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Sample records for regulatory network architecture

  1. Computational architecture of the yeast regulatory network

    NASA Astrophysics Data System (ADS)

    Maslov, Sergei; Sneppen, Kim

    2005-12-01

    The topology of regulatory networks contains clues to their overall design principles and evolutionary history. We find that while in- and out-degrees of a given protein in the regulatory network are not correlated with each other, there exists a strong negative correlation between the out-degree of a regulatory protein and in-degrees of its targets. Such correlation positions large regulatory modules on the periphery of the network and makes them rather well separated from each other. We also address the question of relative importance of different classes of proteins quantified by the lethality of null-mutants lacking one of them as well as by the level of their evolutionary conservation. It was found that in the yeast regulatory network highly connected proteins are in fact less important than their low-connected counterparts.

  2. Establishing the Architecture of Plant Gene Regulatory Networks.

    PubMed

    Yang, F; Ouma, W Z; Li, W; Doseff, A I; Grotewold, E

    2016-01-01

    Gene regulatory grids (GRGs) encompass the space of all the possible transcription factor (TF)-target gene interactions that regulate gene expression, with gene regulatory networks (GRNs) representing a temporal and spatial manifestation of a portion of the GRG, essential for the specification of gene expression. Thus, understanding GRG architecture provides a valuable tool to explain how genes are expressed in an organism, an important aspect of synthetic biology and essential toward the development of the "in silico" cell. Progress has been made in some unicellular model systems (eg, yeast), but significant challenges remain in more complex multicellular organisms such as plants. Key to understanding the organization of GRGs is therefore identifying the genes that TFs bind to, and control. The application of sensitive and high-throughput methods to investigate genome-wide TF-target gene interactions is providing a wealth of information that can be linked to important agronomic traits. We describe here the methods and resources that have been developed to investigate the architecture of plant GRGs and GRNs. We also provide information regarding where to obtain clones or other resources necessary for synthetic biology or metabolic engineering. PMID:27480690

  3. Genetic architecture and regulatory networks in oilseed development

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic analysis of global gene expression level variation provides evidence for transcriptional regulators and gene network relationships. Plant seeds are an important source of oil and protein, and a genome-wide assessment of transcriptional regulation during seed development offers insight into t...

  4. Level architecture in genetic regulatory networks and the role of microRNAs

    NASA Astrophysics Data System (ADS)

    Schwarz, J. M.

    2008-03-01

    It is well known that genes that code for proteins regulate the expression of each other through protein-mediated interactions. With the discovery of microRNAs^1 (miRNAs), it has been conjectured that there are many such regulatory miRNAs in the cell that are never transcribed into proteins but are important for regulation and, hence, could explain the nature of the non-coding (or junk) DNA.^2 Furthermore, miRNAs are highly conserved molecules. So, just as genes that code for proteins form regulatory networks, we conjecture that miRNAs form a higher-level regulatory network amongst themselves as mediated by the genes-coding-for-proteins regulatory network to form a complex organism. We investigate this conjecture within the framework of random Boolean networks where the two-level architecture is modelled via two coupled random Boolean networks with one network taking precedence over the other for various input/output values. Aspects of the evolution of the lower-level network will also be addressed. ^1 D. P. Bartel, Cell 116, 281 (2004). ^2 J. S. Mattick, Sci. Amer. 291, 60 (2004).

  5. Developmental gene regulatory network architecture across 500 million years of echinoderm evolution

    NASA Technical Reports Server (NTRS)

    Hinman, Veronica F.; Nguyen, Albert T.; Cameron, R. Andrew; Davidson, Eric H.

    2003-01-01

    Evolutionary change in morphological features must depend on architectural reorganization of developmental gene regulatory networks (GRNs), just as true conservation of morphological features must imply retention of ancestral developmental GRN features. Key elements of the provisional GRN for embryonic endomesoderm development in the sea urchin are here compared with those operating in embryos of a distantly related echinoderm, a starfish. These animals diverged from their common ancestor 520-480 million years ago. Their endomesodermal fate maps are similar, except that sea urchins generate a skeletogenic cell lineage that produces a prominent skeleton lacking entirely in starfish larvae. A relevant set of regulatory genes was isolated from the starfish Asterina miniata, their expression patterns determined, and effects on the other genes of perturbing the expression of each were demonstrated. A three-gene feedback loop that is a fundamental feature of the sea urchin GRN for endoderm specification is found in almost identical form in the starfish: a detailed element of GRN architecture has been retained since the Cambrian Period in both echinoderm lineages. The significance of this retention is highlighted by the observation of numerous specific differences in the GRN connections as well. A regulatory gene used to drive skeletogenesis in the sea urchin is used entirely differently in the starfish, where it responds to endomesodermal inputs that do not affect it in the sea urchin embryo. Evolutionary changes in the GRNs since divergence are limited sharply to certain cis-regulatory elements, whereas others have persisted unaltered.

