Sample records for cellular signaling networks

  1. Perturbation Biology: inferring signaling networks in cellular systems

    Molinelli, Evan J.; Korkut, Anil; Wang, Weiqing; Miller, Martin L; Gauthier, Nicholas P.; Jing, Xiaohong; Kaushik, Poorvi; He, Qin; Mills, Gordon; Solit, David B.; Pratilas, Christine A.; Weigt, Martin; Braunstein, Alfredo; Pagnani, Andrea; Zecchina, Riccardo


    Author Summary Drugs that target specific effects of signaling proteins are promising agents for treating cancer. One of the many obstacles facing optimal drug design is inadequate quantitative understanding of the coordinated interactions between signaling proteins. De novo model inference of network or pathway models refers to the algorithmic construction of mathematical predictive models from experimental data without dependence on prior knowledge. De novo inference is difficult because of...

  2. Methods for the Analysis of Protein Phosphorylation–Mediated Cellular Signaling Networks

    White, Forest M.; Wolf-Yadlin, Alejandro


    Protein phosphorylation–mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

  3. Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks.

    White, Forest M; Wolf-Yadlin, Alejandro


    Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks. PMID:27049636

  4. Method for analyzing signaling networks in complex cellular systems.

    Plavec, Ivan; Sirenko, Oksana; Privat, Sylvie; Wang, Yuker; Dajee, Maya; Melrose, Jennifer; Nakao, Brian; Hytopoulos, Evangelos; Berg, Ellen L; Butcher, Eugene C


    Now that the human genome has been sequenced, the challenge of assigning function to human genes has become acute. Existing approaches using microarrays or proteomics frequently generate very large volumes of data not directly related to biological function, making interpretation difficult. Here, we describe a technique for integrative systems biology in which: (i) primary cells are cultured under biologically meaningful conditions; (ii) a limited number of biologically meaningful readouts are measured; and (iii) the results obtained under several different conditions are combined for analysis. Studies of human endothelial cells overexpressing different signaling molecules under multiple inflammatory conditions show that this system can capture a remarkable range of functions by a relatively small number of simple measurements. In particular, measurement of seven different protein levels by ELISA under four different conditions is capable of reconstructing pathway associations of 25 different proteins representing four known signaling pathways, implicating additional participants in the NF-kappaBorRAS/mitogen-activated protein kinase pathways and defining additional interactions between these pathways. PMID:14745015

  5. A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy

    Müller, Jens; Müller, Jan; Tetzlaff, Ronald


    For processing of EEG signals, we propose a new architecture for the hardware emulation of discrete-time Cellular Nonlinear Networks (DT-CNN). Our results show the importance of a high computational accuracy in EEG signal prediction that cannot be achieved with existing analogue VLSI circuits. The refined architecture of the processing elements and its resource schedule, the cellular network structure with local couplings, the FPGA-based embedded system containing the DT-CNN, and the data flow in the entire system will be discussed in detail. The proposed DT-CNN design has been implemented and tested on an Xilinx FPGA development platform. The embedded co-processor with a multi-threading kernel is utilised for control and pre-processing tasks and data exchange to the host via Ethernet. The performance of the implemented DT-CNN has been determined for a popular example and compared to that of a conventional computer.

  6. Signal Quality Outage Analysis for Ultra-Reliable Communications in Cellular Networks

    Gerardino, Guillermo Andrés Pocovi; Alvarez, Beatriz Soret; Lauridsen, Mads; Pedersen, Klaus I.; Mogensen, Preben Elgaard

    Ultra-reliable communications over wireless will open the possibility for a wide range of novel use cases and applications. In cellular networks, achieving reliable communication is challenging due to many factors, particularly the fading of the desired signal and the interference. In this regard...... schemes must be complemented with macroscopic diversity as well as interference management techniques in order to ensure the necessary SINR outage performance. Based on the obtained performance results, it is discussed which of the feasible options fulfilling the ultra-reliable criteria are most promising...

  7. Signal processing in cellular clocks

    Forger, Daniel B.


    Many biochemical events within a cell need to be timed properly to occur at specific times of day, after other events have happened within the cell or in response to environmental signals. The cellular biochemical feedback loops that time these events have already received much recent attention in the experimental and modeling communities. Here, we show how ideas from signal processing can be applied to understand the function of these clocks. Consider two signals from the network s(t) and r(...

  8. Molecular and Cellular Signaling

    Beckerman, Martin


    A small number of signaling pathways, no more than a dozen or so, form a control layer that is responsible for all signaling in and between cells of the human body. The signaling proteins belonging to the control layer determine what kinds of cells are made during development and how they function during adult life. Malfunctions in the proteins belonging to the control layer are responsible for a host of human diseases ranging from neurological disorders to cancers. Most drugs target components in the control layer, and difficulties in drug design are intimately related to the architecture of the control layer. Molecular and Cellular Signaling provides an introduction to molecular and cellular signaling in biological systems with an emphasis on the underlying physical principles. The text is aimed at upper-level undergraduates, graduate students and individuals in medicine and pharmacology interested in broadening their understanding of how cells regulate and coordinate their core activities and how diseases ...

  9. The Influence of Gaussian Signaling Approximation on Error Performance in Cellular Networks

    Afify, Laila H.


    Stochastic geometry analysis for cellular networks is mostly limited to outage probability and ergodic rate, which abstracts many important wireless communication aspects. Recently, a novel technique based on the Equivalent-in-Distribution (EiD) approach is proposed to extend the analysis to capture these metrics and analyze bit error probability (BEP) and symbol error probability (SEP). However, the EiD approach considerably increases the complexity of the analysis. In this paper, we propose an approximate yet accurate framework, that is also able to capture fine wireless communication details similar to the EiD approach, but with simpler analysis. The proposed methodology is verified against the exact EiD analysis in both downlink and uplink cellular networks scenarios.

  10. Heterogeneous cellular networks

    Hu, Rose Qingyang


    A timely publication providing coverage of radio resource management, mobility management and standardization in heterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentum in industry and the research community, attracting the attention of standardization bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are looking into increasing the capacity and coverage of the cellular networks. This book focuses on recent progresses,  covering the related topics including scenarios of heterogeneous network deployment, interference management i

  11. From Cellular Attractor Selection to Adaptive Signal Control for Traffic Networks

    Tian, Daxin; Zhou, Jianshan; Sheng, Zhengguo; Wang, Yunpeng; Ma, Jianming


    The management of varying traffic flows essentially depends on signal controls at intersections. However, design an optimal control that considers the dynamic nature of a traffic network and coordinates all intersections simultaneously in a centralized manner is computationally challenging. Inspired by the stable gene expressions of Escherichia coli in response to environmental changes, we explore the robustness and adaptability performance of signalized intersections by incorporating a biological mechanism in their control policies, specifically, the evolution of each intersection is induced by the dynamics governing an adaptive attractor selection in cells. We employ a mathematical model to capture such biological attractor selection and derive a generic, adaptive and distributed control algorithm which is capable of dynamically adapting signal operations for the entire dynamical traffic network. We show that the proposed scheme based on attractor selection can not only promote the balance of traffic loads on each link of the network but also allows the global network to accommodate dynamical traffic demands. Our work demonstrates the potential of bio-inspired intelligence emerging from cells and provides a deep understanding of adaptive attractor selection-based control formation that is useful to support the designs of adaptive optimization and control in other domains.

  12. Mapping the spatiotemporal dynamics of calcium signaling in cellular neural networks using optical flow

    Buibas, Marius; Nizar, Krystal; Silva, Gabriel A


    An optical flow gradient algorithm was applied to spontaneously forming networks of neurons and glia in culture imaged by fluorescence optical microscopy in order to map functional calcium signaling with single pixel resolution. Optical flow estimates the direction and speed of motion of objects in an image between subsequent frames in a recorded digital sequence of images (i.e. a movie). Computed vector field outputs by the algorithm were able to track the spatiotemporal dynamics of calcium signaling patterns. We begin by briefly reviewing the mathematics of the optical flow algorithm, describe how to solve for the displacement vectors, and how to measure their reliability. We then compare computed flow vectors with manually estimated vectors for the progression of a calcium signal recorded from representative astrocyte cultures. Finally, we applied the algorithm to preparations of primary astrocytes and hippocampal neurons and to the rMC-1 Muller glial cell line in order to illustrate the capability of the ...

  13. Designing Underwater Cellular Networks Parameters

    Pejman Khadivi


    Full Text Available Oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation and tactical surveillance are some of the applications of underwater networks. Underwater networks should send the gathered information to other users or an offshore station via a base station in the sea. Since the available bandwidth in underwater is severely limited, frequency reuse and cellular networks concepts are very important. In this paper, after driving the ratio of signal to interference for underwater acoustic channels, the constraints for the cell radius are determined. One of the important results of this work is that, for special parameters like bandwidth, it may be impossible to provide the required signal to interference ratio and bandwidth for the network users. Furthermore, in this paper, number of supportable users, per-user bandwidth, and the user capacity for a cellular underwater network are determined.

  14. Cell Identification based on Received Signal Strength Fingerprints: Concept and Application towards Energy Saving in Cellular Networks

    Elke Roth-Mandutz


    Full Text Available The increasing deployment of small cells aimed at off-loading data traffic from macrocells in heterogeneous networks has resulted in a drastic increase in energy consumption in cellular networks. Energy consumption can be optimized in a selforganized way by adapting the number of active cells in response to the current traffic demand. In this paper we concentrate on the complex problem of how to identify small cells to be reactivated in situations where multiple cells are concurrently inactive. Solely based on the received signal strength, we present cell-specific patterns for the generation of unique cell fingerprints. The cell fingerprints of the deactivated cells are matched with measurements from a high data rate demanding mobile device to identify the most appropriate candidate. Our scheme results in a matching success rate of up to 100% to identify the best cell depending on the number of cells to be activated.

  15. Environment Aware Cellular Networks

    Ghazzai, Hakim


    The unprecedented rise of mobile user demand over the years have led to an enormous growth of the energy consumption of wireless networks as well as the greenhouse gas emissions which are estimated currently to be around 70 million tons per year. This significant growth of energy consumption impels network companies to pay huge bills which represent around half of their operating expenditures. Therefore, many service providers, including mobile operators, are looking for new and modern green solutions to help reduce their expenses as well as the level of their CO2 emissions. Base stations are the most power greedy element in cellular networks: they drain around 80% of the total network energy consumption even during low traffic periods. Thus, there is a growing need to develop more energy-efficient techniques to enhance the green performance of future 4G/5G cellular networks. Due to the problem of traffic load fluctuations in cellular networks during different periods of the day and between different areas (shopping or business districts and residential areas), the base station sleeping strategy has been one of the main popular research topics in green communications. In this presentation, we present several practical green techniques that provide significant gains for mobile operators. Indeed, combined with the base station sleeping strategy, these techniques achieve not only a minimization of the fossil fuel consumption but also an enhancement of mobile operator profits. We start with an optimized cell planning method that considers varying spatial and temporal user densities. We then use the optimal transport theory in order to define the cell boundaries such that the network total transmit power is reduced. Afterwards, we exploit the features of the modern electrical grid, the smart grid, as a new tool of power management for cellular networks and we optimize the energy procurement from multiple energy retailers characterized by different prices and pollutant

  16. Cellular signalling properties in microcircuits

    Toledo-Rodriguez, Maria; El Manira, Abdeljabbar; Wallén, Peter; Svirskis, Gytis; Hounsgaard, Jørn


    Molecules and cells are the signalling elements in microcircuits. Recent studies have uncovered bewildering diversity in postsynaptic signalling properties in all areas of the vertebrate nervous system. Major effort is now being invested in establishing the specialized signalling properties at th...... cellular and molecular levels in microcircuits in specific brain regions. This review is part of the TINS Microcircuits Special Feature....

  17. Phosphoproteomics: new insights into cellular signaling

    Mumby, Marc; Brekken, Deirdre


    Developments in the field of phosphoproteomics have been fueled by the need simultaneously to monitor many different phosphoproteins within the signaling networks that coordinate responses to changes in the cellular environment. This article presents a brief review of phosphoproteomics with an emphasis on the biological insights that have been derived so far.

  18. Multiuser Cellular Network

    Bao, Yi; Chen, Ming


    Modern radio communication is faced with a problem about how to distribute restricted frequency to users in a certain space. Since our task is to minimize the number of repeaters, a natural idea is enlarging coverage area. However, coverage has restrictions. First, service area has to be divided economically as repeater's coverage is limited. In this paper, our fundamental method is to adopt seamless cellular network division. Second, underlying physics content in frequency distribution problem is interference between two close frequencies. Consequently, we choose a proper frequency width of 0.1MHz and a relevantly reliable setting to apply one frequency several times. We make a few general assumptions to simplify real situation. For instance, immobile users yield to homogenous distribution; repeaters can receive and transmit information in any given frequency in duplex operation; coverage is mainly decided by antenna height. Two models are built up to solve 1000 users and 10000 users situations respectively....

  19. MIMO Communication for Cellular Networks

    Huang, Howard; Venkatesan, Sivarama


    As the theoretical foundations of multiple-antenna techniques evolve and as these multiple-input multiple-output (MIMO) techniques become essential for providing high data rates in wireless systems, there is a growing need to understand the performance limits of MIMO in practical networks. To address this need, MIMO Communication for Cellular Networks presents a systematic description of MIMO technology classes and a framework for MIMO system design that takes into account the essential physical-layer features of practical cellular networks. In contrast to works that focus on the theoretical performance of abstract MIMO channels, MIMO Communication for Cellular Networks emphasizes the practical performance of realistic MIMO systems. A unified set of system simulation results highlights relative performance gains of different MIMO techniques and provides insights into how best to use multiple antennas in cellular networks under various conditions. MIMO Communication for Cellular Networks describes single-user,...

  20. Cellular Signaling in Health and Disease

    Beckerman, Martin


    In today’s world, three great classes of non-infectious diseases – the metabolic syndromes (such as type 2 diabetes and atherosclerosis), the cancers, and the neurodegenerative disorders – have risen to the fore. These diseases, all associated with increasing age of an individual, have proven to be remarkably complex and difficult to treat. This is because, in large measure, when the cellular signaling pathways responsible for maintaining homeostasis and health of the body become dysregulated, they generate equally stable disease states. As a result the body may respond positively to a drug, but only for a while and then revert back to the disease state. Cellular Signaling in Health and Disease summarizes our current understanding of these regulatory networks in the healthy and diseased states, showing which molecular components might be prime targets for drug interventions. This is accomplished by presenting models that explain in mechanistic, molecular detail how a particular part of the cellular sign...

  1. Heterogeneous Force Chains in Cellularized Biopolymer Network

    Liang, Long; Jones, Christopher; Sun, Bo; Jiao, Yang


    Biopolymer Networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the mechanical response of a model biopolymer network due to the active contraction of embedded cells. Specifically, a graph (bond-node) model derived from confocal microscopy data is used to represent the network microstructure, and cell contraction is modeled by applying correlated displacements at specific nodes, representing the fo...

  2. Noise in cellular signaling pathways: causes and effects

    Ladbury, John E.; Arold, Stefan T.


    Noise caused by stochastic fluctuations in genetic circuits (transcription and translation) is now appreciated as a central aspect of cell function and phenotypic behavior. Noise has also been detected in signaling networks, but the origin of this noise and how it shapes cellular outcomes remain poorly understood. Here, we argue that noise in signaling networks results from the intrinsic promiscuity of protein-protein interactions, and that this noise has shaped cellular signal transduction. ...

  3. Mapping the Hsp90 Genetic Network Reveals Ergosterol Biosynthesis and Phosphatidylinositol-4-Kinase Signaling as Core Circuitry Governing Cellular Stress

    O’Meara, Teresa R.; Valaei, Seyedeh Fereshteh; Diezmann, Stephanie; Cowen, Leah E.


    Candida albicans is a leading human fungal pathogen that causes life-threatening systemic infections. A key regulator of C. albicans stress response, drug resistance, morphogenesis, and virulence is the molecular chaperone Hsp90. Targeting Hsp90 provides a powerful strategy to treat fungal infections, however, the therapeutic utility of current inhibitors is compromised by toxicity due to inhibition of host Hsp90. To identify components of the Hsp90-dependent circuitry governing virulence and drug resistance that are sufficiently divergent for selective targeting in the pathogen, we pioneered chemical genomic profiling of the Hsp90 genetic network in C. albicans. Here, we screen mutant collections covering ~10% of the genome for hypersensitivity to Hsp90 inhibition in multiple environmental conditions. We identify 158 HSP90 chemical genetic interactors, most of which are important for growth only in specific environments. We discovered that the sterol C-22 desaturase gene ERG5 and the phosphatidylinositol-4-kinase (PI4K) gene STT4 are HSP90 genetic interactors under multiple conditions, suggesting a function upstream of Hsp90. By systematic analysis of the ergosterol biosynthetic cascade, we demonstrate that defects in ergosterol biosynthesis induce cellular stress that overwhelms Hsp90’s functional capacity. By analysis of the phosphatidylinositol pathway, we demonstrate that there is a genetic interaction between the PI4K Stt4 and Hsp90. We also establish that Stt4 is required for normal actin polarization through regulation of Wal1, and suggest a model in which defects in actin remodeling induces stress that creates a cellular demand for Hsp90 that exceeds its functional capacity. Consistent with this model, actin inhibitors are synergistic with Hsp90 inhibitors. We highlight new connections between Hsp90 and virulence traits, demonstrating that Erg5 and Stt4 enable activation of macrophage pyroptosis. This work uncovers novel circuitry regulating Hsp90

  4. Connectivity-driven Attachment in Mobile Cellular Ad Hoc Networks

    Boite, Julien; Leguay, Jérémie


    International audience Cellular wireless technologies (e.g. LTE) can be used to build cellular ad hoc networks. In this new class of ad hoc networks, nodes are equipped with two radio interfaces: one being a terminal, the other one being an access point. In this context, attachment decisions based on traditional criteria (e.g. signal quality) may lead to network partitions or suboptimal path lengths, thus making access point selection critical to ensure efficient network connectivity. This...

  5. Dynamic properties of cellular neural networks

    Angela Slavova


    Full Text Available Dynamic behavior of a new class of information-processing systems called Cellular Neural Networks is investigated. In this paper we introduce a small parameter in the state equation of a cellular neural network and we seek for periodic phenomena. New approach is used for proving stability of a cellular neural network by constructing Lyapunov's majorizing equations. This algorithm is helpful for finding a map from initial continuous state space of a cellular neural network into discrete output. A comparison between cellular neural networks and cellular automata is made.

  6. Protein evolution on a human signaling network

    Purisima Enrico O; Cui Qinghua; Wang Edwin


    Abstract Background The architectural structure of cellular networks provides a framework for innovations as well as constraints for protein evolution. This issue has previously been studied extensively by analyzing protein interaction networks. However, it is unclear how signaling networks influence and constrain protein evolution and conversely, how protein evolution modifies and shapes the functional consequences of signaling networks. In this study, we constructed a human signaling networ...

  7. Boltzmann learning of parameters in cellular neural networks

    Hansen, Lars Kai


    The use of Bayesian methods to design cellular neural networks for signal processing tasks and the Boltzmann machine learning rule for parameter estimation is discussed. The learning rule can be used for models with hidden units, or for completely unsupervised learning. The latter is exemplified ...... unsupervised adaptation of an image segmentation cellular network. The learning rule is applied to adaptive segmentation of satellite imagery......The use of Bayesian methods to design cellular neural networks for signal processing tasks and the Boltzmann machine learning rule for parameter estimation is discussed. The learning rule can be used for models with hidden units, or for completely unsupervised learning. The latter is exemplified by...

  8. Cellular automata modelling of biomolecular networks dynamics.

    Bonchev, D; Thomas, S; Apte, A; Kier, L B


    The modelling of biological systems dynamics is traditionally performed by ordinary differential equations (ODEs). When dealing with intracellular networks of genes, proteins and metabolites, however, this approach is hindered by network complexity and the lack of experimental kinetic parameters. This opened the field for other modelling techniques, such as cellular automata (CA) and agent-based modelling (ABM). This article reviews this emerging field of studies on network dynamics in molecular biology. The basics of the CA technique are discussed along with an extensive list of related software and websites. The application of CA to networks of biochemical reactions is exemplified in detail by the case studies of the mitogen-activated protein kinase (MAPK) signalling pathway, the FAS-ligand (FASL)-induced and Bcl-2-related apoptosis. The potential of the CA method to model basic pathways patterns, to identify ways to control pathway dynamics and to help in generating strategies to fight with cancer is demonstrated. The different line of CA applications presented includes the search for the best-performing network motifs, an analysis of importance for effective intracellular signalling and pathway cross-talk. PMID:20373215

  9. Heterogeneous Force Chains in Cellularized Biopolymer Network

    Liang, Long; Jones, Christopher Allen Rucksack; Sun, Bo; Jiao, Yang

    Biopolymer Networks play an important role in coordinating and regulating collective cellular dynamics via a number of signaling pathways. Here, we investigate the mechanical response of a model biopolymer network due to the active contraction of embedded cells. Specifically, a graph (bond-node) model derived from confocal microscopy data is used to represent the network microstructure, and cell contraction is modeled by applying correlated displacements at specific nodes, representing the focal adhesion sites. A force-based stochastic relaxation method is employed to obtain force-balanced network under cell contraction. We find that the majority of the forces are carried by a small number of heterogeneous force chains emerged from the contracting cells. The force chains consist of fiber segments that either possess a high degree of alignment before cell contraction or are aligned due to the reorientation induced by cell contraction. Large fluctuations of the forces along different force chains are observed. Importantly, the decay of the forces along the force chains is significantly slower than the decay of radially averaged forces in the system, suggesting that the fibreous nature of biopolymer network structure could support long-range mechanical signaling between cells.

  10. Environment Aware Location Estimation in Cellular Networks

    Tuna Tugcu


    Full Text Available We propose a novel mobile positioning algorithm for cellular networks based on the estimation of the radio propagation environment. Since radio propagation characteristics vary in different environments, knowing the environment of the mobile user is essential for accurate Received Signal Strength- (RSS- based location estimation. The key feature of our method is its capability to estimate the environment of the mobile user using machine learning techniques and to utilize this information for enhancing RSS-based distance calculations. The proposed algorithm, namely, EARBALE, has been evaluated using field measurements collected from a GSM network in diverse geographic locations. Our approach turns out to be significantly beneficial, enhancing estimation accuracy, and thereby enabling high-performance mobile positioning in a practical and cost-effective manner. Additionally, it is computationally light-wei

  11. Interworking of Wireless LANs and Cellular Networks

    Song, Wei


    The next-generation of wireless communications are envisioned to be supported by heterogeneous networks by using various wireless access technologies. The popular cellular networks and wireless local area networks (WLANs) present perfectly complementary characteristics in terms of service capacity, mobility support, and quality-of-service (QoS) provisioning. The cellular/WLAN interworking is an effective way to promote the evolution of wireless networks. "Interworking of Wireless LANs and Cellular Networks" focuses on three aspects, namely access selection, call admission control and

  12. Cellular Signaling Pathways and Their Clinical Reflections

    N. Ceren Sumer-Turanligil


    Full Text Available Cellular signaling pathways have important roles in cellular growth, differentiation, inflammatory response and apoptosis and in regulation of cellular responses under various chemical stimulators. Different proteins which belong to these pathways may be exposed to loss-of-function or gain-of-function mutations; this may lead to many clinical phenotypes including primarily cancer. In this review information about basic working principles of these pathways and diseases related to them are included. [Archives Medical Review Journal 2010; 19(3.000: 180-191

  13. Mathematical Modelling Plant Signalling Networks

    Muraro, D.


