using graph-theory methods: bifan, feedforward and multi-input convergence motifs were enriched. This emphasis on activating control mechanisms is consonant with a network that subserves persistent and coordinated responses to

  13. NETWORK CULTURE - INTEGRAL PART OF NEW VALUES OF CIVIL SOCIETY

    OpenAIRE

    Vyacheslav Vladimirovich Sukhanov

    2014-01-01

    New technologies not only improve working conditions or communication, they are also bringing new values to  the society. This article discusses the concept of «network culture», which is now perceived by society as an integral part of values that can only exist in a civil society. We can research ( find)   this kind of society in modern time period in Russia. The article analyzes the meaning of communication, how to use it, development processes in network media.  Nowadays network culture an...

  14. VitisNet: "Omics" integration through grapevine molecular networks.

    Directory of Open Access Journals (Sweden)

    Jérôme Grimplet

    Full Text Available BACKGROUND: Genomic data release for the grapevine has increased exponentially in the last five years. The Vitis vinifera genome has been sequenced and Vitis EST, transcriptomic, proteomic, and metabolomic tools and data sets continue to be developed. The next critical challenge is to provide biological meaning to this tremendous amount of data by annotating genes and integrating them within their biological context. We have developed and validated a system of Grapevine Molecular Networks (VitisNet. METHODOLOGY/PRINCIPAL FINDINGS: The sequences from the Vitis vinifera (cv. Pinot Noir PN40024 genome sequencing project and ESTs from the Vitis genus have been paired and the 39,424 resulting unique sequences have been manually annotated. Among these, 13,145 genes have been assigned to 219 networks. The pathway sets include 88 "Metabolic", 15 "Genetic Information Processing", 12 "Environmental Information Processing", 3 "Cellular Processes", 21 "Transport", and 80 "Transcription Factors". The quantitative data is loaded onto molecular networks, allowing the simultaneous visualization of changes in the transcriptome, proteome, and metabolome for a given experiment. CONCLUSIONS/SIGNIFICANCE: VitisNet uses manually annotated networks in SBML or XML format, enabling the integration of large datasets, streamlining biological functional processing, and improving the understanding of dynamic processes in systems biology experiments. VitisNet is grounded in the Vitis vinifera genome (currently at 8x coverage and can be readily updated with subsequent updates of the genome or biochemical discoveries. The molecular network files can be dynamically searched by pathway name or individual genes, proteins, or metabolites through the MetNet Pathway database and web-portal at http://metnet3.vrac.iastate.edu/. All VitisNet files including the manual annotation of the grape genome encompassing pathway names, individual genes, their genome identifier, and chromosome

  15. A regulatory network of Drosophila germline stem cell self-renewal

    OpenAIRE

    Yan, Dong; Neumüller, Ralph A.; Buckner, Michael; Ayers, Kathleen; Li, Hua; Hu, Yanhui; Yang-Zhou, Donghui; Pan, Lei; Wang, Xiaoxi; Kelley, Colleen; Vinayagam, Arunachalam; Binari, Richard; Randklev, Sakara; Perkins, Lizabeth A.; Xie, Ting

    2014-01-01

    Stem cells possess the capacity to generate two cells of distinct fate upon division; one cell retaining stem cell identity and the other cell destined to differentiate. These cell fates are established by cell-type-specific genetic networks. To comprehensively identify components of these networks, we performed a large-scale RNAi screen in Drosophila female germline stem cells (GSCs) covering ~25% of the genome. The screen identified 366 genes that affect GSC maintenance, differentiation or ...

  16. Intelligent Networks Data Fusion Web-based Services for Ad-hoc Integrated WSNs-RFID

    Directory of Open Access Journals (Sweden)

    Falah Alshahrany

    2016-01-01

    Full Text Available The use of variety of data fusion tools and techniques for big data processing poses the problem of the data and information integration called data fusion having objectives which can differ from one application to another. The design of network data fusion systems aimed at meeting these objectives, need to take into account of the necessary synergy that can result from distributed data processing within the data networks and data centres, involving increased computation and communication. This papers reports on how this processing distribution is functionally structured as configurable integrated web-based support services, in the context of an ad-hoc wireless sensor network used for sensing and tracking, in the context of distributed detection based on complete observations to support real rime decision making. The interrelated functional and hardware RFID-WSN integration is an essential aspect of the data fusion framework that focuses on multi-sensor collaboration as an innovative approach to extend the heterogeneity of the devices and sensor nodes of ad-hoc networks generating a huge amount of heterogeneous soft and hard raw data. The deployment and configuration of these networks require data fusion processing that includes network and service management and enhances the performance and reliability of networks data fusion support systems providing intelligent capabilities for real-time control access and fire detection.

  17. Training and operation of an integrated neuromorphic network based on metal-oxide memristors

    Science.gov (United States)

    Prezioso, M.; Merrikh-Bayat, F.; Hoskins, B. D.; Adam, G. C.; Likharev, K. K.; Strukov, D. B.

    2015-05-01

    Despite much progress in semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex, with its approximately 1014 synapses, makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging. To provide comparable complexity while operating much faster and with manageable power dissipation, networks based on circuits combining complementary metal-oxide-semiconductors (CMOSs) and adjustable two-terminal resistive devices (memristors) have been developed. In such circuits, the usual CMOS stack is augmented with one or several crossbar layers, with memristors at each crosspoint. There have recently been notable improvements in the fabrication of such memristive crossbars and their integration with CMOS circuits, including first demonstrations of their vertical integration. Separately, discrete memristors have been used as artificial synapses in neuromorphic networks. Very recently, such experiments have been extended to crossbar arrays of phase-change memristive devices. The adjustment of such devices, however, requires an additional transistor at each crosspoint, and hence these devices are much harder to scale than metal-oxide memristors, whose nonlinear current-voltage curves enable transistor-free operation. Here we report the experimental implementation of transistor-free metal-oxide memristor crossbars, with device variability sufficiently low to allow operation of integrated neural networks, in a simple network: a single-layer perceptron (an algorithm for linear classification). The network can be taught in situ using a coarse-grain variety of the delta rule algorithm to perform the perfect classification of 3 × 3-pixel black/white images into three classes (representing letters). This demonstration is an important step towards much larger and more complex memristive neuromorphic networks.

  18. Securing Digital Images Integrity using Artificial Neural Networks

    Science.gov (United States)

    Hajji, Tarik; Itahriouan, Zakaria; Ouazzani Jamil, Mohammed

    2018-05-01

    Digital image signature is a technique used to protect the image integrity. The application of this technique can serve several areas of imaging applied to smart cities. The objective of this work is to propose two methods to protect digital image integrity. We present a description of two approaches using artificial neural networks (ANN) to digitally sign an image. The first one is “Direct Signature without learning” and the second is “Direct Signature with learning”. This paper presents the theory of proposed approaches and an experimental study to test their effectiveness.

  19. Integrated Analysis of Environment-driven Operational Effects in Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Park, Alfred J [ORNL; Perumalla, Kalyan S [ORNL

    2007-07-01

    There is a rapidly growing need to evaluate sensor network functionality and performance in the context of the larger environment of infrastructure and applications in which the sensor network is organically embedded. This need, which is motivated by complex applications related to national security operations, leads to a paradigm fundamentally different from that of traditional data networks. In the sensor networks of interest to us, the network dynamics depend strongly on sensor activity, which in turn is triggered by events in the environment. Because the behavior of sensor networks is sensitive to these driving phenomena, the integrity of the sensed observations, measurements and resource usage by the network can widely vary. It is therefore imperative to accurately capture the environmental phenomena, and drive the simulation of the sensor network operation by accounting fully for the environment effects. In this paper, we illustrate the strong, intimate coupling between the sensor network operation and the driving phenomena in their applications with an example sensor network designed to detect and track gaseous plumes.

  20. A Belief-Space Approach to Integrated Intelligence - Research Area 10.3: Intelligent Networks

    Science.gov (United States)

    2017-12-05

    A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks The views, opinions and/or findings contained in this...Technology (MIT) Title: A Belief-Space Approach to Integrated Intelligence- Research Area 10.3: Intelligent Networks Report Term: 0-Other Email: tlp...students presented progress and received feedback from the research group . o wrote papers on their research and submitted them to leading conferences

  1. Academic self-efficacy, growth mindsets, and university students' integration in academic and social support networks

    NARCIS (Netherlands)

    Zander, Lysann; Brouwer, Jasperina; Jansen, Ellen; Crayen, Claudia; Hannover, Bettina

    Combining complete social networks and structural equation modeling, we investigate how two learning-related cognitions, academic self-efficacy and growth mindsets, relate to integration in support networks of 580 university students in 30 seminar groups. We assessed integration as popularity in

  2. Integrative Analysis of Hippocampus Gene Expression Profiles Identifies Network Alterations in Aging and Alzheimer’s Disease

    Directory of Open Access Journals (Sweden)

    Vinay Lanke

    2018-05-01

    Full Text Available Alzheimer’s disease (AD is a neurodegenerative disorder contributing to rapid decline in cognitive function and ultimately dementia. Most cases of AD occur in elderly and later years. There is a growing need for understanding the relationship between aging and AD to identify shared and unique hallmarks associated with the disease in a region and cell-type specific manner. Although genomic studies on AD have been performed extensively, the molecular mechanism of disease progression is still not clear. The major objective of our study is to obtain a higher-order network-level understanding of aging and AD, and their relationship using the hippocampal gene expression profiles of young (20–50 years, aging (70–99 years, and AD (70–99 years. The hippocampus is vulnerable to damage at early stages of AD and altered neurogenesis in the hippocampus is linked to the onset of AD. We combined the weighted gene co-expression network and weighted protein–protein interaction network-level approaches to study the transition from young to aging to AD. The network analysis revealed the organization of co-expression network into functional modules that are cell-type specific in aging and AD. We found that modules associated with astrocytes, endothelial cells and microglial cells are upregulated and significantly correlate with both aging and AD. The modules associated with neurons, mitochondria and endoplasmic reticulum are downregulated and significantly correlate with AD than aging. The oligodendrocytes module does not show significant correlation with neither aging nor disease. Further, we identified aging- and AD-specific interactions/subnetworks by integrating the gene expression with a human protein–protein interaction network. We found dysregulation of genes encoding protein kinases (FYN, SYK, SRC, PKC, MAPK1, ephrin receptors and transcription factors (FOS, STAT3, CEBPB, MYC, NFKβ, and EGR1 in AD. Further, we found genes that encode proteins

  3. Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks

    Directory of Open Access Journals (Sweden)

    Raja Jurdak

    2008-11-01

    Full Text Available Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

  4. Large Scale Environmental Monitoring through Integration of Sensor and Mesh Networks.

    Science.gov (United States)

    Jurdak, Raja; Nafaa, Abdelhamid; Barbirato, Alessio

    2008-11-24

    Monitoring outdoor environments through networks of wireless sensors has received interest for collecting physical and chemical samples at high spatial and temporal scales. A central challenge to environmental monitoring applications of sensor networks is the short communication range of the sensor nodes, which increases the complexity and cost of monitoring commodities that are located in geographically spread areas. To address this issue, we propose a new communication architecture that integrates sensor networks with medium range wireless mesh networks, and provides users with an advanced web portal for managing sensed information in an integrated manner. Our architecture adopts a holistic approach targeted at improving the user experience by optimizing the system performance for handling data that originates at the sensors, traverses the mesh network, and resides at the server for user consumption. This holistic approach enables users to set high level policies that can adapt the resolution of information collected at the sensors, set the preferred performance targets for their application, and run a wide range of queries and analysis on both real-time and historical data. All system components and processes will be described in this paper.

  5. The B-MYB transcriptional network guides cell cycle progression and fate decisions to sustain self-renewal and the identity of pluripotent stem cells.

    Science.gov (United States)

    Zhan, Ming; Riordon, Daniel R; Yan, Bin; Tarasova, Yelena S; Bruweleit, Sarah; Tarasov, Kirill V; Li, Ronald A; Wersto, Robert P; Boheler, Kenneth R

    2012-01-01

    Embryonic stem cells (ESCs) are pluripotent and have unlimited self-renewal capacity. Although pluripotency and differentiation have been examined extensively, the mechanisms responsible for self-renewal are poorly understood and are believed to involve an unusual cell cycle, epigenetic regulators and pluripotency-promoting transcription factors. Here we show that B-MYB, a cell cycle regulated phosphoprotein and transcription factor critical to the formation of inner cell mass, is central to the transcriptional and co-regulatory networks that sustain normal cell cycle progression and self-renewal properties of ESCs. Phenotypically, B-MYB is robustly expressed in ESCs and induced pluripotent stem cells (iPSCs), and it is present predominantly in a hypo-phosphorylated state. Knockdown of B-MYB results in functional cell cycle abnormalities that involve S, G2 and M phases, and reduced expression of critical cell cycle regulators like ccnb1 and plk1. By conducting gene expression profiling on control and B-MYB deficient cells, ChIP-chip experiments, and integrative computational analyses, we unraveled a highly complex B-MYB-mediated transcriptional network that guides ESC self-renewal. The network encompasses critical regulators of all cell cycle phases and epigenetic regulators, pluripotency transcription factors, and differentiation determinants. B-MYB along with E2F1 and c-MYC preferentially co-regulate cell cycle target genes. B-MYB also co-targets genes regulated by OCT4, SOX2 and NANOG that are significantly associated with stem cell differentiation, embryonic development, and epigenetic control. Moreover, loss of B-MYB leads to a breakdown of the transcriptional hierarchy present in ESCs. These results coupled with functional studies demonstrate that B-MYB not only controls and accelerates cell cycle progression in ESCs it contributes to fate decisions and maintenance of pluripotent stem cell identity.

  6. Contingent approach to Internet-based supply network integration

    Science.gov (United States)

    Ho, Jessica; Boughton, Nick; Kehoe, Dennis; Michaelides, Zenon

    2001-10-01

    The Internet is playing an increasingly important role in enhancing the operations of supply networks as many organizations begin to recognize the benefits of Internet- enabled supply arrangements. However, the developments and applications to-date do not extend significantly beyond the dyadic model, whereas the real advantages are to be made with the external and network models to support a coordinated and collaborative based approach. The DOMAIN research group at the University of Liverpool is currently defining new Internet- enabled approaches to enable greater collaboration across supply chains. Different e-business models and tools are focusing on different applications. Using inappropriate e- business models, tools or techniques will bring negative results instead of benefits to all the tiers in the supply network. Thus there are a number of issues to be considered before addressing Internet based supply network integration, in particular an understanding of supply chain management, the emergent business models and evaluating the effects of deploying e-business to the supply network or a particular tier. It is important to utilize a contingent approach to selecting the right e-business model to meet the specific supply chain requirements. This paper addresses the issues and provides a case study on the indirect materials supply networks.

  7. Synthetic Biology Platform for Sensing and Integrating Endogenous Transcriptional Inputs in Mammalian Cells.

    Science.gov (United States)

    Angelici, Bartolomeo; Mailand, Erik; Haefliger, Benjamin; Benenson, Yaakov

    2016-08-30

    One of the goals of synthetic biology is to develop programmable artificial gene networks that can transduce multiple endogenous molecular cues to precisely control cell behavior. Realizing this vision requires interfacing natural molecular inputs with synthetic components that generate functional molecular outputs. Interfacing synthetic circuits with endogenous mammalian transcription factors has been particularly difficult. Here, we describe a systematic approach that enables integration and transduction of multiple mammalian transcription factor inputs by a synthetic network. The approach is facilitated by a proportional amplifier sensor based on synergistic positive autoregulation. The circuits efficiently transduce endogenous transcription factor levels into RNAi, transcriptional transactivation, and site-specific recombination. They also enable AND logic between pairs of arbitrary transcription factors. The results establish a framework for developing synthetic gene networks that interface with cellular processes through transcriptional regulators. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

  8. Sox17-Mediated XEN Cell Conversion Identifies Dynamic Networks Controlling Cell-Fate Decisions in Embryo-Derived Stem Cells

    Directory of Open Access Journals (Sweden)

    Angela C.H. McDonald

    2014-10-01

    Full Text Available Little is known about the gene regulatory networks (GRNs distinguishing extraembryonic endoderm (ExEn stem (XEN cells from those that maintain the extensively characterized embryonic stem cell (ESC. An intriguing network candidate is Sox17, an essential transcription factor for XEN derivation and self-renewal. Here, we show that forced Sox17 expression drives ESCs toward ExEn, generating XEN cells that contribute to ExEn when placed back into early mouse embryos. Transient Sox17 expression is sufficient to drive this fate change during which time cells transit through distinct intermediate states prior to the generation of functional XEN-like cells. To orchestrate this conversion process, Sox17 acts in autoregulatory and feedforward network motifs, regulating dynamic GRNs directing cell fate. Sox17-mediated XEN conversion helps to explain the regulation of cell-fate changes and reveals GRNs regulating lineage decisions in the mouse embryo.

  9. AS Migration and Optimization of the Power Integrated Data Network

    Science.gov (United States)

    Zhou, Junjie; Ke, Yue

    2018-03-01

    In the transformation process of data integration network, the impact on the business has always been the most important reference factor to measure the quality of network transformation. With the importance of the data network carrying business, we must put forward specific design proposals during the transformation, and conduct a large number of demonstration and practice to ensure that the transformation program meets the requirements of the enterprise data network. This paper mainly demonstrates the scheme of over-migrating point-to-point access equipment in the reconstruction project of power data comprehensive network to migrate the BGP autonomous domain to the specified domain defined in the industrial standard, and to smooth the intranet OSPF protocol Migration into ISIS agreement. Through the optimization design, eventually making electric power data network performance was improved on traffic forwarding, traffic forwarding path optimized, extensibility, get larger, lower risk of potential loop, the network stability was improved, and operational cost savings, etc.

  10. Integration of omic networks in a developmental atlas of maize.

    Science.gov (United States)

    Walley, Justin W; Sartor, Ryan C; Shen, Zhouxin; Schmitz, Robert J; Wu, Kevin J; Urich, Mark A; Nery, Joseph R; Smith, Laurie G; Schnable, James C; Ecker, Joseph R; Briggs, Steven P

    2016-08-19

    Coexpression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting functional roles of individual genes at a system-wide scale. To enable network reconstructions, we built a large-scale gene expression atlas composed of 62,547 messenger RNAs (mRNAs), 17,862 nonmodified proteins, and 6227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. Networks in which nodes are genes connected on the basis of highly correlated expression patterns of mRNAs were very different from networks that were based on coexpression of proteins. Roughly 85% of highly interconnected hubs were not conserved in expression between RNA and protein networks. However, networks from either data type were enriched in similar ontological categories and were effective in predicting known regulatory relationships. Integration of mRNA, protein, and phosphoprotein data sets greatly improved the predictive power of GRNs. Copyright © 2016, American Association for the Advancement of Science.

  11. Cell outage compensation in LTE networks: Algorithms and performance assessment

    NARCIS (Netherlands)

    Amirijoo, M.; Jorguseski, L.; Litjens, R.; Schmelz, L.C.

    2011-01-01

    Cell outage compensation is a self-healing function and as such part of the Self-Organising Networks concept for mobile wireless networks. It aims at mitigating the degradation of coverage, capacity and service quality caused by a cell or site level outage. Upon detection of such an outage, cell

  12. Networked Social Reproduction: Crises in the Integrated Circuit

    Directory of Open Access Journals (Sweden)

    Elise Danielle Thorburn

    2016-07-01

    Full Text Available This paper argues that the means of communication are sites for, and aspects of, social reproduction. In contemporary capitalism, motivated as it is by new, networked digital technologies, social reproduction is increasingly virtualised through the means of communication. Although recent political struggles have demonstrated how networked technologies can liberate social reproduction from the profit motive and from commodifying impulses, the tendency is to invoke and accelerate socially reproductive crises—crises in the capacity to reproduce ourselves both daily and intergenerationally. These crises have psychic and corporeal impacts, and intensify Tronti’s “social factory” thesis of capital’s technical composition. In order to develop modes and means of liberatory communication in the integrated circuit it is necessary to untangle and chart both the pathways and outcomes of the crises networked social reproduction invokes.

  13. An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

    Science.gov (United States)

    Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

    2014-06-01

    In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both

  14. Graph analysis of cell clusters forming vascular networks

    Science.gov (United States)

    Alves, A. P.; Mesquita, O. N.; Gómez-Gardeñes, J.; Agero, U.

    2018-03-01

    This manuscript describes the experimental observation of vasculogenesis in chick embryos by means of network analysis. The formation of the vascular network was observed in the area opaca of embryos from 40 to 55 h of development. In the area opaca endothelial cell clusters self-organize as a primitive and approximately regular network of capillaries. The process was observed by bright-field microscopy in control embryos and in embryos treated with Bevacizumab (Avastin), an antibody that inhibits the signalling of the vascular endothelial growth factor (VEGF). The sequence of images of the vascular growth were thresholded, and used to quantify the forming network in control and Avastin-treated embryos. This characterization is made by measuring vessels density, number of cell clusters and the largest cluster density. From the original images, the topology of the vascular network was extracted and characterized by means of the usual network metrics such as: the degree distribution, average clustering coefficient, average short path length and assortativity, among others. This analysis allows to monitor how the largest connected cluster of the vascular network evolves in time and provides with quantitative evidence of the disruptive effects that Avastin has on the tree structure of vascular networks.

  15. Domains I and IV of annexin A2 affect the formation and integrity of in vitro capillary-like networks.

    Directory of Open Access Journals (Sweden)

    Aase M Raddum

    Full Text Available Annexin A2 (AnxA2 is a widely expressed multifunctional protein found in different cellular compartments. In spite of lacking a hydrophobic signal peptide, AnxA2 is found at the cell surface of endothelial cells, indicative of a role in angiogenesis. Increased extracellular levels of AnxA2 in tumours correlate with neoangiogenesis, metastasis and poor prognosis. We hypothesised that extracellular AnxA2 may contribute to angiogenesis by affecting endothelial cell-cell interactions and motility. To address this question, we studied the effect of heterotetrameric and monomeric forms of AnxA2, as well as its two soluble domains on the formation and maintenance of capillary-like structures by using an in vitro co-culture system consisting of endothelial and smooth muscle cells. In particular, addition of purified domains I and IV of AnxA2 potently inhibited the vascular endothelial growth factor (VEGF-dependent formation of the capillary-like networks in a dose-dependent manner. In addition, these AnxA2 domains disrupted endothelial cell-cell contacts in preformed capillary-like networks, resulting in the internalisation of vascular endothelial (VE-cadherin and the formation of VE-cadherin-containing filopodia-like structures between the endothelial cells, suggesting increased cell motility. Addition of monoclonal AnxA2 antibodies, in particular against Tyr23 phosphorylated AnxA2, also strongly inhibited network formation in the co-culture system. These results suggest that extracellular AnxA2, most likely in its Tyr phosphorylated form, plays a pivotal role in angiogenesis. The exogenously added AnxA2 domains most likely mediate their effects by competing with endogenous AnxA2 for extracellular factors necessary for the initiation and maintenance of angiogenesis, such as those involved in the formation/integrity of cell-cell contacts.

  16. Atypical language laterality is associated with large-scale disruption of network integration in children with intractable focal epilepsy.

    Science.gov (United States)

    Ibrahim, George M; Morgan, Benjamin R; Doesburg, Sam M; Taylor, Margot J; Pang, Elizabeth W; Donner, Elizabeth; Go, Cristina Y; Rutka, James T; Snead, O Carter

    2015-04-01

    Epilepsy is associated with disruption of integration in distributed networks, together with altered localization for functions such as expressive language. The relation between atypical network connectivity and altered localization is unknown. In the current study we tested whether atypical expressive language laterality was associated with the alteration of large-scale network integration in children with medically-intractable localization-related epilepsy (LRE). Twenty-three right-handed children (age range 8-17) with medically-intractable LRE performed a verb generation task in fMRI. Language network activation was identified and the Laterality index (LI) was calculated within the pars triangularis and pars opercularis. Resting-state data from the same cohort were subjected to independent component analysis. Dual regression was used to identify associations between resting-state integration and LI values. Higher positive values of the LI, indicating typical language localization were associated with stronger functional integration of various networks including the default mode network (DMN). The normally symmetric resting-state networks showed a pattern of lateralized connectivity mirroring that of language function. The association between atypical language localization and network integration implies a widespread disruption of neural network development. These findings may inform the interpretation of localization studies by providing novel insights into reorganization of neural networks in epilepsy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Petr Maca

    2016-01-01

    Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

  18. Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

    Directory of Open Access Journals (Sweden)

    Matthew Ruffalo

    2015-12-01

    Full Text Available Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at different levels of cellular activity. Namely, we hypothesize that genes that play a role in cancer development and progression may be implicated by neither frequent mutation nor differential expression, and that network-based integration of mutation and differential expression data can reveal these "silent players". For this purpose, we utilize network-propagation algorithms to simulate the information flow in the cell at a sample-specific resolution. We then use the propagated mutation and expression signals to identify genes that are not necessarily mutated or differentially expressed genes, but have an essential role in tumor development and patient outcome. We test the proposed method on breast cancer and glioblastoma multiforme data obtained from TCGA. Our results show that the proposed method can identify important proteins that are not readily revealed by molecular data, providing insights beyond what can be gleaned by analyzing different types of molecular data in isolation.