  6. UMTS network architecture

    NASA Astrophysics Data System (ADS)

    Katoen, J. P.; Saiedi, A.; Baccaro, I.

    1994-05-01

    This paper proposes a Functional Architecture and a corresponding Network Architecture for the Universal Mobile Telecommunication System (UMTS). Procedures like call handling, location management, and handover are considered. The architecture covers the domestic, business, and public environments. Integration with existing and forthcoming networks for fixed communications is anticipated and the Intelligent Network (IN) philosophy is applied.

  7. FTS2000 network architecture

    NASA Technical Reports Server (NTRS)

    Klenart, John

    1991-01-01

    The network architecture of FTS2000 is graphically depicted. A map of network A topology is provided, with interservice nodes. Next, the four basic element of the architecture is laid out. Then, the FTS2000 time line is reproduced. A list of equipment supporting FTS2000 dedicated transmissions is given. Finally, access alternatives are shown.

  8. A genomic regulatory network for development

    NASA Technical Reports Server (NTRS)

    Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar; Otim, Ochan; Brown, C. Titus; Livi, Carolina B.; Lee, Pei Yun; Revilla, Roger; Rust, Alistair G.; Pan, Zheng jun; Schilstra, Maria J.; Clarke, Peter J C.; Arnone, Maria I.; Rowen, Lee; Cameron, R. Andrew; McClay, David R.; Hood, Leroy; Bolouri, Hamid

    2002-01-01

    Development of the body plan is controlled by large networks of regulatory genes. A gene regulatory network that controls the specification of endoderm and mesoderm in the sea urchin embryo is summarized here. The network was derived from large-scale perturbation analyses, in combination with computational methodologies, genomic data, cis-regulatory analysis, and molecular embryology. The network contains over 40 genes at present, and each node can be directly verified at the DNA sequence level by cis-regulatory analysis. Its architecture reveals specific and general aspects of development, such as how given cells generate their ordained fates in the embryo and why the process moves inexorably forward in developmental time.

  9. MSAT network architecture

    NASA Technical Reports Server (NTRS)

    Davies, N. G.; Skerry, B.

    1990-01-01

    The Mobile Satellite (MSAT) communications system will support mobile voice and data services using circuit switched and packet switched facilities with interconnection to the public switched telephone network and private networks. Control of the satellite network will reside in a Network Control System (NCS) which is being designed to be extremely flexible to provide for the operation of the system initially with one multi-beam satellite, but with capability to add additional satellites which may have other beam configurations. The architecture of the NCS is described. The signalling system must be capable of supporting the protocols for the assignment of circuits for mobile public telephone and private network calls as well as identifying packet data networks. The structure of a straw-man signalling system is discussed.

  10. Quantifying Loopy Network Architectures

    PubMed Central

    Katifori, Eleni; Magnasco, Marcelo O.

    2012-01-01

    Biology presents many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture containing closed loops at many different levels. Although a number of approaches have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework, the hierarchical loop decomposition, that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated graphs, such as artificial models and optimal distribution networks, as well as natural graphs extracted from digitized images of dicotyledonous leaves and vasculature of rat cerebral neocortex. We calculate various metrics based on the asymmetry, the cumulative size distribution and the Strahler bifurcation ratios of the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information (exact location of edges and nodes) from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs. PMID:22701593

  11. Apprehending multicellularity: regulatory networks, genomics and evolution

    PubMed Central

    Aravind, L.; Anantharaman, Vivek; Venancio, Thiago M.