    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  14. Empirical multiscale networks of cellular regulation.

    Benjamin de Bivort


    Full Text Available Grouping genes by similarity of expression across multiple cellular conditions enables the identification of cellular modules. The known functions of genes enable the characterization of the aggregate biological functions of these modules. In this paper, we use a high-throughput approach to identify the effective mutual regulatory interactions between modules composed of mouse genes from the Alliance for Cell Signaling (AfCS murine B-lymphocyte database which tracks the response of approximately 15,000 genes following chemokine perturbation. This analysis reveals principles of cellular organization that we discuss along four conceptual axes. (1 Regulatory implications: the derived collection of influences between any two modules quantifies intuitive as well as unexpected regulatory interactions. (2 Behavior across scales: trends across global networks of varying resolution (composed of various numbers of modules reveal principles of assembly of high-level behaviors from smaller components. (3 Temporal behavior: tracking the mutual module influences over different time intervals provides features of regulation dynamics such as duration, persistence, and periodicity. (4 Gene Ontology correspondence: the association of modules to known biological roles of individual genes describes the organization of functions within coexpressed modules of various sizes. We present key specific results in each of these four areas, as well as derive general principles of cellular organization. At the coarsest scale, the entire transcriptional network contains five divisions: two divisions devoted to ATP production/biosynthesis and DNA replication that activate all other divisions, an "extracellular interaction" division that represses all other divisions, and two divisions (proliferation/differentiation and membrane infrastructure that activate and repress other divisions in specific ways consistent with cell cycle control.

  15. Software-Defined Cellular Mobile Network Solutions

    Jiandong Li; Peng Liu; Hongyan Li


    The emergency relating to software-defined networking (SDN), especially in terms of the prototype associated with OpenFlow, pro-vides new possibilities for innovating on network design. Researchers have started to extend SDN to cellular networks. Such new programmable architecture is beneficial to the evolution of mobile networks and allows operators to provide better services. The typical cellular network comprises radio access network (RAN) and core network (CN); hence, the technique roadmap diverges in two ways. In this paper, we investigate SoftRAN, the latest SDN solution for RAN, and SoftCell and MobileFlow, the latest solu-tions for CN. We also define a series of control functions for CROWD. Unlike in the other literature, we emphasize only software-defined cellular network solutions and specifications in order to provide possible research directions.

  16. Early cellular signaling responses to axonal injury

    Wang Ai


    Full Text Available Abstract Background We have used optic nerve injury as a model to study early signaling events in neuronal tissue following axonal injury. Optic nerve injury results in the selective death of retinal ganglion cells (RGCs. The time course of cell death takes place over a period of days with the earliest detection of RGC death at about 48 hr post injury. We hypothesized that in the period immediately following axonal injury, there are changes in the soma that signal surrounding glia and neurons and that start programmed cell death. In the current study, we investigated early changes in cellular signaling and gene expression that occur within the first 6 hrs post optic nerve injury. Results We found evidence of cell to cell signaling within 30 min of axonal injury. We detected differences in phosphoproteins and gene expression within the 6 hrs time period. Activation of TNFα and glutamate receptors, two pathways that can initiate cell death, begins in RGCs within 6 hrs following axonal injury. Differential gene expression at 6 hrs post injury included genes involved in cytokine, neurotrophic factor signaling (Socs3 and apoptosis (Bax. Conclusion We interpret our studies to indicate that both neurons and glia in the retina have been signaled within 30 min after optic nerve injury. The signals are probably initiated by the RGC soma. In addition, signals activating cellular death pathways occur within 6 hrs of injury, which likely lead to RGC degeneration.

  17. Single-Molecule Imaging of Cellular Signaling

    De Keijzer, Sandra; Snaar-Jagalska, B. Ewa; Spaink, Herman P.; Schmidt, Thomas

    Single-molecule microscopy is an emerging technique to understand the function of a protein in the context of its natural environment. In our laboratory this technique has been used to study the dynamics of signal transduction in vivo. A multitude of signal transduction cascades are initiated by interactions between proteins in the plasma membrane. These cascades start by binding a ligand to its receptor, thereby activating downstream signaling pathways which finally result in complex cellular responses. To fully understand these processes it is important to study the initial steps of the signaling cascades. Standard biological assays mostly call for overexpression of the proteins and high concentrations of ligand. This sets severe limits to the interpretation of, for instance, the time-course of the observations, given the large temporal spread caused by the diffusion-limited binding processes. Methods and limitations of single-molecule microscopy for the study of cell signaling are discussed on the example of the chemotactic signaling of the slime-mold Dictyostelium discoideum. Single-molecule studies, as reviewed in this chapter, appear to be one of the essential methodologies for the full spatiotemporal clarification of cellular signaling, one of the ultimate goals in cell biology.

  18. Optimal signal patterns for dynamical cellular communication

    Hasegawa, Yoshihiko


    Cells transmit information via signaling pathways, using temporal dynamical patterns. As optimality with respect to environments is the universal principle in biological systems, organisms have acquired an optimal way of transmitting information. Here we obtain optimal dynamical signal patterns which can transmit information efficiently (low power) and reliably (high accuracy) using the optimal control theory. Adopting an activation-inactivation decoding network, we reproduced several dynamical patterns found in actual signals, such as steep, gradual and overshooting dynamics. Notably, when minimizing the power of the input signal, optimal signals exhibit the overshooting pattern, which is a biphasic pattern with transient and steady phases; this pattern is prevalent in actual dynamical patterns as it can be generated by an incoherent feed-forward loop (FFL), a common motif in biochemical networks. We also identified conditions when the three patterns, steep, gradual and overshooting, confer advantages.

  19. Estimating cellular network performance during hurricanes

    Cellular networks serve a critical role during and immediately after a hurricane, allowing citizens to contact emergency services when land-line communication is lost and serving as a backup communication channel for emergency responders. However, due to their ubiquitous deployment and limited design for extreme loading events, basic network elements, such as cellular towers and antennas are prone to failures during adverse weather conditions such as hurricanes. Accordingly, a systematic and computationally feasible approach is required for assessing and improving the reliability of cellular networks during hurricanes. In this paper we develop a new multi-disciplinary approach to efficiently and accurately assess cellular network reliability during hurricanes. We show how the performance of a cellular network during and immediately after future hurricanes can be estimated based on a combination of hurricane wind field models, structural reliability analysis, Monte Carlo simulation, and cellular network models and simulation tools. We then demonstrate the use of this approach for assessing the improvement in system reliability that can be achieved with discrete topological changes in the system. Our results suggest that adding redundancy, particularly through a mesh topology or through the addition of an optical fiber ring around the perimeter of the system can be an effective way to significantly increase the reliability of some cellular systems during hurricanes.

  20. Cellular Signaling in the Bovine Antral Follicles

    Juan F. Vásquez - Cano; Martha Olivera - A.


    Antral follicle development in the ovary of female cattle is the product of a complex of endocrine, paracrine and autocrine relationships. The interactions of the pituitary gonadotropins over granulosa and theca cells prepare the follicle to produce estradiol and for the final stages of maturation of the oocyte and its potencial ovulation or atresia inside subordinate follicles. It is a dynamic event where cellular signaling patterns changes sequentiallyand quickly at different stages of foll...

  1. Aging cellular networks: chaperones as major participants

    Soti, Csaba; Csermely, Peter


    We increasingly rely on the network approach to understand the complexity of cellular functions. Chaperones (heat shock proteins) are key "networkers", which have among their functions to sequester and repair damaged protein. In order to link the network approach and chaperones with the aging process, we first summarize the properties of aging networks suggesting a "weak link theory of aging". This theory suggests that age-related random damage primarily affects the overwhelming majority of t...

  2. Error performance analysis in downlink cellular networks with interference management

    Afify, Laila H.


    Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly abstract many important wireless communication system aspects (e.g., modulation techniques, signal recovery techniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspects and extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takes into consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interference management techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.

  3. Exponential Stability for Delayed Cellular Neural Networks

    YANG Jin-xiang; ZHONG Shou-ming; YAN Ke-yu


    The exponential stability of the delayed cellular neural networks (DCNN's) is investigated. By dividing the network state variables into some parts according to the characters of the neural networks, some new sufficient conditions of exponential stability are derived via constructing a Liapunov function. It is shown that the conditions differ from previous ones. The new conditions, which are associated with some initial value, are represented by some blocks of the interconnection matrix.

  4. Stability of Stochastic Neutral Cellular Neural Networks

    Chen, Ling; Zhao, Hongyong

    In this paper, we study a class of stochastic neutral cellular neural networks. By constructing a suitable Lyapunov functional and employing the nonnegative semi-martingale convergence theorem we give some sufficient conditions ensuring the almost sure exponential stability of the networks. The results obtained are helpful to design stability of networks when stochastic noise is taken into consideration. Finally, two examples are provided to show the correctness of our analysis.

  5. Microfabricated platforms for the study of neuronal and cellular networks

    Berdondini, L; Generelli, S; Kraus, T; Guenat, O T; Koster, S; Linder, V; Koudelka-Hep, M; Rooij, N F de [SAMLAB, Institute of Microtechnology, University of Neuchatel (Switzerland)


    In this contribution we present the development of three microfabricated devices for the study of neuronal and cellular networks. Together, these devices form an attractive toolbox, which is useful to stimulate and record signals of both electrical and chemical nature. One approach consist of microelectrode arrays for the study of neuronal networks, and allow for the electrical stimulation of individual cells in the network, while the other electrodes of the array record the electrical activity of the remaining cells of the network. We also present the use of micropipettes that can measure the extra- and intracellular concentrations of ions in cells cultures. A third approach exploits the laminar flows in a microfluidic device, to deliver minute amounts of drug to some cells in a cellular network. These three illustrations show that microfabricated platforms are appealing analytical tools in the context of cell biology.

  6. Tension and robustness in multitasking cellular networks.

    Jeffrey V Wong

    Full Text Available Cellular networks multitask by exhibiting distinct, context-dependent dynamics. However, network states (parameters that generate a particular dynamic are often sub-optimal for others, defining a source of "tension" between them. Though multitasking is pervasive, it is not clear where tension arises, what consequences it has, and how it is resolved. We developed a generic computational framework to examine the source and consequences of tension between pairs of dynamics exhibited by the well-studied RB-E2F switch regulating cell cycle entry. We found that tension arose from task-dependent shifts in parameters associated with network modules. Although parameter sets common to distinct dynamics did exist, tension reduced both their accessibility and resilience to perturbation, indicating a trade-off between "one-size-fits-all" solutions and robustness. With high tension, robustness can be preserved by dynamic shifting of modules, enabling the network to toggle between tasks, and by increasing network complexity, in this case by gene duplication. We propose that tension is a general constraint on the architecture and operation of multitasking biological networks. To this end, our work provides a framework to quantify the extent of tension between any network dynamics and how it affects network robustness. Such analysis would suggest new ways to interfere with network elements to elucidate the design principles of cellular networks.

  7. Performance evaluation of cellular phone network based portable ECG device.

    Hong, Joo-Hyun; Cha, Eun-Jong; Lee, Tae-Soo


    In this study, cellular phone network based portable ECG device was developed and three experiments were performed to evaluate the accuracy, reliability and operability, applicability during daily life of the developed device. First, ECG signals were measured using the developed device and Biopac device (reference device) during sitting and marking time and compared to verify the accuracy of R-R intervals. Second, the reliable data transmission to remote server was verified on two types of simulated emergency event using patient simulator. Third, during daily life with five types of motion, accuracy of data transmission to remote server was verified on two types of event occurring. By acquiring and comparing subject's biomedical signal and motion signal, the accuracy, reliability and operability, applicability during daily life of the developed device were verified. Therefore, cellular phone network based portable ECG device can monitor patient with inobtrusive manner. PMID:19162767

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

    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

  9. Mapping functional connectivity in cellular networks

    Buibas, Marius


    My thesis is a collection of theoretical and practical techniques for mapping functional or effective connectivity in cellular neuronal networks, at the cell scale. This is a challenging scale to work with, primarily because of the difficulty in labeling and measuring the activities of networks of cells. It is also important as it underlies behavior, function, and complex diseases. I present methods to measure and quantify the dynamic activities of cells using the optical flow technique, whic...

  10. Cognitive resource management for heterogeneous cellular networks

    Liu, Yongkang


    This Springer Brief focuses on cognitive resource management in heterogeneous cellular networks (Het Net) with small cell deployment for the LTE-Advanced system. It introduces the Het Net features, presents practical approaches using cognitive radio technology in accommodating small cell data relay and optimizing resource allocation and examines the effectiveness of resource management among small cells given limited coordination bandwidth and wireless channel uncertainty. The authors introduce different network characteristics of small cell, investigate the mesh of small cell access points in

  11. Image processing with a cellular nonlinear network

    A cellular nonlinear network (CNN) based on uncoupled nonlinear oscillators is proposed for image processing purposes. It is shown theoretically and numerically that the contrast of an image loaded at the nodes of the CNN is strongly enhanced, even if this one is initially weak. An image inversion can be also obtained without reconfiguration of the network whereas a gray levels extraction can be performed with an additional threshold filtering. Lastly, an electronic implementation of this CNN is presented

  12. A Tractable Approach to Coverage and Rate in Cellular Networks

    Andrews, Jeffrey G.; Baccelli, Francois; Ganti, Radha Krishna


    Cellular networks are usually modeled by placing the base stations on a grid, with mobile users either randomly scattered or placed deterministically. These models have been used extensively but suffer from being both highly idealized and not very tractable, so complex system-level simulations are used to evaluate coverage/outage probability and rate. More tractable models have long been desirable. We develop new general models for the multi-cell signal-to-interference-plus-noise ratio (SINR)...

  13. Quantitative phosphoproteomics to characterize signaling networks

    Rigbolt, Kristoffer T G; Blagoev, Blagoy


    Reversible protein phosphorylation is involved in the regulation of most, if not all, major cellular processes via dynamic signal transduction pathways. During the last decade quantitative phosphoproteomics have evolved from a highly specialized area to a powerful and versatile platform for...... analyzing protein phosphorylation at a system-wide scale and has become the intuitive strategy for comprehensive characterization of signaling networks. Contemporary phosphoproteomics use highly optimized procedures for sample preparation, mass spectrometry and data analysis algorithms to identify and...... quantify thousands of phosphorylations, thus providing extensive overviews of the cellular signaling networks. As a result of these developments quantitative phosphoproteomics have been applied to study processes as diverse as immunology, stem cell biology and DNA damage. Here we review the developments in...

  14. Wireless traffic steering for green cellular networks

    Zhang, Shan; Zhou, Sheng; Niu, Zhisheng; Shen, Xuemin (Sherman)


    This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to reduce on-grid energy consum...

  15. Cellular signaling in eclosion hormone action.

    Morton, David B.; Simpson, P Jeanette


    Eclosion hormone (EH) is a 62 amino acid neuropeptide that plays an integral role in triggering ecdysis behavior at the end of each molt. At least three populations of cells are thought to be targets for EH, each of which show an EH-stimulated increase in the intracellular messenger guanosine 3', 5' cyclic monophosphate (cGMP). These EH target cells are believed to include two pairs of neurons in each of the ganglia of the ventral nerve cord (VNC) that contain the neuropeptide crustacean cardioactive peptide (CCAP), the Inka cells of the peripheral epitracheal glands and intrinsic non-neuronal cells in the abdominal transverse nerves. This review describes likely signaling cascades that result in the EH-stimulated cGMP increase. Several lines of evidence suggest the involvement of a novel nitric oxide insensitive soluble guanylyl cyclase (GC). A novel GC with these properties has recently been identified and we also present evidence to suggest that it is activated by EH and describe possible pathways for its activation. In addition, we review our current knowledge on the cellular and molecular events that take place downstream of the increase in cGMP. PMID:12770127

  16. Mobile Node Localization in Cellular Networks

    Yasir Malik


    Full Text Available Location information is the major component in location based applications. This information is used in different safety and service oriented applications to provide users with services according to their Geolocation. There are many approaches to locate mobile nodes in indoor and outdoor environments. In thispaper, we are interested in outdoor localization particularly in cellular networks of mobile nodes andpresented a localization method based on cell and user location information. Our localization method is based on hello message delay (sending and receiving time and coordinate information of Base Transceiver Station (BTSs. To validate our method across cellular network, we implemented and simulated our method in two scenarios i.e. maintaining database of base stations in centralize and distributed system. Simulation results show the effectiveness of our approach and its implementation applicability in telecommunication systems.

  17. Virtualized cognitive network architecture for 5G cellular networks

    Elsawy, Hesham


    Cellular networks have preserved an application agnostic and base station (BS) centric architecture1 for decades. Network functionalities (e.g. user association) are decided and performed regardless of the underlying application (e.g. automation, tactile Internet, online gaming, multimedia). Such an ossified architecture imposes several hurdles against achieving the ambitious metrics of next generation cellular systems. This article first highlights the features and drawbacks of such architectural ossification. Then the article proposes a virtualized and cognitive network architecture, wherein network functionalities are implemented via software instances in the cloud, and the underlying architecture can adapt to the application of interest as well as to changes in channels and traffic conditions. The adaptation is done in terms of the network topology by manipulating connectivities and steering traffic via different paths, so as to attain the applications\\' requirements and network design objectives. The article presents cognitive strategies to implement some of the classical network functionalities, along with their related implementation challenges. The article further presents a case study illustrating the performance improvement of the proposed architecture as compared to conventional cellular networks, both in terms of outage probability and handover rate.

  18. Regulation patterns in signaling networks of cancer

    Kannabiran Nandakumar


    Full Text Available Abstract Background Formation of cellular malignancy results from the disruption of fine tuned signaling homeostasis for proliferation, accompanied by mal-functional signals for differentiation, cell cycle and apoptosis. We wanted to observe central signaling characteristics on a global view of malignant cells which have evolved to selfishness and independence in comparison to their non-malignant counterparts that fulfill well defined tasks in their sample. Results We investigated the regulation of signaling networks with twenty microarray datasets from eleven different tumor types and their corresponding non-malignant tissue samples. Proteins were represented by their coding genes and regulatory distances were defined by correlating the gene-regulation between neighboring proteins in the network (high correlation = small distance. In cancer cells we observed shorter pathways, larger extension of the networks, a lower signaling frequency of central proteins and links and a higher information content of the network. Proteins of high signaling frequency were enriched with cancer mutations. These proteins showed motifs of regulatory integration in normal cells which was disrupted in tumor cells. Conclusion Our global analysis revealed a distinct formation of signaling-regulation in cancer cells when compared to cells of normal samples. From these cancer-specific regulation patterns novel signaling motifs are proposed.

  19. A multi-scale approach to colorectal cancer: from a biochemical- interaction signaling-network level, to multi-cellular dynamics of malignant transformation. Interplay with mutations and onco-protein inhibitor drugs.

    Tortolina, L; Castagnino, N; De Ambrosi, C; Moran, E; Patrone, F; Ballestrero, A; Parodi, S


    This review article is part of a special Current Cancer Drug Targets issue devoted to colorectal cancer and molecularly targeted treatments. In our paper we made an attempt to connect more basic aspects with preclinical, pharmacological / therapeutic and clinical aspects. Reconstruction of a Molecular Interaction Map (MIM) comprising an important part of the G0 - G1 - S cell cycle transition, was a major component of our review. Such a MIM serves also as a convenient / organized database of a large set of important molecular events. The frequency of mutated / altered signaling-proteins indicates the importance of this signaling-network region. We have considered problems at different scale levels. Our MIM works at a biochemical-interaction level. We have also touched the multi-cellular dynamics of normal and aberrant colon crypts. Until recently, dynamic simulations at a biochemical or multi-cellular scale level were considered as a sort of esoteric approach. We tried to convince the reader, also on the basis of a rapidly growing literature, mostly published in high quality journals, that suspicion towards simulations should dissipate, as the limitations and advantages of their application are better appreciated, opening the door to their permanent adoption in everyday research. What is really required is a more interdisciplinary mentality and an interdisciplinary approach. The prize is a level of understanding going beyond mere intuition. PMID:22385511

  20. Molecular chaperones: The modular evolution of cellular networks

    Tamás Korcsmáros; István A Kovács; Máté S Szalay; Péter Csermely


    Molecular chaperones play a prominent role in signaling and transcriptional regulatory networks of the cell. Recent advances uncovered that chaperones act as genetic buffers stabilizing the phenotype of various cells and organisms and may serve as potential regulators of evolvability. Chaperones have weak links, connect hubs, are in the overlaps of network modules and may uncouple these modules during stress, which gives an additional protection for the cell at the network-level. Moreover, after stress chaperones are essential to re-build inter-modular contacts by their low affinity sampling of the potential interaction partners in different modules. This opens the way to the chaperone-regulated modular evolution of cellular networks, and helps us to design novel therapeutic and anti-aging strategies.

  1. Using Cellular Communication Networks To Detect Air Pollution.

    David, Noam; Gao, H Oliver


    Accurate real time monitoring of atmospheric conditions at ground level is vital for hazard warning, meteorological forecasting, and various environmental applications required for public health and safety. However, conventional monitoring facilities are costly and often insufficient, for example, since they are not representative of the larger space and are not deployed densely enough in the field. There have been numerous scientific works showing the ability of commercial microwave links that comprise the data transmission infrastructure in cellular communication networks to monitor hydrometeors as a potential complementary solution. However, despite the large volume of research carried out in this emerging field during the past decade, no study has shown the ability of the system to provide critical information regarding air quality. Here we reveal the potential for identifying atmospheric conditions prone to air pollution by detecting temperature inversions that trap pollutants at ground level. The technique is based on utilizing standard signal measurements from an existing cellular network during routine operation. PMID:27490182

  2. Cellular recurrent deep network for image registration

    Alam, M.; Vidyaratne, L.; Iftekharuddin, Khan M.


    Image registration using Artificial Neural Network (ANN) remains a challenging learning task. Registration can be posed as a two-step problem: parameter estimation and actual alignment/transformation using the estimated parameters. To date ANN based image registration techniques only perform the parameter estimation, while affine equations are used to perform the actual transformation. In this paper, we propose a novel deep ANN based image rigid registration that combines parameter estimation and transformation as a simultaneous learning task. Our previous work shows that a complex universal approximator known as Cellular Simultaneous Recurrent Network (CSRN) can successfully approximate affine transformations with known transformation parameters. This study introduces a deep ANN that combines a feed forward network with a CSRN to perform full rigid registration. Layer wise training is used to pre-train feed forward network for parameter estimation and followed by a CSRN for image transformation respectively. The deep network is then fine-tuned to perform the final registration task. Our result shows that the proposed deep ANN architecture achieves comparable registration accuracy to that of image affine transformation using CSRN with known parameters. We also demonstrate the efficacy of our novel deep architecture by a performance comparison with a deep clustered MLP.

  3. Call Admission Control in Mobile Cellular Networks

    Ghosh, Sanchita


    Call Admission Control (CAC) and Dynamic Channel Assignments (DCA) are important decision-making problems in mobile cellular communication systems. Current research in mobile communication considers them as two independent problems, although the former greatly depends on the resulting free channels obtained as the outcome of the latter. This book provides a solution to the CAC problem, considering DCA as an integral part of decision-making for call admission. Further, current technical resources ignore movement issues of mobile stations and fluctuation in network load (incoming calls) in the control strategy used for call admission. In addition, the present techniques on call admission offers solution globally for the entire network, instead of considering the cells independently.      CAC here has been formulated by two alternative approaches. The first approach aimed at handling the uncertainty in the CAC problem by employing fuzzy comparators.  The second approach is concerned with formulation of CAC ...