  19. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks

    Directory of Open Access Journals (Sweden)

    Alina Sîrbu

    2015-05-01

    Full Text Available Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions. Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  20. Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks.

    Science.gov (United States)

    Sîrbu, Alina; Crane, Martin; Ruskin, Heather J

    2015-05-14

    Microarray technologies have been the basis of numerous important findings regarding gene expression in the few last decades. Studies have generated large amounts of data describing various processes, which, due to the existence of public databases, are widely available for further analysis. Given their lower cost and higher maturity compared to newer sequencing technologies, these data continue to be produced, even though data quality has been the subject of some debate. However, given the large volume of data generated, integration can help overcome some issues related, e.g., to noise or reduced time resolution, while providing additional insight on features not directly addressed by sequencing methods. Here, we present an integration test case based on public Drosophila melanogaster datasets (gene expression, binding site affinities, known interactions). Using an evolutionary computation framework, we show how integration can enhance the ability to recover transcriptional gene regulatory networks from these data, as well as indicating which data types are more important for quantitative and qualitative network inference. Our results show a clear improvement in performance when multiple datasets are integrated, indicating that microarray data will remain a valuable and viable resource for some time to come.

  1. Genome-wide RNAi Screen Identifies Networks Involved in Intestinal Stem Cell Regulation in Drosophila

    Directory of Open Access Journals (Sweden)

    Xiankun Zeng

    2015-02-01

    Full Text Available The intestinal epithelium is the most rapidly self-renewing tissue in adult animals and maintained by intestinal stem cells (ISCs in both Drosophila and mammals. To comprehensively identify genes and pathways that regulate ISC fates, we performed a genome-wide transgenic RNAi screen in adult Drosophila intestine and identified 405 genes that regulate ISC maintenance and lineage-specific differentiation. By integrating these genes into publicly available interaction databases, we further developed functional networks that regulate ISC self-renewal, ISC proliferation, ISC maintenance of diploid status, ISC survival, ISC-to-enterocyte (EC lineage differentiation, and ISC-to-enteroendocrine (EE lineage differentiation. By comparing regulators among ISCs, female germline stem cells, and neural stem cells, we found that factors related to basic stem cell cellular processes are commonly required in all stem cells, and stem-cell-specific, niche-related signals are required only in the unique stem cell type. Our findings provide valuable insights into stem cell maintenance and lineage-specific differentiation.

  2. Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

    Science.gov (United States)

    de Schipper, Laura J; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

    2017-01-01

    In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

  3. Principles of data integration and interoperability in the GEO Biodiversity Observation Network

    Science.gov (United States)

    Saarenmaa, Hannu; Ó Tuama, Éamonn

    2010-05-01

    The goal of the Global Earth Observation System of Systems (GEOSS) is to link existing information systems into a global and flexible network to address nine areas of critical importance to society. One of these "societal benefit areas" is biodiversity and it will be supported by a GEOSS sub-system known as the GEO Biodiversity Observation Network (GEO BON). In planning the GEO BON, it was soon recognised that there are already a multitude of existing networks and initiatives in place worldwide. What has been lacking is a coordinated framework that allows for information sharing and exchange between the networks. Traversing across the various scales of biodiversity, in particular from the individual and species levels to the ecosystems level has long been a challenge. Furthermore, some of the major regions of the world have already taken steps to coordinate their efforts, but links between the regions have not been a priority until now. Linking biodiversity data to that of the other GEO societal benefit areas, in particular ecosystems, climate, and agriculture to produce useful information for the UN Conventions and other policy-making bodies is another need that calls for integration of information. Integration and interoperability are therefore a major theme of GEO BON, and a "system of systems" is very much needed. There are several approaches to integration that need to be considered. Data integration requires harmonising concepts, agreeing on vocabularies, and building ontologies. Semantic mediation of data using these building blocks is still not easy to achieve. Agreements on, or mappings between, the metadata standards that will be used across the networks is a major requirement that will need to be addressed early on. With interoperable metadata, service integration will be possible through registry of registries systems such as GBIF's forthcoming GBDRS and the GEO Clearinghouse. Chaining various services that build intermediate products using workflow

  4. Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2009-01-01

    A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)

  5. A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

    Science.gov (United States)

    Trevino, Victor; Cassese, Alberto; Nagy, Zsuzsanna; Zhuang, Xiaodong; Herbert, John; Antczak, Philipp; Clarke, Kim; Davies, Nicholas; Rahman, Ayesha; Campbell, Moray J; Guindani, Michele; Bicknell, Roy; Vannucci, Marina; Falciani, Francesco

    2016-04-01

    The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell communication networks

  6. A Network Biology Approach Identifies Molecular Cross-Talk between Normal Prostate Epithelial and Prostate Carcinoma Cells.

    Directory of Open Access Journals (Sweden)

    Victor Trevino

    2016-04-01

    Full Text Available The advent of functional genomics has enabled the genome-wide characterization of the molecular state of cells and tissues, virtually at every level of biological organization. The difficulty in organizing and mining this unprecedented amount of information has stimulated the development of computational methods designed to infer the underlying structure of regulatory networks from observational data. These important developments had a profound impact in biological sciences since they triggered the development of a novel data-driven investigative approach. In cancer research, this strategy has been particularly successful. It has contributed to the identification of novel biomarkers, to a better characterization of disease heterogeneity and to a more in depth understanding of cancer pathophysiology. However, so far these approaches have not explicitly addressed the challenge of identifying networks representing the interaction of different cell types in a complex tissue. Since these interactions represent an essential part of the biology of both diseased and healthy tissues, it is of paramount importance that this challenge is addressed. Here we report the definition of a network reverse engineering strategy designed to infer directional signals linking adjacent cell types within a complex tissue. The application of this inference strategy to prostate cancer genome-wide expression profiling data validated the approach and revealed that normal epithelial cells exert an anti-tumour activity on prostate carcinoma cells. Moreover, by using a Bayesian hierarchical model integrating genetics and gene expression data and combining this with survival analysis, we show that the expression of putative cell communication genes related to focal adhesion and secretion is affected by epistatic gene copy number variation and it is predictive of patient survival. Ultimately, this study represents a generalizable approach to the challenge of deciphering cell

  7. A new approach for determining phase response curves reveals that Purkinje cells can act as perfect integrators.

    Directory of Open Access Journals (Sweden)

    Elena Phoka

    2010-04-01

    Full Text Available Cerebellar Purkinje cells display complex intrinsic dynamics. They fire spontaneously, exhibit bistability, and via mutual network interactions are involved in the generation of high frequency oscillations and travelling waves of activity. To probe the dynamical properties of Purkinje cells we measured their phase response curves (PRCs. PRCs quantify the change in spike phase caused by a stimulus as a function of its temporal position within the interspike interval, and are widely used to predict neuronal responses to more complex stimulus patterns. Significant variability in the interspike interval during spontaneous firing can lead to PRCs with a low signal-to-noise ratio, requiring averaging over thousands of trials. We show using electrophysiological experiments and simulations that the PRC calculated in the traditional way by sampling the interspike interval with brief current pulses is biased. We introduce a corrected approach for calculating PRCs which eliminates this bias. Using our new approach, we show that Purkinje cell PRCs change qualitatively depending on the firing frequency of the cell. At high firing rates, Purkinje cells exhibit single-peaked, or monophasic PRCs. Surprisingly, at low firing rates, Purkinje cell PRCs are largely independent of phase, resembling PRCs of ideal non-leaky integrate-and-fire neurons. These results indicate that Purkinje cells can act as perfect integrators at low firing rates, and that the integration mode of Purkinje cells depends on their firing rate.

  8. Development of optical packet and circuit integrated ring network testbed.

    Science.gov (United States)

    Furukawa, Hideaki; Harai, Hiroaki; Miyazawa, Takaya; Shinada, Satoshi; Kawasaki, Wataru; Wada, Naoya

    2011-12-12

    We developed novel integrated optical packet and circuit switch-node equipment. Compared with our previous equipment, a polarization-independent 4 × 4 semiconductor optical amplifier switch subsystem, gain-controlled optical amplifiers, and one 100 Gbps optical packet transponder and seven 10 Gbps optical path transponders with 10 Gigabit Ethernet (10GbE) client-interfaces were newly installed in the present system. The switch and amplifiers can provide more stable operation without equipment adjustments for the frequent polarization-rotations and dynamic packet-rate changes of optical packets. We constructed an optical packet and circuit integrated ring network testbed consisting of two switch nodes for accelerating network development, and we demonstrated 66 km fiber transmission and switching operation of multiplexed 14-wavelength 10 Gbps optical paths and 100 Gbps optical packets encapsulating 10GbE frames. Error-free (frame error rate optical packets of various packet lengths and packet rates, and stable operation of the network testbed was confirmed. In addition, 4K uncompressed video streaming over OPS links was successfully demonstrated. © 2011 Optical Society of America

  9. Integrated environmental research and networking of economy and information in rural areas of Finland

    Directory of Open Access Journals (Sweden)

    M. LUOSTARINEN

    2008-12-01

    Full Text Available This article uses material from many extensive research projects starting from the construction of the electric power supply network and its water supply systems in northern Finland in 1973-1986, to the Agropolis agricultural strategy and networking for the Loimijoki project. A list of the material and references of the publications is available in Agronet on the Internet. All these projects applied integrated environmental research covering biology, the natural sciences, social sciences, and planning methodology. To be able to promote sustainable agriculture and rural development there is a pressing need to improve research methodology and applications for integrated environmental research. This article reviews the philosophy and development of the theory behind integrated environmental re-search and the theory of network economy.

  10. A mathematical model for optimization of an integrated network logistic design

    Directory of Open Access Journals (Sweden)

    Lida Tafaghodi

    2011-10-01

    Full Text Available In this study, the integrated forward/reverse logistics network is investigated, and a capacitated multi-stage, multi-product logistics network design is proposed by formulating a generalized logistics network problem into a mixed-integer nonlinear programming model (MINLP for minimizing the total cost of the closed-loop supply chain network. Moreover, the proposed model is solved by using optimization solver, which provides the decisions related to the facility location problem, optimum quantity of shipped product, and facility capacity. Numerical results show the power of the proposed MINLP model to avoid th sub-optimality caused by separate design of forward and reverse logistics networks and to handle various transportation modes and periodic demand.

  11. D3.5 Report on ECO social network integration features

    NARCIS (Netherlands)

    Viñuales, Javier; Driesner, Jorge; Tejera, Sara; Tomasini, Alessandra; Loozen, Kjeld; Rocio, Vítor; Bohuschke, Felix; Ternier, Stefaan

    2016-01-01

    This document describes how integrations with social networks are being developed in ECO platforms. With these new features, participants will be able to share results and other contents through Facebook, Twitter, Google plus.

  12. Metro-access integrated network based on optical OFDMA with dynamic sub-carrier allocation and power distribution.

    Science.gov (United States)

    Zhang, Chongfu; Zhang, Qiongli; Chen, Chen; Jiang, Ning; Liu, Deming; Qiu, Kun; Liu, Shuang; Wu, Baojian

    2013-01-28

    We propose and demonstrate a novel optical orthogonal frequency-division multiple access (OFDMA)-based metro-access integrated network with dynamic resource allocation. It consists of a single fiber OFDMA ring and many single fiber OFDMA trees, which transparently integrates metropolitan area networks with optical access networks. The single fiber OFDMA ring connects the core network and the central nodes (CNs), the CNs are on demand reconfigurable and use multiple orthogonal sub-carriers to realize parallel data transmission and dynamic resource allocation, meanwhile, they can also implement flexible power distribution. The remote nodes (RNs) distributed in the user side are connected by the single fiber OFDMA trees with the corresponding CN. The obtained results indicate that our proposed metro-access integrated network is feasible and the power distribution is agile.

  13. A Scalable, Timing-Safe, Network-on-Chip Architecture with an Integrated Clock Distribution Method

    DEFF Research Database (Denmark)

    Bjerregaard, Tobias; Stensgaard, Mikkel Bystrup; Sparsø, Jens

    2007-01-01

    Growing system sizes together with increasing performance variability are making globally synchronous operation hard to realize. Mesochronous clocking constitutes a possible solution to the problems faced. The most fundamental of problems faced when communicating between mesochronously clocked re...... is based purely on local observations. It is demonstrated with a 90 nm CMOS standard cell network-on-chip design which implements completely timing-safe, global communication in a modular system......Growing system sizes together with increasing performance variability are making globally synchronous operation hard to realize. Mesochronous clocking constitutes a possible solution to the problems faced. The most fundamental of problems faced when communicating between mesochronously clocked...... regions concerns the possibility of data corruption caused by metastability. This paper presents an integrated communication and mesochronous clocking strategy, which avoids timing related errors while maintaining a globally synchronous system perspective. The architecture is scalable as timing integrity...

  14. Integrating Network Awareness in ATLAS Distributed Computing Using the ANSE Project

    CERN Document Server

    Klimentov, Alexei; The ATLAS collaboration; Petrosyan, Artem; Batista, Jorge Horacio; Mc Kee, Shawn Patrick

    2015-01-01

    A crucial contributor to the success of the massively scaled global computing system that delivers the analysis needs of the LHC experiments is the networking infrastructure upon which the system is built. The experiments have been able to exploit excellent high-bandwidth networking in adapting their computing models for the most efficient utilization of resources. New advanced networking technologies now becoming available such as software defined networking hold the potential of further leveraging the network to optimize workflows and dataflows, through proactive control of the network fabric on the part of high level applications such as experiment workload management and data management systems. End to end monitoring of networks using perfSONAR combined with data flow performance metrics further allows applications to adapt based on real time conditions. We will describe efforts underway in ATLAS on integrating network awareness at the application level, particularly in workload management, building upon ...

  15. Integration of Bacterial Small RNAs in Regulatory Networks.

    Science.gov (United States)

    Nitzan, Mor; Rehani, Rotem; Margalit, Hanah

    2017-05-22

    Small RNAs (sRNAs) are central regulators of gene expression in bacteria, controlling target genes posttranscriptionally by base pairing with their mRNAs. sRNAs are involved in many cellular processes and have unique regulatory characteristics. In this review, we discuss the properties of regulation by sRNAs and how it differs from and combines with transcriptional regulation. We describe the global characteristics of the sRNA-target networks in bacteria using graph-theoretic approaches and review the local integration of sRNAs in mixed regulatory circuits, including feed-forward loops and their combinations, feedback loops, and circuits made of an sRNA and another regulator, both derived from the same transcript. Finally, we discuss the competition effects in posttranscriptional regulatory networks that may arise over shared targets, shared regulators, and shared resources and how they may lead to signal propagation across the network.

  16. Integrative mining of traditional Chinese medicine literature and MEDLINE for functional gene networks.

    Science.gov (United States)

    Zhou, Xuezhong; Liu, Baoyan; Wu, Zhaohui; Feng, Yi

    2007-10-01

    The amount of biomedical data in different disciplines is growing at an exponential rate. Integrating these significant knowledge sources to generate novel hypotheses for systems biology research is difficult. Traditional Chinese medicine (TCM) is a completely different discipline, and is a complementary knowledge system to modern biomedical science. This paper uses a significant TCM bibliographic literature database in China, together with MEDLINE, to help discover novel gene functional knowledge. We present an integrative mining approach to uncover the functional gene relationships from MEDLINE and TCM bibliographic literature. This paper introduces TCM literature (about 50,000 records) as one knowledge source for constructing literature-based gene networks. We use the TCM diagnosis, TCM syndrome, to automatically congregate the related genes. The syndrome-gene relationships are discovered based on the syndrome-disease relationships extracted from TCM literature and the disease-gene relationships in MEDLINE. Based on the bubble-bootstrapping and relation weight computing methods, we have developed a prototype system called MeDisco/3S, which has name entity and relation extraction, and online analytical processing (OLAP) capabilities, to perform the integrative mining process. We have got about 200,000 syndrome-gene relations, which could help generate syndrome-based gene networks, and help analyze the functional knowledge of genes from syndrome perspective. We take the gene network of Kidney-Yang Deficiency syndrome (KYD syndrome) and the functional analysis of some genes, such as CRH (corticotropin releasing hormone), PTH (parathyroid hormone), PRL (prolactin), BRCA1 (breast cancer 1, early onset) and BRCA2 (breast cancer 2, early onset), to demonstrate the preliminary results. The underlying hypothesis is that the related genes of the same syndrome will have some biological functional relationships, and will constitute a functional network. This paper presents

  17. Alternating Dynamics of Segregation and Integration in Human EEG Functional Networks During Working-memory Task.

    Science.gov (United States)

    Zippo, Antonio G; Della Rosa, Pasquale A; Castiglioni, Isabella; Biella, Gabriele E M

    2018-02-10

    Brain functional networks show high variability in short time windows but mechanisms governing these transient dynamics remain unknown. In this work, we studied the temporal evolution of functional brain networks involved in a working memory (WM) task while recording high-density electroencephalography (EEG) in human normal subjects. We found that functional brain networks showed an initial phase characterized by an increase of the functional segregation index followed by a second phase where the functional segregation faded after the prevailing the functional integration. Notably, wrong trials were associated with different or disrupted sequences of the segregation-integration profiles and measures of network centrality and modularity were able to identify crucial aspects of the oscillatory network dynamics. Additionally, computational investigations further supported the experimental results. The brain functional organization may respond to the information processing demand of a WM task following a 2-step atomic scheme wherein segregation and integration alternately dominate the functional configurations. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  18. Full-Duplex MIMO Small-Cell Networks: Performance Analysis

    OpenAIRE

    Atzeni, Italo; Kountouris, Marios

    2015-01-01

    Full-duplex small-cell relays with multiple antennas constitute a core element of the envisioned 5G network architecture. In this paper, we use stochastic geometry to analyze the performance of wireless networks with full-duplex multiple-antenna small cells, with particular emphasis on the probability of successful transmission. To achieve this goal, we additionally characterize the distribution of the self-interference power of the full-duplex nodes. The proposed framework reveals useful ins...

  19. Techno-economic analysis of sorption-enhanced steam methane reforming in a fixed bed reactor network integrated with fuel cell

    Science.gov (United States)

    Diglio, Giuseppe; Hanak, Dawid P.; Bareschino, Piero; Mancusi, Erasmo; Pepe, Francesco; Montagnaro, Fabio; Manovic, Vasilije

    2017-10-01

    Sorption-enhanced steam methane reforming (SE-SMR) is a promising alternative for H2 production with inherent CO2 capture. This study evaluates the techno-economic performance of SE-SMR in a network of fixed beds and its integration with a solid oxide fuel cell (SE-SMR-SOFC) for power generation. The analysis revealed that both proposed systems are characterised by better economic performance than the reference systems. In particular, for SE-SMR the levelised cost of hydrogen is 1.6 €ṡkg-1 and the cost of CO2 avoided is 29.9 €ṡtCO2-1 (2.4 €ṡkg-1 and 50 €ṡtCO2-1, respectively, for SMR with CO2 capture) while for SE-SMR-SOFC the levelised cost of electricity is 0.078 €ṡkWh-1 and the cost of CO2 avoided is 36.9 €ṡtCO2-1 (0.080 €ṡkWh-1 and 80 €ṡtCO2-1, respectively, for natural gas-fired power plant with carbon capture). The sensitivity analysis showed that the specific cost of fuel and the capital cost of fuel cell mainly affect the economic performance of SE-SMR and SE-SMR-SOFC, respectively. The daily revenue of the SE-SMR-SOFC system is higher than that of the natural gas-fired power plant if the difference between the carbon tax and the CO2 transport and storage cost is > 6 €ṡtCO2-1.

  20. Computing the Local Field Potential (LFP) from Integrate-and-Fire Network Models

    DEFF Research Database (Denmark)

    Mazzoni, Alberto; Linden, Henrik; Cuntz, Hermann

    2015-01-01

    Leaky integrate-and-fire (LIF) network models are commonly used to study how the spiking dynamics of neural networks changes with stimuli, tasks or dynamic network states. However, neurophysiological studies in vivo often rather measure the mass activity of neuronal microcircuits with the local f...... in cases where a single pyramidal population dominates the LFP generation, and thereby facilitate quantitative comparison between computational models and experimental LFP recordings in vivo....

  1. Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics.

    Directory of Open Access Journals (Sweden)

    István A Kovács

    Full Text Available BACKGROUND: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. METHODOLOGY/PRINCIPAL FINDINGS: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1 determine persvasively overlapping modules with high resolution; (2 uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3 allow the determination of key network nodes and (4 help to predict network dynamics. CONCLUSIONS/SIGNIFICANCE: The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction.

  2. Integrated fuel cell stack shunt current prevention arrangement

    Energy Technology Data Exchange (ETDEWEB)

    Roche, Robert P. (Cheshire, CT); Nowak, Michael P. (Bolton, CT)

    1992-01-01

    A fuel cell stack includes a plurality of fuel cells juxtaposed with one another in the stack and each including a pair of plate-shaped anode and cathode electrodes that face one another, and a quantity of liquid electrolyte present at least between the electrodes. A separator plate is interposed between each two successive electrodes of adjacent ones of the fuel cells and is unified therewith into an integral separator plate. Each integral separator plate is provided with a circumferentially complete barrier that prevents flow of shunt currents onto and on an outer peripheral surface of the separator plate. This barrier consists of electrolyte-nonwettable barrier members that are accommodated, prior to the formation of the integral separator plate, in corresponding edge recesses situated at the interfaces between the electrodes and the separator plate proper. Each barrier member extends over the entire length of the associated marginal portion and is flush with the outer periphery of the integral separator plate. This barrier also prevents cell-to-cell migration of any electrolyte that may be present at the outer periphery of the integral separator plate while the latter is incorporated in the fuel cell stack.

  3. Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems

    International Nuclear Information System (INIS)

    Santos, Sérgio F.; Fitiwi, Desta Z.; Cruz, Marco R.M.; Cabrita, Carlos M.P.; Catalão, João P.S.

    2017-01-01

    Highlights: • A dynamic and multi-objective stochastic mixed integer linear programming model is developed. • A new mechanism to quantify the impacts of network flexibility and ESS deployments on RES integration is presented. • Optimal integration of ESSs dramatically increases the level and the optimal exploitation of renewable DGs. • As high as 90% of RES integration level may be possible in distribution network systems. • Joint DG and ESS installations along with optimal network reconfiguration greatly contribute to voltage stability. - Abstract: Nowadays, there is a wide consensus about integrating more renewable energy sources-RESs to solve a multitude of global concerns such as meeting an increasing demand for electricity, reducing energy security and heavy dependence on fossil fuels for energy production, and reducing the overall carbon footprint of power production. Framed in this context, the coordination of RES integration with energy storage systems (ESSs), along with the network’s switching capability and/or reinforcement, is expected to significantly improve system flexibility, thereby increasing the capability of the system in accommodating large-scale RES power. Hence, this paper presents a novel mechanism to quantify the impacts of network switching and/or reinforcement as well as deployment of ESSs on the level of renewable power integrated in the system. To carry out this analysis, a dynamic and multi-objective stochastic mixed integer linear programming (S-MILP) model is developed, which jointly takes the optimal deployment of RES-based DGs and ESSs into account in coordination with distribution network reinforcement and/or reconfiguration. The IEEE 119-bus test system is used as a case study. Numerical results clearly show the capability of ESS deployment in dramatically increasing the level of renewable DGs integrated in the system. Although case-dependent, the impact of network reconfiguration on RES power integration is not

  4. A multi-ring optical packet and circuit integrated network with optical buffering.

    Science.gov (United States)

    Furukawa, Hideaki; Shinada, Satoshi; Miyazawa, Takaya; Harai, Hiroaki; Kawasaki, Wataru; Saito, Tatsuhiko; Matsunaga, Koji; Toyozumi, Tatuya; Wada, Naoya

    2012-12-17

    We newly developed a 3 × 3 integrated optical packet and circuit switch-node. Optical buffers and burst-mode erbium-doped fiber amplifiers with the gain flatness are installed in the 3 × 3 switch-node. The optical buffer can prevent packet collisions and decrease packet loss. We constructed a multi-ring optical packet and circuit integrated network testbed connecting two single-ring networks and a client network by the 3 × 3 switch-node. For the first time, we demonstrated 244 km fiber transmission and 5-node hopping of multiplexed 14-wavelength 10 Gbps optical paths and 100 Gbps optical packets encapsulating 10 Gigabit Ethernet frames on the testbed. Error-free (frame error rate optical packets of various packet lengths. In addition, successful avoidance of packet collisions by optical buffers was confirmed.

  5. Integration of metabolomics data into metabolic networks.

    Science.gov (United States)

    Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

    2015-01-01

    Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data.

  6. Polycation-mediated integrated cell death processes

    DEFF Research Database (Denmark)

    Parhamifar, Ladan; Andersen, Helene; Wu, Linping

    2014-01-01

    standard. PEIs are highly efficient transfectants, but depending on their architecture and size they induce cytotoxicity through different modes of cell death pathways. Here, we briefly review dynamic and integrated cell death processes and pathways, and discuss considerations in cell death assay design...

  7. Network access charges, vertical integration, and property rights structure - experiences from the German electricity markets

    International Nuclear Information System (INIS)

    Growitsch, C.; Wein, T.