    2009-01-01

    The genomic revolution has provided the first glimpses of the architecture of regulatory networks. Combined with evolutionary information, the “network view” of life processes leads to remarkable insights into how biological systems have been shaped by various forces. This understanding is critical because biological systems, including regulatory networks, are not products of engineering but of historical contingencies. In this light, we attempt a synthetic overview of the natural history of regulatory networks operating in the development and differentiation of multicellular organisms. We first introduce regulatory networks and their organizational principles as can be deduced using ideas from the graph theory. We then discuss findings from comparative genomics to illustrate the effects of lineage-specific expansions, gene-loss, and non-protein-coding DNA on the architecture of networks. We consider the interaction between expansions of transcription factors, and cis regulatory and more general chromatin state stabilizing elements in the emergence of morphological complexity. Finally, we consider a case study of the Notch sub-network, which is present throughout Metazoa, to examine how such a regulatory system has been pieced together in evolution from new innovations and pre-existing components that were originally functionally distinct. PMID:19530132

  12. Apprehending multicellularity: regulatory networks, genomics, and evolution.

    PubMed

    Aravind, L; Anantharaman, Vivek; Venancio, Thiago M

    2009-06-01

    The genomic revolution has provided the first glimpses of the architecture of regulatory networks. Combined with evolutionary information, the "network view" of life processes leads to remarkable insights into how biological systems have been shaped by various forces. This understanding is critical because biological systems, including regulatory networks, are not products of engineering but of historical contingencies. In this light, we attempt a synthetic overview of the natural history of regulatory networks operating in the development and differentiation of multicellular organisms. We first introduce regulatory networks and their organizational principles as can be deduced using ideas from the graph theory. We then discuss findings from comparative genomics to illustrate the effects of lineage-specific expansions, gene-loss, and nonprotein-coding DNA on the architecture of networks. We consider the interaction between expansions of transcription factors, and cis regulatory and more general chromatin state stabilizing elements in the emergence of morphological complexity. Finally, we consider a case study of the Notch subnetwork, which is present throughout Metazoa, to examine how such a regulatory system has been pieced together in evolution from new innovations and pre-existing components that were originally functionally distinct. PMID:19530132

  13. Evolving Robust Gene Regulatory Networks

    PubMed Central

    Noman, Nasimul; Monjo, Taku; Moscato, Pablo; Iba, Hitoshi

    2015-01-01

    Design and implementation of robust network modules is essential for construction of complex biological systems through hierarchical assembly of ‘parts’ and ‘devices’. The robustness of gene regulatory networks (GRNs) is ascribed chiefly to the underlying topology. The automatic designing capability of GRN topology that can exhibit robust behavior can dramatically change the current practice in synthetic biology. A recent study shows that Darwinian evolution can gradually develop higher topological robustness. Subsequently, this work presents an evolutionary algorithm that simulates natural evolution in silico, for identifying network topologies that are robust to perturbations. We present a Monte Carlo based method for quantifying topological robustness and designed a fitness approximation approach for efficient calculation of topological robustness which is computationally very intensive. The proposed framework was verified using two classic GRN behaviors: oscillation and bistability, although the framework is generalized for evolving other types of responses. The algorithm identified robust GRN architectures which were verified using different analysis and comparison. Analysis of the results also shed light on the relationship among robustness, cooperativity and complexity. This study also shows that nature has already evolved very robust architectures for its crucial systems; hence simulation of this natural process can be very valuable for designing robust biological systems. PMID:25616055

  14. Airport Surface Network Architecture Definition

    NASA Technical Reports Server (NTRS)

    Nguyen, Thanh C.; Eddy, Wesley M.; Bretmersky, Steven C.; Lawas-Grodek, Fran; Ellis, Brenda L.

    2006-01-01

    Currently, airport surface communications are fragmented across multiple types of systems. These communication systems for airport operations at most airports today are based dedicated and separate architectures that cannot support system-wide interoperability and information sharing. The requirements placed upon the Communications, Navigation, and Surveillance (CNS) systems in airports are rapidly growing and integration is urgently needed if the future vision of the National Airspace System (NAS) and the Next Generation Air Transportation System (NGATS) 2025 concept are to be realized. To address this and other problems such as airport surface congestion, the Space Based Technologies Project s Surface ICNS Network Architecture team at NASA Glenn Research Center has assessed airport surface communications requirements, analyzed existing and future surface applications, and defined a set of architecture functions that will help design a scalable, reliable and flexible surface network architecture to meet the current and future needs of airport operations. This paper describes the systems approach or methodology to networking that was employed to assess airport surface communications requirements, analyze applications, and to define the surface network architecture functions as the building blocks or components of the network. The systems approach used for defining these functions is relatively new to networking. It is viewing the surface network, along with its environment (everything that the surface network interacts with or impacts), as a system. Associated with this system are sets of services that are offered by the network to the rest of the system. Therefore, the surface network is considered as part of the larger system (such as the NAS), with interactions and dependencies between the surface network and its users, applications, and devices. The surface network architecture includes components such as addressing/routing, network management, network