  4. Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial

    ElSawy, Hesham


    This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a basic cellular network model. Then, it characterizes signal-tointerference- plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the baseline unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. Finally, we point out future research directions.

  5. Green Cellular Networks: A Survey, Some Research Issues and Challenges

    Hasan, Ziaul; Bhargava, Vijay K


    Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogenous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative rela...

  6. ROS and ROS-Mediated Cellular Signaling

    Jixiang Zhang


    Full Text Available It has long been recognized that an increase of reactive oxygen species (ROS can modify the cell-signaling proteins and have functional consequences, which successively mediate pathological processes such as atherosclerosis, diabetes, unchecked growth, neurodegeneration, inflammation, and aging. While numerous articles have demonstrated the impacts of ROS on various signaling pathways and clarify the mechanism of action of cell-signaling proteins, their influence on the level of intracellular ROS, and their complex interactions among multiple ROS associated signaling pathways, the systemic summary is necessary. In this review paper, we particularly focus on the pattern of the generation and homeostasis of intracellular ROS, the mechanisms and targets of ROS impacting on cell-signaling proteins (NF-κB, MAPKs, Keap1-Nrf2-ARE, and PI3K-Akt, ion channels and transporters (Ca2+ and mPTP, and modifying protein kinase and Ubiquitination/Proteasome System.

  7. Integrative omics reveals MYCN as a global suppressor of cellular signalling and enables network-based therapeutic target discovery in neuroblastoma

    Fey, Dirk; Iljin, Kristiina; Mehta, Jai Prakash; Killick, Kate; Whilde, Jenny; Turriziani, Benedetta; Haapa-Paananen, Saija; Fey, Vidal; Fischer, Matthias; Westermann, Frank; Henrich, Kai-Oliver; Bannert, Steffen; Higgins, Desmond G.; Kolch, Walter


    Despite intensive study, many mysteries remain about the MYCN oncogene's functions. Here we focus on MYCN's role in neuroblastoma, the most common extracranial childhood cancer. MYCN gene amplification occurs in 20% of cases, but other recurrent somatic mutations are rare. This scarcity of tractable targets has hampered efforts to develop new therapeutic options. We employed a multi-level omics approach to examine MYCN functioning and identify novel therapeutic targets for this largely un-druggable oncogene. We used systems medicine based computational network reconstruction and analysis to integrate a range of omic techniques: sequencing-based transcriptomics, genome-wide chromatin immunoprecipitation, siRNA screening and interaction proteomics, revealing that MYCN controls highly connected networks, with MYCN primarily supressing the activity of network components. MYCN's oncogenic functions are likely independent of its classical heterodimerisation partner, MAX. In particular, MYCN controls its own protein interaction network by transcriptionally regulating its binding partners. Our network-based approach identified vulnerable therapeutically targetable nodes that function as critical regulators or effectors of MYCN in neuroblastoma. These were validated by siRNA knockdown screens, functional studies and patient data. We identified β-estradiol and MAPK/ERK as having functional cross-talk with MYCN and being novel targetable vulnerabilities of MYCN-amplified neuroblastoma. These results reveal surprising differences between the functioning of endogenous, overexpressed and amplified MYCN, and rationalise how different MYCN dosages can orchestrate cell fate decisions and cancerous outcomes. Importantly, this work describes a systems-level approach to systematically uncovering network based vulnerabilities and therapeutic targets for multifactorial diseases by integrating disparate omic data types. PMID:26673823

  8. Optimal flux patterns in cellular metabolic networks

    Almaas, E


    The availability of whole-cell level metabolic networks of high quality has made it possible to develop a predictive understanding of bacterial metabolism. Using the optimization framework of flux balance analysis, I investigate metabolic response and activity patterns to variations in the availability of nutrient and chemical factors such as oxygen and ammonia by simulating 30,000 random cellular environments. The distribution of reaction fluxes is heavy-tailed for the bacteria H. pylori and E. coli, and the eukaryote S. cerevisiae. While the majority of flux balance investigations have relied on implementations of the simplex method, it is necessary to use interior-point optimization algorithms to adequately characterize the full range of activity patterns on metabolic networks. The interior-point activity pattern is bimodal for E. coli and S. cerevisiae, suggesting that most metabolic reaction are either in frequent use or are rarely active. The trimodal activity pattern of H. pylori indicates that a group of its metabolic reactions (20%) are active in approximately half of the simulated environments. Constructing the high-flux backbone of the network for every environment, there is a clear trend that the more frequently a reaction is active, the more likely it is a part of the backbone. Finally, I briefly discuss the predicted activity patterns of the central-carbon metabolic pathways for the sample of random environments.

  9. Chaotic phenomena in Josephson circuits coupled quantum cellular neural networks

    Wang Sen; Cai Li; Li Qin; Wu Gang


    In this paper the nonlinear dynamical behaviour of a quantum cellular neural network (QCNN) by coupling Josephson circuits was investigated and it was shown that the QCNN using only two of them can cause the onset of chaotic oscillation. The theoretical analysis and simulation for the two Josephson-circuits-coupled QCNN have been done by using the amplitude and phase as state variables. The complex chaotic behaviours can be observed and then proved by calculating Lyapunov exponents. The study provides valuable information about QCNNs for future application in high-parallel signal processing and novel chaotic generators.

  10. Simulated Annealing for Location Area Planning in Cellular networks

    N. B. Prajapati


    Full Text Available LA planning in cellular network is useful for minimizing location management cost in GSM network. Infact, size of LA can be optimized to create a balance between the LA update rate and expected pagingrate within LA. To get optimal result for LA planning in cellular network simulated annealing algorithmis used. Simulated annealing give optimal results in acceptable run-time.

  11. A Wireless Communications Laboratory on Cellular Network Planning

    Dawy, Z.; Husseini, A.; Yaacoub, E.; Al-Kanj, L.


    The field of radio network planning and optimization (RNPO) is central for wireless cellular network design, deployment, and enhancement. Wireless cellular operators invest huge sums of capital on deploying, launching, and maintaining their networks in order to ensure competitive performance and high user satisfaction. This work presents a lab…

  12. Simulated Annealing for Location Area Planning in Cellular networks

    Prajapati, N. B.; R. R. Agravat; Hasan, M I


    LA planning in cellular network is useful for minimizing location management cost in GSM network. In fact, size of LA can be optimized to create a balance between the LA update rate and expected paging rate within LA. To get optimal result for LA planning in cellular network simulated annealing algorithm is used. Simulated annealing give optimal results in acceptable run-time.

  13. Advanced Imaging of Cellular Signaling Events

    Cebecauer, Marek; Humpolíčková, Jana; Rossy, J.

    Vol. 505. Amsterdam: Elsevier, 2012, s. 273-289. ISBN 978-0-12-388448-0 R&D Projects: GA ČR GAP305/11/0459 Institutional research plan: CEZ:AV0Z40400503 Keywords : fluorecence fluctuation technique * supersolution microscopy * signaling Subject RIV: CF - Physical ; Theoretical Chemistry

  14. Robust network topologies for generating switch-like cellular responses.

    Najaf A Shah


    Full Text Available Signaling networks that convert graded stimuli into binary, all-or-none cellular responses are critical in processes ranging from cell-cycle control to lineage commitment. To exhaustively enumerate topologies that exhibit this switch-like behavior, we simulated all possible two- and three-component networks on random parameter sets, and assessed the resulting response profiles for both steepness (ultrasensitivity and extent of memory (bistability. Simulations were used to study purely enzymatic networks, purely transcriptional networks, and hybrid enzymatic/transcriptional networks, and the topologies in each class were rank ordered by parametric robustness (i.e., the percentage of applied parameter sets exhibiting ultrasensitivity or bistability. Results reveal that the distribution of network robustness is highly skewed, with the most robust topologies clustering into a small number of motifs. Hybrid networks are the most robust in generating ultrasensitivity (up to 28% and bistability (up to 18%; strikingly, a purely transcriptional framework is the most fragile in generating either ultrasensitive (up to 3% or bistable (up to 1% responses. The disparity in robustness among the network classes is due in part to zero-order ultrasensitivity, an enzyme-specific phenomenon, which repeatedly emerges as a particularly robust mechanism for generating nonlinearity and can act as a building block for switch-like responses. We also highlight experimentally studied examples of topologies enabling switching behavior, in both native and synthetic systems, that rank highly in our simulations. This unbiased approach for identifying topologies capable of a given response may be useful in discovering new natural motifs and in designing robust synthetic gene networks.

  15. Neural networks in signal processing

    Nuclear Engineering has matured during the last decade. In research and design, control, supervision, maintenance and production, mathematical models and theories are used extensively. In all such applications signal processing is embedded in the process. Artificial Neural Networks (ANN), because of their nonlinear, adaptive nature are well suited to such applications where the classical assumptions of linearity and second order Gaussian noise statistics cannot be made. ANN's can be treated as nonparametric techniques, which can model an underlying process from example data. They can also adopt their model parameters to statistical change with time. Algorithms in the framework of Neural Networks in Signal processing have found new applications potentials in the field of Nuclear Engineering. This paper reviews the fundamentals of Neural Networks in signal processing and their applications in tasks such as recognition/identification and control. The topics covered include dynamic modeling, model based ANN's, statistical learning, eigen structure based processing and generalization structures. (orig.)

  16. Analysis of Blocking Probability in a Relay-based Cellular OFDMA Network

    Mehta, Mahima; Jain, Ranjan Bala; Karandikar, Abhay


    Relay deployment in Orthogonal Frequency Division Multiple Access (OFDMA) based cellular networks helps in coverage extension and or capacity improvement. In OFDMA system, each user requires different number of subcarriers to meet its rate requirement. This resource requirement depends on the Signal to Interference Ratio (SIR) experienced by a user. Traditional methods to compute blocking probability cannot be used in relay based cellular OFDMA networks. In this paper, we present an approach ...

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

    Schoof, Erwin M; Linding, Rune


    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...

  18. Simulating Quantitative Cellular Responses Using Asynchronous Threshold Boolean Network Ensembles

    Shah Imran


    Full Text Available Abstract Background With increasing knowledge about the potential mechanisms underlying cellular functions, it is becoming feasible to predict the response of biological systems to genetic and environmental perturbations. Due to the lack of homogeneity in living tissues it is difficult to estimate the physiological effect of chemicals, including potential toxicity. Here we investigate a biologically motivated model for estimating tissue level responses by aggregating the behavior of a cell population. We assume that the molecular state of individual cells is independently governed by discrete non-deterministic signaling mechanisms. This results in noisy but highly reproducible aggregate level responses that are consistent with experimental data. Results We developed an asynchronous threshold Boolean network simulation algorithm to model signal transduction in a single cell, and then used an ensemble of these models to estimate the aggregate response across a cell population. Using published data, we derived a putative crosstalk network involving growth factors and cytokines - i.e., Epidermal Growth Factor, Insulin, Insulin like Growth Factor Type 1, and Tumor Necrosis Factor α - to describe early signaling events in cell proliferation signal transduction. Reproducibility of the modeling technique across ensembles of Boolean networks representing cell populations is investigated. Furthermore, we compare our simulation results to experimental observations of hepatocytes reported in the literature. Conclusion A systematic analysis of the results following differential stimulation of this model by growth factors and cytokines suggests that: (a using Boolean network ensembles with asynchronous updating provides biologically plausible noisy individual cellular responses with reproducible mean behavior for large cell populations, and (b with sufficient data our model can estimate the response to different concentrations of extracellular ligands. Our

  19. Analytical Modeling of Uplink Cellular Networks

    Novlan, Thomas D; Andrews, Jeffrey G


    Cellular uplink analysis has typically been undertaken by either a simple approach that lumps all interference into a single deterministic or random parameter in a Wyner-type model, or via complex system level simulations that often do not provide insight into why various trends are observed. This paper proposes a novel middle way that is both accurate and also results in easy-to-evaluate integral expressions based on the Laplace transform of the interference. We assume mobiles and base stations are randomly placed in the network with each mobile pairing up to its closest base station. The model requires two important changes compared to related recent work on the downlink. First, dependence is introduced between the user and base station point processes to make sure each base station serves a single mobile in the given resource block. Second, per-mobile power control is included, which further couples the locations of the mobiles and their receiving base stations. Nevertheless, we succeed in deriving the cov...

  20. Peroxisomes: a Nexus for Lipid Metabolism and Cellular Signaling

    Lodhi, Irfan J.; Semenkovich, Clay F.


    Peroxisomes are often dismissed as the cellular hoi polloi, relegated to cleaning up reactive oxygen chemical debris discarded by other organelles. However, their functions extend far beyond hydrogen peroxide metabolism. Peroxisomes are intimately associated with lipid droplets and mitochondria, and their ability to carry out fatty acid oxidation and lipid synthesis, especially the production of ether lipids, may be critical for generating cellular signals required for normal physiology. Here...

  1. Dynamic visualization of calcium-dependent signaling in cellular microdomains.

    Mehta, Sohum; Zhang, Jin


    Cells rely on the coordinated action of diverse signaling molecules to sense, interpret, and respond to their highly dynamic external environment. To ensure the specific and robust flow of information, signaling molecules are often spatially organized to form distinct signaling compartments, and our understanding of the molecular mechanisms that guide intracellular signaling hinges on the ability to directly probe signaling events within these cellular microdomains. Ca(2+) signaling in particular owes much of its functional versatility to this type of exquisite spatial regulation. As discussed below, a number of methods have been developed to investigate the mechanistic and functional implications of microdomains of Ca(2+) signaling, ranging from the application of Ca(2+) buffers to the direct and targeted visualization of Ca(2+) signaling microdomains using genetically encoded fluorescent reporters. PMID:25703691

  2. Sources of Uncertainty in Rainfall Maps from Cellular Communication Networks

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko


    Accurate measurements of rainfall are important in many hydrological applications, for instance, flash-flood early-warning systems, hydraulic structures design, agriculture, weather forecasting, and climate modelling. Rainfall intensities can be retrieved from (commercial) microwave link networks. Whenever possible, link networks measure and store the decrease in power of the electromagnetic signal at regular intervals. The decrease in power is largely due to the attenuation by raindrops along the link paths. Such an alternative technique fulfills the continuous strive for measurements of rainfall in time and space at higher resolutions, especially in places where traditional rain gauge networks are scarce or poorly maintained. Rainfall maps from microwave link networks have recently been introduced at country-wide scales. Despite their potential in rainfall estimation at high spatiotemporal resolutions, the uncertainties present in rainfall maps from link networks are not yet fully comprehended. The aim of this work is to identify and quantify the sources of uncertainty present in interpolated rainfall maps from link rainfall depths. In order to disentangle these sources of uncertainty, we classified them into two categories: (1) those associated with the individual microwave link measurements, i.e., the physics involved in the measurements such as wet antenna attenuation, sampling interval of measurements, wet/dry period classification, drop size distribution (DSD), and multi-path propagation; (2) those associated with mapping, i.e., the combined effect of the interpolation methodology, the spatial density of the network, and the availability of link measurements. We computed ~ 3500 rainfall maps from real and simulated link rainfall depths for 12 days for the land surface of The Netherlands. These rainfall maps were compared against quality-controlled gauge-adjusted radar rainfall fields (assumed to be the ground truth). Thus, we were able to not only identify

  3. Autocatalytic closure and the evolution of cellular information processing networks

    Decraene, James


    Cellular Information Processing Networks (CIPNs) are chemical networks of interacting molecules occurring in living cells. Through complex molecular interactions, CIPNs are able to coordinate critical cellular activities in response to internal and external stimuli. We hypothesise that CIPNs may be abstractly regarded as subsets of collectively autocatalytic (i.e., organisationally closed) reaction networks. These closure properties would subsequently interact with the evolution and adaptatio...

  4. SoftCell: Taking Control of Cellular Core Networks

    Jin, Xin; Li, Li Erran; Vanbever, Laurent; Rexford, Jennifer


    Existing cellular networks suffer from inflexible and expensive equipment, and complex control-plane protocols. To address these challenges, we present SoftCell, a scalable architecture for supporting fine-grained policies for mobile devices in cellular core networks. The SoftCell controller realizes high-level service polices by directing traffic over paths that traverse a sequence of middleboxes, optimized to the network conditions and user locations. To ensure scalability, the core switche...

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

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


    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.

  6. Retrograde signaling: Organelles go networking.

    Kleine, Tatjana; Leister, Dario


    The term retrograde signaling refers to the fact that chloroplasts and mitochondria utilize specific signaling molecules to convey information on their developmental and physiological states to the nucleus and modulate the expression of nuclear genes accordingly. Signals emanating from plastids have been associated with two main networks: 'Biogenic control' is active during early stages of chloroplast development, while 'operational' control functions in response to environmental fluctuations. Early work focused on the former and its major players, the GUN proteins. However, our view of retrograde signaling has since been extended and revised. Elements of several 'operational' signaling circuits have come to light, including metabolites, signaling cascades in the cytosol and transcription factors. Here, we review recent advances in the identification and characterization of retrograde signaling components. We place particular emphasis on the strategies employed to define signaling components, spanning the entire spectrum of genetic screens, metabolite profiling and bioinformatics. This article is part of a Special Issue entitled 'EBEC 2016: 19th European Bioenergetics Conference, Riva del Garda, Italy, July 2-6, 2016', edited by Prof. Paolo Bernardi. PMID:26997501

  7. A Review on - Comparative Study of Issues in Cellular, Sensor and Adhoc Networks

    Jayashree V. Shiral


    Full Text Available A cellular network is an asymmetric radio network which is made up of fixed transceivers or nodes, maintain the signal while the mobile transceiver which is using the network is in the vicinity of the node. An ad-hoc network is a local area network (LAN that is built spontaneously as devices connect. Instead of relying on a base station to coordinate the flow of messages to each node in the network, the individual network nodes forward packets to and from each other. This paper focuses on various issues in cellular, adhoc and sensor network. As issues proves helpful for forthcoming research, this paper work as a backbone to elaborate the various research areas.

  8. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan


    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. PMID:26167934

  9. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

    Insoo Sohn

    Full Text Available An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.

  10. Optimizing Cellular Networks Enabled with Renewal Energy via Strategic Learning.

    Sohn, Insoo; Liu, Huaping; Ansari, Nirwan


    An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. PMID:26167934


    LI Hong; ZHOU Zhiyuan; DAI Rongyang; LUO Bo; ZHENG Xiaoli; YANG Wenli; HE Tao; WU Minglu


    In cells, the interactions of distinct signaling transduction pathways originating from cross-talkings between signaling molecules give rise to the formation of signaling transduction networks, which contributes to the changes (emergency) of kinetic behaviors of signaling system compared with single molecule or pathway. Depending on the known experimental data, we have constructed a model for complex cellular signaling transduction system, which is derived from signaling transduction of epidermal growth factor receptor in neuron. By the computational simulating methods, the self-adaptive controls of this system have been investigated. We find that this model exhibits a relatively stable selfadaptive system, especially to over-stimulation of agonist, and the amplitude and duration of signaling intermediates in it could be controlled by multiple self-adaptive effects, such as "signal scattering", "positive feedback", "negative feedback" and "B-Raf shunt". Our results provide an approach to understanding the dynamic behaviors of complex biological systems.

  12. Cellular-signaling pathways unveil the carcinogenic potential of chemicals.

    Hendriks, Giel; van de Water, Bob; Schoonen, Willem; Vrieling, Harry


    Most of the current in vitro carcinogenicity assays assess the potential carcinogenic properties of chemicals through the detection of inflicted DNA damage or subsequent chromosome damage and gene mutations. Unfortunately, these assays generally do not provide mechanistic insight into the reactive properties of a chemical. Upon chemical-induced damage of biomolecules, molecular sensors will activate general and damage-specific cellular response pathways that provide protection against the (geno)toxic and potential carcinogenic properties of chemicals. These cellular defense mechanisms include activation of cell-cycle checkpoints, DNA repair systems and induction of apoptosis or necrosis. Visualization of activated cellular-signaling pathways forms a powerful means to readily detect the genotoxic potential of chemical compounds and simultaneously gain insight into their reactive properties. Over the past years, various in vitro reporter assays have been developed that monitor activation of general and more specific cellular-signaling pathways, including the GreenScreen HC and ToxTracker assays. In this review we provide a perspective on how we can exploit activation of cellular signaling pathways to shed light on the mode of action of the chemical exposure and to develop sophisticated mechanism-based in vitro assays for cancer risk assessment. PMID:23339022

  13. Bootstrap Percolation in Cellular Automata on Small-World Directed Network

    Effects of network topology are studied in a system of cellular automata driven by a totalistic rule. In particular, propagation of a signal is considered in the directed network obtained from a flat (square) lattice by adding directed connections. The model is motivated by features found in human neural system. Cooperation between local dynamics and network organization results in fast stabilization of the system. Simple model of neural pyramidal cell is proposed to stabilize the automata in the oscillating firing patterns form. (author)

  14. The statistical mechanics of complex signaling networks: nerve growth factor signaling

    Brown, K. S.; Hill, C. C.; Calero, G. A.; Myers, C. R.; Lee, K. H.; Sethna, J. P.; Cerione, R. A.


    The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'

  15. Edge detection of noisy images based on cellular neural networks

    Li, Huaqing; Liao, Xiaofeng; Li, Chuandong; Huang, Hongyu; Li, Chaojie


    This paper studies a technique employing both cellular neural networks (CNNs) and linear matrix inequality (LMI) for edge detection of noisy images. Our main work focuses on training templates of noise reduction and edge detection CNNs. Based on the Lyapunov stability theorem, we derive a criterion for global asymptotical stability of a unique equilibrium of the noise reduction CNN. Then we design an approach to train edge detection templates, and this approach can detect the edge precisely and efficiently, i.e., by only one iteration. Finally, we illustrate performance of the proposed methodology from the aspect of peak signal to noise ratio (PSNR) through computer simulations. Moreover, some comparisons are also given to prove that our method outperforms classical operators in gray image edge detection.

  16. Adenylate Kinase and AMP Signaling Networks: Metabolic Monitoring, Signal Communication and Body Energy Sensing

    Andre Terzic


    Full Text Available Adenylate kinase and downstream AMP signaling is an integrated metabolic monitoring system which reads the cellular energy state in order to tune and report signals to metabolic sensors. A network of adenylate kinase isoforms (AK1-AK7 are distributed throughout intracellular compartments, interstitial space and body fluids to regulate energetic and metabolic signaling circuits, securing efficient cell energy economy, signal communication and stress response. The dynamics of adenylate kinase-catalyzed phosphotransfer regulates multiple intracellular and extracellular energy-dependent and nucleotide signaling processes, including excitation-contraction coupling, hormone secretion, cell and ciliary motility, nuclear transport, energetics of cell cycle, DNA synthesis and repair, and developmental programming. Metabolomic analyses indicate that cellular, interstitial and blood AMP levels are potential metabolic signals associated with vital functions including body energy sensing, sleep, hibernation and food intake. Either low or excess AMP signaling has been linked to human disease such as diabetes, obesity and hypertrophic cardiomyopathy. Recent studies indicate that derangements in adenylate kinase-mediated energetic signaling due to mutations in AK1, AK2 or AK7 isoforms are associated with hemolytic anemia, reticular dysgenesis and ciliary dyskinesia. Moreover, hormonal, food and antidiabetic drug actions are frequently coupled to alterations of cellular AMP levels and associated signaling. Thus, by monitoring energy state and generating and distributing AMP metabolic signals adenylate kinase represents a unique hub within the cellular homeostatic network.

  17. Cancer signaling networks and their implications for personalized medicine

    Creixell, Pau

    of the articles that are part of this PhD thesis (part II). In part III, we illustrate with an article that has been submitted recently, how next-generation sequencing data and mass spectrometry data can be combined to uncover genome-specific signaling networks. In part IV, I describe the two computational......) 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......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...