    2005-01-01

    After the deregulation of the German electricity markets in 1998, the German government opted for a regulatory regime called negotiated third party access, which would be subject to ex-post control by the federal cartel office. Network access charges for new competitors are based on contractual arrangements between energy producers and industrial consumers. As the electricity networks are incontestable natural monopolies, the local and regional network operators are able to set (monopolistic) charges at their own discretion, restricted only by the possible interference of the federal cartel office (Bundeskartellamt). In this paper we analyze if there is evidence for varying charging behaviour depending on the supplier's economic independence (structure of property rights) or its level of vertical integration. For this purpose, we hypothesise that incorporated and vertically integrated suppliers set different charges than independent utility companies. Multivariate estimations show a relation between network access charges and the network operator's economic independence as well as level of vertical integration: on the low voltage level for an estimated annual consumption of 1700 kW/h, vertically integrated firms set-in accordance with our hypothesis-significantly lower access charges than vertically separated suppliers, whereas incorporated network operators charge significantly higher charges compared to independent suppliers. These results could not have been confirmed for other consumptions or voltage levels. (author)

  8. Integrated production-distribution planning optimization models: A review in collaborative networks context

    Directory of Open Access Journals (Sweden)

    Beatriz Andres

    2017-01-01

    Full Text Available Researchers in the area of collaborative networks are more and more aware of proposing collaborative approaches to address planning processes, due to the advantages associated when enterprises perform integrated planning models. Collaborative production-distribution planning, among the supply network actors, is considered a proper mechanism to support enterprises on dealing with uncertainties and dynamicity associated to the current markets. Enterprises, and especially SMEs, should be able to overcome the continuous changes of the market by increasing their agility. Carrying out collaborative planning allows enterprises to enhance their readiness and agility for facing the market turbulences. However, SMEs have limited access when incorporating optimization tools to deal with collaborative planning, reducing their ability to respond to the competition. The problem to solve is to provide SMEs affordable solutions to support collaborative planning. In this regard, new optimisation algorithms are required in order to improve the collaboration within the supply network partners. As part of the H2020 Cloud Collaborative Manufacturing Networks (C2NET research project, this paper presents a study on integrated production and distribution plans. The main objective of the research is to identify gaps in current optimization models, proposed to address integrated planning, taking into account the requirements and needs of the industry. Thus, the needs of the companies belonging to the industrial pilots, defined in the C2NET project, are identified; analysing how these needs are covered by the optimization models proposed in the literature, to deal with the integrated production-distribution planning.

  9. Stability of Control Networks in Autonomous Homeostatic Regulation of Stem Cell Lineages.

    Science.gov (United States)

    Komarova, Natalia L; van den Driessche, P

    2018-05-01

    Design principles of biological networks have been studied extensively in the context of protein-protein interaction networks, metabolic networks, and regulatory (transcriptional) networks. Here we consider regulation networks that occur on larger scales, namely the cell-to-cell signaling networks that connect groups of cells in multicellular organisms. These are the feedback loops that orchestrate the complex dynamics of cell fate decisions and are necessary for the maintenance of homeostasis in stem cell lineages. We focus on "minimal" networks that are those that have the smallest possible numbers of controls. For such minimal networks, the number of controls must be equal to the number of compartments, and the reducibility/irreducibility of the network (whether or not it can be split into smaller independent sub-networks) is defined by a matrix comprised of the cell number increments induced by each of the controlled processes in each of the compartments. Using the formalism of digraphs, we show that in two-compartment lineages, reducible systems must contain two 1-cycles, and irreducible systems one 1-cycle and one 2-cycle; stability follows from the signs of the controls and does not require magnitude restrictions. In three-compartment systems, irreducible digraphs have a tree structure or have one 3-cycle and at least two more shorter cycles, at least one of which is a 1-cycle. With further work and proper biological validation, our results may serve as a first step toward an understanding of ways in which these networks become dysregulated in cancer.

  10. Reduced integration and improved segregation of functional brain networks in Alzheimer’s disease

    Science.gov (United States)

    Kabbara, A.; Eid, H.; El Falou, W.; Khalil, M.; Wendling, F.; Hassan, M.

    2018-04-01

    Objective. Emerging evidence shows that cognitive deficits in Alzheimer’s disease (AD) are associated with disruptions in brain functional connectivity. Thus, the identification of alterations in AD functional networks has become a topic of increasing interest. However, to what extent AD induces disruption of the balance of local and global information processing in the human brain remains elusive. The main objective of this study is to explore the dynamic topological changes of AD networks in terms of brain network segregation and integration. Approach. We used electroencephalography (EEG) data recorded from 20 participants (10 AD patients and 10 healthy controls) during resting state. Functional brain networks were reconstructed using EEG source connectivity computed in different frequency bands. Graph theoretical analyses were performed assess differences between both groups. Main results. Results revealed that AD networks, compared to networks of age-matched healthy controls, are characterized by lower global information processing (integration) and higher local information processing (segregation). Results showed also significant correlation between the alterations in the AD patients’ functional brain networks and their cognitive scores. Significance. These findings may contribute to the development of EEG network-based test that could strengthen results obtained from currently-used neurophysiological tests in neurodegenerative diseases.

  11. Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

    Science.gov (United States)

    Ye, Yusen; Gao, Lin; Zhang, Shihua

    2017-01-01

    Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

  12. Integrating Networking into ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2018-01-01

    Networking is foundational to the ATLAS distributed infrastructure and there are many ongoing activities related to networking both within and outside of ATLAS. We will report on the progress in a number of areas exploring ATLAS's use of networking and our ability to monitor the network, analyze metrics from the network, and tune and optimize application and end-host parameters to make the most effective use of the network. Specific topics will include work on Open vSwitch for production systems, network analytics, FTS testing and tuning, and network problem alerting and alarming.

  13. MINET [momentum integral network] code documentation

    International Nuclear Information System (INIS)

    Van Tuyle, G.J.; Nepsee, T.C.; Guppy, J.G.

    1989-12-01

    The MINET computer code, developed for the transient analysis of fluid flow and heat transfer, is documented in this four-part reference. In Part 1, the MINET models, which are based on a momentum integral network method, are described. The various aspects of utilizing the MINET code are discussed in Part 2, The User's Manual. The third part is a code description, detailing the basic code structure and the various subroutines and functions that make up MINET. In Part 4, example input decks, as well as recent validation studies and applications of MINET are summarized. 32 refs., 36 figs., 47 tabs

  14. Handoff Triggering and Network Selection Algorithms for Load-Balancing Handoff in CDMA-WLAN Integrated Networks

    Directory of Open Access Journals (Sweden)

    Khalid Qaraqe

    2008-10-01

    Full Text Available This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection. The handoff trigger is decided based on the received signal strength (RSS. To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service, and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.

  15. Handoff Triggering and Network Selection Algorithms for Load-Balancing Handoff in CDMA-WLAN Integrated Networks

    Directory of Open Access Journals (Sweden)

    Kim Jang-Sub

    2008-01-01

    Full Text Available This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection. The handoff trigger is decided based on the received signal strength (RSS. To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service, and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.

  16. Brain network analysis: separating cost from topology using cost-integration.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    Full Text Available A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i differences in weighted costs and (ii differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration.

  17. Brain Network Analysis: Separating Cost from Topology Using Cost-Integration

    Science.gov (United States)

    Ginestet, Cedric E.; Nichols, Thomas E.; Bullmore, Ed T.; Simmons, Andrew

    2011-01-01

    A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i) differences in weighted costs and (ii) differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration. PMID:21829437

  18. A network analysis of leadership theory : the infancy of integration.

    OpenAIRE

    Meuser, J. D.; Gardner, W. L.; Dinh, J. E.; Hu, J.; Liden, R. C.; Lord, R. G.

    2016-01-01

    We investigated the status of leadership theory integration by reviewing 14 years of published research (2000 through 2013) in 10 top journals (864 articles). The authors of these articles examined 49 leadership approaches/theories, and in 293 articles, 3 or more of these leadership approaches were included in their investigations. Focusing on these articles that reflected relatively extensive integration, we applied an inductive approach and used graphic network analysis as a guide for drawi...

  19. An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

    Directory of Open Access Journals (Sweden)

    Liu Lili

    2013-06-01

    Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

  20. Semantic integration to identify overlapping functional modules in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Ramanathan Murali

    2007-07-01

    Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

  1. Design and analysis of heat exchanger networks for integrated Ca-looping systems

    International Nuclear Information System (INIS)

    Lara, Yolanda; Lisbona, Pilar; Martínez, Ana; Romeo, Luis M.

    2013-01-01

    Highlights: • Heat integration is essential to minimize energy penalties in calcium looping cycles. • A design and analysis of four heat exchanger networks is stated. • New design with higher power, lower costs and lower destroyed exergy than base case. - Abstract: One of the main challenges of carbon capture and storage technologies deals with the energy penalty associated with CO 2 separation and compression processes. Thus, heat integration plays an essential role in the improvement of these systems’ efficiencies. CO 2 capture systems based on Ca-looping process present a great potential for residual heat integration with a new supercritical power plant. The pinch methodology is applied in this study to define the minimum energy requirements of the process and to design four configurations for the required heat exchanger network. The Second Law of Thermodynamics represents a powerful tool for reducing the energy demand since identifying the exergy losses of the system serves to allocate inefficiencies. In parallel, an economic analysis is required to asses the cost reduction achieved by each configuration. This work presents a combination of pinch methodology with economic and exergetic analyses to select the more appropriate configuration of heat exchanger network. The lower costs and minor destroyed exergy obtained for the best proposed network result in a of 0.91% global energy efficiency increase

  2. Design and implementation of interface units for high speed fiber optics local area networks and broadband integrated services digital networks

    Science.gov (United States)

    Tobagi, Fouad A.; Dalgic, Ismail; Pang, Joseph

    1990-01-01

    The design and implementation of interface units for high speed Fiber Optic Local Area Networks and Broadband Integrated Services Digital Networks are discussed. During the last years, a number of network adapters that are designed to support high speed communications have emerged. This approach to the design of a high speed network interface unit was to implement package processing functions in hardware, using VLSI technology. The VLSI hardware implementation of a buffer management unit, which is required in such architectures, is described.

  3. Label-free single-cell separation and imaging of cancer cells using an integrated microfluidic system

    DEFF Research Database (Denmark)

    Antfolk, Maria; Kim, Soo Hyeon; Koizumi, Saori

    2017-01-01

    , an integrated system is presented that efficiently eliminates this risk by integrating label-free separation with single cell arraying of the target cell population, enabling direct on-chip tumor cell identification and enumeration. Prostate cancer cells (DU145) spiked into a sample with whole blood...... a fully integrated system for rapid label-free separation and on-chip phenotypic characterization of circulating tumor cells from peripheral venous blood in clinical practice....

  4. Social networks in nursing work processes: an integrative literature review

    Directory of Open Access Journals (Sweden)

    Ana Cláudia Mesquita

    Full Text Available Abstract OBJECTIVE To identify and analyze the available evidence in the literature on the use of social networks in nursing work processes. METHOD An integrative review of the literature conducted in PubMed, CINAHL, EMBASE and LILACS databases in January 2016, using the descriptors social media, social networking, nursing, enfermagem, redes sociais, mídias sociais, and the keyword nursing practice, without year restriction. RESULTS The sample consisted of 27 international articles which were published between 2011 and 2016. The social networks used were Facebook (66.5%, Twitter (30% and WhatsApp (3.5%. In 70.5% of the studies, social networks were used for research purposes, in 18.5% they were used as a tool aimed to assist students in academic activities, and in 11% for executing interventions via the internet. CONCLUSION Nurses have used social networks in their work processes such as Facebook, Twitter and WhatsApp to research, teach and watch. The articles show several benefits in using such tools in the nursing profession; however, ethical considerations regarding the use of social networks deserve further discussion.

  5. Nano-topography Enhances Communication in Neural Cells Networks

    KAUST Repository

    Onesto, V.; Cancedda, L.; Coluccio, M. L.; Nanni, M.; Pesce, M.; Malara, N.; Cesarelli, M.; Di Fabrizio, Enzo M.; Amato, F.; Gentile, F.

    2017-01-01

    Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can

  6. Integrated evolutionary computation neural network quality controller for automated systems

    Energy Technology Data Exchange (ETDEWEB)

    Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

    1999-06-01

    With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

  7. Social integration in friendship networks: The synergy of network structure and peer influence in relation to cigarette smoking among high risk adolescents

    Science.gov (United States)

    Lakon, Cynthia M.; Valente, Thomas W.

    2013-01-01

    Using data from a study of high risk adolescents in Southern California, U.S.A. (N = 851), this study examined synergy between social network measures of social integration and peer influence in relation to past month cigarette smoking. Using Hierarchical Linear Modeling, results indicated that being central in networks was significantly and positively related to past month cigarette smoking, across all study models. In addition, there is modest evidence that the number of reciprocated friendship ties was positively related to past month cigarette smoking. There is also some modest evidence that the relationship between having reciprocated friendships and past month cigarette smoking was moderated by a network peer influence process, smoking with those in youths’ best friend networks. Findings indicate that being integrated within a social network context of peer influences favoring drug use relates to more smoking among these high risk youth. PMID:22436575

  8. Cell cycle control by a minimal Cdk network.

    Directory of Open Access Journals (Sweden)

    Claude Gérard

    2015-02-01

    Full Text Available In present-day eukaryotes, the cell division cycle is controlled by a complex network of interacting proteins, including members of the cyclin and cyclin-dependent protein kinase (Cdk families, and the Anaphase Promoting Complex (APC. Successful progression through the cell cycle depends on precise, temporally ordered regulation of the functions of these proteins. In light of this complexity, it is surprising that in fission yeast, a minimal Cdk network consisting of a single cyclin-Cdk fusion protein can control DNA synthesis and mitosis in a manner that is indistinguishable from wild type. To improve our understanding of the cell cycle regulatory network, we built and analysed a mathematical model of the molecular interactions controlling the G1/S and G2/M transitions in these minimal cells. The model accounts for all observed properties of yeast strains operating with the fusion protein. Importantly, coupling the model's predictions with experimental analysis of alternative minimal cells, we uncover an explanation for the unexpected fact that elimination of inhibitory phosphorylation of Cdk is benign in these strains while it strongly affects normal cells. Furthermore, in the strain without inhibitory phosphorylation of the fusion protein, the distribution of cell size at division is unusually broad, an observation that is accounted for by stochastic simulations of the model. Our approach provides novel insights into the organization and quantitative regulation of wild type cell cycle progression. In particular, it leads us to propose a new mechanistic model for the phenomenon of mitotic catastrophe, relying on a combination of unregulated, multi-cyclin-dependent Cdk activities.

  9. An anatomical substrate for integration among functional networks in human cortex.

    Science.gov (United States)

    van den Heuvel, Martijn P; Sporns, Olaf

    2013-09-04

    The human brain shows several characteristics of an efficient communication network architecture, including short communication paths and the existence of modules interlinked by a small set of highly connected regions. Studies of structural networks comprising macroscopic white matter projections have shown that these putative hubs are densely interconnected, giving rise to a spatially distributed and topologically central collective called the "rich club." In parallel, studies of intrinsic brain activity have consistently revealed distinct functional communities or resting-state networks (RSNs), indicative of specialized processing and segregation of neuronal information. However, the pattern of structural connectivity interconnecting these functional RSNs and how such inter-RSN structural connections might bring about functional integration between RSNs remain largely unknown. Combining high-resolution diffusion weighted imaging with resting-state fMRI, we present novel evidence suggesting that the rich club structure plays a central role in cross-linking macroscopic RSNs of the human brain. Rich club hub nodes were present in all functional networks, accounted for a large proportion of "connector nodes," and were found to coincide with regions in which multiple networks overlap. In addition, a large proportion of all inter-RSN connections were found to involve rich club nodes, and these connections participated in a disproportionate number of communication paths linking nodes in different RSNs. Our findings suggest that the brain's rich club serves as a macroscopic anatomical substrate to cross-link functional networks and thus plays an important role in the integration of information between segregated functional domains of the human cortex.

  10. Digital photocontrol of the network of live excitable cells

    Science.gov (United States)

    Erofeev, I. S.; Magome, N.; Agladze, K. I.

    2011-11-01

    Recent development of tissue engineering techniques allows creating and maintaining almost indefinitely networks of excitable cells with desired architecture. We coupled the network of live excitable cardiac cells with a common computer by sensitizing them to light, projecting a light pattern on the layer of cells, and monitoring excitation with the aid of fluorescent probes (optical mapping). As a sensitizing substance we used azobenzene trimethylammonium bromide (AzoTAB). This substance undergoes cis-trans-photoisomerization and trans-isomer of AzoTAB inhibits excitation in the cardiac cells, while cis-isomer does not. AzoTAB-mediated sensitization allows, thus, reversible and dynamic control of the excitation waves through the entire cardiomyocyte network either uniformly, or in a preferred spatial pattern. Technically, it was achieved by coupling a common digital projector with a macroview microscope and using computer graphic software for creating the projected pattern of conducting pathways. This approach allows real time interactive photocontrol of the heart tissue.

  11. Abnormal functional integration across core brain networks in migraine without aura.

    Science.gov (United States)

    Yu, Dahua; Yuan, Kai; Luo, Lin; Zhai, Jinquan; Bi, Yanzhi; Xue, Ting; Ren, Xiaoying; Zhang, Ming; Ren, Guoyin; Lu, Xiaoqi

    2017-01-01

    As a complex subjective experience, pain processing may be related to functional integration among intrinsic connectivity networks of migraine patients without aura. However, few study focused on the pattern alterations in the intrinsic connectivity networks of migraine patients without aura. Thirty-one migraine patients without aura and 31 age- and education-matched healthy controls participated in this study. After identifying the default mode network, central executive network and salience network as core intrinsic connectivity networks by using independent component analysis, functional connectivity, and effective connectivity during the resting state were used to investigate the abnormalities in intrinsic connectivity network interactions. Migraine patients without aura showed decreased functional connectivity among intrinsic connectivity networks compared with healthy controls. The strength of causal influences from the right frontoinsular cortex to the right anterior cingulate cortex became weaker, and the right frontoinsular cortex to the right medial prefrontal cortex became stronger in migraine patients without aura. These changes suggested that the salience network may play a major role in the pathophysiological features of migraine patients without aura and helped us to synthesize previous findings into an aberrant network dynamical framework.

  12. Integral inventory control in spare parts networks with capacity restrictions

    NARCIS (Netherlands)

    Sleptchenko, Andrei

    2002-01-01

    Integral inventory control of repairable items in service networks can result in a significant gain compared to traditional local control mechanisms, in terms of both efficiency and customer service. Research on quantitative decision support models has yielded various useful results. However, in

  13. Dynamic state estimation for distribution networks with renewable energy integration

    NARCIS (Netherlands)

    Nguyen, P.H.; Venayagamoorthy, G.K.; Kling, W.L.; Ribeiro, P.F.

    2013-01-01

    The massive integration of variable and unpredictable Renewable Energy Sources (RES) and new types of load consumptions increases the dynamic and uncertain nature of the electricity grid. Emerging interests have focused on improving the monitoring capabilities of network operators so that they can

  14. An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

    Science.gov (United States)

    Mallik, Mrinmay Kumar

    2018-02-07

    Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that

  15. A complex regulatory network coordinating cell cycles during C. elegans development is revealed by a genome-wide RNAi screen.

    Science.gov (United States)

    Roy, Sarah H; Tobin, David V; Memar, Nadin; Beltz, Eleanor; Holmen, Jenna; Clayton, Joseph E; Chiu, Daniel J; Young, Laura D; Green, Travis H; Lubin, Isabella; Liu, Yuying; Conradt, Barbara; Saito, R Mako

    2014-02-28

    The development and homeostasis of multicellular animals requires precise coordination of cell division and differentiation. We performed a genome-wide RNA interference screen in Caenorhabditis elegans to reveal the components of a regulatory network that promotes developmentally programmed cell-cycle quiescence. The 107 identified genes are predicted to constitute regulatory networks that are conserved among higher animals because almost half of the genes are represented by clear human orthologs. Using a series of mutant backgrounds to assess their genetic activities, the RNA interference clones displaying similar properties were clustered to establish potential regulatory relationships within the network. This approach uncovered four distinct genetic pathways controlling cell-cycle entry during intestinal organogenesis. The enhanced phenotypes observed for animals carrying compound mutations attest to the collaboration between distinct mechanisms to ensure strict developmental regulation of cell cycles. Moreover, we characterized ubc-25, a gene encoding an E2 ubiquitin-conjugating enzyme whose human ortholog, UBE2Q2, is deregulated in several cancers. Our genetic analyses suggested that ubc-25 acts in a linear pathway with cul-1/Cul1, in parallel to pathways employing cki-1/p27 and lin-35/pRb to promote cell-cycle quiescence. Further investigation of the potential regulatory mechanism demonstrated that ubc-25 activity negatively regulates CYE-1/cyclin E protein abundance in vivo. Together, our results show that the ubc-25-mediated pathway acts within a complex network that integrates the actions of multiple molecular mechanisms to control cell cycles during development. Copyright © 2014 Roy et al.

  16. Local Health Integration Networks: Build on their purpose.

    Science.gov (United States)

    MacLeod, Hugh

    2015-11-01

    This article provides a high-level overview on the creation of Local Health Integration Networks (LHINs) and illustrates the complexities involved in their implementation. To understand regional structures such as LHINs, one must understand the context in which design and execution takes place. The article ends with a commentary on how Ontario is performing post-LHINs and discusses next steps. © 2015 The Canadian College of Health Leaders.

  17. Network motif-based identification of transcription factor-target gene relationships by integrating multi-source biological data

    Directory of Open Access Journals (Sweden)

    de los Reyes Benildo G

    2008-04-01

    Full Text Available Abstract Background Integrating data from multiple global assays and curated databases is essential to understand the spatio-temporal interactions within cells. Different experiments measure cellular processes at various widths and depths, while databases contain biological information based on established facts or published data. Integrating these complementary datasets helps infer a mutually consistent transcriptional regulatory network (TRN with strong similarity to the structure of the underlying genetic regulatory modules. Decomposing the TRN into a small set of recurring regulatory patterns, called network motifs (NM, facilitates the inference. Identifying NMs defined by specific transcription factors (TF establishes the framework structure of a TRN and allows the inference of TF-target gene relationship. This paper introduces a computational framework for utilizing data from multiple sources to infer TF-target gene relationships on the basis of NMs. The data include time course gene expression profiles, genome-wide location analysis data, binding sequence data, and gene ontology (GO information. Results The proposed computational framework was tested using gene expression data associated with cell cycle progression in yeast. Among 800 cell cycle related genes, 85 were identified as candidate TFs and classified into four previously defined NMs. The NMs for a subset of TFs are obtained from literature. Support vector machine (SVM classifiers were used to estimate NMs for the remaining TFs. The potential downstream target genes for the TFs were clustered into 34 biologically significant groups. The relationships between TFs and potential target gene clusters were examined by training recurrent neural networks whose topologies mimic the NMs to which the TFs are classified. The identified relationships between TFs and gene clusters were evaluated using the following biological validation and statistical analyses: (1 Gene set enrichment

  18. A Review on Radio-Over-Fiber Technology-Based Integrated (Optical/Wireless) Networks

    Science.gov (United States)

    Rajpal, Shivika; Goyal, Rakesh

    2017-06-01

    In the present paper, radio-over-fiber (RoF) technology has been proposed, which is the integration of the optical and radio networks. With a high transmission capacity, comparatively low cost and low attenuation, optical fiber provides an ideal solution for accomplishing the interconnections. In addition, a radio system enables the significant mobility, flexibility and easy access. Therefore, the system integration can meet the increasing demands of subscribers for voice, data and multimedia services that require the access network to support high data rates at any time and any place inexpensively. RoF has the potentiality to the backbone of the wireless access network and it has gained significant momentum in the last decade as a potential last-mile access scheme. This paper gives the comprehensive review of RoF technology used in the communication system. Concept, applications, advantages and limitations of RoF technology are also discussed in this paper.

  19. Ties that Bind: A Social Network Approach To Understanding Student Integration and Persistence.

    Science.gov (United States)

    Thomas, Scott L.

    2000-01-01

    This study used a social network paradigm to examine college student integration of 329 college freshmen at a private liberal arts college. Analysis of the structural aspects of students' on-campus associations found differential effects of various social network characteristics on student commitment and persistence. (DB)

  20. Mechanical behaviour of textile-reinforced thermoplastics with integrated sensor network components

    International Nuclear Information System (INIS)

    Hufenbach, W.; Adam, F.; Fischer, W.-J.; Kunadt, A.; Weck, D.