  15. Understanding genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Kauffman, Stuart

    2003-04-01

    Random Boolean networks (RBM) were introduced about 35 years ago as first crude models of genetic regulatory networks. RBNs are comprised of N on-off genes, connected by a randomly assigned regulatory wiring diagram where each gene has K inputs, and each gene is controlled by a randomly assigned Boolean function. This procedure samples at random from the ensemble of all possible NK Boolean networks. The central ideas are to study the typical, or generic properties of this ensemble, and see 1) whether characteristic differences appear as K and biases in Boolean functions are introducted, and 2) whether a subclass of this ensemble has properties matching real cells. Such networks behave in an ordered or a chaotic regime, with a phase transition, "the edge of chaos" between the two regimes. Networks with continuous variables exhibit the same two regimes. Substantial evidence suggests that real cells are in the ordered regime. A key concept is that of an attractor. This is a reentrant trajectory of states of the network, called a state cycle. The central biological interpretation is that cell types are attractors. A number of properties differentiate the ordered and chaotic regimes. These include the size and number of attractors, the existence in the ordered regime of a percolating "sea" of genes frozen in the on or off state, with a remainder of isolated twinkling islands of genes, a power law distribution of avalanches of gene activity changes following perturbation to a single gene in the ordered regime versus a similar power law distribution plus a spike of enormous avalanches of gene changes in the chaotic regime, and the existence of branching pathway of "differentiation" between attractors induced by perturbations in the ordered regime. Noise is serious issue, since noise disrupts attractors. But numerical evidence suggests that attractors can be made very stable to noise, and meanwhile, metaplasias may be a biological manifestation of noise. As we learn more

  16. Regulatory gene networks and the properties of the developmental process

    NASA Technical Reports Server (NTRS)

    Davidson, Eric H.; McClay, David R.; Hood, Leroy

    2003-01-01

    Genomic instructions for development are encoded in arrays of regulatory DNA. These specify large networks of interactions among genes producing transcription factors and signaling components. The architecture of such networks both explains and predicts developmental phenomenology. Although network analysis is yet in its early stages, some fundamental commonalities are already emerging. Two such are the use of multigenic feedback loops to ensure the progressivity of developmental regulatory states and the prevalence of repressive regulatory interactions in spatial control processes. Gene regulatory networks make it possible to explain the process of development in causal terms and eventually will enable the redesign of developmental regulatory circuitry to achieve different outcomes.

  17. Data center networks and network architecture

    NASA Astrophysics Data System (ADS)

    Esaki, Hiroshi

    2014-02-01

    This paper discusses and proposes the architectural framework, which is for data center networks. The data center networks require new technical challenges, and it would be good opportunity to change the functions, which are not need in current and future networks. Based on the observation and consideration on data center networks, this paper proposes; (i) Broadcast-free layer 2 network (i.e., emulation of broadcast at the end-node), (ii) Full-mesh point-to-point pipes, and (iii) IRIDES (Invitation Routing aDvertisement for path Engineering System).

  18. Transcriptional Regulatory Networks in Saccharomyces cerevisiae

    NASA Astrophysics Data System (ADS)

    Lee, Tong Ihn; Rinaldi, Nicola J.; Robert, François; Odom, Duncan T.; Bar-Joseph, Ziv; Gerber, Georg K.; Hannett, Nancy M.; Harbison, Christopher T.; Thompson, Craig M.; Simon, Itamar; Zeitlinger, Julia; Jennings, Ezra G.; Murray, Heather L.; Gordon, D. Benjamin; Ren, Bing; Wyrick, John J.; Tagne, Jean-Bosco; Volkert, Thomas L.; Fraenkel, Ernest; Gifford, David K.; Young, Richard A.