  18. Quantitative proteomic assessment of very early cellular signaling events

    Dengjel, Joern; Akimov, Vyacheslav; Olsen, Jesper V;


    Technical limitations have prevented proteomic analyses of events occurring less than 30 s after signal initiation. We developed an automated, continuous quench-flow system allowing quantitative proteomic assessment of very early cellular signaling events (qPACE) with a time resolution of 1 s....... Using this technique, we determined that autophosphorylation of the epidermal growth factor receptor occurs within 1 s after ligand stimulation and is followed rapidly by phosphorylation of the downstream signaling intermediates Src homologous and collagen-like protein and phospholipase C gamma 1....

  19. Integrated cellular network of transcription regulations and protein-protein interactions

    Chen Bor-Sen


    Full Text Available Abstract Background With the accumulation of increasing omics data, a key goal of systems biology is to construct networks at different cellular levels to investigate cellular machinery of the cell. However, there is currently no satisfactory method to construct an integrated cellular network that combines the gene regulatory network and the signaling regulatory pathway. Results In this study, we integrated different kinds of omics data and developed a systematic method to construct the integrated cellular network based on coupling dynamic models and statistical assessments. The proposed method was applied to S. cerevisiae stress responses, elucidating the stress response mechanism of the yeast. From the resulting integrated cellular network under hyperosmotic stress, the highly connected hubs which are functionally relevant to the stress response were identified. Beyond hyperosmotic stress, the integrated network under heat shock and oxidative stress were also constructed and the crosstalks of these networks were analyzed, specifying the significance of some transcription factors to serve as the decision-making devices at the center of the bow-tie structure and the crucial role for rapid adaptation scheme to respond to stress. In addition, the predictive power of the proposed method was also demonstrated. Conclusions We successfully construct the integrated cellular network which is validated by literature evidences. The integration of transcription regulations and protein-protein interactions gives more insight into the actual biological network and is more predictive than those without integration. The method is shown to be powerful and flexible and can be used under different conditions and for different species. The coupling dynamic models of the whole integrated cellular network are very useful for theoretical analyses and for further experiments in the fields of network biology and synthetic biology.

  20. Load-Aware Modeling and Analysis of Heterogeneous Cellular Networks

    Dhillon, Harpreet S; Andrews, Jeffrey G


    Random spatial models are attractive for modeling heterogeneous cellular networks (HCNs) due to their realism, tractability, and scalability. A major limitation of such models to date in the context of HCNs is the neglect of network traffic and load: all base stations (BSs) have typically been assumed to always be transmitting. Small cells in particular will have a lighter load than macrocells, and so their contribution to the network interference may be significantly overstated in a fully loaded model. This paper incorporates a flexible notion of BS load by introducing a new idea of conditionally thinning the interference field. For a $K$-tier HCN where BSs across tiers differ in terms of transmit power, supported data rate, deployment density, and now load, we derive the coverage probability for a typical mobile, which connects to the strongest BS signal. Conditioned on this connection, the interfering BSs of the $i^{th}$ tier are assumed to transmit independently with probability $p_i$, which models the lo...


    Md. Humayun Kabir


    Full Text Available In this paper, we propose a novel SDN-based cellular network architecture that will be able to utilize the opportunities of centralized administration of today’s emerging mobile network. Our proposed architecture would not depend on a single controller, rather it divides the whole cellular area into clusters, and each cluster is controlled by a separate controller. A number of controller services are provided on top of each controller to manage all the major functionalities of the network and help to make the network programmable and more agile, and create opportunities for policy-driven supervision and more automation.

  2. 1,4-Naphthoquinones: From Oxidative Damage to Cellular and Inter-Cellular Signaling

    Lars-Oliver Klotz


    Full Text Available Naphthoquinones may cause oxidative stress in exposed cells and, therefore, affect redox signaling. Here, contributions of redox cycling and alkylating properties of quinones (both natural and synthetic, such as plumbagin, juglone, lawsone, menadione, methoxy-naphthoquinones, and others to cellular and inter-cellular signaling processes are discussed: (i naphthoquinone-induced Nrf2-dependent modulation of gene expression and its potentially beneficial outcome; (ii the modulation of receptor tyrosine kinases, such as the epidermal growth factor receptor by naphthoquinones, resulting in altered gap junctional intercellular communication. Generation of reactive oxygen species and modulation of redox signaling are properties of naphthoquinones that render them interesting leads for the development of novel compounds of potential use in various therapeutic settings.

  3. Uncovering the footprints of malicious traffic in cellular data networks

    Raghuramu, A; Zang, H.; Chuah, CN


    © Springer International Publishing Switzerland 2015. In this paper, we present a comprehensive characterization of malicious traffic generated by mobile devices using Deep Packet Inspection (DPI) records and security event logs from a large US based cellular provider network. Our analysis reveals that 0.17% of mobile devices in the cellular network are affected by security threats. This proportion, while small, is orders of magnitude higher than the last reported (in 2013) infection rate of ...

  4. Summarizing cellular responses as biological process networks

    Lasher, Christopher D; Rajagopalan, Padmavathy; Murali, T.M.


    Abstract Background Microarray experiments can simultaneously identify thousands of genes that show significant perturbation in expression between two experimental conditions. Response networks, computed through the integration of gene interaction networks with expression perturbation data, may themselves contain tens of thousands of interactions. Gene set enrichment has become standard for summarizing the results of these analyses in te...

  5. Persistent cellular motion control and trapping using mechanotactic signaling.

    Xiaoying Zhu

    Full Text Available Chemotactic signaling and the associated directed cell migration have been extensively studied owing to their importance in emergent processes of cellular aggregation. In contrast, mechanotactic signaling has been relatively overlooked despite its potential for unique ways to artificially signal cells with the aim to effectively gain control over their motile behavior. The possibility of mimicking cellular mechanotactic signals offers a fascinating novel strategy to achieve targeted cell delivery for in vitro tissue growth if proven to be effective with mammalian cells. Using (i optimal level of extracellular calcium ([Ca(2+]ext = 3 mM we found, (ii controllable fluid shear stress of low magnitude (σ < 0.5 Pa, and (iii the ability to swiftly reverse flow direction (within one second, we are able to successfully signal Dictyostelium discoideum amoebae and trigger migratory responses with heretofore unreported control and precision. Specifically, we are able to systematically determine the mechanical input signal required to achieve any predetermined sequences of steps including straightforward motion, reversal and trapping. The mechanotactic cellular trapping is achieved for the first time and is associated with a stalling frequency of 0.06 ~ 0.1 Hz for a reversing direction mechanostimulus, above which the cells are effectively trapped while maintaining a high level of directional sensing. The value of this frequency is very close to the stalling frequency recently reported for chemotactic cell trapping [Meier B, et al. (2011 Proc Natl Acad Sci USA 108:11417-11422], suggesting that the limiting factor may be the slowness of the internal chemically-based motility apparatus.

  6. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Overeem, Aart; Uijlenhoet, Remko; Leijnse, Hidde


    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. We present a rainfall retrieval algorithm, which is employed to obtain rainfall maps from microwave links in a cellular communication network. We compare these rainfall maps to gauge-adjusted radar rainfall maps. The microwave link data set, as well as the developed code, a package in the open source scripting language "R", are freely available at GitHub ( The purpose of this presentation is to promote rainfall mapping utilizing microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  7. Determination of Sphingosine Kinase Activity for Cellular Signaling Studies

    Lee, Katherine J.; Mwongela, Simon M.; Kottegoda, Sumith; Borland, Laura; Nelson, Allison R.; Sims, Christopher E.; Allbritton, Nancy L.


    Regulation of sphingosine and sphingosine-1-phosphate concentrations is of growing interest due to their importance in cellular signal transduction. Furthermore, new pharmaceutical agents moderating the intracellular and extracellular levels of sphingosine metabolites are showing promise in preclinical and clinical trials. In the present work, a quantitative assay relying on capillary electrophoresis with laser-induced fluorescence detection was developed to measure the interconversion of sph...

  8. Bioinformatics analyses for signal transduction networks

    LIU Wei; LI Dong; ZHU YunPing; HE FuChu


    Research in signaling networks contributes to a deeper understanding of organism living activities. With the development of experimental methods in the signal transduction field, more and more mechanisms of signaling pathways have been discovered. This paper introduces such popular bioin-formatics analysis methods for signaling networks as the common mechanism of signaling pathways and database resource on the Internet, summerizes the methods of analyzing the structural properties of networks, including structural Motif finding and automated pathways generation, and discusses the modeling and simulation of signaling networks in detail, as well as the research situation and tendency in this area. Now the investigation of signal transduction is developing from small-scale experiments to large-scale network analysis, and dynamic simulation of networks is closer to the real system. With the investigation going deeper than ever, the bioinformatics analysis of signal transduction would have immense space for development and application.

  9. Fundamental Tradeoffs among Reliability, Latency and Throughput in Cellular Networks

    Soret, Beatriz; Mogensen, Preben; Pedersen, Klaus I.;


    We address the fundamental tradeoffs among latency, reliability and throughput in a cellular network. The most important elements influencing the KPIs in a 4G network are identified, and the inter-relationships among them is discussed. We use the effective bandwidth and the effective capacity the...

  10. Cellular and synaptic network defects in autism

    Peça, João; Feng, Guoping


    Many candidate genes are now thought to confer susceptibility to autism spectrum disorders (ASDs). Here we review four interrelated complexes, each composed of multiple families of genes that functionally coalesce on common cellular pathways. We illustrate a common thread in the organization of glutamatergic synapses and suggest a link between genes involved in Tuberous Sclerosis Complex, Fragile X syndrome, Angelman syndrome and several synaptic ASD candidate genes. When viewed in this conte...

  11. Energy management in wireless cellular and ad-hoc networks

    Imran, Muhammad; Qaraqe, Khalid; Alouini, Mohamed-Slim; Vasilakos, Athanasios


    This book investigates energy management approaches for energy efficient or energy-centric system design and architecture and presents end-to-end energy management in the recent heterogeneous-type wireless network medium. It also considers energy management in wireless sensor and mesh networks by exploiting energy efficient transmission techniques and protocols. and explores energy management in emerging applications, services and engineering to be facilitated with 5G networks such as WBANs, VANETS and Cognitive networks. A special focus of the book is on the examination of the energy management practices in emerging wireless cellular and ad hoc networks. Considering the broad scope of energy management in wireless cellular and ad hoc networks, this book is organized into six sections covering range of Energy efficient systems and architectures; Energy efficient transmission and techniques; Energy efficient applications and services. .

  12. A new small-world network created by Cellular Automata

    Ruan, Yuhong; Li, Anwei


    In this paper, we generate small-world networks by the Cellular Automaton based on starting with one-dimensional regular networks. Besides the common properties of small-world networks with small average shortest path length and large clustering coefficient, the small-world networks generated in this way have other properties: (i) The edges which are cut in the regular network can be controlled that whether the edges are reconnected or not, and (ii) the number of the edges of the small-world network model equals the number of the edges of the original regular network. In other words, the average degree of the small-world network model equals to the average degree of the original regular network.

  13. Country-wide rainfall maps from cellular communication networks

    Leijnse, Hidde; Overeem, Aart; Uijlenhoet, Remko


    Accurate rainfall observations with high spatial and temporal resolutions are needed for hydrological applications, agriculture, meteorology, and climate monitoring. However, the majority of the land surface of the earth lacks accurate rainfall information and the number of rain gauges is even severely declining in Europe, South-America, and Africa. This calls for alternative sources of rainfall information. Various studies have shown that microwave links from operational cellular telecommunication networks may be employed for rainfall monitoring. Such networks cover 20% of the land surface of the earth and have a high density, especially in urban areas. The basic principle of rainfall monitoring using microwave links is as follows. Rainfall attenuates the electromagnetic signals transmitted from one telephone tower to another. By measuring the received power at one end of a microwave link as a function of time, the path-integrated attenuation due to rainfall can be calculated. Previous studies have shown that average rainfall intensities over the length of a link can be derived from the path-integrated attenuation. Here we show how one cellular telecommunication network can be used to retrieve the space-time dynamics of rainfall for an entire country. A dataset from a commercial microwave link network over the Netherlands is analyzed, containing data from an unprecedented number of links (2400) covering the land surface of the Netherlands (35500 km2). This dataset consists of 24 days with substantial rainfall in June - September 2011. A rainfall retrieval algorithm is presented to derive rainfall intensities from the microwave link data, which have a temporal resolution of 15 min. Rainfall maps (1 km spatial resolution) are generated from these rainfall intensities using Kriging. This algorithm is suited for real-time application, and is calibrated on a subset (12 days) of the dataset. The other 12 days in the dataset are used to validate the algorithm. Both

  14. Existence and exponential stability of almost periodic solution for stochastic cellular neural networks with delay

    The paper considers the problems of existence of quadratic mean almost periodic and global exponential stability for stochastic cellular neural networks with delays. By employing the Holder's inequality and fixed points principle, we present some new criteria ensuring existence and uniqueness of a quadratic mean almost periodic and global exponential stability. These criteria are important in signal processing and the design of networks. Moreover, these criteria are also applied in others stochastic biological neural systems.

  15. TRANSWESD : inferring cellular networks with transitive reduction

    Klamt, S; Flassig, R.; Sundmacher, K.


    Motivation: Distinguishing direct from indirect influences is a central issue in reverse engineering of biological networks because it facilitates detection and removal of false positive edges. Transitive reduction is one approach for eliminating edges reflecting indirect effects but its use in reconstructing cyclic interaction graphs with true redundant structures is problematic. Results: We present TRANSWESD, an elaborated variant of TRANSitive reduction for WEighted Signed Digraphs that ov...

  16. Incorporating scale invariance into the cellular associative neural network

    Burles, Nathan; O'Keefe, Simon; Austin, James


    This paper describes an improvement to the Cellular Associative Neural Network, an architecture based on the distributed model of a cellular automaton, allowing it to perform scale invariant pattern matching. The use of tensor products and superposition of patterns allows the system to recall patterns at multiple resolutions simultaneously. Our experimental results show that the architecture is capable of scale invariant pattern matching, but that further investigation is needed to reduce the...

  17. Green Cellular Network Deployment To Reduce RF Pollution

    Katiyar, Sumit; Agrawal, N K


    As the mobile telecommunication systems are growing tremendously all over the world, the numbers of handheld and base stations are also rapidly growing and it became very popular to see these base stations distributed everywhere in the neighborhood and on roof tops which has caused a considerable amount of panic to the public in Palestine concerning wither the radiated electromagnetic fields from these base stations may cause any health effect or hazard. Recently UP High Court in India ordered for removal of BTS towers from residential area, it has created panic among cellular communication network designers too. Green cellular networks could be a solution for the above problem. This paper deals with green cellular networks with the help of multi-layer overlaid hierarchical structure (macro / micro / pico / femto cells). Macrocell for area coverage, micro for pedestrian and a slow moving traffic while pico for indoor use and femto for individual high capacity users. This could be the answer of the problem of ...

  18. Silymarin Suppresses Cellular Inflammation By Inducing Reparative Stress Signaling

    Lovelace, Erica S.; Wagoner, Jessica; MacDonald, James; Bammler, Theo; Bruckner, Jacob; Brownell, Jessica; Beyer, Richard; Zink, Erika M.; Kim, Young-Mo; Kyle, Jennifer E.; Webb-Robertson, Bobbie-Jo M.; Waters, Katrina M.; Metz, Thomas O.; Farin, Federico; Oberlies, Nicholas H.; Polyak, Steve


    Silymarin (SM), a natural product, is touted as a liver protectant and preventer of both chronic inflammation and diseases. To define how SM elicits these effects at a systems level, we performed transcriptional profiling, metabolomics, and signaling studies in human liver and T cell lines. Multiple pathways associated with cellular stress and metabolism were modulated by SM treatment within 0.5 to four hours: activation of Activating Transcription Factor 4 (ATF-4) and adenosine monophosphate protein kinase (AMPK) and inhibition of mammalian target of rapamycin (mTOR) signaling, the latter being associated with induction of DNA-damage-inducible transcript 4 (DDIT4). Metabolomics analyses revealed suppression of glycolytic, TCA cycle, and amino acid metabolism by SM treatment. Antiinflammatory effects arose with prolonged (i.e. 24 hours) SM exposure, with suppression of multiple proinflammatory mRNAs and nuclear factor kappa B (NF-κB) and forkhead box O (FOXO) signaling. Studies with murine knock out cells revealed that SM inhibition of both mTOR and NF-κB was partially AMPK dependent, while SM inhibition of the mTOR pathway in part required DDIT4. Thus, SM activates stress and repair responses that culminate in an anti-inflammatory phenotype. Other natural products induced similar stress responses, which correlated with their ability to suppress inflammation. Therefore, natural products like SM may be useful as tools to define how metabolic, stress, and repair pathways regulate cellular inflammation.

  19. SPIKE – a database, visualization and analysis tool of cellular signaling pathways

    Blekhman Ran


    Full Text Available Abstract Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1 A database (DB of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2 A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3 An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data.


    Strychalski, Wanda; Adalsteinsson, David; Elston, Timothy C


    Signaling networks regulate cellular responses to environmental stimuli through cascades of protein interactions. External signals can trigger cells to polarize and move in a specific direction. During migration, spatially localized activity of proteins is maintained. To investigate the effects of morphological changes on intracellular signaling, we developed a numerical scheme consisting of a cut cell finite volume spatial discretization coupled with level set methods to simulate the resulting advection-reaction-diffusion system. We then apply the method to several biochemical reaction networks in changing geometries. We found that a Turing instability can develop exclusively by cell deformations that maintain constant area. For a Turing system with a geometry-dependent single or double peak solution, simulations in a dynamically changing geometry suggest that a single peak solution is the only stable one, independent of the oscillation frequency. The method is also applied to a model of a signaling network in a migrating fibroblast. PMID:24086102

  1. Phosphoproteomics-based systems analysis of signal transduction networks

    Hiroko eKozuka-Hata


    Full Text Available Signal transduction systems coordinate complex cellular information to regulate biological events such as cell proliferation and differentiation. Although the accumulating evidence on widespread association of signaling molecules has revealed essential contribution of phosphorylation-dependent interaction networks to cellular regulation, their dynamic behavior is mostly yet to be analyzed. Recent technological advances regarding mass spectrometry-based quantitative proteomics have enabled us to describe the comprehensive status of phosphorylated molecules in a time-resolved manner. Computational analyses based on the phosphoproteome dynamics accelerate generation of novel methodologies for mathematical analysis of cellular signaling. Phosphoproteomics-based numerical modeling can be used to evaluate regulatory network elements from a statistical point of view. Integration with transcriptome dynamics also uncovers regulatory hubs at the transcriptional level. These omics-based computational methodologies, which have firstly been applied to representative signaling systems such as the epidermal growth factor receptor pathway, have now opened up a gate for systems analysis of signaling networks involved in immune response and cancer.

  2. Optimising base station location for UMTS cellular networks

    Rapid development of universal mobile telecommunication systems put demands on tools for assisting planning of cellular network infrastructure. The tools need to focus on critical issues in modern cellular networks and techniques used for previous generation system no longer serve useful. In this paper, an algorithm based on Branch and Bound approach is proposed for solving base station location problem, covering interference levels, traffic demands and power control mechanism. The efficiency of the algorithm is evaluated with respect to existing approaches for solving this problem – using the designed and implemented experimentation system

  3. Cytokine expression and signaling in drug-induced cellular senescence

    Nováková, Zora; Hubáčková, Soňa; Košař, Martin; Janderová-Rossmeislová, Lenka; Dobrovolná, Jana; Vašicová, Pavla; Vančurová, Markéta; Hořejší, Zuzana; Hozák, Pavel; Bartek, Jiří; Hodný, Zdeněk


    Roč. 29, č. 2 (2010), s. 273-284. ISSN 0950-9232 R&D Projects: GA AV ČR IAA500390501; GA ČR GA204/08/1418; GA MŠk LC545 Grant ostatní: EC(XE) TRIREME Institutional research plan: CEZ:AV0Z50520514; CEZ:AV0Z50200510 Keywords : cellular senescence * cytokines * JAK/STAT signaling pathway Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 7.414, year: 2010

  4. DMPD: Cellular signaling in macrophage migration and chemotaxis. [Dynamic Macrophage Pathway CSML Database

    Full Text Available 11073096 Cellular signaling in macrophage migration and chemotaxis. Jones GE. J Leu...koc Biol. 2000 Nov;68(5):593-602. (.png) (.svg) (.html) (.csml) Show Cellular signaling in macrophage migration... and chemotaxis. PubmedID 11073096 Title Cellular signaling in macrophage migration and chemotaxis. Autho

  5. Solar Energy Empowered 5G Cognitive Metro-Cellular Networks

    Zaidi, SAR; Afzal, A; M. Hafeez; Ghogho, M.; McLernon, DC; Swami, A


    Harvesting energy from natural (solar, wind, vibration, etc.) and synthesized (microwave power transfer) sources is envisioned as a key enabler for realizing green wireless networks. Energy efficient scheduling is one of the prime objectives in emerging cognitive radio platforms. To that end, in this article we present a comprehensive framework to characterize the performance of a cognitive metro-cellular network empowered by solar energy harvesting. The proposed model allows designers to cap...

  6. Cellular Underwater Wireless Optical CDMA Network: Potentials and Challenges

    Akhoundi, Farhad; Jamali, Mohammad Vahid; Banihassan, Navid; Beyranvand, Hamzeh; Minoofar, Amir; Salehi, Jawad A.


    Underwater wireless optical communications is an emerging solution to the expanding demand for broadband links in oceans and seas. In this paper, a cellular underwater wireless optical code division multiple-access (UW-OCDMA) network is proposed to provide broadband links for commercial and military applications. The optical orthogonal codes (OOC) are employed as signature codes of underwater mobile users. Fundamental key aspects of the network such as its backhaul architecture, its potential...

  7. Performance methods for mobility management in cellular networks

    Liu, LQ; Munro, ATD; Barton, MH; McGeehan, JP


    This paper presents performance methods for mobility management in cellular networks. A queueing analysis is first undertaken, in which the system is modelled as an open Jackson network, consisting of M M/M/1 queues. Given environmental parameters, the corresponding probability matrix is obtained, and hence the traffic matrix equations. From these equations, the traffic load in each cell is evaluated. Secondly, a BONeS DESIGNER simulation model is created and applied to the evaluation of mobi...

  8. Cellular neural networks for the stereo matching problem

    Taraglio, S. [ENEA, Centro Ricerche Casaccia, Rome (Italy). Dipt. Innovazione; Zanela, A. [Rome Univ. `La Sapienza` (Italy). Dipt. di Fisica


    The applicability of the Cellular Neural Network (CNN) paradigm to the problem of recovering information on the tridimensional structure of the environment is investigated. The approach proposed is the stereo matching of video images. The starting point of this work is the Zhou-Chellappa neural network implementation for the same problem. The CNN based system we present here yields the same results as the previous approach, but without the many existing drawbacks.

  9. Cellular neural networks for the stereo matching problem

    The applicability of the Cellular Neural Network (CNN) paradigm to the problem of recovering information on the tridimensional structure of the environment is investigated. The approach proposed is the stereo matching of video images. The starting point of this work is the Zhou-Chellappa neural network implementation for the same problem. The CNN based system we present here yields the same results as the previous approach, but without the many existing drawbacks

  10. On Hardware Implementation of Discrete-Time Cellular Neural Networks

    Malki, Suleyman


    Cellular Neural Networks are characterized by simplicity of operation. The network consists of a large number of nonlinear processing units; called cells; that are equally spread in the space. Each cell has a simple function (sequence of multiply-add followed by a single discrimination) that takes an element of a topographic map and then interacts with all cells within a specified sphere of interest through direct connections. Due to their intrinsic parallel computing power, CNNs have attract...