    2011-01-01

    Highlights: → Consideration of two types of integrated bus systems for textile-reinforced thermoplastics with embedded sensor networks. → Specimens with bus systems made of flexible printed circuit boards show good mechanical performance compared to the reference. → Inhomogeneous interface and reduced stiffnesses and strengths for specimens with bus systems basing on single copper wires. -- Abstract: The embedding of sensor networks into textile-reinforced thermoplastics enables the design of function-integrative lightweight components suitable for high volume production. In order to investigate the mechanical behaviour of such functionalised composites, two types of bus systems are selected as exemplary components of sensor networks. These elements are embedded into glass fibre-reinforced polypropylene (GF/PP) during the layup process of unconsolidated weft-knitted GF/PP-preforms. Two fibre orientations are considered and orthotropic composite plates are manufactured by hot pressing technology. Micrograph investigations and computer tomography analyses show different interface qualities between the thermoplastic composite and the two types of bus systems. Mechanical tests under tensile and flexural loading indicate a significant influence of the embedded bus system elements on the structural stiffness and strength.

  1. PLANNING THE NETWORKING OF ODL INSTITUTIONS FOR ESTABLISHING INTEGRATED DISTANCE EDUCATION SYSTEM IN INDIA

    Directory of Open Access Journals (Sweden)

    Pankaj KHANNA

    2011-07-01

    Full Text Available It is proposed to establish an Integrated Distance Education System in India by designing modern technology based information communication network, connecting all its ODL (Open and Distance Learning institutions to the headquarters of the ODL system in India. The principle roles to be performed by such a system have been discussed; according to which it would enable, educate and empower every member of the academic community including distance learners so as to provide them quality distance education. The connectivity between the ODL institutions would be achieved through the use of VPN (Virtual Private Network involving wireless networking and optical networking. Various benefits of providing VPN connectivity to the ODL institutions in India, such as cost effectiveness, security, and shared applications/services have also been discussed. Thus, the networking of all the ODL institutions in India would provide a national framework so as to build an excellent Integrated Distance Education System necessary for providing equity and quality distance education at national level.

  2. Thermal photovoltaic solar integrated system analysis using neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

    2007-07-01

    The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.

  3. [Network structures in biological systems].

    Science.gov (United States)

    Oleskin, A V

    2013-01-01

    Network structures (networks) that have been extensively studied in the humanities are characterized by cohesion, a lack of a central control unit, and predominantly fractal properties. They are contrasted with structures that contain a single centre (hierarchies) as well as with those whose elements predominantly compete with one another (market-type structures). As far as biological systems are concerned, their network structures can be subdivided into a number of types involving different organizational mechanisms. Network organization is characteristic of various structural levels of biological systems ranging from single cells to integrated societies. These networks can be classified into two main subgroups: (i) flat (leaderless) network structures typical of systems that are composed of uniform elements and represent modular organisms or at least possess manifest integral properties and (ii) three-dimensional, partly hierarchical structures characterized by significant individual and/or intergroup (intercaste) differences between their elements. All network structures include an element that performs structural, protective, and communication-promoting functions. By analogy to cell structures, this element is denoted as the matrix of a network structure. The matrix includes a material and an immaterial component. The material component comprises various structures that belong to the whole structure and not to any of its elements per se. The immaterial (ideal) component of the matrix includes social norms and rules regulating network elements' behavior. These behavioral rules can be described in terms of algorithms. Algorithmization enables modeling the behavior of various network structures, particularly of neuron networks and their artificial analogs.

  4. Flow control and routing techniques for integrated voice and data networks

    Science.gov (United States)

    Ibe, O. C.

    1981-10-01

    We consider a model of integrated voice and data networks. In this model the network flow problem is formulated as a convex optimization problem. The objective function comprises two types of cost functions: the congestion cost functions, which limit the average input traffic to values compatible with the network conditions; and the rate limitation cost functions, which ensure that all conversations are fairly treated. A joint flow control and routing algorithm is constructed which determines the routes for each conversation, and effects flow control by setting voice packet lengths and data input rates in a manner that achieves optimal tradeoff between each user's satisfaction and the cost of network congestion. An additional congestion control protocol is specified which could be used in conjunction with the algorithm to make the latter respond more dynamically to network congestion.

  5. Cancer signaling networks and their implications for personalized medicine

    DEFF Research Database (Denmark)

    Creixell, Pau

    Amongst the unique features of cancer cells perhaps the most crucial one is the change in the cellular decision-making process. While both non-cancer and cancer cells are constantly integrating different external cues that reach them and computing cellular decisions (e.g. proliferation or apoptosis......) based on the integration of these cues; this integration and consequently the cellular decisions taken by cancer cells are arguably very distinct from the decisions that would be expected from non-cancer cells. Since cellular signaling networks and its different states are the computational circuits...

  6. Motif statistics and spike correlations in neuronal networks

    International Nuclear Information System (INIS)

    Hu, Yu; Shea-Brown, Eric; Trousdale, James; Josić, Krešimir

    2013-01-01

    Motifs are patterns of subgraphs of complex networks. We studied the impact of such patterns of connectivity on the level of correlated, or synchronized, spiking activity among pairs of cells in a recurrent network of integrate and fire neurons. For a range of network architectures, we find that the pairwise correlation coefficients, averaged across the network, can be closely approximated using only three statistics of network connectivity. These are the overall network connection probability and the frequencies of two second order motifs: diverging motifs, in which one cell provides input to two others, and chain motifs, in which two cells are connected via a third intermediary cell. Specifically, the prevalence of diverging and chain motifs tends to increase correlation. Our method is based on linear response theory, which enables us to express spiking statistics using linear algebra, and a resumming technique, which extrapolates from second order motifs to predict the overall effect of coupling on network correlation. Our motif-based results seek to isolate the effect of network architecture perturbatively from a known network state. (paper)

  7. Improvement of Bioactive Compound Classification through Integration of Orthogonal Cell-Based Biosensing Methods

    Directory of Open Access Journals (Sweden)

    Goran N. Jovanovic

    2007-01-01

    Full Text Available Lack of specificity for different classes of chemical and biological agents, and false positives and negatives, can limit the range of applications for cell-based biosensors. This study suggests that the integration of results from algal cells (Mesotaenium caldariorum and fish chromatophores (Betta splendens improves classification efficiency and detection reliability. Cells were challenged with paraquat, mercuric chloride, sodium arsenite and clonidine. The two detection systems were independently investigated for classification of the toxin set by performing discriminant analysis. The algal system correctly classified 72% of the bioactive compounds, whereas the fish chromatophore system correctly classified 68%. The combined classification efficiency was 95%. The algal sensor readout is based on fluorescence measurements of changes in the energy producing pathways of photosynthetic cells, whereas the response from fish chromatophores was quantified using optical density. Change in optical density reflects interference with the functioning of cellular signal transduction networks. Thus, algal cells and fish chromatophores respond to the challenge agents through sufficiently different mechanisms of action to be considered orthogonal.

  8. Social network approaches to leadership: an integrative conceptual review.

    Science.gov (United States)

    Carter, Dorothy R; DeChurch, Leslie A; Braun, Michael T; Contractor, Noshir S

    2015-05-01

    Contemporary definitions of leadership advance a view of the phenomenon as relational, situated in specific social contexts, involving patterned emergent processes, and encompassing both formal and informal influence. Paralleling these views is a growing interest in leveraging social network approaches to study leadership. Social network approaches provide a set of theories and methods with which to articulate and investigate, with greater precision and rigor, the wide variety of relational perspectives implied by contemporary leadership theories. Our goal is to advance this domain through an integrative conceptual review. We begin by answering the question of why-Why adopt a network approach to study leadership? Then, we offer a framework for organizing prior research. Our review reveals 3 areas of research, which we term: (a) leadership in networks, (b) leadership as networks, and (c) leadership in and as networks. By clarifying the conceptual underpinnings, key findings, and themes within each area, this review serves as a foundation for future inquiry that capitalizes on, and programmatically builds upon, the insights of prior work. Our final contribution is to advance an agenda for future research that harnesses the confluent ideas at the intersection of leadership in and as networks. Leadership in and as networks represents a paradigm shift in leadership research-from an emphasis on the static traits and behaviors of formal leaders whose actions are contingent upon situational constraints, toward an emphasis on the complex and patterned relational processes that interact with the embedding social context to jointly constitute leadership emergence and effectiveness. (c) 2015 APA, all rights reserved.

  9. QKD-Based Secured Burst Integrity Design for Optical Burst Switched Networks

    Science.gov (United States)

    Balamurugan, A. M.; Sivasubramanian, A.; Parvathavarthini, B.

    2016-03-01

    The field of optical transmission has undergone numerous advancements and is still being researched mainly due to the fact that optical data transmission can be done at enormous speeds. It is quite evident that people prefer optical communication when it comes to large amount of data involving its transmission. The concept of switching in networks has matured enormously with several researches, architecture to implement and methods starting with Optical circuit switching to Optical Burst Switching. Optical burst switching is regarded as viable solution for switching bursts over networks but has several security vulnerabilities. However, this work exploited the security issues associated with Optical Burst Switching with respect to integrity of burst. This proposed Quantum Key based Secure Hash Algorithm (QKBSHA-512) with enhanced compression function design provides better avalanche effect over the conventional integrity algorithms.

  10. Integration of metabolome data with metabolic networks reveals reporter reactions

    DEFF Research Database (Denmark)

    Çakir, Tunahan; Patil, Kiran Raosaheb; Önsan, Zeynep Ilsen

    2006-01-01

    Interpreting quantitative metabolome data is a difficult task owing to the high connectivity in metabolic networks and inherent interdependency between enzymatic regulation, metabolite levels and fluxes. Here we present a hypothesis-driven algorithm for the integration of such data with metabolic...... network topology. The algorithm thus enables identification of reporter reactions, which are reactions where there are significant coordinated changes in the level of surrounding metabolites following environmental/genetic perturbations. Applicability of the algorithm is demonstrated by using data from...... is measured. By combining the results with transcriptome data, we further show that it is possible to infer whether the reactions are hierarchically or metabolically regulated. Hereby, the reported approach represents an attempt to map different layers of regulation within metabolic networks through...

  11. Regulation of Cell Wall Biogenesis in Saccharomyces cerevisiae: The Cell Wall Integrity Signaling Pathway

    Science.gov (United States)

    Levin, David E.

    2011-01-01

    The yeast cell wall is a strong, but elastic, structure that is essential not only for the maintenance of cell shape and integrity, but also for progression through the cell cycle. During growth and morphogenesis, and in response to environmental challenges, the cell wall is remodeled in a highly regulated and polarized manner, a process that is principally under the control of the cell wall integrity (CWI) signaling pathway. This pathway transmits wall stress signals from the cell surface to the Rho1 GTPase, which mobilizes a physiologic response through a variety of effectors. Activation of CWI signaling regulates the production of various carbohydrate polymers of the cell wall, as well as their polarized delivery to the site of cell wall remodeling. This review article centers on CWI signaling in Saccharomyces cerevisiae through the cell cycle and in response to cell wall stress. The interface of this signaling pathway with other pathways that contribute to the maintenance of cell wall integrity is also discussed. PMID:22174182

  12. Data Portal for the Library of Integrated Network-based Cellular Signatures (LINCS) program: integrated access to diverse large-scale cellular perturbation response data

    Science.gov (United States)

    Koleti, Amar; Terryn, Raymond; Stathias, Vasileios; Chung, Caty; Cooper, Daniel J; Turner, John P; Vidović, Dušica; Forlin, Michele; Kelley, Tanya T; D’Urso, Alessandro; Allen, Bryce K; Torre, Denis; Jagodnik, Kathleen M; Wang, Lily; Jenkins, Sherry L; Mader, Christopher; Niu, Wen; Fazel, Mehdi; Mahi, Naim; Pilarczyk, Marcin; Clark, Nicholas; Shamsaei, Behrouz; Meller, Jarek; Vasiliauskas, Juozas; Reichard, John; Medvedovic, Mario; Ma’ayan, Avi; Pillai, Ajay

    2018-01-01

    Abstract The Library of Integrated Network-based Cellular Signatures (LINCS) program is a national consortium funded by the NIH to generate a diverse and extensive reference library of cell-based perturbation-response signatures, along with novel data analytics tools to improve our understanding of human diseases at the systems level. In contrast to other large-scale data generation efforts, LINCS Data and Signature Generation Centers (DSGCs) employ a wide range of assay technologies cataloging diverse cellular responses. Integration of, and unified access to LINCS data has therefore been particularly challenging. The Big Data to Knowledge (BD2K) LINCS Data Coordination and Integration Center (DCIC) has developed data standards specifications, data processing pipelines, and a suite of end-user software tools to integrate and annotate LINCS-generated data, to make LINCS signatures searchable and usable for different types of users. Here, we describe the LINCS Data Portal (LDP) (http://lincsportal.ccs.miami.edu/), a unified web interface to access datasets generated by the LINCS DSGCs, and its underlying database, LINCS Data Registry (LDR). LINCS data served on the LDP contains extensive metadata and curated annotations. We highlight the features of the LDP user interface that is designed to enable search, browsing, exploration, download and analysis of LINCS data and related curated content. PMID:29140462

  13. Integrated System for Performance Monitoring of ATLAS TDAQ Network

    CERN Document Server

    Savu, D; The ATLAS collaboration; Martin, B; Sjoen, R; Batraneanu, S; Stancu, S

    2010-01-01

    The ATLAS TDAQ Network consists of three separate networks spanning four levels of the experimental building. Over 200 edge switches and 5 multi-blade chassis routers are used to interconnect 2000 processors, adding up to more than 7000 high speed interfaces. In order to substantially speed-up ad-hoc and post mortem analysis, a scalable, yet flexible, integrated system for monitoring both network statistics and environmental conditions, processor parameters and data taking characteristics was required. For successful up-to-the-minute monitoring, information from many SNMP compliant devices, independent databases and custom APIs was gathered, stored and displayed in an optimal way. Easy navigation and compact aggregation of multiple data sources were the main requirements; characteristics not found in any of the tested products, either open-source or commercial. This paper describes how performance, scalability and display issues were addressed and what challenges the project faced during development and deplo...

  14. Trade Integration and Trade Imbalances in the European Union: A Network Perspective

    Science.gov (United States)

    Krings, Gautier M.; Carpantier, Jean-François; Delvenne, Jean-Charles

    2014-01-01

    We study the ever more integrated and ever more unbalanced trade relationships between European countries. To better capture the complexity of economic networks, we propose two global measures that assess the trade integration and the trade imbalances of the European countries. These measures are the network (or indirect) counterparts to traditional (or direct) measures such as the trade-to-GDP (Gross Domestic Product) and trade deficit-to-GDP ratios. Our indirect tools account for the European inter-country trade structure and follow (i) a decomposition of the global trade flow into elementary flows that highlight the long-range dependencies between exporting and importing economies and (ii) the commute-time distance for trade integration, which measures the impact of a perturbation in the economy of a country on another country, possibly through intermediate partners by domino effect. Our application addresses the impact of the launch of the Euro. We find that the indirect imbalance measures better identify the countries ultimately bearing deficits and surpluses, by neutralizing the impact of trade transit countries, such as the Netherlands. Among others, we find that ultimate surpluses of Germany are quite concentrated in only three partners. We also show that for some countries, the direct and indirect measures of trade integration diverge, thereby revealing that these countries (e.g. Greece and Portugal) trade to a smaller extent with countries considered as central in the European Union network. PMID:24465381

  15. Trade integration and trade imbalances in the European Union: a network perspective.

    Science.gov (United States)

    Krings, Gautier M; Carpantier, Jean-François; Delvenne, Jean-Charles

    2014-01-01

    We study the ever more integrated and ever more unbalanced trade relationships between European countries. To better capture the complexity of economic networks, we propose two global measures that assess the trade integration and the trade imbalances of the European countries. These measures are the network (or indirect) counterparts to traditional (or direct) measures such as the trade-to-GDP (Gross Domestic Product) and trade deficit-to-GDP ratios. Our indirect tools account for the European inter-country trade structure and follow (i) a decomposition of the global trade flow into elementary flows that highlight the long-range dependencies between exporting and importing economies and (ii) the commute-time distance for trade integration, which measures the impact of a perturbation in the economy of a country on another country, possibly through intermediate partners by domino effect. Our application addresses the impact of the launch of the Euro. We find that the indirect imbalance measures better identify the countries ultimately bearing deficits and surpluses, by neutralizing the impact of trade transit countries, such as the Netherlands. Among others, we find that ultimate surpluses of Germany are quite concentrated in only three partners. We also show that for some countries, the direct and indirect measures of trade integration diverge, thereby revealing that these countries (e.g. Greece and Portugal) trade to a smaller extent with countries considered as central in the European Union network.

  16. Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases.

    Science.gov (United States)

    Peters, D T J M; Raab, J; Grêaux, K M; Stronks, K; Harting, J

    2017-12-01

    Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as addressing environmental determinants of health. This study examines these relations in different phases of the policy process. A multiple-case study was performed on four public health-related policy networks. Using a snowball method among network actors, overall and sub-networks per policy phase were identified and the policy sector of each actor was assigned. To operationalise the outcome variable, interventions were classified by the proportion of environmental determinants they addressed. In the overall networks, no relation was found between structural network characteristics and network performance. In most effective cases, the policy development sub-networks were characterised by integration with less interrelations between actors (low cohesion), more equally distributed distances between the actors (low closeness centralisation), and horizontal integration in inter-sectoral cliques. The most effective case had non-public health central actors with less connections in all sub-networks. The results suggest that, to address environmental determinants of health, sub-networks should be inter-sectorally composed in the policy development rather than in the intervention development and implementation phases, and that policy development actors should have the opportunity to connect with other actors, without strong direction from a central actor. Copyright © 2017 Elsevier B.V. All rights reserved.

  17. Magnets and Seekers: A Network Perspective on Academic Integration inside Two Residential Communities

    Science.gov (United States)

    Smith, Rachel A.

    2015-01-01

    Residential learning communities aim to foster increased academic and social integration, ideally leading to greater student success. However, the concept of academic integration is often conceptualized and measured at the individual level, rather than the theoretically more consistent community level. Network analysis provides a paradigm and…

  18. Neuronal oscillations form parietal/frontal networks during contour integration.

    Science.gov (United States)

    Castellano, Marta; Plöchl, Michael; Vicente, Raul; Pipa, Gordon

    2014-01-01

    The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13-30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites.

  19. Exotic plant species receive adequate pollinator service despite variable integration into plant-pollinator networks.

    Science.gov (United States)

    Thompson, Amibeth H; Knight, Tiffany M

    2018-05-01

    Both exotic and native plant species rely on insect pollinators for reproductive success, and yet few studies have evaluated whether and how exotic plant species receive services from native pollinators for successful reproduction in their introduced range. Plant species are expected to successfully reproduce in their exotic range if they have low reliance on animal pollinators or if they successfully integrate themselves into resident plant-pollinator networks. Here, we quantify the breeding system, network integration, and pollen limitation for ten focal exotic plant species in North America. Most exotic plant species relied on animal pollinators for reproduction, and these species varied in their network integration. However, plant reproduction was limited by pollen receipt for only one plant species. Our results demonstrate that even poorly integrated exotic plant species can still have high pollination service and high reproductive success. The comprehensive framework considered here provides a method to consider the contribution of plant breeding systems and the pollinator community to pollen limitation, and can be applied to future studies to provide a more synthetic understanding of the factors that determine reproductive success of exotic plant species.

  20. Teaching Students How to Integrate and Assess Social Networking Tools in Marketing Communications

    Science.gov (United States)

    Schlee, Regina Pefanis; Harich, Katrin R.

    2013-01-01

    This research is based on two studies that focus on teaching students how to integrate and assess social networking tools in marketing communications. Study 1 examines how students in marketing classes utilize social networking tools and explores their attitudes regarding the use of such tools for marketing communications. Study 2 focuses on an…

  1. The brain as a "hyper-network": the key role of neural networks as main producers of the integrated brain actions especially via the "broadcasted" neuroconnectomics.

    Science.gov (United States)

    Agnati, Luigi F; Marcoli, Manuela; Maura, Guido; Woods, Amina; Guidolin, Diego

    2018-06-01

    Investigations of brain complex integrative actions should consider beside neural networks, glial, extracellular molecular, and fluid channels networks. The present paper proposes that all these networks are assembled into the brain hyper-network that has as fundamental components, the tetra-partite synapses, formed by neural, glial, and extracellular molecular networks. Furthermore, peri-synaptic astrocytic processes by modulating the perviousness of extracellular fluid channels control the signals impinging on the tetra-partite synapses. It has also been surmised that global signalling via astrocytes networks and highly pervasive signals, such as electromagnetic fields (EMFs), allow the appropriate integration of the various networks especially at crucial nodes level, the tetra-partite synapses. As a matter of fact, it has been shown that astrocytes can form gap-junction-coupled syncytia allowing intercellular communication characterised by a rapid and possibly long-distance transfer of signals. As far as the EMFs are concerned, the concept of broadcasted neuroconnectomics (BNC) has been introduced to describe highly pervasive signals involved in resetting the information handling of brain networks at various miniaturisation levels. In other words, BNC creates, thanks to the EMFs, generated especially by neurons, different assemblages among the various networks forming the brain hyper-network. Thus, it is surmised that neuronal networks are the "core components" of the brain hyper-network that has as special "nodes" the multi-facet tetra-partite synapses. Furthermore, it is suggested that investigations on the functional plasticity of multi-partite synapses in response to BNC can be the background for a new understanding and perhaps a new modelling of brain morpho-functional organisation and integrative actions.

  2. Brain networks engaged in audiovisual integration during speech perception revealed by persistent homology-based network filtration.

    Science.gov (United States)

    Kim, Heejung; Hahm, Jarang; Lee, Hyekyoung; Kang, Eunjoo; Kang, Hyejin; Lee, Dong Soo

    2015-05-01

    The human brain naturally integrates audiovisual information to improve speech perception. However, in noisy environments, understanding speech is difficult and may require much effort. Although the brain network is supposed to be engaged in speech perception, it is unclear how speech-related brain regions are connected during natural bimodal audiovisual or unimodal speech perception with counterpart irrelevant noise. To investigate the topological changes of speech-related brain networks at all possible thresholds, we used a persistent homological framework through hierarchical clustering, such as single linkage distance, to analyze the connected component of the functional network during speech perception using functional magnetic resonance imaging. For speech perception, bimodal (audio-visual speech cue) or unimodal speech cues with counterpart irrelevant noise (auditory white-noise or visual gum-chewing) were delivered to 15 subjects. In terms of positive relationship, similar connected components were observed in bimodal and unimodal speech conditions during filtration. However, during speech perception by congruent audiovisual stimuli, the tighter couplings of left anterior temporal gyrus-anterior insula component and right premotor-visual components were observed than auditory or visual speech cue conditions, respectively. Interestingly, visual speech is perceived under white noise by tight negative coupling in the left inferior frontal region-right anterior cingulate, left anterior insula, and bilateral visual regions, including right middle temporal gyrus, right fusiform components. In conclusion, the speech brain network is tightly positively or negatively connected, and can reflect efficient or effortful processes during natural audiovisual integration or lip-reading, respectively, in speech perception.

  3. From in silico astrocyte cell models to neuron-astrocyte network models: A review.

    Science.gov (United States)

    Oschmann, Franziska; Berry, Hugues; Obermayer, Klaus; Lenk, Kerstin

    2018-01-01

    The idea that astrocytes may be active partners in synaptic information processing has recently emerged from abundant experimental reports. Because of their spatial proximity to neurons and their bidirectional communication with them, astrocytes are now considered as an important third element of the synapse. Astrocytes integrate and process synaptic information and by doing so generate cytosolic calcium signals that are believed to reflect neuronal transmitter release. Moreover, they regulate neuronal information transmission by releasing gliotransmitters into the synaptic cleft affecting both pre- and postsynaptic receptors. Concurrent with the first experimental reports of the astrocytic impact on neural network dynamics, computational models describing astrocytic functions have been developed. In this review, we give an overview over the published computational models of astrocytic functions, from single-cell dynamics to the tripartite synapse level and network models of astrocytes and neurons. Copyright © 2017 Elsevier Inc. All rights reserved.

  4. Cooperation among cancer cells as public goods games on Voronoi networks.

    Science.gov (United States)

    Archetti, Marco

    2016-05-07

    Cancer cells produce growth factors that diffuse and sustain tumour proliferation, a form of cooperation that can be studied using mathematical models of public goods in the framework of evolutionary game theory. Cell populations, however, form heterogeneous networks that cannot be described by regular lattices or scale-free networks, the types of graphs generally used in the study of cooperation. To describe the dynamics of growth factor production in populations of cancer cells, I study public goods games on Voronoi networks, using a range of non-linear benefits that account for the known properties of growth factors, and different types of diffusion gradients. The results are surprisingly similar to those obtained on regular graphs and different from results on scale-free networks, revealing that network heterogeneity per se does not promote cooperation when public goods diffuse beyond one-step neighbours. The exact shape of the diffusion gradient is not crucial, however, whereas the type of non-linear benefit is an essential determinant of the dynamics. Public goods games on Voronoi networks can shed light on intra-tumour heterogeneity, the evolution of resistance to therapies that target growth factors, and new types of cell therapy. Copyright © 2016 Elsevier Ltd. All rights reserved.

  5. CRCHD Integrated Networks

    Science.gov (United States)

    INB supports two network-based programs—the National Outreach Network (NON) and the Geographic Management of Cancer Health Disparities Program (GMaP)—as well as advising on women’s health and sexual and gender minority opportunities within and across the NCI.