  11. Almost sure exponential stability of delayed cellular neural networks

    Chuangxia Huang


    Full Text Available The stability of stochastic delayed Cellular Neural Networks (DCNN is investigated in this paper. Using suitable Lyapunov functional and the semimartingale convergence theorem, we obtain some sufficient conditions for checking the almost sure exponential stability of the DCNN.

  12. Multi-robot Coordination by using Cellular Neural Networks

    A. Gacsadi


    Full Text Available Vision-based algorithms for multi-robot coordination,are presented in this paper. Cellular Neural Networks (CNNsprocessing techniques are used for real time motion planning ofthe robots. The CNN methods are considered an advantageoussolution for image processing in autonomous mobile robotsguidance.

  13. Millimeter-Wave Evolution for 5G Cellular Networks

    Sakaguchi, Kei; Tran, Gia Khanh; Shimodaira, Hidekazu; Nanba, Shinobu; Sakurai, Toshiaki; Takinami, Koji; Siaud, Isabelle; Strinati, Emilio Calvanese; Capone, Antonio; Karls, Ingolf; Arefi, Reza; Haustein, Thomas

    Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.

  14. Gateway Deployment optimization in Cellular Wi-Fi Mesh Networks

    Rajesh Prasad


    Full Text Available With the standardization of IEEE 802.11, there has been an explosive growth of wireless local area networks (WLAN. Recently, this cost effective technology is being developed aggressively for establishing metro-scale “cellular Wi-Fi” network to support seamless Internet access in the urban area. We envision a large scale WLAN system in the future where Access Points (APs will be scattered over an entire city enabling people to use their mobile devices ubiquitously. The problem addressed in this paper involves finding the minimum number of gateways and their optimal placement so as to minimize the network installation costs while maintaining reliability, flexibility and an acceptable grade of service. The problem is modeled taking a network graph, where the nodes represents either the Access Points of IEEE 802.11 or wired backbone gateways. In this paper, we present two methods (1 an innovative approach using integer linear programming (ILP for gateway selection in the cellular Wi-Fi network, and (2 a completely new heuristic (OPEN/CLOSE to solve the gateway selection problem. In the ILP model, we developed a set of linear inequalities based on various constraints. The ILP model is solved by using lp-solve, a simplex-based software for linear and integer programming problems. The second approach is an OPEN/CLOSE heuristic, tailored for cellular Wi-Fi, which arrives at a sub-optimal solution. Java programming language is used for simulation in OPEN/CLOSE heuristic. Extensive simulations are carried out for performance evaluation. Simulation results show that the proposed approaches can effectively identify a set of gateways at optimal locations in a cellular Wi-Fi network, resulting in an overall cost reduction of up to 50%. The technique presented in this paper is generalized and can be used for gateway selection for other networks as well.

  15. Global stability analysis on a class of cellular neural networks


    The existence, uniqueness, globally exponential stability andspeed of exponential convergence for a class of cellular neural networks are investigated. The existence of a unique equilibrium is proved under very concise conditions, and theorems for estimating the global convergence speed approaching the equilibrium and criteria for its globally exponential stability are derived, Considering synapse time delay, by constructing appropriate Lyapunov functional, the existence of a unique equilibrium and its global stability for the delayed network are also proved. The results, which do not require the cloning template to be symmetric, are easy to use in network design.

  16. Coverage and Economy of Cellular Networks with Many Base Stations

    Lee, Seunghyun


    The performance of a cellular network can be significantly improved by employing many base stations (BSs), which shortens transmission distances. However, there exist no known results on quantifying the performance gains from deploying many BSs. To address this issue, we adopt a stochastic-geometry model of the downlink cellular network and analyze the mobile outage probability. Specifically, given Poisson distributed BSs, the outage probability is shown to diminish inversely with the increasing ratio between the BS and mobile densities. Furthermore, we analyze the optimal tradeoff between the performance gain from increasing the BS density and the resultant network cost accounting for energy consumption, BS hardware and backhaul cables. The optimal BS density is proved to be proportional to the square root of the mobile density and the inverse of the square root of the cost factors considered.

  17. Signaling in large-scale neural networks

    Berg, Rune W; Hounsgaard, Jørn


    We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this...... metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons....

  18. Area Green Efficiency (AGE) of Two Tier Heterogeneous Cellular Networks

    Tabassum, Hina


    Small cell networks are becoming standard part of the future heterogeneous networks. In this paper, we consider a two tier heterogeneous network which promises energy savings by integrating the femto and macro cellular networks and thereby reducing CO2 emissions, operational and capital expenditures (OPEX and CAPEX) whilst enhancing the area spectral efficiency (ASE) of the network. In this context, we define a performance metric which characterize the aggregate energy savings per unit macrocell area and is referred to as area green efficiency (AGE) of the two tier heterogeneous network where the femto base stations are arranged around the edge of the reference macrocell such that the configuration is referred to as femto-on-edge (FOE). The mobile users in macro and femto cellular networks are transmitting with the adaptive power while maintaining the desired link quality such that the energy aware FOE configuration mandates to (i) save energy, and (ii) reduce the co-channel interference. We present a mathematical analysis to incorporate the uplink power control mechanism adopted by the mobile users and calibrate the uplink ASE and AGE of the energy aware FOE configuration. Next, we derive analytical expressions to compute the bounds on the uplink ASE of energy aware FOE configuration and demonstrate that the derived bounds are useful in evaluating the ASE under worst and best case interference scenarios. Simulation results are produced to demonstrate the ASE and AGE improvements in comparison to macro-only and macro-femto configuration with uniformly distributed femtocells.

  19. Probing cellular dynamics with a chemical signal generator.

    Brandon Kuczenski

    Full Text Available Observations of material and cellular systems in response to time-varying chemical stimuli can aid the analysis of dynamic processes. We describe a microfluidic "chemical signal generator," a technique to apply continuously varying chemical concentration waveforms to arbitrary locations in a microfluidic channel through feedback control of the interface between parallel laminar (co-flowing streams. As the flow rates of the streams are adjusted, the channel walls are exposed to a chemical environment that shifts between the individual streams. This approach can be used to probe the dynamic behavior of objects or substances adherent to the interior of the channel. To demonstrate the technique, we exposed live fibroblast cells to ionomycin, a membrane-permeable calcium ionophore, while assaying cytosolic calcium concentration. Through the manipulation of the laminar flow interface, we exposed the cells' endogenous calcium handling machinery to spatially-contained discrete and oscillatory intracellular disturbances, which were observed to elicit a regulatory response. The spatiotemporal precision of the generated signals opens avenues to previously unapproachable areas for potential investigation of cell signaling and material behavior.

  20. Two programmed replicative lifespans of Saccharomyces cerevisiae formed by the endogenous molecular-cellular network.

    Hu, Jie; Zhu, Xiaomei; Wang, Xinan; Yuan, Ruoshi; Zheng, Wei; Xu, Minjuan; Ao, Ping


    Cellular replicative capacity is a therapeutic target for regenerative medicine as well as cancer treatment. The mechanism of replicative senescence and cell immortality is still unclear. We investigated the diauxic growth of Saccharomyces cerevisiae and demonstrate that the replicative capacity revealed by the yeast growth curve can be understood by using the dynamical property of the molecular-cellular network regulating S. cerevisiae. The endogenous network we proposed has a limit cycle when pheromone signaling is disabled, consistent with the exponential growth phase with an infinite replicative capacity. In the post-diauxic phase, the cooperative effect of the pheromone activated mitogen-activated protein kinase (MAPK) signaling pathway with the cell cycle leads to a fixed point attractor instead of the limit cycle. The cells stop dividing after several generations counting from the beginning of the post-diauxic growth. By tuning the MAPK pathway, S. cerevisiae therefore programs the number of offsprings it replicates. PMID:24447585

  1. Cellular mechanisms of tissue fibrosis. 6. Purinergic signaling and response in fibroblasts and tissue fibrosis.

    Lu, David; Insel, Paul A


    Tissue fibrosis occurs as a result of the dysregulation of extracellular matrix (ECM) synthesis. Tissue fibroblasts, resident cells responsible for the synthesis and turnover of ECM, are regulated via numerous hormonal and mechanical signals. The release of intracellular nucleotides and their resultant autocrine/paracrine signaling have been shown to play key roles in the homeostatic maintenance of tissue remodeling and in fibrotic response post-injury. Extracellular nucleotides signal through P2 nucleotide and P1 adenosine receptors to activate signaling networks that regulate the proliferation and activity of fibroblasts, which, in turn, influence tissue structure and pathologic remodeling. An important component in the signaling and functional responses of fibroblasts to extracellular ATP and adenosine is the expression and activity of ectonucleotideases that attenuate nucleotide-mediated signaling, and thereby integrate P2 receptor- and subsequent adenosine receptor-initiated responses. Results of studies of the mechanisms of cellular nucleotide release and the effects of this autocrine/paracrine signaling axis on fibroblast-to-myofibroblast conversion and the fibrotic phenotype have advanced understanding of tissue remodeling and fibrosis. This review summarizes recent findings related to purinergic signaling in the regulation of fibroblasts and the development of tissue fibrosis in the heart, lungs, liver, and kidney. PMID:24352335

  2. The role of actin networks in cellular mechanosensing

    Azatov, Mikheil

    Physical processes play an important role in many biological phenomena, such as wound healing, organ development, and tumor metastasis. During these processes, cells constantly interact with and adapt to their environment by exerting forces to mechanically probe the features of their surroundings and generating appropriate biochemical responses. The mechanisms underlying how cells sense the physical properties of their environment are not well understood. In this thesis, I present my studies to investigate cellular responses to the stiffness and topography of the environment. In order to sense the physical properties of their environment, cells dynamically reorganize the structure of their actin cytoskeleton, a dynamic network of biopolymers, altering the shape and spatial distribution of protein assemblies. Several observations suggest that proteins that crosslink actin filaments may play an important role in cellular mechanosensitivity. Palladin is an actin-crosslinking protein that is found in the lamellar actin network, stress fibers and focal adhesions, cellular structures that are critical for mechanosensing of the physical environment. By virtue of its close interactions with these structures in the cell, palladin may play an important role in cell mechanics. However, the role of actin crosslinkers in general, and palladin in particular, in cellular force generation and mechanosensing is not well known. I have investigated the role of palladin in regulating the plasticity of the actin cytoskeleton and cellular force generation in response to alterations in substrate stiffness. I have shown that the expression levels of palladin modulate the forces exerted by cells and their ability to sense substrate stiffness. Perturbation experiments also suggest that palladin levels in cells altered myosin motor activity. These results suggest that the actin crosslinkers, such as palladin, and myosin motors coordinate for optimal cell function and to prevent aberrant

  3. Cellular chromophores and signaling in low level light therapy

    Hamblin, Michael R.; Demidova-Rice, Tatiana N.


    particular, signaling cascades are initiated via cyclic adenosine monophosphate (cAMP) and nuclear factor kappa B (NF-κB). These signal transduction pathways in turn lead to increased cell proliferation and migration (particularly by fibroblasts), modulation in levels of cytokines, growth factors and inflammatory mediators, and increases in anti-apoptotic proteins. The results of these biochemical and cellular changes in animals and patients include such benefits as increased healing in chronic wounds, improvements in sports injuries and carpal tunnel syndrome, pain reduction in arthritis and neuropathies, and amelioration of damage after heart attacks, stroke, nerve injury and retinal toxicity.

  4. Organisation of signal flow in directed networks

    Bányai, M; Négyessy, L; Bazsó, F


    Structure of signal flow in the network is mapped using the notion of convergence degree (CD), introduced in N\\'egyessy et al 2008 Proc. Roy. Soc. B, vol. 275 p. 2403. We refine the definition of convergence degree and complement it with the notion of the overlapping set of an edge. Definitions of the edge measures are based on the notion of shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality. Properties of CD are explored on two model graphs, convergence degree values are calculated for regular oriented trees and its probability density function for networks grown with preferential attachment mechanism. Based on the node-reduced convergence degree representation of the network we distinguish nodes according to their local and global signal transmitting and processing properties. In case of real-world networks, local and global signal transmitting and processing properties differ, exhi...

  5. Resource allocation in cellular networks employing mobile femtocells with deterministic mobility

    Jangsher, S; Li, VOK


    Improvement in signal quality and service quality by femtocells offers a natural opportunity for them to be deployed in vehicles. However, resource allocation with mobile femtocells becomes challenging due to the dynamic interference patterns as the mobile femtocells move. In this paper, we introduce the problem of allocating resources in a cellular network with mobile femtocells. We consider two types of femtocells in the scenario, a) fixed femtocells (deployed in stationary location e.g tra...

  6. Analytical Performance Evaluation of Various Frequency Reuse and Scheduling Schemes in Cellular OFDMA Networks

    Maqbool, Masood; Godlewski, Philippe; Coupechoux, Marceau; Kélif, Jean-Marc


    In this paper, we present an analytical solution to carry out performance analysis of various frequency reuse schemes in an OFDMA based cellular network. We study the performance in downlink in terms of signal to interference (SIR) ratio and total cell data rate. The latter is analyzed while keeping in view three different scheduling schemes: equal data rate, equal bandwidth and opportunist. Analytical models are proposed for integer frequency reuse (IFR), fractional frequency reuse (FFR) and...

  7. On Power and Load Coupling in Cellular Networks for Energy Optimization

    Ho, Chin Keong; Yuan, Di; Lei, Lei; Sun, Sumei


    We consider the problem of minimization of sum transmission energy in cellular networks where coupling occurs between cells due to mutual interference. The coupling relation is characterized by the signal-to-interference-and-noise-ratio (SINR) coupling model. Both cell load and transmission power, where cell load measures the average level of resource usage in the cell, interact via the coupling model. The coupling is implicitly characterized with load and power as the variables of interest u...

  8. Mobile Agents in Wireless LAN and Cellular Data Networks

    R. B. Patel


    Full Text Available Advancing technology in wireless communication offers users anytime, anywhere access to information and network resources without restricting them to the fixed network infrastructure. Mobile computing represents a shift in the distributed systems paradigm. The potential of decoupled and disconnected operation, location-dependent computation and communication and powerful portable computing devices gives rise to opportunities for new patterns of distributed computation that require a revised view of distributed systems. Mobile environment brings different challenges to users and service providers when compared to fixed, wired networks. Mobility brings uncertainties, as well as opportunities to provide new services and supplementary information to users in the locations where they find themselves. A mobile user is one who, on occasion, disconnects from his/her home network to change location and then reconnects, possibly using a different access technology. A necessary feature of mobility management is the ability to continue to provide system and network services to mobile users seamlessly, regardless of their location and the form of their connection. In general, most application software, operating systems and network infrastructures are intended for more conventional environments and so the mobile user has great difficulty in exploiting the computational infrastructure as fully as he/she might. The Internet Roaming solution for corporate wireless data users integrates mobile networking across private wireless local area networks (WLANs, public WLANs and cellular data networks. In this study we have developed an infrastructure using mobile agent for integrating the Wireless LAN and cellular data called Internet Roaming System (IRS. It is implemented on PMADE mobile agent system developed at IIT Roorkee.

  9. Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network

    Overeem, Aart; Leijnse, Hidde; Uijlenhoet, Remko


    Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language "R") is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.

  10. Signal Propagation in Cortical Networks: A Digital Signal Processing Approach

    Rodrigues, Francisco A.


    This work reports a digital signal processing approach to representing and modeling transmission and combination of signals in cortical networks. The signal dynamics is modeled in terms of diffusion, which allows the information processing undergone between any pair of nodes to be fully characterized in terms of a finite impulse response (FIR) filter. Diffusion without and with time decay are investigated. All filters underlying the cat and macaque cortical organization are found to be of l...

  11. Organization of signal flow in directed networks

    Confining an answer to the question of whether and how the coherent operation of network elements is determined by the network structure is the topic of our work. We map the structure of signal flow in directed networks by analysing the degree of edge convergence and the overlap between the in- and output sets of an edge. Definitions of convergence degree and overlap are based on the shortest paths, thus they encapsulate global network properties. Using the defining notions of convergence degree and overlapping set we clarify the meaning of network causality and demonstrate the crucial role of chordless circles. In real-world networks the flow representation distinguishes nodes according to their signal transmitting, processing and control properties. The analysis of real-world networks in terms of flow representation was in accordance with the known functional properties of the network nodes. It is shown that nodes with different signal processing, transmitting and control properties are randomly connected at the global scale, while local connectivity patterns depart from randomness. The grouping of network nodes according to their signal flow properties was unrelated to the network's community structure. We present evidence that the signal flow properties of small-world-like, real-world networks cannot be reconstructed by algorithms used to generate small-world networks. Convergence degree values were calculated for regular oriented trees, and the probability density function for networks grown with the preferential attachment mechanism. For Erdos–Rényi graphs we calculated the probability density function of both convergence degrees and overlaps

  12. Integration of Neural Networks and Cellular Automata for Urban Planning

    Anthony Gar-on Yeh; LI Xia


    This paper presents a new type of cellular automata (CA) model for the simulation of alternative land development using neural networks for urban planning. CA models can be regarded as a planning tool because they can generate alternative urban growth. Alternative development patterns can be formed by using different sets of parameter values in CA simulation. A critical issue is how to define parameter values for realistic and idealized simulation. This paper demonstrates that neural networks can simplify CA models but generate more plausible results. The simulation is based on a simple three-layer network with an output neuron to generate conversion probability. No transition rules are required for the simulation. Parameter values are automatically obtained from the training of network by using satellite remote sensing data. Original training data can be assessed and modified according to planning objectives. Alternative urban patterns can be easily formulated by using the modified training data sets rather than changing the model.

  13. Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

    Jagyasi Bhushan


    Full Text Available Abstract Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN. DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

  14. Distributed Velocity-Dependent Protocol for Multihop Cellular Sensor Networks

    Deepthi Chander


    Full Text Available Cell phones are embedded with sensors form a Cellular Sensor Network which can be used to localize a moving event. The inherent mobility of the application and of the cell phone users warrants distributed structure-free data aggregation and on-the-fly routing. We propose a Distributed Velocity-Dependent (DVD protocol to localize a moving event using a Multihop Cellular Sensor Network (MCSN. DVD is based on a novel form of connectivity determined by the waiting time of nodes for a Random Waypoint (RWP distribution of cell phone users. This paper analyzes the time-stationary and spatial distribution of the proposed waiting time to explain the superior event localization and delay performances of DVD over the existing Randomized Waiting (RW protocol. A sensitivity analysis is also performed to compare the performance of DVD with RW and the existing Centralized approach.

  15. A Fluid Model for Performance Analysis in Cellular Networks

    Coupechoux Marceau


    Full Text Available We propose a new framework to study the performance of cellular networks using a fluid model and we derive from this model analytical formulas for interference, outage probability, and spatial outage probability. The key idea of the fluid model is to consider the discrete base station (BS entities as a continuum of transmitters that are spatially distributed in the network. This model allows us to obtain simple analytical expressions to reveal main characteristics of the network. In this paper, we focus on the downlink other-cell interference factor (OCIF, which is defined for a given user as the ratio of its outer cell received power to its inner cell received power. A closed-form formula of the OCIF is provided in this paper. From this formula, we are able to obtain the global outage probability as well as the spatial outage probability, which depends on the location of a mobile station (MS initiating a new call. Our analytical results are compared to Monte Carlo simulations performed in a traditional hexagonal network. Furthermore, we demonstrate an application of the outage probability related to cell breathing and densification of cellular networks.

  16. Neural networks and cellular automata in experimental high energy physics

    Within the past few years, two novel computing techniques, cellular automata and neural networks, have shown considerable promise in the solution of problems of a very high degree of complexity, such as turbulent fluid flow, image processing, and pattern recognition. Many of the problems faced in experimental high energy physics are also of this nature. Track reconstruction in wire chambers and cluster finding in cellular calorimeters, for instance, involve pattern recognition and high combinatorial complexity since many combinations of hits or cells must be considered in order to arrive at the final tracks or clusters. Here we examine in what way connective network methods can be applied to some of the problems of experimental high physics. It is found that such problems as track and cluster finding adapt naturally to these approaches. When large scale hardwired connective networks become available, it will be possible to realize solutions to such problems in a fraction of the time required by traditional methods. For certain types of problems, faster solutions are already possible using model networks implemented on vector or other massively parallel machines. It should also be possible, using existing technology, to build simplified networks that will allow detailed reconstructed event information to be used in fast trigger decisions

  17. Ion beam analysis based on cellular nonlinear networks

    Senger, V.; R. Tetzlaff; H. Reichau; Ratzinger, U.


    The development of a non- destructive measurement method for ion beam parameters has been treated in various projects. Although results are promising, the high complexity of beam dynamics has made it impossible to implement a real time process control up to now. In this paper we will propose analysing methods based on the dynamics of Cellular Nonlinear Networks (CNN) that can be implemented on pixel parallel CNN based architectures and yield satisfying results even at low re...

  18. Traffic Convexity Aware Cellular Networks: A Vehicular Heavy User Perspective

    Shim, Taehyoung; Park, Jihong; Ko, Seung-Woo; Kim, Seong-Lyun; Lee, Beom Hee; Choi, Jin Gu


    Rampant mobile traffic increase in modern cellular networks is mostly caused by large-sized multimedia contents. Recent advancements in smart devices as well as radio access technologies promote the consumption of bulky content, even for people in moving vehicles, referred to as vehicular heavy users. In this article the emergence of vehicular heavy user traffic is observed by field experiments conducted in 2012 and 2015 in Seoul, Korea. The experiments reveal that such traffic is becoming do...

  19. Ion beam analysis based on cellular nonlinear networks

    Senger, V.; Tetzlaff, R.; Reichau, H.; Ratzinger, U.


    The development of a non- destructive measurement method for ion beam parameters has been treated in various projects. Although results are promising, the high complexity of beam dynamics has made it impossible to implement a real time process control up to now. In this paper we will propose analysing methods based on the dynamics of Cellular Nonlinear Networks (CNN) that can be implemented on pixel parallel CNN based architectures and yield satisfying results even at low resolutions.

  20. Application of neural networks and cellular automata to calorimetric problems

    Brenton, V.; Fonvieille, H.; Guicheney, C.; Jousset, J.; Roblin, Y.; Tamin, F.; Grenier, P.


    Computing techniques based on parallel processing have been used to treat the information from the electromagnetic calorimeters in SLAC experiments E142/E143. Cluster finding and separation of overlapping showers are performed by a cellular automaton, pion and electron identification is done by using a multilayered neural network. Both applications are presented and their resulting performances are shown to be improved compared to more standard approaches. (author). 9 refs.; Submitted to Nuclear Instruments and Methods (NL).

  1. Cellular Neural Networks for NP-Hard Optimization

    Mária Ercsey-Ravasz; Tamás Roska; Zoltán Néda


    Nowadays, Cellular Neural Networks (CNN) are practically implemented in parallel, analog computers, showing a fast developing trend. Physicist must be aware that such computers are appropriate for solving in an elegant manner practically important problems, which are extremely slow on the classical digital architecture. Here, CNN is used for solving NP-hard optimization problems on lattices. It is proved, that a CNN in which the parameters of all cells can be separately controlled, is the ana...

  2. Hybrid Spectral Efficient Cellular Network Deployment to Reduce RF Pollution

    Katiyar, Sumit; K. Jain, R.; K. Agrawal, N.


    As the mobile telecommunication systems are growing tremendously all over the world, the numbers of handheld and base stations are also rapidly growing and it became very popular to see these base stations distributed everywhere in the neighborhood and on roof tops which has caused a considerable amount of panic to the public in Palestine concerning wither the radiated electromagnetic fields from these base stations may cause any health effect or hazard. Recently UP High Court in India ordered for removal of BTS towers from residential area, it has created panic among cellular communication network designers too. Green cellular networks could be a solution for the above problem. This paper deals with green cellular networks with the help of multi-layer overlaid hierarchical structure (macro / micro / pico / femto cells). Macrocell for area coverage, micro for pedestrian and a slow moving traffic while pico for indoor use and femto for individual high capacity users. This could be the answer of the problem of energy conservation and enhancement of spectral density also.

  3. Dynamic Topology Re-Configuration in Multihop Cellular Networks Using Sequential Genetic Algorithm

    B.Shantha Kumari; Mr. Mohammed Ali Shaik Asst. Prof


    Cellular communications has experienced explosive growth in the past two decades. Today millions of people around the world use cellular phones. Cellular phones allow a person to make or receive a call from almost anywhere. Likewise, a person is allowed to continue the phone conversation while on the move. Cellular communications is supported by an infrastructure called a cellular network, which integrates cellular phones into the public switched telephone network. The cellula...

  4. Signal processing devices and networks

    Graveline, S. W.


    According to an axiom employed with respect to electronic warfare (EW) behavior, system effectiveness increases directly with the amount of information recovered from an intercepted signal. The evolution in EW signal processing capability has proceeded accordingly. After an initiation of EW systems as broadband receivers, the most significant advance was related to the development of digital instantaneous frequency measurement (DIFM) devices. The use of such devices provides significant improvements regarding signal identification and RF measurement to within a few MHz. An even more accurate processing device, the digital RF memory (DRFM), allows frequency characterization to within a few Hz. This invention was made in response to the need to process coherent pulse signals. Attention is given to the generic EW system, the modern EW system, and the generic receiver function for a modern EW system showing typical output signals.

  5. Model calibration and uncertainty analysis in signaling networks.

    Heinemann, Tim; Raue, Andreas


    For a long time the biggest challenges in modeling cellular signal transduction networks has been the inference of crucial pathway components and the qualitative description of their interactions. As a result of the emergence of powerful high-throughput experiments, it is now possible to measure data of high temporal and spatial resolution and to analyze signaling dynamics quantitatively. In addition, this increase of high-quality data is the basis for a better understanding of model limitations and their influence on the predictive power of models. We review established approaches in signal transduction network modeling with a focus on ordinary differential equation models as well as related developments in model calibration. As central aspects of the calibration process we discuss possibilities of model adaptation based on data-driven parameter optimization and the concomitant objective of reducing model uncertainties. PMID:27085224

  6. Modeling and Performance Analyses of Hybrid Cellular and Broadcasting Networks

    Peter Unger


    Full Text Available Mobile communication services are getting more and more important and, in particular, multimedia services have attracted the interest of the users. Mobile TV is one of the most demanded candidates. Powerful and efficient communication systems are needed, which provide high capacities, especially at the downlink. Furthermore, interactivity is essential for supporting the user needs and to extend the service offering. As one possible solution to meet the mentioned requirements, we consider the combination of the cellular network UMTS and the mobile broadcast network DVB-H, which form a hybrid network. We investigate the performance of hybrid networks and develop a system model, which describes the hybrid network and the load switching between both networks. One of the contributions is the definition of the switching bound concept, which represents an efficient tool to assess the necessity and the feasibility of hybrid networks and the amount of load switching. The performance indicators cell load and grade of service are analyzed by using theoretical and realistic scenarios.

  7. Topological Decoupled Group Key Management for Cellular Networks

    Jorge E. Ramirez


    Full Text Available Problem statement: The continuous increasing capacity of the cellular networks motivates the development of multiparty applications, such as interactive mobile TV and mobile social networks. For these environments, security group services are required. A practical way to provide security services is by using cryptographic methods. However, the key management needed for these methods, which considers a dynamic group membership, introduces a high communication and storage overheads. Approach: In this study we propose an efficient group key management scheme suitable for cellular networks. Results: Our scheme reduces the number of keys to be transmitted and to be stored at a mobile host in the presence of membership changes. The scheme is based on a two tier structure to organize the cells in areas and the mobile hosts in clusters within an area. The main objective of the two tier structure is to dissociate, in an advantageous manner, the mobile hosts’ distribution from the topological network. Conclusion: Our approach offers security services to a large number of mobile hosts by using lower cryptographic resources, thus providing us a more efficient key updating process.

  8. Signalling in voice over IP Networks

    Moreno, José Ignacio; Soto, Ignacio; Larrabeiti, David


    Voice signalling protocols have evolved, keeping with the prevalent move from circuit to packet switched networks. Standardization bodies have provided solutions for carrying voice traffic over packet networks while the main manufacturers are already providing products in workgroup, enterprise, or operator portfolio. This trend will accrue in next years due to the evolution of UMTS mobile networks to an “all-IP” environment. In this paper we present the various architectures that are proposed...

  9. Effects of multiple enzyme–substrate interactions in basic units of cellular signal processing

    Covalent modification cycles are a ubiquitous feature of cellular signalling networks. In these systems, the interaction of an active enzyme with the unmodified form of its substrate is essential for signalling to occur. However, this interaction is not necessarily the only enzyme–substrate interaction possible. In this paper, we analyse the behaviour of a basic model of signalling in which additional, non-essential enzyme–substrate interactions are possible. These interactions include those between the inactive form of an enzyme and its substrate, and between the active form of an enzyme and its product. We find that these additional interactions can result in increased sensitivity and biphasic responses, respectively. The dynamics of the responses are also significantly altered by the presence of additional interactions. Finally, we evaluate the consequences of these interactions in two variations of our basic model, involving double modification of substrate and scaffold-mediated signalling, respectively. We conclude that the molecular details of protein–protein interactions are important in determining the signalling properties of enzymatic signalling pathways. (paper)

  10. Reverse Engineering Cellular Networks with Information Theoretic Methods

    Julio R. Banga


    Full Text Available Building mathematical models of cellular networks lies at the core of systems biology. It involves, among other tasks, the reconstruction of the structure of interactions between molecular components, which is known as network inference or reverse engineering. Information theory can help in the goal of extracting as much information as possible from the available data. A large number of methods founded on these concepts have been proposed in the literature, not only in biology journals, but in a wide range of areas. Their critical comparison is difficult due to the different focuses and the adoption of different terminologies. Here we attempt to review some of the existing information theoretic methodologies for network inference, and clarify their differences. While some of these methods have achieved notable success, many challenges remain, among which we can mention dealing with incomplete measurements, noisy data, counterintuitive behaviour emerging from nonlinear relations or feedback loops, and computational burden of dealing with large data sets.

  11. Assessing the weather monitoring capabilities of cellular microwave link networks

    Fencl, Martin; Vrzba, Miroslav; Rieckermann, Jörg; Bareš, Vojtěch


    Using of microwave links for rainfall monitoring was suggested already by (Atlas and Ulbrich, 1977). However, this technique attracted broader attention of scientific community only in the recent decade, with the extensive growth of cellular microwave link (CML) networks, which form the backbone of today's cellular telecommunication infrastructure. Several studies have already shown that CMLs can be conveniently used as weather sensors and have potential to provide near-ground path-integrated observations of rainfall but also humidity or fog. However, although research is still focusing on algorithms to improve the weather sensing capabilities (Fencl et al., 2015), it is not clear how to convince cellular operators to provide the power levels of their network. One step in this direction is to show in which regions or municipalities the networks are sufficiently dense to provide/develop good services. In this contribution we suggest a standardized approach to evaluate CML networks in terms of rainfall observation and to identify suitable regions for CML rainfall monitoring. We estimate precision of single CML based on its sensitivity to rainfall, i.e. as a function of frequency, polarization and path length. Capability of a network to capture rainfall spatial patterns is estimated from the CML coverage and path lengths considering that single CML provides path-integrated rain rates. We also search for suitable predictors for regions where no network topologies are available. We test our approach on several European networks and discuss the results. Our results show that CMLs are very dense in urban areas (> 1 CML/km2), but less in rural areas (evaluate the suitability of their region for CML weather monitoring and estimate the credible spatial-resolution of a CML weather monitoring product. Atlas, D. and Ulbrich, C. W. (1977) Path- and Area-Integrated Rainfall Measurement by Microwave Attenuation in the 1-3 cm Band. Journal of Applied Meteorology, 16(12), 1322

  12. Energy Efficient Resource Allocation for Phantom Cellular Networks

    Abdelhady, Amr


    Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a

  13. Location Estimation and Mobility Prediction Using Neuro-fuzzy Networks In Cellular Networks

    Maryam Borna; Mohammad Soleimani


    In this paper an approach is proposed for location estimation, tracking and mobility prediction in cellular networks in dense urban areas using neural and neuro-fuzzy networks. In urban areas with high buildings, due to the effects of multipath fading and Non-Line-of-Sight conditions, the accuracy of positioning methods based on direction finding and ranging degrades significantly. Also in these areas, due to high user traffic there's a need for network resources management. Knowing the next ...

  14. Study and Simulation of Traffic Behavior in Cellular Network

    Madhup, D. K.; Shrestha, C. L.; Sharma, R. K.


    Cellular radio systems accommodate a large number of users with a limited radio spectrum. The concept of trunking allows a large number of users to share the relatively small number of channels in a cell by providing access to each user, on demand, from a pool of available channels. Traffic engineering deals with provisioning of communication circuits in a given area for a number of subscribers with a required grade of service. Traffic in any cell depends upon the number of users, the average request rate and average call duration. Certain number of channels is required for the required GOS. To design an optimum capacity cellular system, traffic behavior on that system is important. The number of channel required can be estimated by using Erlang formula and Erlang table. Erlang table is not always useful to calculate the probability of blocking in various complex scenarios such as channel borrowing strategies. When the total number of channel available in a given cell are divided to serve partly for newly generated calls and partly for handover calls, and if they use dynamic channel assignment strategies like channel borrowing, then the probability of blocking can't be calculated from Erlang table. Simulation model of the behavior help us to determine the blocking and the channel utilization while using various channel assignment strategies. The title "Study and Simulation of Traffic Behavior in Cellular Network" entail the study of the blocking probability of traffic in cellular network for static channel assignment strategies and dynamic channel borrowing strategies through MATLAB programming language and graphic user interface (GUI). The result shows that the dynamic scheme can perform better than static maximizing the overall utilization of the circuits and minimizing the overall blocking.

  15. Stochastic effects as a force to increase the complexity of signaling networks

    Kuwahara, Hiroyuki


    Cellular signaling networks are complex and appear to include many nonfunctional elements. Recently, it was suggested that nonfunctional interactions of proteins cause signaling noise, which, perhaps, shapes the signal transduction mechanism. However, the conditions under which molecular noise influences cellular information processing remain unclear. Here, we explore a large number of simple biological models of varying network sizes to understand the architectural conditions under which the interactions of signaling proteins can exhibit specific stochastic effects - called deviant effects - in which the average behavior of a biological system is substantially altered in the presence of molecular noise. We find that a small fraction of these networks does exhibit deviant effects and shares a common architectural feature whereas most of the networks show only insignificant levels of deviations. Interestingly, addition of seemingly unimportant interactions into protein networks gives rise to deviant effects.

  16. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    Coyle, Scott M


    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems. PMID:27128855

  17. Emulating fire propagation by using cellular nonlinear networks

    Buscarino, A.; Fortuna, L.; Frasca, M.; Xibilia, M. G.


    In this paper a new approach based on Cellular Nonlinear Networks (CNNs) for modeling the diffusion of forest fires is presented. Based on a model relying on an hyperbolic reaction-diffusion equation, the proposed approach exploits the peculiarity of CNNs allowing the investigation of different types of forest fires, also considering specific morphological characteristics of the terrain and the presence of external perturbations like wind flows. Results show the emergence of particular phenomena really observed in wildfires, allowing to assess the validity of the approach.

  18. Controllability of time-varying cellular neural networks

    Wadie Aziz


    Full Text Available In this work, we consider the model of Cellular Neural Network (CNN introduced by Chua and Yang in 1988, but with the cloning templates $omega$-periodic in time. By imposing periodic boundary conditions the matrices involved in the system become circulant and $omega$-periodic. We show some results on the controllability of the linear model using a Theorem by Brunovsky for the case of linear and $omega$-periodic system. Also we use this approach in image detection, specifically foreground, background and contours of figures in different scales of grey.

  19. Edge Detection in Satellite Image Using Cellular Neural Network

    Osama Basil Gazi


    Full Text Available The present paper proposes a novel approach for edge detection in satellite images based on cellular neural networks. CNN based edge detector in used conjunction with image enhancement and noise removal techniques, in order to deliver accurate edge detection results, compared with state of the art approaches. Thus, considering the obtained results, a comparison with optimal Canny edge detector is performed. The proposed image processing chain deliver more details regarding edges than canny edge detector. The proposed method aims to preserve salient information, due to its importance in all satellite image processing applications.

  20. GPM ground validation via commercial cellular networks: an exploratory approach

    Rios Gaona, Manuel Felipe; Overeem, Aart; Leijnse, Hidde; Brasjen, Noud; Uijlenhoet, Remko


    The suitability of commercial microwave link networks for ground validation of GPM (Global Precipitation Measurement) data is evaluated here. Two state-of-the-art rainfall products are compared over the land surface of the Netherlands for a period of 7 months, i.e., rainfall maps from commercial cellular communication networks and Integrated Multi-satellite Retrievals for GPM (IMERG). Commercial microwave link networks are nowadays the core component in telecommunications worldwide. Rainfall rates can be retrieved from measurements of attenuation between transmitting and receiving antennas. If adequately set up, these networks enable rainfall monitoring tens of meters above the ground at high spatiotemporal resolutions (temporal sampling of seconds to tens of minutes, and spatial sampling of hundreds of meters to tens of kilometers). The GPM mission is the successor of TRMM (Tropical Rainfall Measurement Mission). For two years now, IMERG offers rainfall estimates across the globe (180°W - 180°E and 60°N - 60°S) at spatiotemporal resolutions of 0.1° x 0.1° every 30 min. These two data sets are compared against a Dutch gauge-adjusted radar data set, considered to be the ground truth given its accuracy, spatiotemporal resolution and availability. The suitability of microwave link networks in satellite rainfall evaluation is of special interest, given the independent character of this technique, its high spatiotemporal resolutions and availability. These are valuable assets for water management and modeling of floods, landslides, and weather extremes; especially in places where rain gauge networks are scarce or poorly maintained, or where weather radar networks are too expensive to acquire and/or maintain.

  1. Cellular telephone-based wide-area radiation detection network

    Craig, William W.; Labov, Simon E.


    A network of radiation detection instruments, each having a small solid state radiation sensor module integrated into a cellular phone for providing radiation detection data and analysis directly to a user. The sensor module includes a solid-state crystal bonded to an ASIC readout providing a low cost, low power, light weight compact instrument to detect and measure radiation energies in the local ambient radiation field. In particular, the photon energy, time of event, and location of the detection instrument at the time of detection is recorded for real time transmission to a central data collection/analysis system. The collected data from the entire network of radiation detection instruments are combined by intelligent correlation/analysis algorithms which map the background radiation and detect, identify and track radiation anomalies in the region.

  2. Joint Uplink and Downlink Relay Selection in Cooperative Cellular Networks

    Yang, Wei; Wu, Gang; Wang, Haifeng; Wang, Ying


    We consider relay selection technique in a cooperative cellular network where user terminals act as mobile relays to help the communications between base station (BS) and mobile station (MS). A novel relay selection scheme, called Joint Uplink and Downlink Relay Selection (JUDRS), is proposed in this paper. Specifically, we generalize JUDRS in two key aspects: (i) relay is selected jointly for uplink and downlink, so that the relay selection overhead can be reduced, and (ii) we consider to minimize the weighted total energy consumption of MS, relay and BS by taking into account channel quality and traffic load condition of uplink and downlink. Information theoretic analysis of the diversity-multiplexing tradeoff demonstrates that the proposed scheme achieves full spatial diversity in the quantity of cooperating terminals in this network. And numerical results are provided to further confirm a significant energy efficiency gain of the proposed algorithm comparing to the previous best worse channel selection an...

  3. Coping with handover effects in video streaming over cellular networks



    The 3rd generation partnership project (3GPP) has defined the protocols and codecs for implementing media streaming services over packet-switched 3G mobile networks. The specification is based on IETF RFCs on audio/video transport.It also adds new features to achieve better adaptation to the mobile network environment. In this paper, we propose an algorithm for handover detection and fast buffer refill that is based on the existing feedback and signaling mechanisms. The proposed algorithm refills the receiver buffer at a faster pace during a limited time frame after a hard handover is detected in order to achieve higher video quality.

  4. Area Spectral and Energy Efficiency Analysis of Cellular Networks with Cell DTX

    Chang, Peiliang; Miao, Guowang


    Cell discontinuous transmission (DTX) has been proposed as an effective solution to reduce energy consumption of cellular networks. In this paper, we investigate the impact of network traffic load on area spectral efficiency (ASE) and energy efficiency (EE) of cellular networks with cell DTX. Closedform expressions of ASE and EE as functions of traffic load for cellular networks with cell DTX are derived. It is shown that ASE increases monotonically in traffic load, while EE depends on the po...

  5. Trend Analysis of Key Cellular Network Quality Performance Metrics

    Patrick O. Olabisi


    Full Text Available Assessment and analysis of key quality performance indicators of a cellular network is better done over a period of time like days or months in order to have a proper perspective of the reliability of performance of the network or of its base stations (BSs as had been done in this work than to do so over hourly periods of the day or in isolated manner. This normally helps to consider investigating various social and environmental factors that may be affecting the functionality, reliability, and capacity of the network systems. The effect on one key performance indicator is proved to be more likely to affect all other performance indicators of the network or its base stations as was discovered for majorly the fourth day of our measurements. With the highest total traffic occurring on the fourth day other indicators were also worsen, thereby affecting the service quality experienced by the users. KPIs considered were Total Traffic, CSSR, CDR, HoSR, SDCCH Cong, SDR, TCH Cong and TCHA BH.

  6. Regulatory Roles of Metabolites in Cell Signaling Networks

    Feng Li; Wei Xu; Shimin Zhao


    Mounting evidence suggests that cellular metabolites,in addition to being sources of fuel and macromolecular substrates,are actively involved in signaling and epigenetic regulation.Many metabolites,such as cyclic AMP,which regulates phosphorylation/dephosphorylation,have been identified to modulate DNA and histone methylation and protein stability.Metabolite-driven cellular regulation occurs through two distinct mechanisms:proteins allosterically bind or serve as substrates for protein signaling pathways,and metabolites covalently modify proteins to regulate their functions.Such novel protein metabolites include fumarate,succinyl-CoA,propionyl-CoA,butyryl-CoA and crontonyl-CoA.Other metabolites,including α-ketoglutarate,succinate and fumarate,regulate epigenetic processes and cell signaling via protein binding.Here,we summarize recent progress in metabolite-derived post-translational protein modification and metabolite-binding associated signaling regulation.Uncovering metabolites upstream of cell signaling and epigenetic networks permits the linkage of metabolic disorders and human diseases,and suggests that metabolite modulation may be a strategy for innovative therapeutics and disease prevention techniques.

  7. Neural networks for intelligent signal processing

    Zaknich, Anthony


    This book provides a thorough theoretical and practical introduction to the application of neural networks to pattern recognition and intelligent signal processing. It has been tested on students, unfamiliar with neural networks, who were able to pick up enough details to successfully complete their masters or final year undergraduate projects. The text also presents a comprehensive treatment of a class of neural networks called common bandwidth spherical basis function NNs, including the probabilistic NN, the modified probabilistic NN and the general regression NN. Contents: A Brief Historica

  8. Impact of Channel Partitioning and Relay Placement on Resource Allocation in OFDMA Cellular Networks

    Sultan F. Meko


    Full Text Available Tremendous growth in the demand for wireless applications such as streaming audio/videos, Skype and video games require high data rate irrespective of user’s location in the cellular network. However, the Quality of Service (QoS of users degrades at the cell boundary. Relay enhanced multi-hop cellular network is one of the cost effective solution to improve the performance of cell edge users. Optimal deployment of Fixed Relay Nodes (FRNs is essential to satisfy the QoS requirement of edge users. We propose new schemes for channel partitioning and FRN placement in cellular networks. Path-loss, Signal to Interference and Noise Ratio (SINR experienced by users, and effects of shadowing have been considered. The analysis gives more emphasis on the cell-edge users (worst case scenario. The results show that these schemes achieve higher system performance in terms of spectral efficiency and also increase the user data rate at the cell edge.

  9. Dynamic Topology Re-Configuration in Multihop Cellular Networks Using Sequential Genetic Algorithm

    B.Shantha Kumari


    Full Text Available Cellular communications has experienced explosive growth in the past two decades. Today millions of people around the world use cellular phones. Cellular phones allow a person to make or receive a call from almost anywhere. Likewise, a person is allowed to continue the phone conversation while on the move. Cellular communications is supported by an infrastructure called a cellular network, which integrates cellular phones into the public switched telephone network. The cellular network has gone through three generations.The first generation of cellular networks is analog in nature. To accommodate more cellular phone subscribers, digital TDMA (time division multiple access and CDMA (code division multiple access technologies are used in the second generation (2G to increase the network capacity. With digital technologies, digitized voice can be coded and encrypted. Therefore, the 2G cellular network is also more secure. The third generation (3G integrates cellular phones into the Internet world by providing highspeed packet-switching data transmission in addition to circuit-switching voice transmission. The 3G cellular networks have been deployed in some parts of Asia, Europe, and the United States since 2002 and will be widely deployed in the coming years. The high increase in traffic and data rate for future generations of mobile communication systems, with simultaneous requirement for reduced power consumption, makes Multihop Cellular Networks (MCNs an attractive technology. To exploit the potentials of MCNs a new network paradigm is proposed in this paper. In addition, a novel sequential genetic algorithm (SGA is proposed as a heuristic approximation to reconfigure the optimum relaying topology as the network traffic changes. Network coding is used to combine the uplink and downlink transmissions, and incorporate it into the optimum bidirectional relaying with ICI awareness. Numerical results have shown that the algorithms suggested in this

  10. Feedback Loops Shape Cellular Signals in Space and Time

    Brandman, Onn; Meyer, Tobias


    Positive and negative feedback loops are common regulatory elements in biological signaling systems. We discuss core feedback motifs that have distinct roles in shaping signaling responses in space and time. We also discuss approaches to experimentally investigate feedback loops in signaling systems.

  11. Collaborative Multi-Layer Network Coding in Hybrid Cellular Cognitive Radio Networks

    Moubayed, Abdallah


    In this paper, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other\\'s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network\\'s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network\\'s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. © 2015 IEEE.


    Falade A. J


    Full Text Available Cellular wireless systems like GSM suffer from congestion resulting in overall system degradation and poor service delivery. When the traffic demand in a geographical area is high, the input traffic rate will exceed thecapacity of the output lines. This work focused on homogenous wireless network (the network traffic and resource dimensioning that are statistically identical such that the network performance evaluation can be reduced to a system with single cell and a single traffic type. Such system can employa queuing model to evaluate the performance metric of a cell in terms of blocking probability. Five congestion control models were compared in the work to ascertain their peculiarities, they are Erlang B, Erlang C, Engset (cleared, Engset (buffered, and Bernoulli. To analyze the system, an aggregate onedimensional Markov chain wasderived, such that it describes a call arrival process under the assumption that it is Poisson distributed. The models were simulated and their results show varying performances, however the Bernoulli model (Pb5 tends to show a situation that allows more users access to the system and the congestion level remain unaffected despite increase in the number of users and the offered traffic into the system.