  6. Integrated Service Provisioning in an Ipv6 over ATM Research Network

    Energy Technology Data Exchange (ETDEWEB)

    Eli Dart; Helen Chen; Jerry Friesen; Jim Brandt; Jim Hutchins; Perry Robertson

    1999-02-01

    During the past few years, the worldwide Internet has grown at a phenomenal rate, which has spurred the proposal of innovative network technologies to support the fast, efficient and low-latency transport of a wide spectrum of multimedia traffic types. Existing network infrastructures have been plagued by their inability to provide for real-time application traffic as well as their general lack of resources and resilience to congestion. This work proposes to address these issues by implementing a prototype high-speed network infrastructure consisting of Internet Protocol Version 6 (IPv6) on top of an Asynchronous Transfer Mode (ATM) transport medium. Since ATM is connection-oriented whereas IP uses a connection-less paradigm, the efficient integration of IPv6 over ATM is especially challenging and has generated much interest in the research community. We propose, in collaboration with an industry partner, to implement IPv6 over ATM using a unique approach that integrates IP over fast A TM hardware while still preserving IP's connection-less paradigm. This is achieved by replacing ATM's control software with IP's routing code and by caching IP's forwarding decisions in ATM's VPI/VCI translation tables. Prototype ''VR'' and distributed-parallel-computing applications will also be developed to exercise the realtime capability of our IPv6 over ATM network.

  7. Design principles in biological networks

    Science.gov (United States)

    Goyal, Sidhartha

    Much of biology emerges from networks of interactions. Even in a single bacterium such as Escherichia coli, there are hundreds of coexisting gene and protein networks. Although biological networks are the outcome of evolution, various physical and biological constraints limit their functional capacity. The focus of this thesis is to understand how functional constraints such as optimal growth in mircoorganisms and information flow in signaling pathways shape the metabolic network of bacterium E. coli and the quorum sensing network of marine bacterium Vibrio harveyi, respectively. Metabolic networks convert basic elemental sources into complex building-blocks eventually leading to cell's growth. Therefore, typically, metabolic pathways are often coupled both by the use of a common substrate and by stoichiometric utilization of their products for cell growth. We showed that such a coupled network with product-feedback inhibition may exhibit limit-cycle oscillations which arise via a Hopf bifurcation. Furthermore, we analyzed several representative metabolic modules and find that, in all cases, simple product-feedback inhibition allows nearly optimal growth, in agreement with the predicted growth-rate by the flux-balance analysis (FBA). Bacteria have fascinating and diverse social lives. They display coordinated group behaviors regulated by quorum sensing (QS) systems. The QS circuit of V. harveyi integrates and funnels different ecological information through a common phosphorelay cascade to a set of small regulatory RNAs (sRNAs) that enables collective behavior. We analyzed the signaling properties and information flow in the QS circuit, which provides a model for information flow in signaling networks more generally. A comparative study of post-transcriptional and conventional transcriptional regulation suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. Furthermore, we develop a new framework for analyzing signal

  8. Altered Integration of Structural Covariance Networks in Young Children With Type 1 Diabetes.

    Science.gov (United States)

    Hosseini, S M Hadi; Mazaika, Paul; Mauras, Nelly; Buckingham, Bruce; Weinzimer, Stuart A; Tsalikian, Eva; White, Neil H; Reiss, Allan L

    2016-11-01

    Type 1 diabetes mellitus (T1D), one of the most frequent chronic diseases in children, is associated with glucose dysregulation that contributes to an increased risk for neurocognitive deficits. While there is a bulk of evidence regarding neurocognitive deficits in adults with T1D, little is known about how early-onset T1D affects neural networks in young children. Recent data demonstrated widespread alterations in regional gray matter and white matter associated with T1D in young children. These widespread neuroanatomical changes might impact the organization of large-scale brain networks. In the present study, we applied graph-theoretical analysis to test whether the organization of structural covariance networks in the brain for a cohort of young children with T1D (N = 141) is altered compared to healthy controls (HC; N = 69). While the networks in both groups followed a small world organization-an architecture that is simultaneously highly segregated and integrated-the T1D network showed significantly longer path length compared with HC, suggesting reduced global integration of brain networks in young children with T1D. In addition, network robustness analysis revealed that the T1D network model showed more vulnerability to neural insult compared with HC. These results suggest that early-onset T1D negatively impacts the global organization of structural covariance networks and influences the trajectory of brain development in childhood. This is the first study to examine structural covariance networks in young children with T1D. Improving glycemic control for young children with T1D might help prevent alterations in brain networks in this population. Hum Brain Mapp 37:4034-4046, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. Construction and modelling of an inducible positive feedback loop stably integrated in a mammalian cell-line.

    Directory of Open Access Journals (Sweden)

    Velia Siciliano

    2011-06-01

    Full Text Available Understanding the relationship between topology and dynamics of transcriptional regulatory networks in mammalian cells is essential to elucidate the biology of complex regulatory and signaling pathways. Here, we characterised, via a synthetic biology approach, a transcriptional positive feedback loop (PFL by generating a clonal population of mammalian cells (CHO carrying a stable integration of the construct. The PFL network consists of the Tetracycline-controlled transactivator (tTA, whose expression is regulated by a tTA responsive promoter (CMV-TET, thus giving rise to a positive feedback. The same CMV-TET promoter drives also the expression of a destabilised yellow fluorescent protein (d2EYFP, thus the dynamic behaviour can be followed by time-lapse microscopy. The PFL network was compared to an engineered version of the network lacking the positive feedback loop (NOPFL, by expressing the tTA mRNA from a constitutive promoter. Doxycycline was used to repress tTA activation (switch off, and the resulting changes in fluorescence intensity for both the PFL and NOPFL networks were followed for up to 43 h. We observed a striking difference in the dynamics of the PFL and NOPFL networks. Using non-linear dynamical models, able to recapitulate experimental observations, we demonstrated a link between network topology and network dynamics. Namely, transcriptional positive autoregulation can significantly slow down the "switch off" times, as compared to the non-autoregulated system. Doxycycline concentration can modulate the response times of the PFL, whereas the NOPFL always switches off with the same dynamics. Moreover, the PFL can exhibit bistability for a range of Doxycycline concentrations. Since the PFL motif is often found in naturally occurring transcriptional and signaling pathways, we believe our work can be instrumental to characterise their behaviour.

  10. Construction and modelling of an inducible positive feedback loop stably integrated in a mammalian cell-line.

    Science.gov (United States)

    Siciliano, Velia; Menolascina, Filippo; Marucci, Lucia; Fracassi, Chiara; Garzilli, Immacolata; Moretti, Maria Nicoletta; di Bernardo, Diego

    2011-06-01

    Understanding the relationship between topology and dynamics of transcriptional regulatory networks in mammalian cells is essential to elucidate the biology of complex regulatory and signaling pathways. Here, we characterised, via a synthetic biology approach, a transcriptional positive feedback loop (PFL) by generating a clonal population of mammalian cells (CHO) carrying a stable integration of the construct. The PFL network consists of the Tetracycline-controlled transactivator (tTA), whose expression is regulated by a tTA responsive promoter (CMV-TET), thus giving rise to a positive feedback. The same CMV-TET promoter drives also the expression of a destabilised yellow fluorescent protein (d2EYFP), thus the dynamic behaviour can be followed by time-lapse microscopy. The PFL network was compared to an engineered version of the network lacking the positive feedback loop (NOPFL), by expressing the tTA mRNA from a constitutive promoter. Doxycycline was used to repress tTA activation (switch off), and the resulting changes in fluorescence intensity for both the PFL and NOPFL networks were followed for up to 43 h. We observed a striking difference in the dynamics of the PFL and NOPFL networks. Using non-linear dynamical models, able to recapitulate experimental observations, we demonstrated a link between network topology and network dynamics. Namely, transcriptional positive autoregulation can significantly slow down the "switch off" times, as compared to the non-autoregulated system. Doxycycline concentration can modulate the response times of the PFL, whereas the NOPFL always switches off with the same dynamics. Moreover, the PFL can exhibit bistability for a range of Doxycycline concentrations. Since the PFL motif is often found in naturally occurring transcriptional and signaling pathways, we believe our work can be instrumental to characterise their behaviour.

  11. Hydrogen and fuel cell research networking in Ontario

    Energy Technology Data Exchange (ETDEWEB)

    Peppley, B.A. [Queen' s-RMC Fuel Cell Research Centre, Kingston, ON (Canada)

    2009-07-01

    This presentation reviewed the activities of the Ontario Fuel Cell Research and Innovation Network since its launch in 2006. Funded by the Ontario Ministry of Research and Innovation, the project involves 17 academic researchers from 8 universities and is supported by 8 industrial partners. The group of researchers has made progress in supporting the developing fuel cell industry in Ontario and in Canada. Their work has the potential to help deploy the province's automotive-oriented manufacturing sector in directions that address the issues of clean air and climate change. New initiatives in the development of hydrogen and fuel cell technologies are instrumental in expanding this network to leverage new business activities in the post financial crisis period. These activities are expected to result in economic benefits for job and economic growth.

  12. Ground rules of the pluripotency gene regulatory network.

    KAUST Repository

    Li, Mo

    2017-01-03

    Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

  13. Ground rules of the pluripotency gene regulatory network.

    KAUST Repository

    Li, Mo; Belmonte, Juan Carlos Izpisua

    2017-01-01

    Pluripotency is a state that exists transiently in the early embryo and, remarkably, can be recapitulated in vitro by deriving embryonic stem cells or by reprogramming somatic cells to become induced pluripotent stem cells. The state of pluripotency, which is stabilized by an interconnected network of pluripotency-associated genes, integrates external signals and exerts control over the decision between self-renewal and differentiation at the transcriptional, post-transcriptional and epigenetic levels. Recent evidence of alternative pluripotency states indicates the regulatory flexibility of this network. Insights into the underlying principles of the pluripotency network may provide unprecedented opportunities for studying development and for regenerative medicine.

  14. INTEGRAL INDEX OF OPERATION QUALITY FOR EVALUATION OF IMPACT OF DISTRIBUTIVE GENERATION SOURCES ON ELECTRIC NETWORK MODES

    Directory of Open Access Journals (Sweden)

    Petro D. Lezhniuk

    2017-06-01

    Full Text Available Method of operation quality evaluation of electric network, comprising renewable sources of energy (RSE is considered. Integral index that enables to evaluate the impact of RSE on energy losses and its quality as well as balance reliability in electric network is suggested. Mathematical model is constructed, taking into account the assumption that electric network with RSE may be in various operation modes, characterized by different technical economic indices. To determine the integral index of operation quality of electric network with RSE in all possible states tools of Markov processes theory and criterial method are used.

  15. Sparse Representation Based Range-Doppler Processing for Integrated OFDM Radar-Communication Networks

    Directory of Open Access Journals (Sweden)

    Bo Kong

    2017-01-01

    Full Text Available In an integrated radar-communication network, multiuser access techniques with minimal performance degradation and without range-Doppler ambiguities are required, especially in a dense user environment. In this paper, a multiuser access scheme with random subcarrier allocation mechanism is proposed for orthogonal frequency division multiplexing (OFDM based integrated radar-communication networks. The expression of modulation Symbol-Domain method combined with sparse representation (SR for range-Doppler estimation is introduced and a parallel reconstruction algorithm is employed. The radar target detection performance is improved with less spectrum occupation. Additionally, a Doppler frequency detector is exploited to decrease the computational complexity. Numerical simulations show that the proposed method outperforms the traditional modulation Symbol-Domain method under ideal and realistic nonideal scenarios.

  16. Improvements to Integrated Tradespace Analysis of Communications Architectures (ITACA) Network Loading Analysis Tool

    Science.gov (United States)

    Lee, Nathaniel; Welch, Bryan W.

    2018-01-01

    NASA's SCENIC project aims to simplify and reduce the cost of space mission planning by replicating the analysis capabilities of commercially licensed software which are integrated with relevant analysis parameters specific to SCaN assets and SCaN supported user missions. SCENIC differs from current tools that perform similar analyses in that it 1) does not require any licensing fees, 2) will provide an all-in-one package for various analysis capabilities that normally requires add-ons or multiple tools to complete. As part of SCENIC's capabilities, the ITACA network loading analysis tool will be responsible for assessing the loading on a given network architecture and generating a network service schedule. ITACA will allow users to evaluate the quality of service of a given network architecture and determine whether or not the architecture will satisfy the mission's requirements. ITACA is currently under development, and the following improvements were made during the fall of 2017: optimization of runtime, augmentation of network asset pre-service configuration time, augmentation of Brent's method of root finding, augmentation of network asset FOV restrictions, augmentation of mission lifetimes, and the integration of a SCaN link budget calculation tool. The improvements resulted in (a) 25% reduction in runtime, (b) more accurate contact window predictions when compared to STK(Registered Trademark) contact window predictions, and (c) increased fidelity through the use of specific SCaN asset parameters.

  17. The Knowledge-Integrated Network Biomarkers Discovery for Major Adverse Cardiac Events

    Science.gov (United States)

    Jin, Guangxu; Zhou, Xiaobo; Wang, Honghui; Zhao, Hong; Cui, Kemi; Zhang, Xiang-Sun; Chen, Luonan; Hazen, Stanley L.; Li, King; Wong, Stephen T. C.

    2010-01-01

    The mass spectrometry (MS) technology in clinical proteomics is very promising for discovery of new biomarkers for diseases management. To overcome the obstacles of data noises in MS analysis, we proposed a new approach of knowledge-integrated biomarker discovery using data from Major Adverse Cardiac Events (MACE) patients. We first built up a cardiovascular-related network based on protein information coming from protein annotations in Uniprot, protein–protein interaction (PPI), and signal transduction database. Distinct from the previous machine learning methods in MS data processing, we then used statistical methods to discover biomarkers in cardiovascular-related network. Through the tradeoff between known protein information and data noises in mass spectrometry data, we finally could firmly identify those high-confident biomarkers. Most importantly, aided by protein–protein interaction network, that is, cardiovascular-related network, we proposed a new type of biomarkers, that is, network biomarkers, composed of a set of proteins and the interactions among them. The candidate network biomarkers can classify the two groups of patients more accurately than current single ones without consideration of biological molecular interaction. PMID:18665624

  18. Cell Deployment Optimization for Cloud Radio Access Networks using Teletraffic Theory

    DEFF Research Database (Denmark)

    Popovska Avramova, Andrijana; Christiansen, Henrik Lehrmann; Iversen, Villy Bæk

    2015-01-01

    Cloud Radio Access Network (C-RAN) is a new mobile radio access network design based on centralized and pooled processing. It offers potential cost savings by utilizing the so-called tidal effect due to user mobility in cellular networks. This paper provides a quantitative analysis...... to dynamically re-assign cells to a pool of baseband units. The re-assignment is based on the cell load and traffic characteristics such that effective utilization of the baseband resources is assured....

  19. Silicon-based optical integrated circuits for terabit communication networks

    International Nuclear Information System (INIS)

    Svidzinsky, K K

    2003-01-01

    A brief review is presented of the development of silicon-based optical integrated circuits used as components in modern all-optical communication networks with the terabit-per-second transmission capacity. The designs and technologies for manufacturing these circuits are described and the problems related to their development and application in WDM communication systems are considered. (special issue devoted to the memory of academician a m prokhorov)

  20. Simulation electromagnetic scattering on bodies through integral equation and neural networks methods

    Science.gov (United States)

    Lvovich, I. Ya; Preobrazhenskiy, A. P.; Choporov, O. N.

    2018-05-01

    The paper deals with the issue of electromagnetic scattering on a perfectly conducting diffractive body of a complex shape. Performance calculation of the body scattering is carried out through the integral equation method. Fredholm equation of the second time was used for calculating electric current density. While solving the integral equation through the moments method, the authors have properly described the core singularity. The authors determined piecewise constant functions as basic functions. The chosen equation was solved through the moments method. Within the Kirchhoff integral approach it is possible to define the scattered electromagnetic field, in some way related to obtained electrical currents. The observation angles sector belongs to the area of the front hemisphere of the diffractive body. To improve characteristics of the diffractive body, the authors used a neural network. All the neurons contained a logsigmoid activation function and weighted sums as discriminant functions. The paper presents the matrix of weighting factors of the connectionist model, as well as the results of the optimized dimensions of the diffractive body. The paper also presents some basic steps in calculation technique of the diffractive bodies, based on the combination of integral equation and neural networks methods.

  1. An integrated artificial neural networks approach for predicting global radiation

    International Nuclear Information System (INIS)

    Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

    2009-01-01

    This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

  2. Phase resetting reveals network dynamics underlying a bacterial cell cycle.

    Science.gov (United States)

    Lin, Yihan; Li, Ying; Crosson, Sean; Dinner, Aaron R; Scherer, Norbert F

    2012-01-01

    Genomic and proteomic methods yield networks of biological regulatory interactions but do not provide direct insight into how those interactions are organized into functional modules, or how information flows from one module to another. In this work we introduce an approach that provides this complementary information and apply it to the bacterium Caulobacter crescentus, a paradigm for cell-cycle control. Operationally, we use an inducible promoter to express the essential transcriptional regulatory gene ctrA in a periodic, pulsed fashion. This chemical perturbation causes the population of cells to divide synchronously, and we use the resulting advance or delay of the division times of single cells to construct a phase resetting curve. We find that delay is strongly favored over advance. This finding is surprising since it does not follow from the temporal expression profile of CtrA and, in turn, simulations of existing network models. We propose a phenomenological model that suggests that the cell-cycle network comprises two distinct functional modules that oscillate autonomously and couple in a highly asymmetric fashion. These features collectively provide a new mechanism for tight temporal control of the cell cycle in C. crescentus. We discuss how the procedure can serve as the basis for a general approach for probing network dynamics, which we term chemical perturbation spectroscopy (CPS).

  3. Integration Of An MR Image Network Into A Clinical PACS

    Science.gov (United States)

    Ratib, Osman M.; Mankovich, Nicholas J.; Taira, Ricky K.; Cho, Paul S.; Huang, H. K.

    1988-06-01

    A direct link between a clinical pediatric PACS module and a FONAR MRI image network was implemented. The original MR network combines together the MR scanner, a remote viewing station and a central archiving station. The pediatric PACS directly connects to the archiving unit through an Ethernet TCP-IP network adhering to FONAR's protocol. The PACS communication software developed supports the transfer of patient studies and the patient information directly from the MR archive database to the pediatric PACS. In the first phase of our project we developed a package to transfer data between a VAX-111750 and the IBM PC I AT-based MR archive database through the Ethernet network. This system served as a model for PACS-to-modality network communication. Once testing was complete on this research network, the software and network hardware was moved to the clinical pediatric VAX for full PACS integration. In parallel to the direct transmission of digital images to the Pediatric PACS, a broadband communication system in video format was developed for real-time broadcasting of images originating from the MR console to 8 remote viewing stations distributed in the radiology department. These analog viewing stations allow the radiologists to directly monitor patient positioning and to select the scan levels during a patient examination from remote locations in the radiology department. This paper reports (1) the technical details of this implementation, (2) the merits of this network development scheme, and (3) the performance statistics of the network-to-PACS interface.

  4. S100A4 and its role in metastasis – computational integration of data on biological networks.

    Science.gov (United States)

    Buetti-Dinh, Antoine; Pivkin, Igor V; Friedman, Ran

    2015-08-01

    Characterising signal transduction networks is fundamental to our understanding of biology. However, redundancy and different types of feedback mechanisms make it difficult to understand how variations of the network components contribute to a biological process. In silico modelling of signalling interactions therefore becomes increasingly useful for the development of successful therapeutic approaches. Unfortunately, quantitative information cannot be obtained for all of the proteins or complexes that comprise the network, which limits the usability of computational models. We developed a flexible computational framework for the analysis of biological signalling networks. We demonstrate our approach by studying the mechanism of metastasis promotion by the S100A4 protein, and suggest therapeutic strategies. The advantage of the proposed method is that only limited information (interaction type between species) is required to set up a steady-state network model. This permits a straightforward integration of experimental information where the lack of details are compensated by efficient sampling of the parameter space. We investigated regulatory properties of the S100A4 network and the role of different key components. The results show that S100A4 enhances the activity of matrix metalloproteinases (MMPs), causing higher cell dissociation. Moreover, it leads to an increased stability of the pathological state. Thus, avoiding metastasis in S100A4-expressing tumours requires multiple target inhibition. Moreover, the analysis could explain the previous failure of MMP inhibitors in clinical trials. Finally, our method is applicable to a wide range of biological questions that can be represented as directional networks.

  5. Integration and segregation of large-scale brain networks during short-term task automatization.

    Science.gov (United States)

    Mohr, Holger; Wolfensteller, Uta; Betzel, Richard F; Mišić, Bratislav; Sporns, Olaf; Richiardi, Jonas; Ruge, Hannes

    2016-11-03

    The human brain is organized into large-scale functional networks that can flexibly reconfigure their connectivity patterns, supporting both rapid adaptive control and long-term learning processes. However, it has remained unclear how short-term network dynamics support the rapid transformation of instructions into fluent behaviour. Comparing fMRI data of a learning sample (N=70) with a control sample (N=67), we find that increasingly efficient task processing during short-term practice is associated with a reorganization of large-scale network interactions. Practice-related efficiency gains are facilitated by enhanced coupling between the cingulo-opercular network and the dorsal attention network. Simultaneously, short-term task automatization is accompanied by decreasing activation of the fronto-parietal network, indicating a release of high-level cognitive control, and a segregation of the default mode network from task-related networks. These findings suggest that short-term task automatization is enabled by the brain's ability to rapidly reconfigure its large-scale network organization involving complementary integration and segregation processes.

  6. Functional network integrity presages cognitive decline in preclinical Alzheimer disease.

    Science.gov (United States)

    Buckley, Rachel F; Schultz, Aaron P; Hedden, Trey; Papp, Kathryn V; Hanseeuw, Bernard J; Marshall, Gad; Sepulcre, Jorge; Smith, Emily E; Rentz, Dorene M; Johnson, Keith A; Sperling, Reisa A; Chhatwal, Jasmeer P

    2017-07-04

    To examine the utility of resting-state functional connectivity MRI (rs-fcMRI) measurements of network integrity as a predictor of future cognitive decline in preclinical Alzheimer disease (AD). A total of 237 clinically normal older adults (aged 63-90 years, Clinical Dementia Rating 0) underwent baseline β-amyloid (Aβ) imaging with Pittsburgh compound B PET and structural and rs-fcMRI. We identified 7 networks for analysis, including 4 cognitive networks (default, salience, dorsal attention, and frontoparietal control) and 3 noncognitive networks (primary visual, extrastriate visual, motor). Using linear and curvilinear mixed models, we used baseline connectivity in these networks to predict longitudinal changes in preclinical Alzheimer cognitive composite (PACC) performance, both alone and interacting with Aβ burden. Median neuropsychological follow-up was 3 years. Baseline connectivity in the default, salience, and control networks predicted longitudinal PACC decline, unlike connectivity in the dorsal attention and all noncognitive networks. Default, salience, and control network connectivity was also synergistic with Aβ burden in predicting decline, with combined higher Aβ and lower connectivity predicting the steepest curvilinear decline in PACC performance. In clinically normal older adults, lower functional connectivity predicted more rapid decline in PACC scores over time, particularly when coupled with increased Aβ burden. Among examined networks, default, salience, and control networks were the strongest predictors of rate of change in PACC scores, with the inflection point of greatest decline beyond the fourth year of follow-up. These results suggest that rs-fcMRI may be a useful predictor of early, AD-related cognitive decline in clinical research settings. © 2017 American Academy of Neurology.

  7. The gene regulatory network for breast cancer: Integrated regulatory landscape of cancer hallmarks

    Directory of Open Access Journals (Sweden)

    Frank eEmmert-Streib

    2014-02-01

    Full Text Available In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of $351$ patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome $21$ is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.

  8. Data-driven quantification of the robustness and sensitivity of cell signaling networks

    International Nuclear Information System (INIS)

    Mukherjee, Sayak; Seok, Sang-Cheol; Vieland, Veronica J; Das, Jayajit

    2013-01-01

    Robustness and sensitivity of responses generated by cell signaling networks has been associated with survival and evolvability of organisms. However, existing methods analyzing robustness and sensitivity of signaling networks ignore the experimentally observed cell-to-cell variations of protein abundances and cell functions or contain ad hoc assumptions. We propose and apply a data-driven maximum entropy based method to quantify robustness and sensitivity of Escherichia coli (E. coli) chemotaxis signaling network. Our analysis correctly rank orders different models of E. coli chemotaxis based on their robustness and suggests that parameters regulating cell signaling are evolutionary selected to vary in individual cells according to their abilities to perturb cell functions. Furthermore, predictions from our approach regarding distribution of protein abundances and properties of chemotactic responses in individual cells based on cell population averaged data are in excellent agreement with their experimental counterparts. Our approach is general and can be used to evaluate robustness as well as generate predictions of single cell properties based on population averaged experimental data in a wide range of cell signaling systems. (paper)

  9. PharmDB-K: Integrated Bio-Pharmacological Network Database for Traditional Korean Medicine.

    Directory of Open Access Journals (Sweden)

    Ji-Hyun Lee

    Full Text Available Despite the growing attention given to Traditional Medicine (TM worldwide, there is no well-known, publicly available, integrated bio-pharmacological Traditional Korean Medicine (TKM database for researchers in drug discovery. In this study, we have constructed PharmDB-K, which offers comprehensive information relating to TKM-associated drugs (compound, disease indication, and protein relationships. To explore the underlying molecular interaction of TKM, we integrated fourteen different databases, six Pharmacopoeias, and literature, and established a massive bio-pharmacological network for TKM and experimentally validated some cases predicted from the PharmDB-K analyses. Currently, PharmDB-K contains information about 262 TKMs, 7,815 drugs, 3,721 diseases, 32,373 proteins, and 1,887 side effects. One of the unique sets of information in PharmDB-K includes 400 indicator compounds used for standardization of herbal medicine. Furthermore, we are operating PharmDB-K via phExplorer (a network visualization software and BioMart (a data federation framework for convenient search and analysis of the TKM network. Database URL: http://pharmdb-k.org, http://biomart.i-pharm.org.

  10. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-01-01

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

  11. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

    Science.gov (United States)

    Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

    2015-11-17

    This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

  12. Integrative Network Analysis Unveils Convergent Molecular Pathways in Parkinson's Disease and Diabetes

    OpenAIRE

    Santiago, Jose A.; Potashkin, Judith A.

    2013-01-01

    Background Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. ...

  13. Detection of silent cells, synchronization and modulatory activity in developing cellular networks.

    NARCIS (Netherlands)

    Hjorth, J.J.J.; Dawitz, J.; Kroon, T.; da Silva Dias Pires, J.H.; Dassen, V.J.; Berkhout, J.A.; Emperador Melero, J.; Nadadhur, A.G.; Alevra, M.; Toonen, R.F.G.; Heine, V.M.; Mansvelder, H.D.; Meredith, R.M.

    2016-01-01

    Developing networks in the immature nervous system and in cellular cultures are characterized by waves of synchronous activity in restricted clusters of cells. Synchronized activity in immature networks is proposed to regulate many different developmental processes, from neuron growth and cell

  14. Establishment of a hydrological monitoring network in a tropical African catchment: An integrated participatory approach

    Science.gov (United States)

    Gomani, M. C.; Dietrich, O.; Lischeid, G.; Mahoo, H.; Mahay, F.; Mbilinyi, B.; Sarmett, J.

    Sound decision making for water resources management has to be based on good knowledge of the dominant hydrological processes of a catchment. This information can only be obtained through establishing suitable hydrological monitoring networks. Research catchments are typically established without involving the key stakeholders, which results in instruments being installed at inappropriate places as well as at high risk of theft and vandalism. This paper presents an integrated participatory approach for establishing a hydrological monitoring network. We propose a framework with six steps beginning with (i) inception of idea; (ii) stakeholder identification; (iii) defining the scope of the network; (iv) installation; (v) monitoring; and (vi) feedback mechanism integrated within the participatory framework. The approach is illustrated using an example of the Ngerengere catchment in Tanzania. In applying the approach, the concept of establishing the Ngerengere catchment monitoring network was initiated in 2008 within the Resilient Agro-landscapes to Climate Change in Tanzania (ReACCT) research program. The main stakeholders included: local communities; Sokoine University of Agriculture; Wami Ruvu Basin Water Office and the ReACCT Research team. The scope of the network was based on expert experience in similar projects and lessons learnt from literature review of similar projects from elsewhere integrated with local expert knowledge. The installations involved reconnaissance surveys, detailed surveys, and expert consultations to identify best sites. First, a Digital Elevation Model, land use, and soil maps were used to identify potential monitoring sites. Local and expert knowledge was collected on flow regimes, indicators of shallow groundwater plant species, precipitation pattern, vegetation, and soil types. This information was integrated and used to select sites for installation of an automatic weather station, automatic rain gauges, river flow gauging stations

  15. Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases

    NARCIS (Netherlands)

    Peters, D. T. J. M.; Raab, J.; Grêaux, K. M.; Stronks, K.; Harting, J.

    2017-01-01

    Background: Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as

  16. Structural integration and performance of inter-sectoral public health-related policy networks : An analysis across policy phases

    NARCIS (Netherlands)

    Peters, Dorothee; Raab, J.; Grêaux, Kimberley M.; Stronks, Karien; Harting, Janneke

    2017-01-01

    Background: Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structure and network characteristics (i.e., composition and integration) and network performance, such

  17. Energy in Southeast Asia: from Networks to Markets Integration

    International Nuclear Information System (INIS)

    Cornot-Gandolphe, Sylvie

    2017-01-01

    Southeast Asia is one of the world's most dynamic regions and experiences strong economic and energy demand growth rates. In this context, the Association of Southeast Asian Nations (ASEAN) is seeking to interconnect the electric grids and gas networks of the countries through two initiatives, the Asean Power Grid and the Trans-Asean Gas Pipeline, in order to pool resources and optimize energy markets integration in the region

  18. MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

    Directory of Open Access Journals (Sweden)

    Wasserman Wyeth W

    2011-03-01

    Full Text Available Abstract Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs, microRNAs (miRNAs and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs. Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL. In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT, an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http

  19. Frogs, fish and forestry: An integrated watershed network paradigm conserves biodiversity and ecological services

    Science.gov (United States)

    Hartwell H. Welsh Jr.

    2011-01-01

    Successfully addressing the multitude of stresses influencing forest catchments, their native biota, and the vital ecological services they provide humanity will require adapting an integrated view that incorporates the full range of natural and anthropogenic disturbances acting on these landscapes and their embedded fluvial networks. The concepts of dendritic networks...

  20. Determining the control networks regulating stem cell lineages in colonic crypts

    OpenAIRE

    Yang, J; Axelrod, DE; Komarova, NL

    2017-01-01

    The question of stem cell control is at the center of our understanding of tissue functioning, both in healthy and cancerous conditions. It is well accepted that cellular fate decisions (such as divisions, differentiation, apoptosis) are orchestrated by a network of regulatory signals emitted by different cell populations in the lineage and the surrounding tissue. The exact regulatory network that governs stem cell lineages in a given tissue is usually unknown. Here we propose an algorithm to...

  1. Energetic and Exergetic Analysis of Low and Medium Temperature District Heating Network Integration

    DEFF Research Database (Denmark)

    Li, Hongwei; Svendsen, Svend

    In this paper, energetic and exergetic approaches were applied to an exemplary low temperature district heating (LTDH) network with supply/return water temperature at 55oC/25 oC. The small LTDH network is annexed to a large medium temperature district heating (MTDH) network. The LTDH network can ...... will reduce the amount of water supply from the MTDH network and improve the system energy conversion efficiency. Through the simulation, the system energetic and exergetic efficiencies based on the two network integration approaches were calculated and evaluated.......In this paper, energetic and exergetic approaches were applied to an exemplary low temperature district heating (LTDH) network with supply/return water temperature at 55oC/25 oC. The small LTDH network is annexed to a large medium temperature district heating (MTDH) network. The LTDH network can...... be supplied through upgrading the return water from the MTDH network with a small centralized heat pump. Alternatively, the supply and return water from the MTDH network can be mixed with a shunt at the junction point to supply the LTDH network. Comparing with the second approach, the heat pump system...

  2. DO DYNAMIC NEURAL NETWORKS STAND A BETTER CHANCE IN FRACTIONALLY INTEGRATED PROCESS FORECASTING?

    Directory of Open Access Journals (Sweden)

    Majid Delavari

    2013-04-01

    Full Text Available The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model and a regressive (Auto Regressive Fractionally Integrated Moving Average model which is based on Fractional Integration Approach in forecasting daily data related to the return index of Tehran Stock Exchange (TSE. In order to compare these models under similar conditions, Mean Square Error (MSE and also Root Mean Square Error (RMSE were selected as criteria for the models’ simulated out-of-sample forecasting performance. Besides, fractal markets hypothesis was examined and according to the findings, fractal structure was confirmed to exist in the time series under investigation. Another finding of the study was that dynamic artificial neural network model had the best performance in out-of-sample forecasting based on the criteria introduced for calculating forecasting error in comparison with the ARFIMA model.

  3. Successful integration efforts in water quality from the integrated Ocean Observing System Regional Associations and the National Water Quality Monitoring Network

    Science.gov (United States)

    Ragsdale, R.; Vowinkel, E.; Porter, D.; Hamilton, P.; Morrison, R.; Kohut, J.; Connell, B.; Kelsey, H.; Trowbridge, P.

    2011-01-01

    The Integrated Ocean Observing System (IOOS??) Regional Associations and Interagency Partners hosted a water quality workshop in January 2010 to discuss issues of nutrient enrichment and dissolved oxygen depletion (hypoxia), harmful algal blooms (HABs), and beach water quality. In 2007, the National Water Quality Monitoring Council piloted demonstration projects as part of the National Water Quality Monitoring Network (Network) for U.S. Coastal Waters and their Tributaries in three IOOS Regional Associations, and these projects are ongoing. Examples of integrated science-based solutions to water quality issues of major concern from the IOOS regions and Network demonstration projects are explored in this article. These examples illustrate instances where management decisions have benefited from decision-support tools that make use of interoperable data. Gaps, challenges, and outcomes are identified, and a proposal is made for future work toward a multiregional water quality project for beach water quality.

  4. All-Optical Network Subsystems Using Integrated SOA-Based Optical Gates and Flip-Flops for Label-Swapped Netorks

    DEFF Research Database (Denmark)

    Seoane, Jorge; Holm-Nielsen, Pablo Villanueva; Kehayas, E.

    2006-01-01

    In this letter, we demonstrate that all-optical network subsystems, offering intelligence in the optical layer, can be constructed by functional integration of integrated all-optical logic gates and flip-flops. In this context, we show 10-Gb/s all-optical 2-bit label address recognition......-level advantages of these all-optical subsystems combined with their realization with compact integrated devices, suggest that they are strong candidates for future packet/label switched optical networks....... by interconnecting two optical gates that perform xor operation on incoming optical labels. We also demonstrate 40-Gb/s all-optical wavelength-switching through an optically controlled wavelength converter, consisting of an integrated flip-flop prototype device driven by an integrated optical gate. The system...

  5. Osteogenic stimulatory conditions enhance growth and maturation of endothelial cell microvascular networks in culture with mesenchymal stem cells

    Directory of Open Access Journals (Sweden)

    Torbjorn O Pedersen

    2012-12-01

    Full Text Available To optimize culture conditions for in vitro prevascularization of tissue-engineered bone constructs, the development of organotypic blood vessels under osteogenic stimulatory conditions (OM was investigated. Coculture of endothelial cells and mesenchymal stem cells was used to assess proangiogenic effects of mesenchymal stem cells on endothelial cells. Four different culture conditions were evaluated for their effect on development of microvascular endothelial cell networks. Mineralization, deposition of extracellular matrix, and perivascular gene expression were studied in OM. After 3 days, endothelial cells established elongated capillary-like networks, and upregulated expression of vascular markers was seen. After 15 days, all parameters evaluated were significantly increased for cultures in OM. Mature networks developed in OM presented lumens enveloped by basement membrane-like collagen IV, with obvious mineralization and upregulated perivascular gene expression from mesenchymal stem cells. Our results suggest osteogenic stimulatory conditions to be appropriate for in vitro development of vascularized bone implants for tissue engineering.

  6. Conceptual plan for closer integration of network- and project-level pavement management

    Science.gov (United States)

    1998-01-01

    This report presents an evaluation of current performance modeling concepts and a feasibility study of the possibility of integrating network- and project-level performance prediction. The widely differing modeling methods in use today are reviewed a...

  7. Australian national networked tele-test facility for integrated systems

    Science.gov (United States)

    Eshraghian, Kamran; Lachowicz, Stefan W.; Eshraghian, Sholeh

    2001-11-01

    The Australian Commonwealth government recently announced a grant of 4.75 million as part of a 13.5 million program to establish a world class networked IC tele-test facility in Australia. The facility will be based on a state-of-the-art semiconductor tester located at Edith Cowan University in Perth that will operate as a virtual centre spanning Australia. Satellite nodes will be located at the University of Western Australia, Griffith University, Macquarie University, Victoria University and the University of Adelaide. The facility will provide vital equipment to take Australia to the frontier of critically important and expanding fields in microelectronics research and development. The tele-test network will provide state of the art environment for the electronics and microelectronics research and the industry community around Australia to test and prototype Very Large Scale Integrated (VLSI) circuits and other System On a Chip (SOC) devices, prior to moving to the manufacturing stage. Such testing is absolutely essential to ensure that the device performs to specification. This paper presents the current context in which the testing facility is being established, the methodologies behind the integration of design and test strategies and the target shape of the tele-testing Facility.

  8. 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

    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...

  9. Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.

    Science.gov (United States)

    Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J

    2016-01-01

    Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.

  10. NKT Cell Networks in the Regulation of Tumor Immunity

    Science.gov (United States)

    Robertson, Faith C.; Berzofsky, Jay A.; Terabe, Masaki

    2014-01-01

    CD1d-restricted natural killer T (NKT) cells lie at the interface between the innate and adaptive immune systems and are important mediators of immune responses and tumor immunosurveillance. These NKT cells uniquely recognize lipid antigens, and their rapid yet specific reactions influence both innate and adaptive immunity. In tumor immunity, two NKT subsets (type I and type II) have contrasting roles in which they not only cross-regulate one another, but also impact innate immune cell populations, including natural killer, dendritic, and myeloid lineage cells, as well as adaptive populations, especially CD8+ and CD4+ T cells. The extent to which NKT cells promote or suppress surrounding cells affects the host’s ability to prevent neoplasia and is consequently of great interest for therapeutic development. Data have shown the potential for therapeutic use of NKT cell agonists and synergy with immune response modifiers in both pre-clinical studies and preliminary clinical studies. However, there is room to improve treatment efficacy by further elucidating the biological mechanisms underlying NKT cell networks. Here, we discuss the progress made in understanding NKT cell networks, their consequent role in the regulation of tumor immunity, and the potential to exploit that knowledge in a clinical setting. PMID:25389427

  11. NKT cell networks in the regulation of tumor immunity.

    Science.gov (United States)

    Robertson, Faith C; Berzofsky, Jay A; Terabe, Masaki

    2014-01-01

    CD1d-restricted natural killer T (NKT) cells lie at the interface between the innate and adaptive immune systems and are important mediators of immune responses and tumor immunosurveillance. These NKT cells uniquely recognize lipid antigens, and their rapid yet specific reactions influence both innate and adaptive immunity. In tumor immunity, two NKT subsets (type I and type II) have contrasting roles in which they not only cross-regulate one another, but also impact innate immune cell populations, including natural killer, dendritic, and myeloid lineage cells, as well as adaptive populations, especially CD8(+) and CD4(+) T cells. The extent to which NKT cells promote or suppress surrounding cells affects the host's ability to prevent neoplasia and is consequently of great interest for therapeutic development. Data have shown the potential for therapeutic use of NKT cell agonists and synergy with immune response modifiers in both pre-clinical studies and preliminary clinical studies. However, there is room to improve treatment efficacy by further elucidating the biological mechanisms underlying NKT cell networks. Here, we discuss the progress made in understanding NKT cell networks, their consequent role in the regulation of tumor immunity, and the potential to exploit that knowledge in a clinical setting.

  12. NKT cell networks in the regulation of tumor immunity

    Directory of Open Access Journals (Sweden)

    Faith C Robertson

    2014-10-01

    Full Text Available CD1d-restricted natural killer T (NKT cells lie at the interface between the innate and adaptive immune systems and are important mediators of immune responses and tumor immunosurveillance. These NKT cells uniquely recognize lipid antigens, and their rapid yet specific reactions influence both innate and adaptive immunity. In tumor immunity, two NKT subsets (type I and type II have contrasting roles in which they not only cross-regulate one another, but also impact innate immune cell populations, including natural killer, dendritic and myeloid lineage cells, as well as adaptive populations, especially CD8+ and CD4+ T cells. The extent to which NKT cells promote or suppress surrounding cells affects the host’s ability to prevent neoplasia and is consequently of great interest for therapeutic development. Data have shown the potential for therapeutic use of NKT cell agonists and synergy with immune response modifiers in both pre-clinical studies and preliminary clinical studies. However, there is room to improve treatment efficacy by further elucidating the biological mechanisms underlying NKT cell networks. Here, we discuss the progress made in understanding NKT cell networks, their consequent role in the regulation of tumor immunity, and the potential to exploit that knowledge in a clinical setting.

  13. Life on magnets: stem cell networking on micro-magnet arrays.

    Science.gov (United States)

    Zablotskii, Vitalii; Dejneka, Alexandr; Kubinová, Šárka; Le-Roy, Damien; Dumas-Bouchiat, Frédéric; Givord, Dominique; Dempsey, Nora M; Syková, Eva

    2013-01-01

    Interactions between a micro-magnet array and living cells may guide the establishment of cell networks due to the cellular response to a magnetic field. To manipulate mesenchymal stem cells free of magnetic nanoparticles by a high magnetic field gradient, we used high quality micro-patterned NdFeB films around which the stray field's value and direction drastically change across the cell body. Such micro-magnet arrays coated with parylene produce high magnetic field gradients that affect the cells in two main ways: i) causing cell migration and adherence to a covered magnetic surface and ii) elongating the cells in the directions parallel to the edges of the micro-magnet. To explain these effects, three putative mechanisms that incorporate both physical and biological factors influencing the cells are suggested. It is shown that the static high magnetic field gradient generated by the micro-magnet arrays are capable of assisting cell migration to those areas with the strongest magnetic field gradient, thereby allowing the build up of tunable interconnected stem cell networks, which is an elegant route for tissue engineering and regenerative medicine.

  14. Computing with networks of spiking neurons on a biophysically motivated floating-gate based neuromorphic integrated circuit.

    Science.gov (United States)

    Brink, S; Nease, S; Hasler, P

    2013-09-01

    Results are presented from several spiking network experiments performed on a novel neuromorphic integrated circuit. The networks are discussed in terms of their computational significance, which includes applications such as arbitrary spatiotemporal pattern generation and recognition, winner-take-all competition, stable generation of rhythmic outputs, and volatile memory. Analogies to the behavior of real biological neural systems are also noted. The alternatives for implementing the same computations are discussed and compared from a computational efficiency standpoint, with the conclusion that implementing neural networks on neuromorphic hardware is significantly more power efficient than numerical integration of model equations on traditional digital hardware. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Technology advancement for integrative stem cell analyses.

    Science.gov (United States)

    Jeong, Yoon; Choi, Jonghoon; Lee, Kwan Hyi

    2014-12-01

    Scientists have endeavored to use stem cells for a variety of applications ranging from basic science research to translational medicine. Population-based characterization of such stem cells, while providing an important foundation to further development, often disregard the heterogeneity inherent among individual constituents within a given population. The population-based analysis and characterization of stem cells and the problems associated with such a blanket approach only underscore the need for the development of new analytical technology. In this article, we review current stem cell analytical technologies, along with the advantages and disadvantages of each, followed by applications of these technologies in the field of stem cells. Furthermore, while recent advances in micro/nano technology have led to a growth in the stem cell analytical field, underlying architectural concepts allow only for a vertical analytical approach, in which different desirable parameters are obtained from multiple individual experiments and there are many technical challenges that limit vertically integrated analytical tools. Therefore, we propose--by introducing a concept of vertical and horizontal approach--that there is the need of adequate methods to the integration of information, such that multiple descriptive parameters from a stem cell can be obtained from a single experiment.

  16. Integration of hormonal signaling networks and mobile microRNAs is required for vascular patterning in Arabidopsis roots

    KAUST Repository

    Muraro, D.

    2013-12-31

    As multicellular organisms grow, positional information is continually needed to regulate the pattern in which cells are arranged. In the Arabidopsis root, most cell types are organized in a radially symmetric pattern; however, a symmetry-breaking event generates bisymmetric auxin and cytokinin signaling domains in the stele. Bidirectional cross-talk between the stele and the surrounding tissues involving a mobile transcription factor, SHORT ROOT (SHR), and mobile microRNA species also determines vascular pattern, but it is currently unclear how these signals integrate. We use a multicellular model to determine a minimal set of components necessary for maintaining a stable vascular pattern. Simulations perturbing the signaling network show that, in addition to the mutually inhibitory interaction between auxin and cytokinin, signaling through SHR, microRNA165/6, and PHABULOSA is required to maintain a stable bisymmetric pattern. We have verified this prediction by observing loss of bisymmetry in shr mutants. The model reveals the importance of several features of the network, namely the mutual degradation of microRNA165/6 and PHABULOSA and the existence of an additional negative regulator of cytokinin signaling. These components form a plausible mechanism capable of patterning vascular tissues in the absence of positional inputs provided by the transport of hormones from the shoot.

  17. Integration of hormonal signaling networks and mobile microRNAs is required for vascular patterning in Arabidopsis roots

    KAUST Repository

    Muraro, D.; Mellor, N.; Pound, M. P.; Help, H.; Lucas, M.; Chopard, J.; Byrne, H. M.; Godin, C.; Hodgman, T. C.; King, J. R.; Pridmore, T. P.; Helariutta, Y.; Bennett, M. J.; Bishopp, A.

    2013-01-01

    As multicellular organisms grow, positional information is continually needed to regulate the pattern in which cells are arranged. In the Arabidopsis root, most cell types are organized in a radially symmetric pattern; however, a symmetry-breaking event generates bisymmetric auxin and cytokinin signaling domains in the stele. Bidirectional cross-talk between the stele and the surrounding tissues involving a mobile transcription factor, SHORT ROOT (SHR), and mobile microRNA species also determines vascular pattern, but it is currently unclear how these signals integrate. We use a multicellular model to determine a minimal set of components necessary for maintaining a stable vascular pattern. Simulations perturbing the signaling network show that, in addition to the mutually inhibitory interaction between auxin and cytokinin, signaling through SHR, microRNA165/6, and PHABULOSA is required to maintain a stable bisymmetric pattern. We have verified this prediction by observing loss of bisymmetry in shr mutants. The model reveals the importance of several features of the network, namely the mutual degradation of microRNA165/6 and PHABULOSA and the existence of an additional negative regulator of cytokinin signaling. These components form a plausible mechanism capable of patterning vascular tissues in the absence of positional inputs provided by the transport of hormones from the shoot.

  18. Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

    Science.gov (United States)

    Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

    2013-01-01

    The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  19. Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models

    Science.gov (United States)

    2015-03-03

    based whole-cell models of E. coli [6]. Conversely , highly abstracted kinetic frameworks, such as the cybernetic framework, represented a paradigm shift...metabolic objective function has been the optimization of biomass formation [18], although other metabolic objectives have also been estimated [19...experimental data. Toward these questions, we explored five hypothetical cell-free networks. Each network shared the same enzymatic connectivity, but

  20. The cell wall of Arabidopsis thaliana influences actin network dynamics.

    Science.gov (United States)

    Tolmie, Frances; Poulet, Axel; McKenna, Joseph; Sassmann, Stefan; Graumann, Katja; Deeks, Michael; Runions, John

    2017-07-20

    In plant cells, molecular connections link the cell wall-plasma membrane-actin cytoskeleton to form a continuum. It is hypothesized that the cell wall provides stable anchor points around which the actin cytoskeleton remodels. Here we use live cell imaging of fluorescently labelled marker proteins to quantify the organization and dynamics of the actin cytoskeleton and to determine the impact of disrupting connections within the continuum. Labelling of the actin cytoskeleton with green fluorescent protein (GFP)-fimbrin actin-binding domain 2 (FABD2) resulted in a network composed of fine filaments and thicker bundles that appeared as a highly dynamic remodelling meshwork. This differed substantially from the GFP-Lifeact-labelled network that appeared much more sparse with thick bundles that underwent 'simple movement', in which the bundles slightly change position, but in such a manner that the structure of the network was not substantially altered during the time of observation. Label-dependent differences in actin network morphology and remodelling necessitated development of two new image analysis techniques. The first of these, 'pairwise image subtraction', was applied to measurement of the more rapidly remodelling actin network labelled with GFP-FABD2, while the second, 'cumulative fluorescence intensity', was used to measure bulk remodelling of the actin cytoskeleton when labelled with GFP-Lifeact. In each case, these analysis techniques show that the actin cytoskeleton has a decreased rate of bulk remodelling when the cell wall-plasma membrane-actin continuum is disrupted either by plasmolysis or with isoxaben, a drug that specifically inhibits cellulose deposition. Changes in the rate of actin remodelling also affect its functionality, as observed by alteration in Golgi body motility. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  1. Dielectrophoretic focusing integrated pulsed laser activated cell sorting

    Science.gov (United States)

    Zhu, Xiongfeng; Kung, Yu-Chun; Wu, Ting-Hsiang; Teitell, Michael A.; Chiou, Pei-Yu

    2017-08-01

    We present a pulsed laser activated cell sorter (PLACS) integrated with novel sheathless size-independent dielectrophoretic (DEP) focusing. Microfluidic fluorescence activated cell sorting (μFACS) systems aim to provide a fully enclosed environment for sterile cell sorting and integration with upstream and downstream microfluidic modules. Among them, PLACS has shown a great potential in achieving comparable performance to commercial aerosol-based FACS (>90% purity at 25,000 cells sec-1). However conventional sheath flow focusing method suffers a severe sample dilution issue. Here we demonstrate a novel dielectrophoresis-integrated pulsed laser activated cell sorter (DEP-PLACS). It consists of a microfluidic channel with 3D electrodes laid out to provide a tunnel-shaped electric field profile along a 4cmlong channel for sheathlessly focusing microparticles/cells into a single stream in high-speed microfluidic flows. All focused particles pass through the fluorescence detection zone along the same streamline regardless of their sizes and types. Upon detection of target fluorescent particles, a nanosecond laser pulse is triggered and focused in a neighboring channel to generate a rapidly expanding cavitation bubble for precise sorting. DEP-PLACS has achieved a sorting purity of 91% for polystyrene beads at a throughput of 1,500 particle/sec.