  13. Dynamic Time-domain Duplexing for Self-backhauled Millimeter Wave Cellular Networks

    Ford, Russell; Gomez-Cuba, Felipe; Mezzavilla, Marco; Rangan, Sundeep


    Millimeter wave (mmW) bands between 30 and 300 GHz have attracted considerable attention for next-generation cellular networks due to vast quantities of available spectrum and the possibility of very high-dimensional antenna ar-rays. However, a key issue in these systems is range: mmW signals are extremely vulnerable to shadowing and poor high-frequency propagation. Multi-hop relaying is therefore a natural technology for such systems to improve cell range and cell edge rates without the addi...

  14. A Stream Control Transmission Protocol Based OAM System of 3G Cellular Network


    OAM (Operations, Administration and Maintenance) system is a very important component of 3G cellular network. In order to acquire overall management, fast response and steady operation, an SCTP (Stream Control Transmission Protocol) based OAM, i. e. , SOAM system was proposed. SOAM implements new characters of SCTP such as multi-stream, enforced SACK and heartbeat mechanism on its transport layer. These characters help SOAM decrease the message transmission delay and accelerate the link failure detection. Besides, a new component named SOAM agent was introduced to improve the operation efficiency of SOAM. The experimental results prove the proposed SOAM system achieves better performance on signaling transmission compared with conventional TCP based OAM system.

  15. Distributed SIR-Aware Opportunistic Access Control for D2D Underlaid Cellular Networks

    Chen, Zheng; Kountouris, Marios


    In this paper, we propose a distributed interference and channel-aware opportunistic access control technique for D2D underlaid cellular networks, in which each potential D2D link is active whenever its estimated signal-to-interference ratio (SIR) is above a predetermined threshold so as to maximize the D2D area spectral efficiency. The objective of our SIR-aware opportunistic access scheme is to provide sufficient coverage probability and to increase the aggregate rate of D2D links by harnes...

  16. Topological basis of signal integration in the transcriptional-regulatory network of the yeast, Saccharomyces cerevisiae

    Chennubhotla Chakra; Wu Chuang; Farkas Illés J; Bahar Ivet; Oltvai Zoltán N


    Abstract Background Signal recognition and information processing is a fundamental cellular function, which in part involves comprehensive transcriptional regulatory (TR) mechanisms carried out in response to complex environmental signals in the context of the cell's own internal state. However, the network topological basis of developing such integrated responses remains poorly understood. Results By studying the TR network of the yeast Saccharomyces cerevisiae we show that an intermediate l...

  17. Regulation of ARE-mRNA Stability by Cellular Signaling

    Damgaard, Christian Kroun; Lykke-Andersen, Jens

    response to different cellular cues they can become either stabilized, allowing expression of a given gene, or further destabilized to silence their expression. These tightly regulated mRNAs include many that encode growth factors, proto-oncogenes, cytokines, and cell cycle regulators. Failure to properly...

  18. Cellular Neural Networks for NP-Hard Optimization

    Mária Ercsey-Ravasz


    Full Text Available A cellular neural/nonlinear network (CNN is used for NP-hard optimization. We prove that a CNN in which the parameters of all cells can be separately controlled is the analog correspondent of a two-dimensional Ising-type (Edwards-Anderson spin-glass system. Using the properties of CNN, we show that one single operation (template always yields a local minimum of the spin-glass energy function. This way, a very fast optimization method, similar to simulated annealing, can be built. Estimating the simulation time needed on CNN-based computers, and comparing it with the time needed on normal digital computers using the simulated annealing algorithm, the results are astonishing. CNN computers could be faster than digital computers already at 10×10 lattice sizes. The local control of the template parameters was already partially realized on some of the hardwares, we think this study could further motivate their development in this direction.

  19. Location Management Technique to Reduce Complexity in Cellular Networks

    C. Selvan


    Full Text Available An important issue in the design of mobile computing is how to manage the location information of mobile nodes in wireless cellular networks. The existing system has two approaches. First approach is spatial quantization technique in which location update takes place only when the mobile terminal move from one location area to other and second approach is temporal quantization in which location update takes place only after a specific time threshold. In this paper, we introduce Intelligent Agent Quantization(IAQ which is based on prediction of movements and distance between node and Base Station Controller(BSC to locate the mobile nodes. The main idea of using IAQ is reduce the update cost considerably with slight increase in paging cost.

  20. Global Network Model based on Earth Grid and Cellular

    Dongqi Lu


    Full Text Available We aim to understand the current health state of the Earth and find how human activities influence it. Based on the theory of Earth’s Grid and Cellular Automata, we define and test a global network model, analyze the mutual interactions and feedbacks of ecosystem, hydrologic circle and atmosphere. In addition, we consult a lot of data to find a benchmark for the “Earth Health Map”, with the ecosystem distribution on it, which can be helpful for making a strategic decision for policy makers and prediction. Our model can be extended to other similar fields. In the end, we discuss the sensitivity of parameters selection, and the superiorities and weaknesses of our model.

  1. Spatio-Temporal Dynamics in Cellular Neural Networks

    Liviu GORAS


    Full Text Available Analog Parallel Architectures like Cellular Neural Networks (CNN’s have been thoroughly studied not only for their potential in high-speed image processing applications but also for their rich and exciting spatio-temporal dynamics. An interesting behavior such architectures can exhibit is spatio-temporal filtering and pattern formation, aspects that will be discussed in this work for a general structure consisting of linear cells locally and homogeneously connected within a specified neighborhood. The results are generalizations of those regarding Turing pattern formation in CNN’s. Using linear cells (or piecewise linear cells working in the central linear part of their characteristic allows the use of the decoupling technique – a powerful technique that gives significant insight into the dynamics of the CNN. The roles of the cell structure as well as that of the connection template are discussed and models for the spatial modes dynamics are made as well.

  2. Cellular Neural Network for Real Time Image Processing

    Since their introduction in 1988, Cellular Nonlinear Networks (CNNs) have found a key role as image processing instruments. Thanks to their structure they are able of processing individual pixels in a parallel way providing fast image processing capabilities that has been applied to a wide range of field among which nuclear fusion. In the last years, indeed, visible and infrared video cameras have become more and more important in tokamak fusion experiments for the twofold aim of understanding the physics and monitoring the safety of the operation. Examining the output of these cameras in real-time can provide significant information for plasma control and safety of the machines. The potentiality of CNNs can be exploited to this aim. To demonstrate the feasibility of the approach, CNN image processing has been applied to several tasks both at the Frascati Tokamak Upgrade (FTU) and the Joint European Torus (JET)

  3. Full-Duplex Communications in Large-Scale Cellular Networks

    AlAmmouri, Ahmad


    In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This thesis presents a tractable framework, based on stochastic geometry, to study FD communications in multi-tier cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that the improved FD rate gains harvested in the downlink (up to 97%) comes at the expense of a significant degradation in the uplink rate (up to 94%). Therefore, we propose a novel fine-grained duplexing scheme, denoted as α-duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the α-duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the α-duplex scheme provides a simultaneous improvement of 28% for the downlink rate and 56% for the uplink rate. We also show that the amount of the overlap can be optimized based on the network design objective. Moreover, backward compatibility is an essential ingredient for the success of new technologies. In the context of in-band FD communication, FD base stations (BSs) should support HD users\\' equipment (UEs) without sacrificing the foreseen FD gains. The results show that FD-UEs are not necessarily required to harvest rate gains from FD-BSs. In particular, the results show that adding FD-UEs to FD-BSs offers a maximum of 5% rate gain over FD-BSs and HD-UEs case, which is a marginal gain compared to the burden required to implement FD transceivers at the UEs\\' side. To this end, we shed light on practical scenarios where HD-UEs operation with FD-BSs outperforms the

  4. AdCell: Ad Allocation in Cellular Networks

    Alaei, Saeed; Liaghat, Vahid; Pei, Dan; Saha, Barna


    With more than four billion usage of cellular phones worldwide, mobile advertising has become an attractive alternative to online advertisements. In this paper, we propose a new targeted advertising policy for Wireless Service Providers (WSPs) via SMS or MMS- namely {\\em AdCell}. In our model, a WSP charges the advertisers for showing their ads. Each advertiser has a valuation for specific types of customers in various times and locations and has a limit on the maximum available budget. Each query is in the form of time and location and is associated with one individual customer. In order to achieve a non-intrusive delivery, only a limited number of ads can be sent to each customer. Recently, new services have been introduced that offer location-based advertising over cellular network that fit in our model (e.g., ShopAlerts by AT&T) . We consider both online and offline version of the AdCell problem and develop approximation algorithms with constant competitive ratio. For the online version, we assume tha...

  5. Segmentation algorithm via Cellular Neural/Nonlinear Network: implementation on Bio-inspired hardware platform

    Karabiber, Fethullah; Vecchio, Pietro; Grassi, Giuseppe


    The Bio-inspired (Bi-i) Cellular Vision System is a computing platform consisting of sensing, array sensing-processing, and digital signal processing. The platform is based on the Cellular Neural/Nonlinear Network (CNN) paradigm. This article presents the implementation of a novel CNN-based segmentation algorithm onto the Bi-i system. Each part of the algorithm, along with the corresponding implementation on the hardware platform, is carefully described through the article. The experimental results, carried out for Foreman and Car-phone video sequences, highlight the feasibility of the approach, which provides a frame rate of about 26 frames/s. Comparisons with existing CNN-based methods show that the conceived approach is more accurate, thus representing a good trade-off between real-time requirements and accuracy.

  6. Signaling pathway networks mined from human pituitary adenoma proteomics data

    Zhan Xianquan


    pituitary control related to gene expression and cellular development, and no canonical toxicity pathways were identified. Conclusions This pathway network analysis demonstrated that mitochondrial dysfunction, oxidative stress, cell-cycle dysregulation, and the MAPK-signaling abnormality are significantly associated with a pituitary adenoma. These pathway-network data provide new insights into the molecular mechanisms of human pituitary adenoma pathogenesis, and new clues for an in-depth investigation of pituitary adenoma and biomarker discovery.

  7. Collaborative Multi-Layer Network Coding For Hybrid Cellular Cognitive Radio Networks

    Moubayed, Abdallah J.


    In this thesis, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other’s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network’s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network’s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. Furthermore, with the use of fractional cooperation, the average recovery overhead is further reduced by around 5% for the primary network and around 10% for the secondary network when a high fractional cooperation probability is used.

  8. Alveologenesis: key cellular players and fibroblast growth factor 10 signaling

    Chao, Cho-Ming; Moiseenko, Alena; Zimmer, Klaus-Peter; Bellusci, Saverio


    Background Alveologenesis is the last stage in lung development and is essential for building the gas-exchanging units called alveoli. Despite intensive lung research, the intricate crosstalk between mesenchymal and epithelial cell lineages during alveologenesis is poorly understood. This crosstalk contributes to the formation of the secondary septae, which are key structures of healthy alveoli. Conclusions A better understanding of the cellular and molecular processes underlying the formatio...

  9. User Association for Load Balancing in Heterogeneous Cellular Networks

    Ye, Qiaoyang; Chen, Yudong; Al-Shalash, Mazin; Caramanis, Constantine; Andrews, Jeffrey G


    For small cell technology to significantly increase the capacity of tower-based cellular networks, mobile users will need to be actively pushed onto the more lightly loaded tiers (corresponding to, e.g., pico and femtocells), even if they offer a lower instantaneous SINR than the macrocell base station (BS). Optimizing a function of the long-term rates for each user requires (in general) a massive utility maximization problem over all the SINRs and BS loads. On the other hand, an actual implementation will likely resort to a simple biasing approach where a BS in tier j is treated as having its SINR multiplied by a factor A_j>=1, which makes it appear more attractive than the heavily-loaded macrocell. This paper bridges the gap between these approaches through several physical relaxations of the network-wide optimal association problem, whose solution is NP hard. We provide a low-complexity distributed algorithm that converges to a near-optimal solution with a theoretical performance guarantee, and we observe ...

  10. The multifaceted roles of the HORMA domain in cellular signaling

    Rosenberg, Scott C.


    The HORMA domain is a multifunctional protein–protein interaction module found in diverse eukaryotic signaling pathways including the spindle assembly checkpoint, numerous DNA recombination/repair pathways, and the initiation of autophagy. In all of these pathways, HORMA domain proteins occupy key signaling junctures and function through the controlled assembly and disassembly of signaling complexes using a stereotypical “safety belt” peptide interaction mechanism. A recent explosion of structural and functional work has shed new light on these proteins, illustrating how strikingly similar structural mechanisms give rise to radically different functional outcomes in each family of HORMA domain proteins. PMID:26598612

  11. Dynamic circadian protein-protein interaction networks predict temporal organization of cellular functions.

    Thomas Wallach


    Full Text Available Essentially all biological processes depend on protein-protein interactions (PPIs. Timing of such interactions is crucial for regulatory function. Although circadian (~24-hour clocks constitute fundamental cellular timing mechanisms regulating important physiological processes, PPI dynamics on this timescale are largely unknown. Here, we identified 109 novel PPIs among circadian clock proteins via a yeast-two-hybrid approach. Among them, the interaction of protein phosphatase 1 and CLOCK/BMAL1 was found to result in BMAL1 destabilization. We constructed a dynamic circadian PPI network predicting the PPI timing using circadian expression data. Systematic circadian phenotyping (RNAi and overexpression suggests a crucial role for components involved in dynamic interactions. Systems analysis of a global dynamic network in liver revealed that interacting proteins are expressed at similar times likely to restrict regulatory interactions to specific phases. Moreover, we predict that circadian PPIs dynamically connect many important cellular processes (signal transduction, cell cycle, etc. contributing to temporal organization of cellular physiology in an unprecedented manner.

  12. Signals for the lysosome: a control center for cellular clearance and energy metabolism

    Settembre, Carmine; Fraldi, Alessandro; Medina, Diego L.; Ballabio, Andrea


    For a long time lysosomes were considered merely to be cellular “incinerators” involved in the degradation and recycling of cellular waste. However, there is now compelling evidence indicating that lysosomes have a much broader function and that they are involved in fundamental processes such as secretion, plasma membrane repair, signaling and energy metabolism. Furthermore, the essential role of lysosomes in the autophagic pathway puts these organelles at the crossroads of several cellular p...

  13. Muscle biopsies off-set normal cellular signaling in surrounding musculature

    Krag, Thomas O; Hauerslev, Simon; Dahlqvist, Julia R;


    Studies of muscle physiology and muscular disorders often require muscle biopsies to answer questions about muscle biology. In this context, we have often wondered if muscle biopsies, especially if performed repeatedly, would affect interpretation of muscle morphology and cellular signaling. We...... hypothesized that muscle morphology and cellular signaling involved in myogenesis/regeneration and protein turnover can be changed by a previous muscle biopsy in close proximity to the area under investigation. Here we report a case where a past biopsy or biopsies affect cellular signaling of the surrounding...... muscle tissue for at least 3 weeks after the biopsy was performed and magnetic resonance imaging suggests that an effect of a biopsy may persist for at least 5 months. Cellular signaling after a biopsy resembles what is seen in severe limb-girdle muscular dystrophy type 2I with respect to protein...

  14. Collaborative multi-layer network coding for cellular cognitive radio networks

    Sorour, Sameh


    In this paper, we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in underlay cellular cognitive radio networks. This scheme allows the collocated primary and cognitive radio base-stations to collaborate with each other, in order to minimize their own and each other\\'s packet recovery overheads, and thus improve their throughput, without any coordination between them. This non-coordinated collaboration is done using a novel multi-layer instantly decodable network coding scheme, which guarantees that each network\\'s help to the other network does not result in any degradation in its own performance. It also does not cause any violation to the primary networks interference thresholds in the same and adjacent cells. Yet, our proposed scheme both guarantees the reduction of the recovery overhead in collocated primary and cognitive radio networks, and allows early recovery of their packets compared to non-collaborative schemes. Simulation results show that a recovery overhead reduction of 15% and 40% can be achieved by our proposed scheme in the primary and cognitive radio networks, respectively, compared to the corresponding non-collaborative scheme. © 2013 IEEE.

  15. Systematic identification of cellular signals reactivating Kaposi sarcoma-associated herpesvirus.

    Fuqu Yu; Harada, Josephine N.; Brown, Helen J.; Hongyu Deng; Moon Jung Song; Ting-Ting Wu; Juran Kato-Stankiewicz; Nelson, Christian G; Jeffrey Vieira; Fuyuhiko Tamanoi; Chanda, Sumit K.; Ren Sun


    The herpesvirus life cycle has two distinct phases: latency and lytic replication. The balance between these two phases is critical for viral pathogenesis. It is believed that cellular signals regulate the switch from latency to lytic replication. To systematically evaluate the cellular signals regulating this reactivation process in Kaposi sarcoma–associated herpesvirus, the effects of 26,000 full-length cDNA expression constructs on viral reactivation were individually assessed in primary e...

  16. Protease-associated cellular networks in malaria parasite Plasmodium falciparum

    Lilburn Timothy G


    Full Text Available Abstract Background Malaria continues to be one of the most severe global infectious diseases, responsible for 1-2 million deaths yearly. The rapid evolution and spread of drug resistance in parasites has led to an urgent need for the development of novel antimalarial targets. Proteases are a group of enzymes that play essential roles in parasite growth and invasion. The possibility of designing specific inhibitors for proteases makes them promising drug targets. Previously, combining a comparative genomics approach and a machine learning approach, we identified the complement of proteases (degradome in the malaria parasite Plasmodium falciparum and its sibling species 123, providing a catalog of targets for functional characterization and rational inhibitor design. Network analysis represents another route to revealing the role of proteins in the biology of parasites and we use this approach here to expand our understanding of the systems involving the proteases of P. falciparum. Results We investigated the roles of proteases in the parasite life cycle by constructing a network using protein-protein association data from the STRING database 4, and analyzing these data, in conjunction with the data from protein-protein interaction assays using the yeast 2-hybrid (Y2H system 5, blood stage microarray experiments 678, proteomics 9101112, literature text mining, and sequence homology analysis. Seventy-seven (77 out of 124 predicted proteases were associated with at least one other protein, constituting 2,431 protein-protein interactions (PPIs. These proteases appear to play diverse roles in metabolism, cell cycle regulation, invasion and infection. Their degrees of connectivity (i.e., connections to other proteins, range from one to 143. The largest protease-associated sub-network is the ubiquitin-proteasome system which is crucial for protein recycling and stress response. Proteases are also implicated in heat shock response, signal peptide

  17. Two-tier cellular random network planning for minimum deployment cost

    Mekikis, Prodromos Vasileios; KARTSAKLI, Elli; Antonopoulos, Angelos; Lalos, Aris S.; Alonso Zárate, Luis Gonzaga; Verikoukis, Christos


    Random dense deployment of heterogeneous networks (HetNets), consisting of macro base stations (BS) and small cells (SC), can provide higher quality of service (QoS) while increasing the energy efficiency of the cellular network. In addition, it is possible to achieve lower deployment cost and, therefore, maximize the benefits for the network providers. In this paper, we propose a novel method to determine the minimum deployment cost of a two-tier heterogeneous cellular network using random d...

  18. DNA-damage response network at the crossroads of cell-cycle checkpoints,cellular senescence and apoptosis

    SCHMITT Estelle; PAQUET Claudie; BEAUCHEMIN Myriam; BERTRAND Richard


    Tissue homeostasis requires a carefully-orchestrated balance between cell proliferation,cellular senescence and cell death.Cells proliferate through a cell cycle that is tightly regulated by cyclin-dependent kinase activities.Cellular senescence is a safeguard program limiting the proliferative competence of cells in living organisms.Apoptosis eliminates unwanted cells by the coordinated activity of gene products that regulate and effect cell death.The intimate link between the cell cycle,cellular senescence,apoptosis regulation,cancer development and tumor responses to cancer treatment has become eminently apparent.Extensive research on tumor suppressor genes,oncogenes,the cell cycle and apoptosis regulatory genes has revealed how the DNA damage-sensing and -signaling pathways,referred to as the DNA-damage response network,are tied to cell proliferation,cell-cycle arrest,cellular senescence and apoptosis.DNA-damage responses are complex,involving "sensor" proteins that sense the damage,and transmit signals to "transducer" proteins,which,in turn,convey the signals to numerous "effector" proteins implicated in specific cellular pathways,including DNA repair mechanisms,cell-cycle checkpoints,cellular senescence and apoptosis.The Bcl-2 family of proteins stands among the most crucial regulators of apoptosis and performs vital functions in deciding whether a cell will live or die after cancer chemotherapy and irradiation.In addition,several studies have now revealed that members of the Bcl-2 family also interface with the cell cycle,DNA repair/recombination and cellular senescence,effects that are generally distinct from their function in apoptosis.In this review,we report progress in understanding the molecular networks that regulate cell-cycle checkpoints,cellular senescence and apoptosis after DNA damage,and discuss the influence of some Bcl-2 family members on cell-cycle checkpoint regulation.

  19. A computable cellular stress network model for non-diseased pulmonary and cardiovascular tissue

    Drubin David


    Full Text Available Abstract Background Humans and other organisms are equipped with a set of responses that can prevent damage from exposure to a multitude of endogenous and environmental stressors. If these stress responses are overwhelmed, this can result in pathogenesis of diseases, which is reflected by an increased development of, e.g., pulmonary and cardiac diseases in humans exposed to chronic levels of environmental stress, including inhaled cigarette smoke (CS. Systems biology data sets (e.g., transcriptomics, phosphoproteomics, metabolomics could enable comprehensive investigation of the biological impact of these stressors. However, detailed mechanistic networks are needed to determine which specific pathways are activated in response to different stressors and to drive the qualitative and eventually quantitative assessment of these data. A current limiting step in this process is the availability of detailed mechanistic networks that can be used as an analytical substrate. Results We have built a detailed network model that captures the biology underlying the physiological cellular response to endogenous and exogenous stressors in non-diseased mammalian pulmonary and cardiovascular cells. The contents of the network model reflect several diverse areas of signaling, including oxidative stress, hypoxia, shear stress, endoplasmic reticulum stress, and xenobiotic stress, that are elicited in response to common pulmonary and cardiovascular stressors. We then tested the ability of the network model to identify the mechanisms that are activated in response to CS, a broad inducer of cellular stress. Using transcriptomic data from the lungs of mice exposed to CS, the network model identified a robust increase in the oxidative stress response, largely mediated by the anti-oxidant NRF2 pathways, consistent with previous reports on the impact of CS exposure in the mammalian lung. Conclusions The results presented here describe the construction of a cellular stress

  20. Device-Relaying in Cellular D2D Networks: A Fairness Perspective

    Chaaban, Anas


    Device-to-Device (D2D) communication is envisioned to play a key role in 5G networks as a technique for meeting the demand for high data rates. In a cellular network, D2D allows not only direct communication between users, but also device relaying. In this paper, a simple instance of device-relaying is investigated, and its impact on fairness among users is studied. Namely, a cellular network consisting of two D2D-enabled users and a base-station (BS) is considered. Thus, the users who want to establish communication with the BS can act as relays for each other’s signals. While this problem is traditionally considered in the literature as a multiple-access channel with cooperation in the uplink, and a broadcast channel with cooperation in the downlink, we propose a different treatment of the problem as a multi-way channel. A simple communication scheme is proposed, and is shown to achieve significant gain in terms of fairness (measured by the symmetric rate supported) in comparison to the aforementioned traditional treatment.