  2. Performance evaluation of multi-stratum resources integration based on network function virtualization in software defined elastic data center optical interconnect.

    Science.gov (United States)

    Yang, Hui; Zhang, Jie; Ji, Yuefeng; Tian, Rui; Han, Jianrui; Lee, Young

    2015-11-30

    Data center interconnect with elastic optical network is a promising scenario to meet the high burstiness and high-bandwidth requirements of data center services. In our previous work, we implemented multi-stratum resilience between IP and elastic optical networks that allows to accommodate data center services. In view of this, this study extends to consider the resource integration by breaking the limit of network device, which can enhance the resource utilization. We propose a novel multi-stratum resources integration (MSRI) architecture based on network function virtualization in software defined elastic data center optical interconnect. A resource integrated mapping (RIM) scheme for MSRI is introduced in the proposed architecture. The MSRI can accommodate the data center services with resources integration when the single function or resource is relatively scarce to provision the services, and enhance globally integrated optimization of optical network and application resources. The overall feasibility and efficiency of the proposed architecture are experimentally verified on the control plane of OpenFlow-based enhanced software defined networking (eSDN) testbed. The performance of RIM scheme under heavy traffic load scenario is also quantitatively evaluated based on MSRI architecture in terms of path blocking probability, provisioning latency and resource utilization, compared with other provisioning schemes.

  3. On the area spectral efficiency improvement of heterogeneous network by exploiting the integration of macro-femto cellular networks

    KAUST Repository

    Shakir, Muhammad

    2012-06-01

    Heterogeneous networks are an attractive means of expanding mobile network capacity. A heterogeneous network is typically composed of multiple radio access technologies (RATs) where the base stations are transmitting with variable power. In this paper, we consider a Heterogeneous network where we complement the macrocell network with low-power low-cost user deployed nodes, such as femtocell base stations to increase the mean achievable capacity of the system. In this context, we integrate macro-femto cellular networks and derive the area spectral efficiency of the proposed two tier Heterogeneous network. We consider the deployment of femtocell base stations around the edge of the macrocell such that this configuration is referred to as femto-on-edge (FOE) configuration. Moreover, FOE configuration mandates reduction in intercell interference due to the mobile users which are located around the edge of the macrocell since these femtocell base stations are low-power nodes which has significantly lower transmission power than macrocell base stations. We present a mathematical analysis to calculate the instantaneous carrier to interference ratio (CIR) of the desired mobile user in macro and femto cellular networks and determine the total area spectral efficiency of the Heterogeneous network. Details of the simulation processes are included to support the analysis and show the efficacy of the proposed deployment. It has been shown that the proposed setup of the Heterogeneous network offers higher area spectral efficiency which aims to fulfill the expected demand of the future mobile users. © 2012 IEEE.

  4. Reconstruction and signal propagation analysis of the Syk signaling network in breast cancer cells.

    Directory of Open Access Journals (Sweden)

    Aurélien Naldi

    2017-03-01

    Full Text Available The ability to build in-depth cell signaling networks from vast experimental data is a key objective of computational biology. The spleen tyrosine kinase (Syk protein, a well-characterized key player in immune cell signaling, was surprisingly first shown by our group to exhibit an onco-suppressive function in mammary epithelial cells and corroborated by many other studies, but the molecular mechanisms of this function remain largely unsolved. Based on existing proteomic data, we report here the generation of an interaction-based network of signaling pathways controlled by Syk in breast cancer cells. Pathway enrichment of the Syk targets previously identified by quantitative phospho-proteomics indicated that Syk is engaged in cell adhesion, motility, growth and death. Using the components and interactions of these pathways, we bootstrapped the reconstruction of a comprehensive network covering Syk signaling in breast cancer cells. To generate in silico hypotheses on Syk signaling propagation, we developed a method allowing to rank paths between Syk and its targets. We first annotated the network according to experimental datasets. We then combined shortest path computation with random walk processes to estimate the importance of individual interactions and selected biologically relevant pathways in the network. Molecular and cell biology experiments allowed to distinguish candidate mechanisms that underlie the impact of Syk on the regulation of cortactin and ezrin, both involved in actin-mediated cell adhesion and motility. The Syk network was further completed with the results of our biological validation experiments. The resulting Syk signaling sub-networks can be explored via an online visualization platform.

  5. Coal Integrated Gasification Fuel Cell System Study

    Energy Technology Data Exchange (ETDEWEB)

    Gregory Wotzak; Chellappa Balan; Faress Rahman; Nguyen Minh

    2003-08-01

    The pre-baseline configuration for an Integrated Gasification Fuel Cell (IGFC) system has been developed. This case uses current gasification, clean-up, gas turbine, and bottoming cycle technologies together with projected large planar Solid Oxide Fuel Cell (SOFC) technology. This pre-baseline case will be used as a basis for identifying the critical factors impacting system performance and the major technical challenges in implementing such systems. Top-level system requirements were used as the criteria to evaluate and down select alternative sub-systems. The top choice subsystems were subsequently integrated to form the pre-baseline case. The down-selected pre-baseline case includes a British Gas Lurgi (BGL) gasification and cleanup sub-system integrated with a GE Power Systems 6FA+e gas turbine and the Hybrid Power Generation Systems planar Solid Oxide Fuel Cell (SOFC) sub-system. The overall efficiency of this system is estimated to be 43.0%. The system efficiency of the pre-baseline system provides a benchmark level for further optimization efforts in this program.

  6. Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

    DEFF Research Database (Denmark)

    Lehmann, Torsten

    1998-01-01

    In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

  7. Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Antônio Dâmaso

    2017-11-01

    Full Text Available Power consumption is a primary interest in Wireless Sensor Networks (WSNs, and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way.

  8. Integrated Evaluation of Reliability and Power Consumption of Wireless Sensor Networks

    Science.gov (United States)

    Dâmaso, Antônio; Maciel, Paulo

    2017-01-01

    Power consumption is a primary interest in Wireless Sensor Networks (WSNs), and a large number of strategies have been proposed to evaluate it. However, those approaches usually neither consider reliability issues nor the power consumption of applications executing in the network. A central concern is the lack of consolidated solutions that enable us to evaluate the power consumption of applications and the network stack also considering their reliabilities. To solve this problem, we introduce a fully automatic solution to design power consumption aware WSN applications and communication protocols. The solution presented in this paper comprises a methodology to evaluate the power consumption based on the integration of formal models, a set of power consumption and reliability models, a sensitivity analysis strategy to select WSN configurations and a toolbox named EDEN to fully support the proposed methodology. This solution allows accurately estimating the power consumption of WSN applications and the network stack in an automated way. PMID:29113078

  9. LmSmdB: an integrated database for metabolic and gene regulatory network in Leishmania major and Schistosoma mansoni

    Directory of Open Access Journals (Sweden)

    Priyanka Patel

    2016-03-01

    Full Text Available A database that integrates all the information required for biological processing is essential to be stored in one platform. We have attempted to create one such integrated database that can be a one stop shop for the essential features required to fetch valuable result. LmSmdB (L. major and S. mansoni database is an integrated database that accounts for the biological networks and regulatory pathways computationally determined by integrating the knowledge of the genome sequences of the mentioned organisms. It is the first database of its kind that has together with the network designing showed the simulation pattern of the product. This database intends to create a comprehensive canopy for the regulation of lipid metabolism reaction in the parasite by integrating the transcription factors, regulatory genes and the protein products controlled by the transcription factors and hence operating the metabolism at genetic level. Keywords: L.major, S.mansoni, Regulatory networks, Transcription factors, Database

  10. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Science.gov (United States)

    Kwak, Doyeon; Kim, Wonjoon

    2017-01-01

    It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  11. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

    Directory of Open Access Journals (Sweden)

    Doyeon Kwak

    Full Text Available It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

  12. Research network on capital markets and financial integration in Europe : results and experience after two years

    OpenAIRE

    European Central Bank ; Center for Financial Studies (CFS)

    2008-01-01

    In April 2002 the European Central Bank (ECB) and the Center for Financial Studies (CFS) launched the ECB-CFS Research Network to promote research on “Capital Markets and Financial Integration in Europe”. The ECB-CFS research network aims at stimulating top-level and policy-relevant research, significantly contributing to the understanding of the current and future structure and integration of the financial system in Europe and its international linkages with the United States and Japan. This...

  13. Complex fluid network optimization and control integrative design based on nonlinear dynamic model

    International Nuclear Information System (INIS)

    Sui, Jinxue; Yang, Li; Hu, Yunan

    2016-01-01

    In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.

  14. Definition, analysis and development of an optical data distribution network for integrated avionics and control systems. Part 2: Component development and system integration

    Science.gov (United States)

    Yen, H. W.; Morrison, R. J.

    1984-01-01

    Fiber optic transmission is emerging as an attractive concept in data distribution onboard civil aircraft. Development of an Optical Data Distribution Network for Integrated Avionics and Control Systems for commercial aircraft will provide a data distribution network that gives freedom from EMI-RFI and ground loop problems, eliminates crosstalk and short circuits, provides protection and immunity from lightning induced transients and give a large bandwidth data transmission capability. In addition there is a potential for significantly reducing the weight and increasing the reliability over conventional data distribution networks. Wavelength Division Multiplexing (WDM) is a candidate method for data communication between the various avionic subsystems. With WDM all systems could conceptually communicate with each other without time sharing and requiring complicated coding schemes for each computer and subsystem to recognize a message. However, the state of the art of optical technology limits the application of fiber optics in advanced integrated avionics and control systems. Therefore, it is necessary to address the architecture for a fiber optics data distribution system for integrated avionics and control systems as well as develop prototype components and systems.

  15. Human embryonic stem cell-derived neurons adopt and regulate the activity of an established neural network

    Science.gov (United States)

    Weick, Jason P.; Liu, Yan; Zhang, Su-Chun

    2011-01-01

    Whether hESC-derived neurons can fully integrate with and functionally regulate an existing neural network remains unknown. Here, we demonstrate that hESC-derived neurons receive unitary postsynaptic currents both in vitro and in vivo and adopt the rhythmic firing behavior of mouse cortical networks via synaptic integration. Optical stimulation of hESC-derived neurons expressing Channelrhodopsin-2 elicited both inhibitory and excitatory postsynaptic currents and triggered network bursting in mouse neurons. Furthermore, light stimulation of hESC-derived neurons transplanted to the hippocampus of adult mice triggered postsynaptic currents in host pyramidal neurons in acute slice preparations. Thus, hESC-derived neurons can participate in and modulate neural network activity through functional synaptic integration, suggesting they are capable of contributing to neural network information processing both in vitro and in vivo. PMID:22106298

  16. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  17. Hierarchical feedback modules and reaction hubs in cell signaling networks.

    Directory of Open Access Journals (Sweden)

    Jianfeng Xu

    Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

  18. Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

    Science.gov (United States)

    Xu, Jianfeng; Lan, Yueheng

    2015-01-01

    Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

  19. Integration of fuel cells into residential buildings

    International Nuclear Information System (INIS)

    Bell, J.M.; Entchev, E.; Gusdorf, J.; Szadkowski, F.; Swinton, M.; Kalbfleisch, W.; Marchand, R.

    2004-01-01

    Integration of small combined heat and power systems (CHP) into residential buildings is challenging as the loads are small, the load diversity is limited and there are a number of unresolved issues concerning sizing, control, peak loads, emergency operation, grid connection and export, etc. Natural Resources Canada has undertaken an initiative to investigate and develop techniques for the integration of small CHP systems into residential buildings using a highly instrumented house modified to allow quick installation and thorough monitoring of CHP integration techniques as well determining the performance of the CHP systems themselves when operating in a house. The first CHP system installed was a Stirling engine residential CHP system. It was used to examine the completeness of the CHP modifications to the house, to evaluate various building integration techniques and to measure the performance of the CHP system itself. The testing demonstrated the modified house to be an excellent facility for the development of CHP building integration techniques and the testing of residential CHP systems. The Stirling engine CHP system was found to operate well and produce meaningful input to the house. A second system (residential fuel cell) is presently being installed and building integration techniques and the performance of the fuel cell will be tested over the coming year. (author)

  20. Integrating Social Networking Tools into ESL Writing Classroom: Strengths and Weaknesses

    Science.gov (United States)

    Yunus, Melor Md; Salehi, Hadi; Chenzi, Chen

    2012-01-01

    With the rapid development of world and technology, English learning has become more important. Teachers frequently use teacher-centered pedagogy that leads to lack of interaction with students. This paper aims to investigate the advantages and disadvantages of integrating social networking tools into ESL writing classroom and discuss the ways to…

  1. Integration, mentoring & networking

    DEFF Research Database (Denmark)

    Bloksgaard, Lotte

    KVINFOs mentornetværk har siden 2003 anvendt mentoring og networking med det formål at åbne døre til det danske samfund og arbejdsmarked for kvinder med indvandrer-/flygtningebaggrund. I mentoringdelen matches kvinder med flygtninge- og indvandrerbaggrund (mentees) med kvinder, som er solidt...... KVINFOs mentornetværk, at indsamle og analysere disses erfaringer med at indgå i netværket samt opnå større viden om mentoring og networking som integrationsfremmende metoder....

  2. A control technique for integration of DG units to the electrical networks

    DEFF Research Database (Denmark)

    Pouresmaeil, Edris; Miguel-Espinar, Carlos; Massot-Campos, Miquel

    2013-01-01

    This paper deals with a multiobjective control technique for integration of distributed generation (DG) resources to the electrical power network. The proposed strategy provides compensation for active, reactive, and harmonic load current components during connection of DG link to the grid...

  3. Biomarker MicroRNAs for Diagnosis of Oral Squamous Cell Carcinoma Identified Based on Gene Expression Data and MicroRNA-mRNA Network Analysis

    Science.gov (United States)

    Zhang, Hui; Li, Tangxin; Zheng, Linqing

    2017-01-01

    Oral squamous cell carcinoma is one of the most malignant tumors with high mortality rate worldwide. Biomarker discovery is critical for early diagnosis and precision treatment of this disease. MicroRNAs are small noncoding RNA molecules which often regulate essential biological processes and are good candidates for biomarkers. By integrative analysis of both the cancer-associated gene expression data and microRNA-mRNA network, miR-148b-3p, miR-629-3p, miR-27a-3p, and miR-142-3p were screened as novel diagnostic biomarkers for oral squamous cell carcinoma based on their unique regulatory abilities in the network structure of the conditional microRNA-mRNA network and their important functions. These findings were confirmed by literature verification and functional enrichment analysis. Future experimental validation is expected for the further investigation of their molecular mechanisms. PMID:29098014

  4. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  5. Integrated workflows for spiking neuronal network simulations

    Directory of Open Access Journals (Sweden)

    Ján eAntolík

    2013-12-01

    Full Text Available The increasing availability of computational resources is enabling more detailed, realistic modelling in computational neuroscience, resulting in a shift towards more heterogeneous models of neuronal circuits, and employment of complex experimental protocols. This poses a challenge for existing tool chains, as the set of tools involved in a typical modeller's workflow is expanding concomitantly, with growing complexity in the metadata flowing between them. For many parts of the workflow, a range of tools is available; however, numerous areas lack dedicated tools, while integration of existing tools is limited. This forces modellers to either handle the workflow manually, leading to errors, or to write substantial amounts of code to automate parts of the workflow, in both cases reducing their productivity.To address these issues, we have developed Mozaik: a workflow system for spiking neuronal network simulations written in Python. Mozaik integrates model, experiment and stimulation specification, simulation execution, data storage, data analysis and visualisation into a single automated workflow, ensuring that all relevant metadata are available to all workflow components. It is based on several existing tools, including PyNN, Neo and Matplotlib. It offers a declarative way to specify models and recording configurations using hierarchically organised configuration files. Mozaik automatically records all data together with all relevant metadata about the experimental context, allowing automation of the analysis and visualisation stages. Mozaik has a modular architecture, and the existing modules are designed to be extensible with minimal programming effort. Mozaik increases the productivity of running virtual experiments on highly structured neuronal networks by automating the entire experimental cycle, while increasing the reliability of modelling studies by relieving the user from manual handling of the flow of metadata between the individual

  6. Synaptic network activity induces neuronal differentiation of adult hippocampal precursor cells through BDNF signaling

    Directory of Open Access Journals (Sweden)

    Harish Babu

    2009-09-01

    Full Text Available Adult hippocampal neurogenesis is regulated by activity. But how do neural precursor cells in the hippocampus respond to surrounding network activity and translate increased neural activity into a developmental program? Here we show that long-term potential (LTP-like synaptic activity within a cellular network of mature hippocampal neurons promotes neuronal differentiation of newly generated cells. In co-cultures of precursor cells with primary hippocampal neurons, LTP-like synaptic plasticity induced by addition of glycine in Mg2+-free media for 5 min, produced synchronous network activity and subsequently increased synaptic strength between neurons. Furthermore, this synchronous network activity led to a significant increase in neuronal differentiation from the co-cultured neural precursor cells. When applied directly to precursor cells, glycine and Mg2+-free solution did not induce neuronal differentiation. Synaptic plasticity-induced neuronal differentiation of precursor cells was observed in the presence of GABAergic neurotransmission blockers but was dependent on NMDA-mediated Ca2+ influx. Most importantly, neuronal differentiation required the release of brain-derived neurotrophic factor (BDNF from the underlying substrate hippocampal neurons as well as TrkB receptor phosphorylation in precursor cells. This suggests that activity-dependent stem cell differentiation within the hippocampal network is mediated via synaptically evoked BDNF signaling.

  7. Fuel Cell Development and Test Laboratory | Energy Systems Integration

    Science.gov (United States)

    Facility | NREL Fuel Cell Development and Test Laboratory Fuel Cell Development and Test Laboratory The Energy System Integration Facility's Fuel Cell Development and Test Laboratory supports fuel cell research and development projects through in-situ fuel cell testing. Photo of a researcher running

  8. Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

    Science.gov (United States)

    Banerjee, Ipsita

    2009-03-01

    Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

  9. Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks.

    Science.gov (United States)

    de Araújo, Paulo Régis C; Filho, Raimir Holanda; Rodrigues, Joel J P C; Oliveira, João P C M; Braga, Stephanie A

    2018-04-24

    At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

  10. Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Paulo Régis C. de Araújo

    2018-04-01

    Full Text Available At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs. In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

  11. Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

    Science.gov (United States)

    Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

    2015-10-01

    This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

  12. Cognitive small cell networks: energy efficiency and trade-offs

    NARCIS (Netherlands)

    Wildemeersch, M.; Wildemeersch, Matthias; Quek, T.Q.S.; Slump, Cornelis H.; Rabbachin, A.

    2013-01-01

    Heterogeneous networks using a mix of macrocells and small cells are foreseen as one of the solutions to meet the ever increasing mobile traffic demand. Nevertheless, a massive deployment of small cell access points (SAPs) leads also to a considerable increase in energy consumption. Spurred by

  13. Life on magnets: stem cell networking on micro-magnet arrays.

    Directory of Open Access Journals (Sweden)

    Vitalii Zablotskii

    Full Text Available Interactions between a micro-magnet array and living cells may guide the establishment of cell networks due to the cellular response to a magnetic field. To manipulate mesenchymal stem cells free of magnetic nanoparticles by a high magnetic field gradient, we used high quality micro-patterned NdFeB films around which the stray field's value and direction drastically change across the cell body. Such micro-magnet arrays coated with parylene produce high magnetic field gradients that affect the cells in two main ways: i causing cell migration and adherence to a covered magnetic surface and ii elongating the cells in the directions parallel to the edges of the micro-magnet. To explain these effects, three putative mechanisms that incorporate both physical and biological factors influencing the cells are suggested. It is shown that the static high magnetic field gradient generated by the micro-magnet arrays are capable of assisting cell migration to those areas with the strongest magnetic field gradient, thereby allowing the build up of tunable interconnected stem cell networks, which is an elegant route for tissue engineering and regenerative medicine.

  14. Integrating a social network group with a 3D collaborative learning environment

    NARCIS (Netherlands)

    Pourmirza, S.; Gardner, M.; Callaghan, V; Augusto, J.C.; Zhang, T.

    2014-01-01

    Although extensive research has been carried out on virtual learning environments and the role of groups and communities in social networks, few studies exist which adequately cover the relationship between these two domains. In this paper, the authors demonstrate the effectiveness of integrating

  15. Students' network integration as a predictor of persistence in introductory physics courses

    Science.gov (United States)

    Zwolak, Justyna P.; Dou, Remy; Williams, Eric A.; Brewe, Eric

    2017-06-01

    Increasing student retention (successfully finishing a particular course) and persistence (continuing through a sequence of courses or the major area of study) is currently a major challenge for universities. While students' academic and social integration into an institution seems to be vital for student retention, research into the effect of interpersonal interactions is rare. We use network analysis as an approach to investigate academic and social experiences of students in the classroom. In particular, centrality measures identify patterns of interaction that contribute to integration into the university. Using these measures, we analyze how position within a social network in a Modeling Instruction (MI) course—an introductory physics course that strongly emphasizes interactive learning—predicts their persistence in taking a subsequent physics course. Students with higher centrality at the end of the first semester of MI are more likely to enroll in a second semester of MI. Moreover, we found that chances of successfully predicting individual student's persistence based on centrality measures are fairly high—up to 75%, making the centrality a good predictor of persistence. These findings suggest that increasing student social integration may help in improving persistence in science, technology, engineering, and mathematics fields.

  16. Improving the Reliability of Network Metrics in Structural Brain Networks by Integrating Different Network Weighting Strategies into a Single Graph

    Directory of Open Access Journals (Sweden)

    Stavros I. Dimitriadis

    2017-12-01

    Full Text Available Structural brain networks estimated from diffusion MRI (dMRI via tractography have been widely studied in healthy controls and patients with neurological and psychiatric diseases. However, few studies have addressed the reliability of derived network metrics both node-specific and network-wide. Different network weighting strategies (NWS can be adopted to weight the strength of connection between two nodes yielding structural brain networks that are almost fully-weighted. Here, we scanned five healthy participants five times each, using a diffusion-weighted MRI protocol and computed edges between 90 regions of interest (ROI from the Automated Anatomical Labeling (AAL template. The edges were weighted according to nine different methods. We propose a linear combination of these nine NWS into a single graph using an appropriate diffusion distance metric. We refer to the resulting weighted graph as an Integrated Weighted Structural Brain Network (ISWBN. Additionally, we consider a topological filtering scheme that maximizes the information flow in the brain network under the constraint of the overall cost of the surviving connections. We compared each of the nine NWS and the ISWBN based on the improvement of: (a intra-class correlation coefficient (ICC of well-known network metrics, both node-wise and per network level; and (b the recognition accuracy of each subject compared to the remainder of the cohort, as an attempt to access the uniqueness of the structural brain network for each subject, after first applying our proposed topological filtering scheme. Based on a threshold where the network level ICC should be >0.90, our findings revealed that six out of nine NWS lead to unreliable results at the network level, while all nine NWS were unreliable at the node level. In comparison, our proposed ISWBN performed as well as the best performing individual NWS at the network level, and the ICC was higher compared to all individual NWS at the node

  17. Astrocyte physiopathology: At the crossroads of intercellular networking, inflammation and cell death.

    Science.gov (United States)

    Rossi, Daniela

    2015-07-01

    Recent breakthroughs in neuroscience have led to the awareness that we should revise our traditional mode of thinking and studying the CNS, i.e. by isolating the privileged network of "intelligent" synaptic contacts. We may instead need to contemplate all the variegate communications occurring between the different neural cell types, and centrally involving the astrocytes. Basically, it appears that a single astrocyte should be considered as a core that receives and integrates information from thousands of synapses, other glial cells and the blood vessels. In turn, it generates complex outputs that control the neural circuitry and coordinate it with the local microcirculation. Astrocytes thus emerge as the possible fulcrum of the functional homeostasis of the healthy CNS. Yet, evidence indicates that the bridging properties of the astrocytes can change in parallel with, or as a result of, the morphological, biochemical and functional alterations these cells undergo upon injury or disease. As a consequence, they have the potential to transform from supportive friends and interactive partners for neurons into noxious foes. In this review, we summarize the currently available knowledge on the contribution of astrocytes to the functioning of the CNS and what goes wrong in various pathological conditions, with a particular focus on Amyotrophic Lateral Sclerosis, Alzheimer's Disease and ischemia. The observations described convincingly demonstrate that the development and progression of several neurological disorders involve the de-regulation of a finely tuned interplay between multiple cell populations. Thus, it seems that a better understanding of the mechanisms governing the integrated communication and detrimental responses of the astrocytes as well as their impact towards the homeostasis and performance of the CNS is fundamental to open novel therapeutic perspectives. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. Protein complex detection in PPI networks based on data integration and supervised learning method.

    Science.gov (United States)

    Yu, Feng; Yang, Zhi; Hu, Xiao; Sun, Yuan; Lin, Hong; Wang, Jian

    2015-01-01

    Revealing protein complexes are important for understanding principles of cellular organization and function. High-throughput experimental techniques have produced a large amount of protein interactions, which makes it possible to predict protein complexes from protein-protein interaction (PPI) networks. However, the small amount of known physical interactions may limit protein complex detection. The new PPI networks are constructed by integrating PPI datasets with the large and readily available PPI data from biomedical literature, and then the less reliable PPI between two proteins are filtered out based on semantic similarity and topological similarity of the two proteins. Finally, the supervised learning protein complex detection (SLPC), which can make full use of the information of available known complexes, is applied to detect protein complex on the new PPI networks. The experimental results of SLPC on two different categories yeast PPI networks demonstrate effectiveness of the approach: compared with the original PPI networks, the best average improvements of 4.76, 6.81 and 15.75 percentage units in the F-score, accuracy and maximum matching ratio (MMR) are achieved respectively; compared with the denoising PPI networks, the best average improvements of 3.91, 4.61 and 12.10 percentage units in the F-score, accuracy and MMR are achieved respectively; compared with ClusterONE, the start-of the-art complex detection method, on the denoising extended PPI networks, the average improvements of 26.02 and 22.40 percentage units in the F-score and MMR are achieved respectively. The experimental results show that the performances of SLPC have a large improvement through integration of new receivable PPI data from biomedical literature into original PPI networks and denoising PPI networks. In addition, our protein complexes detection method can achieve better performance than ClusterONE.

  19. SAMNet: a network-based approach to integrate multi-dimensional high throughput datasets.

    Science.gov (United States)

    Gosline, Sara J C; Spencer, Sarah J; Ursu, Oana; Fraenkel, Ernest

    2012-11-01

    The rapid development of high throughput biotechnologies has led to an onslaught of data describing genetic perturbations and changes in mRNA and protein levels in the cell. Because each assay provides a one-dimensional snapshot of active signaling pathways, it has become desirable to perform multiple assays (e.g. mRNA expression and phospho-proteomics) to measure a single condition. However, as experiments expand to accommodate various cellular conditions, proper analysis and interpretation of these data have become more challenging. Here we introduce a novel approach called SAMNet, for Simultaneous Analysis of Multiple Networks, that is able to interpret diverse assays over multiple perturbations. The algorithm uses a constrained optimization approach to integrate mRNA expression data with upstream genes, selecting edges in the protein-protein interaction network that best explain the changes across all perturbations. The result is a putative set of protein interactions that succinctly summarizes the results from all experiments, highlighting the network elements unique to each perturbation. We evaluated SAMNet in both yeast and human datasets. The yeast dataset measured the cellular response to seven different transition metals, and the human dataset measured cellular changes in four different lung cancer models of Epithelial-Mesenchymal Transition (EMT), a crucial process in tumor metastasis. SAMNet was able to identify canonical yeast metal-processing genes unique to each commodity in the yeast dataset, as well as human genes such as β-catenin and TCF7L2/TCF4 that are required for EMT signaling but escaped detection in the mRNA and phospho-proteomic data. Moreover, SAMNet also highlighted drugs likely to modulate EMT, identifying a series of less canonical genes known to be affected by the BCR-ABL inhibitor imatinib (Gleevec), suggesting a possible influence of this drug on EMT.

  20. A local network integrated into a balloon-borne apparatus

    Science.gov (United States)

    Imori, Masatosi; Ueda, Ikuo; Shimamura, Kotaro; Maeno, Tadashi; Murata, Takahiro; Sasaki, Makoto; Matsunaga, Hiroyuki; Matsumoto, Hiroshi; Shikaze, Yoshiaki; Anraku, Kazuaki; Matsui, Nagataka; Yamagami, Takamasa

    A local network is incorporated into an apparatus for a balloon-borne experiment. A balloon-borne system implemented in the apparatus is composed of subsystems interconnected through a local network, which introduces modular architecture into the system. The network decomposes the balloon-borne system into subsystems, which are similarly structured from the point of view that the systems is kept under the control of a ground station. The subsystem is functionally self-contained and electrically independent. A computer is integrated into a subsystem, keeping the subsystem under the control. An independent group of batteries, being dedicated to a subsystem, supplies the whole electricity of the subsystem. The subsystem could be turned on and off independently of the other subsystems. So communication among the subsystems needs to be based on such a protocol that could guarantee the independence of the individual subsystems. An Omninet protocol is employed to network the subsystems. A ground station sends commands to the balloon-borne system. The command is received and executed at the system, then results of the execution are returned to the ground station. Various commands are available so that the system borne on a balloon could be controlled and monitored remotely from the ground station. A subsystem responds to a specific group of commands. A command is received by a transceiver subsystem and then transferred through the network to the subsystem to which the command is addressed. Then the subsystem executes the command and returns results to the transceiver subsystem, where the results are telemetered to the ground station. The network enhances independence of the individual subsystems, which enables programs of the individual subsystems to be coded independently. Independence facilitates development and debugging of programs, improving the quality of the system borne on a balloon.

  1. Study on Network Error Analysis and Locating based on Integrated Information Decision System

    Science.gov (United States)

    Yang, F.; Dong, Z. H.

    2017-10-01

    Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.

  2. Standard cell-based implementation of a digital optoelectronic neural-network hardware.

    Science.gov (United States)

    Maier, K D; Beckstein, C; Blickhan, R; Erhard, W

    2001-03-10

    A standard cell-based implementation of a digital optoelectronic neural-network architecture is presented. The overall structure of the multilayer perceptron network that was used, the optoelectronic interconnection system between the layers, and all components required in each layer are defined. The design process from VHDL-based modeling from synthesis and partly automatic placing and routing to the final editing of one layer of the circuit of the multilayer perceptrons are described. A suitable approach for the standard cell-based design of optoelectronic systems is presented, and shortcomings of the design tool that was used are pointed out. The layout for the microelectronic circuit of one layer in a multilayer perceptron neural network with a performance potential 1 magnitude higher than neural networks that are purely electronic based has been successfully designed.

  3. Yeast casein kinase 2 governs morphology, biofilm formation, cell wall integrity, and host cell damage of Candida albicans.

    Science.gov (United States)

    Jung, Sook-In; Rodriguez, Natalie; Irrizary, Jihyun; Liboro, Karl; Bogarin, Thania; Macias, Marlene; Eivers, Edward; Porter, Edith; Filler, Scott G; Park, Hyunsook

    2017-01-01

    The regulatory networks governing morphogenesis of a pleomorphic fungus, Candida albicans are extremely complex and remain to be completely elucidated. This study investigated the function of C. albicans yeast casein kinase 2 (CaYck2p). The yck2Δ/yck2Δ strain displayed constitutive pseudohyphae in both yeast and hyphal growth conditions, and formed enhanced biofilm under non-biofilm inducing condition. This finding was further supported by gene expression analysis of the yck2Δ/yck2Δ strain which showed significant upregulation of UME6, a key transcriptional regulator of hyphal transition and biofilm formation, and cell wall protein genes ALS3, HWP1, and SUN41, all of which are associated with morphogenesis and biofilm architecture. The yck2Δ/yck2Δ strain was hypersensitive to cell wall damaging agents and had increased compensatory chitin deposition in the cell wall accompanied by an upregulation of the expression of the chitin synthase genes, CHS2, CHS3, and CHS8. Absence of CaYck2p also affected fungal-host interaction; the yck2Δ/yck2Δ strain had significantly reduced ability to damage host cells. However, the yck2Δ/yck2Δ strain had wild-type susceptibility to cyclosporine and FK506, suggesting that CaYck2p functions independently from the Ca+/calcineurin pathway. Thus, in C. albicans, Yck2p is a multifunctional kinase that governs morphogenesis, biofilm formation, cell wall integrity, and host cell interactions.

  4. Multilayer network modeling of integrated biological systems. Comment on "Network science of biological systems at different scales: A review" by Gosak et al.

    Science.gov (United States)

    De Domenico, Manlio

    2018-03-01

    Biological systems, from a cell to the human brain, are inherently complex. A powerful representation of such systems, described by an intricate web of relationships across multiple scales, is provided by complex networks. Recently, several studies are highlighting how simple networks - obtained by aggregating or neglecting temporal or categorical description of biological data - are not able to account for the richness of information characterizing biological systems. More complex models, namely multilayer networks, are needed to account for interdependencies, often varying across time, of biological interacting units within a cell, a tissue or parts of an organism.

  5. Cell Culture Systems To Study Human Herpesvirus 6A/B Chromosomal Integration.

    Science.gov (United States)

    Gravel, Annie; Dubuc, Isabelle; Wallaschek, Nina; Gilbert-Girard, Shella; Collin, Vanessa; Hall-Sedlak, Ruth; Jerome, Keith R; Mori, Yasuko; Carbonneau, Julie; Boivin, Guy; Kaufer, Benedikt B; Flamand, Louis

    2017-07-15

    Human herpesviruses 6A/B (HHV-6A/B) can integrate their viral genomes in the telomeres of human chromosomes. The viral and cellular factors contributing to HHV-6A/B integration remain largely unknown, mostly due to the lack of efficient and reproducible cell culture models to study HHV-6A/B integration. In this study, we characterized the HHV-6A/B integration efficiencies in several human cell lines using two different approaches. First, after a short-term infection (5 h), cells were processed for single-cell cloning and analyzed for chromosomally integrated HHV-6A/B (ciHHV-6A/B). Second, cells were infected with HHV-6A/B and allowed to grow in bulk for 4 weeks or longer and then analyzed for the presence of ciHHV-6. Using quantitative PCR (qPCR), droplet digital PCR, and fluorescent in situ hybridization, we could demonstrate that HHV-6A/B integrated in most human cell lines tested, including telomerase-positive (HeLa, MCF-7, HCT-116, and HEK293T) and telomerase-negative cell lines (U2OS and GM847). Our results also indicate that inhibition of DNA replication, using phosphonoacetic acid, did not affect HHV-6A/B integration. Certain clones harboring ciHHV-6A/B spontaneously express viral genes and proteins. Treatment of cells with phorbol ester or histone deacetylase inhibitors triggered the expression of many viral genes, including U39 , U90 , and U100 , without the production of infectious virus, suggesting that the tested stimuli were not sufficient to trigger full reactivation. In summary, both integration models yielded comparable results and should enable the identification of viral and cellular factors contributing to HHV-6A/B integration and the screening of drugs influencing viral gene expression, as well as the release of infectious HHV-6A/B from the integrated state. IMPORTANCE The analysis and understanding of HHV-6A/B genome integration into host DNA is currently limited due to the lack of reproducible and efficient viral integration systems. In the

  6. Demonstration of Hydrogen Energy Network and Fuel Cells in Residential Homes

    International Nuclear Information System (INIS)

    Hirohisa Aki; Tetsuhiko Maeda; Itaru Tamura; Akeshi Kegasa; Yoshiro Ishikawa; Ichiro Sugimoto; Itaru Ishii

    2006-01-01

    The authors proposed the setting up of an energy interchange system by establishing energy networks of electricity, hot water, and hydrogen in residential homes. In such networks, some homes are equipped with fuel cell stacks, fuel processors, hydrogen storage devices, and large storage tanks for hot water. The energy network enables the flexible operation of the fuel cell stacks and fuel processors. A demonstration project has been planned in existing residential homes to evaluate the proposal. The demonstration will be presented in a small apartment building. The building will be renovated and will be equipped with a hydrogen production facility, a hydrogen interchange pipe, and fuel cell stacks with a heat recovery device. The energy flow process from hydrogen production to consumption in the homes will be demonstrated. This paper presents the proposed energy interchange system and demonstration project. (authors)

  7. Integrated Meteorological Observation Network in Castile-León (Spain)

    Science.gov (United States)

    Merino, A.; Guerrero-Higueras, A. M.; Ortiz de Galisteo, J. P.; López, L.; García-Ortega, E.; Nafría, D. A.; Sánchez, J. L.

    2012-04-01

    In the region of Castile-Leon, in the northwest of Spain, the study of weather risks is extremely complex because of the topography, the large land area of the region and the variety of climatic features involved. Therefore, as far as the calibration and validation of the necessary tools for the identification and nowcasting of these risks are concerned, one of the most important difficulties is the lack of observed data. The same problem arises, for example, in the analysis of particularly relevant case studies. It was hence deemed necessary to create an INTEGRATED METEOROLOGICAL OBSERVATION NETWORK FOR CASTILE-LEON. The aim of this network is to integrate within one single platform all the ground truth data available. These data enable us to detect a number of weather risks in real time. The various data sources should include the networks from the weather stations run by different public institutions - national and regional ones (AEMET, Junta de Castilla y León, Universities, etc.) -, as well as the stations run by voluntary observers. The platform will contain real or cuasi-real time data from the ground weather stations, but it will also have applications to enable voluntary observers to indicate the presence or absence of certain meteors (snow, hail) or even provide detailed information about them (hailstone size, graupel, etc.). The data managed by this network have a high scientific potential, as they may be used for a number of different purposes: calibration and validation of remote sensing tools, assimilation of observation data from numerical models, study of extreme weather events, etc. An additional aim of the network is the drawing of maps of weather risks in real time. These maps are of great importance for the people involved in risk management in each region, as well as for the general public. Finally, one of the first applications developed has been the creation of observation maps in real time. These applications have been constructed using NCL

  8. Characteristics of DNA-AuNP networks on cell membranes and real-time movies for viral infection.

    Science.gov (United States)

    Li, Chunmei; Zheng, Linling; Yang, Xiaoxi; Wan, Xiaoyan; Wu, Wenbi; Zhen, Shujun; Li, Yuanfang; Luo, Lingfei; Huang, Chengzhi

    2016-03-01

    This data article provides complementary data for the article entitled "DNA-AuNP networks on cell membranes as a protective barrier to inhibit viral attachment, entry and budding" Li et al. (2016) [1]. The experimental methods for the preparation and characterization of DNA-conjugated nanoparticle networks on cell membranes were described. Confocal fluorescence images, agarose gel electrophoresis images and hydrodynamic diameter of DNA-conjugated gold nanoparticle (DNA-AuNP) networks were presented. In addition, we have prepared QDs-labeled RSV (QDs-RSV) to real-time monitor the RSV infection on HEp-2 cells in the absence and presence of DNA-AuNP networks. Finally, the cell viability of HEp-2 cells coated by six types of DNA-nanoparticle networks was determined after RSV infection.

  9. Ties That Bind: A Social Network Approach to Understanding Student Integration and Persistence. ASHE Annual Meeting Paper.

    Science.gov (United States)

    Thomas, Scott L.

    This study examined the social networks of college students and how such networks affect student commitment and persistence. The study's theoretical framework was based on application of the social network paradigm to Tinto's Student Integration Model, in which a student's initial commitment is modified over time as a result of the student's…

  10. Integrating intracellular dynamics using CompuCell3D and Bionetsolver: applications to multiscale modelling of cancer cell growth and invasion.

    Directory of Open Access Journals (Sweden)

    Vivi Andasari

    Full Text Available In this paper we present a multiscale, individual-based simulation environment that integrates CompuCell3D for lattice-based modelling on the cellular level and Bionetsolver for intracellular modelling. CompuCell3D or CC3D provides an implementation of the lattice-based Cellular Potts Model or CPM (also known as the Glazier-Graner-Hogeweg or GGH model and a Monte Carlo method based on the metropolis algorithm for system evolution. The integration of CC3D for cellular systems with Bionetsolver for subcellular systems enables us to develop a multiscale mathematical model and to study the evolution of cell behaviour due to the dynamics inside of the cells, capturing aspects of cell behaviour and interaction that is not possible using continuum approaches. We then apply this multiscale modelling technique to a model of cancer growth and invasion, based on a previously published model of Ramis-Conde et al. (2008 where individual cell behaviour is driven by a molecular network describing the dynamics of E-cadherin and β-catenin. In this model, which we refer to as the centre-based model, an alternative individual-based modelling technique was used, namely, a lattice-free approach. In many respects, the GGH or CPM methodology and the approach of the centre-based model have the same overall goal, that is to mimic behaviours and interactions of biological cells. Although the mathematical foundations and computational implementations of the two approaches are very different, the results of the presented simulations are compatible with each other, suggesting that by using individual-based approaches we can formulate a natural way of describing complex multi-cell, multiscale models. The ability to easily reproduce results of one modelling approach using an alternative approach is also essential from a model cross-validation standpoint and also helps to identify any modelling artefacts specific to a given computational approach.

  11. Trends in Energy Management Technology: BCS Integration Technologies - Open Communications Networking

    Energy Technology Data Exchange (ETDEWEB)

    Webster, Tom

    2002-09-18

    Our overall purpose in writing this series of articles is to provide Federal energy managers some basic informational tools to assist their decision making process relative to energy management systems design, specification, procurement, and energy savings potential. Since Federal buildings rely on energy management systems more than their commercial counterparts, it is important for energy practitioners to have a high level of knowledge and understanding of these complex systems. This is the second article in a series and will focus on building control system (BCS) networking fundamentals and an assessment of current approaches to open communications protocols. This is important because networking is a complex subject and the networks form the basic infrastructure for energy management functions and for integrating a wide variety of OEM equipment into a complete EMCIS. The first article [1] covered enabling technologies for emerging energy management systems. Future topics will concentrate on more practical aspects including applications software, product offerings, networking strategies, and case studies of actual installations. Please refer to the first article for a more complete overview of the purpose and background for this series.

  12. Sum rate maximization in the uplink of multi-cell OFDMA networks

    KAUST Repository

    Tabassum, Hina; Alouini, Mohamed-Slim; Dawy, Zaher

    2012-01-01

    of each cell, while ignoring the significant effect of inter-cell interference. This paper investigates the problem of resource allocation (i.e., subcarriers and powers) in the uplink of a multi-cell OFDMA network. The problem has a non

  13. Neural Networks Integrated Circuit for Biomimetics MEMS Microrobot

    Directory of Open Access Journals (Sweden)

    Ken Saito

    2014-06-01

    Full Text Available In this paper, we will propose the neural networks integrated circuit (NNIC which is the driving waveform generator of the 4.0, 2.7, 2.5 mm, width, length, height in size biomimetics microelectromechanical systems (MEMS microrobot. The microrobot was made from silicon wafer fabricated by micro fabrication technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ant-like switching behavior. The NNIC generates the driving waveform using synchronization phenomena such as biological neural networks. The driving waveform can operate the actuators of the MEMS microrobot directly. Therefore, the NNIC bare chip realizes the robot control without using any software programs or A/D converters. The microrobot performed forward and backward locomotion, and also changes direction by inputting an external single trigger pulse. The locomotion speed of the microrobot was 26.4 mm/min when the step width was 0.88 mm. The power consumption of the system was 250 mWh when the room temperature was 298 K.

  14. The Value of Partial Resource Pooling: Should a Service Network Be Integrated or Product-Focused?

    OpenAIRE

    Bar{\\i}\\c{s} Ata; Jan A. Van Mieghem

    2009-01-01

    We investigate how dynamic resource substitution in service systems impacts capacity requirements and responsiveness. Inspired by the contrasting network strategies of FedEx and United Parcel Service (UPS), we study when two service classes (e.g., express or regular) should be served by dedicated resources (e.g., air or ground) or by an integrated network (e.g., air also serves regular). Using call center terminology, the question is whether to operate two independent queues or one N-network....

  15. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    Energy Technology Data Exchange (ETDEWEB)

    Santra, Tapesh, E-mail: tapesh.santra@ucd.ie [Systems Biology Ireland, University College Dublin, Dublin (Ireland)

    2014-05-20

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  16. A Bayesian Framework That Integrates Heterogeneous Data for Inferring Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Santra, Tapesh

    2014-01-01

    Reconstruction of gene regulatory networks (GRNs) from experimental data is a fundamental challenge in systems biology. A number of computational approaches have been developed to infer GRNs from mRNA expression profiles. However, expression profiles alone are proving to be insufficient for inferring GRN topologies with reasonable accuracy. Recently, it has been shown that integration of external data sources (such as gene and protein sequence information, gene ontology data, protein–protein interactions) with mRNA expression profiles may increase the reliability of the inference process. Here, I propose a new approach that incorporates transcription factor binding sites (TFBS) and physical protein interactions (PPI) among transcription factors (TFs) in a Bayesian variable selection (BVS) algorithm which can infer GRNs from mRNA expression profiles subjected to genetic perturbations. Using real experimental data, I show that the integration of TFBS and PPI data with mRNA expression profiles leads to significantly more accurate networks than those inferred from expression profiles alone. Additionally, the performance of the proposed algorithm is compared with a series of least absolute shrinkage and selection operator (LASSO) regression-based network inference methods that can also incorporate prior knowledge in the inference framework. The results of this comparison suggest that BVS can outperform LASSO regression-based method in some circumstances.

  17. Quantitative proteomics reveals middle infrared radiation-interfered networks in breast cancer cells.

    Science.gov (United States)

    Chang, Hsin-Yi; Li, Ming-Hua; Huang, Tsui-Chin; Hsu, Chia-Lang; Tsai, Shang-Ru; Lee, Si-Chen; Huang, Hsuan-Cheng; Juan, Hsueh-Fen

    2015-02-06

    Breast cancer is one of the leading cancer-related causes of death worldwide. Treatment of triple-negative breast cancer (TNBC) is complex and challenging, especially when metastasis has developed. In this study, we applied infrared radiation as an alternative approach for the treatment of TNBC. We used middle infrared (MIR) with a wavelength range of 3-5 μm to irradiate breast cancer cells. MIR significantly inhibited cell proliferation in several breast cancer cells but did not affect the growth of normal breast epithelial cells. We performed iTRAQ-coupled LC-MS/MS analysis to investigate the MIR-triggered molecular mechanisms in breast cancer cells. A total of 1749 proteins were identified, quantified, and subjected to functional enrichment analysis. From the constructed functionally enriched network, we confirmed that MIR caused G2/M cell cycle arrest, remodeled the microtubule network to an astral pole arrangement, altered the actin filament formation and focal adhesion molecule localization, and reduced cell migration activity and invasion ability. Our results reveal the coordinative effects of MIR-regulated physiological responses in concentrated networks, demonstrating the potential implementation of infrared radiation in breast cancer therapy.

  18. Natural killer cell signal integration balances synapse symmetry and migration.

    Directory of Open Access Journals (Sweden)

    Fiona J Culley

    2009-07-01

    Full Text Available Natural killer (NK cells discern the health of other cells by recognising the balance of activating and inhibitory ligands expressed by each target cell. However, how the integration of activating and inhibitory signals relates to formation of the NK cell immune synapse remains a central question in our understanding of NK cell recognition. Here we report that ligation of LFA-1 on NK cells induced asymmetrical cell spreading and migration. In contrast, ligation of the activating receptor NKG2D induced symmetrical spreading of ruffled lamellipodia encompassing a dynamic ring of f-actin, concurrent with polarization towards a target cell and a "stop" signal. Ligation of both LFA-1 and NKG2D together resulted in symmetrical spreading but co-ligation of inhibitory receptors reverted NK cells to an asymmetrical migratory configuration leading to inhibitory synapses being smaller and more rapidly disassembled. Using micropatterned activating and inhibitory ligands, signals were found to be continuously and locally integrated during spreading. Together, these data demonstrate that NK cells spread to form large, stable, symmetrical synapses if activating signals dominate, whereas asymmetrical migratory "kinapses" are favoured if inhibitory signals dominate. This clarifies how the integration of activating and inhibitory receptor signals is translated to an appropriate NK cell response.

  19. Analysis of network motifs in cellular regulation: Structural similarities, input-output relations and signal integration.

    Science.gov (United States)

    Straube, Ronny

    2017-12-01

    Much of the complexity of regulatory networks derives from the necessity to integrate multiple signals and to avoid malfunction due to cross-talk or harmful perturbations. Hence, one may expect that the input-output behavior of larger networks is not necessarily more complex than that of smaller network motifs which suggests that both can, under certain conditions, be described by similar equations. In this review, we illustrate this approach by discussing the similarities that exist in the steady state descriptions of a simple bimolecular reaction, covalent modification cycles and bacterial two-component systems. Interestingly, in all three systems fundamental input-output characteristics such as thresholds, ultrasensitivity or concentration robustness are described by structurally similar equations. Depending on the system the meaning of the parameters can differ ranging from protein concentrations and affinity constants to complex parameter combinations which allows for a quantitative understanding of signal integration in these systems. We argue that this approach may also be extended to larger regulatory networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  20. Elucidation of time-dependent systems biology cell response patterns with time course network enrichment

    DEFF Research Database (Denmark)

    Wiwie, Christian; Rauch, Alexander; Haakonsson, Anders

    2018-01-01

    , no methods exist to integrate time series data with networks, thus preventing the identification of time-dependent systems biology responses. We close this gap with Time Course Network Enrichment (TiCoNE). It combines a new kind of human-augmented clustering with a novel approach to network enrichment...