  1. BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling.

    Feng, Song; Ollivier, Julien F; Swain, Peter S; Soyer, Orkun S


    Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: and PMID:26101250

  2. Cellular Interrogation: Exploiting Cell-to-Cell Variability to Discriminate Regulatory Mechanisms in Oscillatory Signalling

    Gibson, Daniel; Chang, Frederick; Gnad, Florian; Gunawardena, Jeremy


    The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cell’s environment. This suggests that the external environment may be harnessed to interrogate the cell’s internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a “correct” model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology. PMID:27367445

  3. Proteomes and Neural Stem Cells: cellular signalling during differentiation

    Skalníková, Helena; Halada, Petr; Vodička, Petr; Motlík, Jan; Horning, O.; Jensen, O. N.; Gadher, S. J.; Pelech, S.; Kovářová, Hana

    Cambridge : -, 2007, s. 1-1. [BSPR-EBI Meeting: Integrative Proteomics: From Molecules to Systems,. Cambridge (GB), 25.07.2007-27.07.2007] Institutional research plan: CEZ:AV0Z50450515; CEZ:AV0Z50200510 Keywords : neural stem cells * differentiation * signalling * proteome Subject RIV: EB - Genetics ; Molecular Biology

  4. Systematic Identification of Cellular Signals Reactivating Kaposi Sarcoma–Associated Herpesvirus

    Yu, Fuqu; Harada, Josephine N; Brown, Helen J; Deng, Hongyu; Song, Moon Jung; Wu, Ting-Ting; Kato-Stankiewicz, Juran; Nelson, Christian G; Vieira, Jeffrey; Tamanoi, Fuyuhiko; Chanda, Sumit K; Sun, Ren


    The herpesvirus life cycle has two distinct phases: latency and lytic replication. The balance between these two phases is critical for viral pathogenesis. It is believed that cellular signals regulate the switch from latency to lytic replication. To systematically evaluate the cellular signals regulating this reactivation process in Kaposi sarcoma–associated herpesvirus, the effects of 26,000 full-length cDNA expression constructs on viral reactivation were individually assessed in primary effusion lymphoma–derived cells that harbor the latent virus. A group of diverse cellular signaling proteins were identified and validated in their effect of inducing viral lytic gene expression from the latent viral genome. The results suggest that multiple cellular signaling pathways can reactivate the virus in a genetically homogeneous cell population. Further analysis revealed that the Raf/MEK/ERK/Ets-1 pathway mediates Ras-induced reactivation. The same pathway also mediates spontaneous reactivation, which sets the first example to our knowledge of a specific cellular pathway being studied in the spontaneous reactivation process. Our study provides a functional genomic approach to systematically identify the cellular signals regulating the herpesvirus life cycle, thus facilitating better understanding of a fundamental issue in virology and identifying novel therapeutic targets. PMID:17397260

  5. Systematic identification of cellular signals reactivating Kaposi sarcoma-associated herpesvirus.

    Fuqu Yu


    Full Text Available The herpesvirus life cycle has two distinct phases: latency and lytic replication. The balance between these two phases is critical for viral pathogenesis. It is believed that cellular signals regulate the switch from latency to lytic replication. To systematically evaluate the cellular signals regulating this reactivation process in Kaposi sarcoma-associated herpesvirus, the effects of 26,000 full-length cDNA expression constructs on viral reactivation were individually assessed in primary effusion lymphoma-derived cells that harbor the latent virus. A group of diverse cellular signaling proteins were identified and validated in their effect of inducing viral lytic gene expression from the latent viral genome. The results suggest that multiple cellular signaling pathways can reactivate the virus in a genetically homogeneous cell population. Further analysis revealed that the Raf/MEK/ERK/Ets-1 pathway mediates Ras-induced reactivation. The same pathway also mediates spontaneous reactivation, which sets the first example to our knowledge of a specific cellular pathway being studied in the spontaneous reactivation process. Our study provides a functional genomic approach to systematically identify the cellular signals regulating the herpesvirus life cycle, thus facilitating better understanding of a fundamental issue in virology and identifying novel therapeutic targets.

  6. Molecular and cellular mechanisms of vomeronasal signaling in mammals

    Cichy, Annika


    The mouse vomeronasal organ plays a critical role in chemosensory communication and regulates diverse social and sexual behaviors. However, many physiological mechanisms underlying vomeronasal chemosensory signaling remain elusive. Therefore, the overall aim of my thesis was to gain a deeper understanding of the basic mechanisms that control VNO physiology. Specifically, my research focused on HCN channel-mediated vomeronasal proton-sensing and its potential role in sensory gain control of so...

  7. Synchronous networks for bio-environmental surveillance based on cellular automata

    Bao Hoai Lam; Hiep Xuan Huynh; Bernard Pottier


    The paper proposes a new approach to model a bio-environmental surveillance network as synchronous network systems, systems consist of components running simultaneously. In the network, bio-environmental factors compose a physical system of which executions proceed concurrently in synchronous rounds. This system is synchronized with a synchronous wireless sensor network, the observation network. Topology of the surveillance network is based on cellular automata to depict its concurrent charac...

  8. Cellular neural networks for motion estimation and obstacle detection

    D. Feiden


    Full Text Available Obstacle detection is an important part of Video Processing because it is indispensable for a collision prevention of autonomously navigating moving objects. For example, vehicles driving without human guidance need a robust prediction of potential obstacles, like other vehicles or pedestrians. Most of the common approaches of obstacle detection so far use analytical and statistical methods like motion estimation or generation of maps. In the first part of this contribution a statistical algorithm for obstacle detection in monocular video sequences is presented. The proposed procedure is based on a motion estimation and a planar world model which is appropriate to traffic scenes. The different processing steps of the statistical procedure are a feature extraction, a subsequent displacement vector estimation and a robust estimation of the motion parameters. Since the proposed procedure is composed of several processing steps, the error propagation of the successive steps often leads to inaccurate results. In the second part of this contribution it is demonstrated, that the above mentioned problems can be efficiently overcome by using Cellular Neural Networks (CNN. It will be shown, that a direct obstacle detection algorithm can be easily performed, based only on CNN processing of the input images. Beside the enormous computing power of programmable CNN based devices, the proposed method is also very robust in comparison to the statistical method, because is shows much less sensibility to noisy inputs. Using the proposed approach of obstacle detection in planar worlds, a real time processing of large input images has been made possible.

  9. Modelling lava flows by Cellular Nonlinear Networks (CNN: preliminary results

    C. Del Negro


    Full Text Available The forecasting of lava flow paths is a complex problem in which temperature, rheology and flux-rate all vary with space and time. The problem is more difficult to solve when lava runs down a real topography, considering that the relations between characteristic parameters of flow are typically nonlinear. An alternative approach to this problem that does not use standard differential equation methods is Cellular Nonlinear Networks (CNNs. The CNN paradigm is a natural and flexible framework for describing locally interconnected, simple, dynamic systems that have a lattice-like structure. They consist of arrays of essentially simple, nonlinearly coupled dynamic circuits containing linear and non-linear elements able to process large amounts of information in real time. Two different approaches have been implemented in simulating some lava flows. Firstly, a typical technique of the CNNs to analyze spatio-temporal phenomena (as Autowaves in 2-D and in 3-D has been utilized. Secondly, the CNNs have been used as solvers of partial differential equations of the Navier-Stokes treatment of Newtonian flow.

  10. Optimal Channel Allocation with Dynamic Power Control in Cellular Networks

    Xin Wu


    Full Text Available Techniques for channel allocation in cellular networks have been an area of intense research interest formany years. An efficient channel allocation scheme can significantly reduce call-blocking and calldroppingprobabilities. Another important issue is to effectively manage the power requirements forcommunication. An efficient power control strategy leads to reduced power consumption and improvedsignal quality. In this paper, we present a novel integer linear program (ILP formulation that jointlyoptimizes channel allocation and power control for incoming calls, based on the carrier-to-interferenceratio (CIR. In our approach we use a hybrid channel assignment scheme, where an incoming call isadmitted only if a suitable channel is found such that the CIR of all ongoing calls on that channel, as wellas that of the new call, will be above a specified value. Our formulation also guarantees that the overallpower requirement for the selected channel will be minimized as much as possible and that no ongoingcalls will be dropped as a result of admitting the new call. We have run simulations on a benchmark 49cell environment with 70 channels to investigate the effect of different parameters such as the desiredCIR. The results indicate that our approach leads to significant improvements over existing techniques.

  11. Cellular nonlinear networks for strike-point localization at JET

    At JET, the potential of fast image processing for real-time purposes is thoroughly investigated. Particular attention is devoted to smart sensors based on system on chip technology. The data of the infrared cameras were processed with a chip implementing a cellular nonlinear network (CNN) structure so as to support and complement the magnetic diagnostics in the real-time localization of the strike-point position in the divertor. The circuit consists of two layers of complementary metal-oxide semiconductor components, the first being the sensor and the second implementing the actual CNN. This innovative hardware has made it possible to determine the position of the maximum thermal load with a time resolution of the order of 30 ms. Good congruency has been found with the measurement from the thermocouples in the divertor, proving the potential of the infrared data in locating the region of the maximum thermal load. The results are also confirmed by JET magnetic codes, both those used for the equilibrium reconstructions and those devoted to the identification of the plasma boundary

  12. Qualitative networks: a symbolic approach to analyze biological signaling networks

    Henzinger Thomas A


    Full Text Available Abstract Background A central goal of Systems Biology is to model and analyze biological signaling pathways that interact with one another to form complex networks. Here we introduce Qualitative networks, an extension of Boolean networks. With this framework, we use formal verification methods to check whether a model is consistent with the laboratory experimental observations on which it is based. If the model does not conform to the data, we suggest a revised model and the new hypotheses are tested in-silico. Results We consider networks in which elements range over a small finite domain allowing more flexibility than Boolean values, and add target functions that allow to model a rich set of behaviors. We propose a symbolic algorithm for analyzing the steady state of these networks, allowing us to scale up to a system consisting of 144 elements and state spaces of approximately 1086 states. We illustrate the usefulness of this approach through a model of the interaction between the Notch and the Wnt signaling pathways in mammalian skin, and its extensive analysis. Conclusion We introduce an approach for constructing computational models of biological systems that extends the framework of Boolean networks and uses formal verification methods for the analysis of the model. This approach can scale to multicellular models of complex pathways, and is therefore a useful tool for the analysis of complex biological systems. The hypotheses formulated during in-silico testing suggest new avenues to explore experimentally. Hence, this approach has the potential to efficiently complement experimental studies in biology.

  13. Patterns of human gene expression variance show strong associations with signaling network hierarchy

    Ram Prahlad T


    Full Text Available Abstract Background Understanding organizational principles of cellular networks is one of the central goals of systems biology. Although much has been learnt about gene expression programs under specific conditions, global patterns of expressional variation (EV of genes and their relationship to cellular functions and physiological responses is poorly understood. Results To understand global principles of relationship between transcriptional regulation of human genes and their functions, we have leveraged large-scale datasets of human gene expression measurements across a wide spectrum of cell conditions. We report that human genes are highly diverse in terms of their EV; while some genes have highly variable expression pattern, some seem to be relatively ubiquitously expressed across a wide range of conditions. The wide spectrum of gene EV strongly correlates with the positioning of proteins within the signaling network hierarchy, such that, secreted extracellular receptor ligands and membrane receptors have the highest EV, and intracellular signaling proteins have the lowest EV in the genome. Our analysis shows that this pattern of EV reflects functional centrality: proteins with highly specific signaling functions are modulated more frequently than those with highly central functions in the network, which is also consistent with previous studies on tissue-specific gene expression. Interestingly, these patterns of EV along the signaling network hierarchy have significant correlations with promoter architectures of respective genes. Conclusion Our analyses suggest a generic systems level mechanism of regulation of the cellular signaling network at the transcriptional level.

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

    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: [Division of Brain Diseases, Center for Biomedical Science, Korea National Institute of Health, Osong 363-951 (Korea, Republic of)


    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.

  15. Computational study of noise in a large signal transduction network

    Ruohonen Keijo


    Full Text Available Abstract Background Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor. Results We implemented a large nonlinear signal transduction network combining protein kinase C, mitogen-activated protein kinase, phospholipase A2, and β isoform of phospholipase C networks. We simulated the network in 300 different cellular volumes using the exact Gillespie stochastic simulation algorithm and analyzed the results in both the time and frequency domain. In order to perform simulations in a reasonable time, we used modern parallel computing techniques. The analysis revealed that time and frequency domain characteristics depend on the system volume. The simulation results also indicated that there are several kinds of noise processes in the network, all of them representing different kinds of low-frequency fluctuations. In the simulations, the power of noise decreased on all frequencies when the system volume was increased. Conclusions We concluded that basic frequency domain techniques can be applied to the analysis of simulation results produced by the Gillespie stochastic simulation algorithm. This approach is suited not only to the study of fluctuations but also to the study of pure noise processes. Noise seems to have an important role in biochemical systems and its properties can be numerically studied by simulating the reacting system in different cellular volumes. Parallel computing techniques make it possible to run massive simulations in hundreds of volumes and, as a result, accurate statistics can be obtained from computational studies.

  16. Secure D2D Communication in Large-Scale Cognitive Cellular Networks: A Wireless Power Transfer Model

    Liu, Yuanwei; Wang, Lifeng; Zaidi, Syed Ali Raza; Elkashlan, Maged; Duong, Trung Q.


    In this paper, we investigate secure device-to-device (D2D) communication in energy harvesting large-scale cognitive cellular networks. The energy constrained D2D transmitter harvests energy from multiantenna equipped power beacons (PBs), and communicates with the corresponding receiver using the spectrum of the primary base stations (BSs). We introduce a power transfer model and an information signal model to enable wireless energy harvesting and secure information transmission. In the power...

  17. Towards an Appropriate Beamforming Scheme for Initial Cell Discovery in mmW 5G Cellular Networks

    Abbas, Waqas bin; Zorzi, Michele


    Beamforming is an essential requirement to combat high pathloss and to improve signal-to-noise ratio during initial cell discovery in future millimeter wave cellular networks. The choice of an appropriate beamforming is directly coupled with its energy consumption. The energy consumption is even of more concern at a battery limited mobile station (MS). In this work, we provide an energy consumption based comparison of different beamforming schemes while considering both a low power and a high...

  18. Genetic and logic networks with the signal-inhibitor-activator structure are dynamically robust

    LI Fangting; TAN Ning


    The proteins, DNA and RNA interaction networks govern various biological functions in living cells, these networks should be dynamically robust in the intracellular and environmental fluctuations. Here, we use Boolean network to study the robust structure of both genetic and logic networks. First, SOS network in bacteria E. coli, which regulates cell survival and repair after DNA damage, is shown to be dynamically robust. Comparing with cell cycle network in budding yeast and flagella network in E. coli, we find the signal-inhibitor-activator (SIA) structure in transcription regulatory networks. Second, under the dynamical rule that inhibition is much stronger than activation, we have searched 3-node non-self-loop logical networks that are dynamically robust, and that if the attractive basin of a final attractor is as large as seven, and the final attractor has only one active node, then the active node acts as inhibitor, and the SIA and signal-inhibitor (SI) structures are fundamental architectures of robust networks. SIA and SI networks with dynamic robustness against environment uncertainties may be selected and maintained over the course of evolution, rather than blind trial-error testing and be ing an accidental consequence of particular evolutionary history. SIA network can perform a more complex process than SI network, andSIA might be used to design robust artificial genetic network. Our results provide dynamical support for why the inhibitors and SIA/SI structures are frequently employed in cellular regulatory networks.

  19. Proteomics, pathway array and signaling network-based medicine in cancer

    Xu Hong


    Full Text Available Abstract Cancer is a multifaceted disease that results from dysregulated normal cellular signaling networks caused by genetic, genomic and epigenetic alterations at cell or tissue levels. Uncovering the underlying protein signaling network changes, including cell cycle gene networks in cancer, aids in understanding the molecular mechanism of carcinogenesis and identifies the characteristic signaling network signatures unique for different cancers and specific cancer subtypes. The identified signatures can be used for cancer diagnosis, prognosis, and personalized treatment. During the past several decades, the available technology to study signaling networks has significantly evolved to include such platforms as genomic microarray (expression array, SNP array, CGH array, etc. and proteomic analysis, which globally assesses genetic, epigenetic, and proteomic alterations in cancer. In this review, we compared Pathway Array analysis with other proteomic approaches in analyzing protein network involved in cancer and its utility serving as cancer biomarkers in diagnosis, prognosis and therapeutic target identification. With the advent of bioinformatics, constructing high complexity signaling networks is possible. As the use of signaling network-based cancer diagnosis, prognosis and treatment is anticipated in the near future, medical and scientific communities should be prepared to apply these techniques to further enhance personalized medicine.

  20. Morbilliviruses Use Signaling Lymphocyte Activation Molecules (CD150) as Cellular Receptors

    Tatsuo, Hironobu; Ono, Nobuyuki; Yanagi, Yusuke


    Morbilliviruses comprise measles virus, canine distemper virus, rinderpest virus, and several other viruses that cause devastating human and animal diseases accompanied by severe immunosuppression and lymphopenia. Recently, we have shown that human signaling lymphocyte activation molecule (SLAM) is a cellular receptor for measles virus. In this study, we examined whether canine distemper and rinderpest viruses also use canine and bovine SLAMs, respectively, as cellular receptors. The Onderste...

  1. Adaptive scheduling in cellular access, wireless mesh and IP networks

    Nieminen, Johanna


    Networking scenarios in the future will be complex and will include fixed networks and hybrid Fourth Generation (4G) networks, consisting of both infrastructure-based and infrastructureless, wireless parts. In such scenarios, adaptive provisioning and management of network resources becomes of critical importance. Adaptive mechanisms are desirable since they enable a self-configurable network that is able to adjust itself to varying traffic and channel conditions. The operation of adaptive me...

  2. Analysis of blocking rate and bandwidth usage of mobile IPTV services in wireless cellular networks.

    Li, Mingfu


    Mobile IPTV services over wireless cellular networks become more and more popular, owing to the significant growth in access bandwidth of wireless cellular networks such as 3G/4G and WiMAX. However, the spectrum resources of wireless cellular networks is rare. How to enhance the spectral efficiency of mobile networks becomes an important issue. Unicast, broadcast, and multicast are the most important transport schemes for offering mobile IPTV services over wireless cellular networks. Therefore, bandwidth usages and blocking rates of unicast, broadcast, and multicast IPTV services were analyzed and compared in this paper. Simulations were also conducted to validate the analytical results. Numerical results demonstrate that the presented analysis is correct, and multicast scheme achieves the best bandwidth usage and blocking rate performance, relative to the other two schemes. PMID:25379521

  3. The primary cilium as a cellular receiver: organizing ciliary GPCR signaling.

    Hilgendorf, Keren I; Johnson, Carl T; Jackson, Peter K


    The primary cilium is an antenna-like cellular protrusion mediating sensory and neuroendocrine signaling. Its localization within tissue architecture and a growing list of cilia-localized receptors, in particular G-protein-coupled receptors, determine a host of crucial physiologies, which are disrupted in human ciliopathies. Here, we discuss recent advances in the identification and characterization of ciliary signaling components and pathways. Recent studies have highlighted the unique signaling environment of the primary cilium and we are just beginning to understand how this design allows for highly amplified and regulated signaling. PMID:26926036

  4. A cellular network model with Ginibre configured base stations

    Miyoshi, Naoto; Shirai, Tomoyuki


    Stochastic geometry models for wireless communication networks have recently attracted much attention. This is because the performance of such networks critically depends on the spatial configuration of wireless nodes and the irregularity of the node configuration in a real network can be captured by a spatial point process. However, most analysis of such stochastic geometry models for wireless networks assumes, owing to its tractability, that the wireless nodes are deployed...

  5. Load-aware modeling for uplink cellular networks in a multi-channel environment

    Alammouri, Ahmad Mohammad Abdel-Karim


    We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint for the users\\' equipment (UEs). The proposed analytical paradigm is based on a simple per-user power control scheme in which each user inverts his path-loss such that the signal is received at his serving base station (BS) with a certain power threshold ρ Due to the limited transmit power of the UEs, users that cannot invert their path-loss to their serving BSs are allowed to transmit with their maximum transmit power. We show that the proposed power control scheme not only provides a balanced cell center and cell edge user performance, it also facilitates the analysis when compared to the state-of-the-art approaches in the literature. To this end, we discuss how to manipulate the design variable ρ in response to the network parameters to optimize one or more of the performance metrics such as the outage probability, the network capacity, and the energy efficiency.

  6. Traffic Driven Analysis of Cellular and WiFi Networks

    Paul, Utpal Kumar


    Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

  7. Magnetoencephalography from signals to dynamic cortical networks

    Aine, Cheryl


    "Magnetoencephalography (MEG) provides a time-accurate view into human brain function. The concerted action of neurons generates minute magnetic fields that can be detected---totally noninvasively---by sensitive multichannel magnetometers. The obtained millisecond accuracycomplements information obtained by other modern brain-imaging tools. Accurate timing is quintessential in normal brain function, often distorted in brain disorders. The noninvasiveness and time-sensitivityof MEG are great assets to developmental studies, as well. This multiauthored book covers an ambitiously wide range of MEG research from introductory to advanced level, from sensors to signals, and from focal sources to the dynamics of cortical networks. Written by active practioners of this multidisciplinary field, the book contains tutorials for newcomers and chapters of new challenging methods and emerging technologies to advanced MEG users. The reader will obtain a firm grasp of the possibilities of MEG in the study of audition, vision...

  8. Radio Access Sharing Strategies for Multiple Operators in Cellular Networks

    Popovska Avramova, Andrijana; Iversen, Villy Bæk


    Mobile operators are moving towards sharing network capacity in order to reduce capital and operational expenditures, while meeting the increasing demand for mobile broadband data services. Radio access network sharing is a promising technique that leads to reduced number of physical base station....... The model used to assess the sharing strategies is based on multidimensional loss systems, and blocking probability is considered as performance metrics....... deployments (required for coverage enhancement), increased base station utilization, and reduced overall power consumption. Today, network sharing in the radio access part is passive and limited to cell sites. With the introduction of Cloud Radio Access Network and Software Defined Networking adoption to the...

  9. Global Optimization for Transport Network Expansion and Signal Setting

    Haoxiang Liu


    Full Text Available This paper proposes a model to address an urban transport planning problem involving combined network design and signal setting in a saturated network. Conventional transport planning models usually deal with the network design problem and signal setting problem separately. However, the fact that network capacity design and capacity allocation determined by network signal setting combine to govern the transport network performance requires the optimal transport planning to consider the two problems simultaneously. In this study, a combined network capacity expansion and signal setting model with consideration of vehicle queuing on approaching legs of intersection is developed to consider their mutual interactions so that best transport network performance can be guaranteed. We formulate the model as a bilevel program and design an approximated global optimization solution method based on mixed-integer linearization approach to solve the problem, which is inherently nnonlinear and nonconvex. Numerical experiments are conducted to demonstrate the model application and the efficiency of solution algorithm.

  10. On the Global Dissipativity of a Class of Cellular Neural Networks with Multipantograph Delays

    Liqun Zhou


    Full Text Available For the first time the global dissipativity of a class of cellular neural networks with multipantograph delays is studied. On the one hand, some delay-dependent sufficient conditions are obtained by directly constructing suitable Lyapunov functionals; on the other hand, firstly the transformation transforms the cellular neural networks with multipantograph delays into the cellular neural networks with constant delays and variable coefficients, and then constructing Lyapunov functionals, some delay-independent sufficient conditions are given. These new sufficient conditions can ensure global dissipativity together with their sets of attraction and can be applied to design global dissipative cellular neural networks with multipantograph delays and easily checked in practice by simple algebraic methods. An example is given to illustrate the correctness of the results.