    2002-10-01

    We have determined how most of the transcriptional regulators encoded in the eukaryote Saccharomyces cerevisiae associate with genes across the genome in living cells. Just as maps of metabolic networks describe the potential pathways that may be used by a cell to accomplish metabolic processes, this network of regulator-gene interactions describes potential pathways yeast cells can use to regulate global gene expression programs. We use this information to identify network motifs, the simplest units of network architecture, and demonstrate that an automated process can use motifs to assemble a transcriptional regulatory network structure. Our results reveal that eukaryotic cellular functions are highly connected through networks of transcriptional regulators that regulate other transcriptional regulators.

  19. Regulatory modules controlling maize inflorescence architecture

    PubMed Central

    Eveland, Andrea L.; Goldshmidt, Alexander; Pautler, Michael; Morohashi, Kengo; Liseron-Monfils, Christophe; Lewis, Michael W.; Kumari, Sunita; Hiraga, Susumu; Yang, Fang; Unger-Wallace, Erica; Olson, Andrew; Hake, Sarah; Vollbrecht, Erik; Grotewold, Erich; Ware, Doreen; Jackson, David

    2014-01-01

    Genetic control of branching is a primary determinant of yield, regulating seed number and harvesting ability, yet little is known about the molecular networks that shape grain-bearing inflorescences of cereal crops. Here, we used the maize (Zea mays) inflorescence to investigate gene networks that modulate determinacy, specifically the decision to allow branch growth. We characterized developmental transitions by associating spatiotemporal expression profiles with morphological changes resulting from genetic perturbations that disrupt steps in a pathway controlling branching. Developmental dynamics of genes targeted in vivo by the transcription factor RAMOSA1, a key regulator of determinacy, revealed potential mechanisms for repressing branches in distinct stem cell populations, including interactions with KNOTTED1, a master regulator of stem cell maintenance. Our results uncover discrete developmental modules that function in determining grass-specific morphology and provide a basis for targeted crop improvement and translation to other cereal crops with comparable inflorescence architectures. PMID:24307553

  20. Modeling DNA sequence-based cis-regulatory gene networks.

    PubMed

    Bolouri, Hamid; Davidson, Eric H

    2002-06-01

    Gene network analysis requires computationally based models which represent the functional architecture of regulatory interactions, and which provide directly testable predictions. The type of model that is useful is constrained by the particular features of developmentally active cis-regulatory systems. These systems function by processing diverse regulatory inputs, generating novel regulatory outputs. A computational model which explicitly accommodates this basic concept was developed earlier for the cis-regulatory system of the endo16 gene of the sea urchin. This model represents the genetically mandated logic functions that the system executes, but also shows how time-varying kinetic inputs are processed in different circumstances into particular kinetic outputs. The same basic design features can be utilized to construct models that connect the large number of cis-regulatory elements constituting developmental gene networks. The ultimate aim of the network models discussed here is to represent the regulatory relationships among the genomic control systems of the genes in the network, and to state their functional meaning. The target site sequences of the cis-regulatory elements of these genes constitute the physical basis of the network architecture. Useful models for developmental regulatory networks must represent the genetic logic by which the system operates, but must also be capable of explaining the real time dynamics of cis-regulatory response as kinetic input and output data become available. Most importantly, however, such models must display in a direct and transparent manner fundamental network design features such as intra- and intercellular feedback circuitry; the sources of parallel inputs into each cis-regulatory element; gene battery organization; and use of repressive spatial inputs in specification and boundary formation. Successful network models lead to direct tests of key architectural features by targeted cis-regulatory analysis. PMID

  1. Building Developmental Gene Regulatory Networks

    PubMed Central

    Li, Enhu; Davidson, Eric H.

    2009-01-01

    Animal development is an elaborate process programmed by genomic regulatory instructions. Regulatory genes encode transcription factors and signal molecules, and their expression is under the control of cis-regulatory modules that define the logic of transcriptional responses to the inputs of other regulatory genes. The functional linkages amongst regulatory genes constitute the gene regulatory networks (GRNs) that govern cell specification and patterning in development. Constructing such networks requires identification of the regulatory genes involved and characterization of their temporal and spatial expression patterns. Interactions (activation/repression) among transcription factors or signals can be investigated by large-scale perturbation analysis, in which the function of each gene is specifically blocked. Resultant expression changes are then integrated to identify direct linkages, and to reveal the structure of the GRN. Predicted GRN linkages can be tested and verified by cis-regulatory analysis. The explanatory power of the GRN was shown in the lineage specification of sea urchin endomesoderm. Acquiring such networks is essential for a systematic and mechanistic understanding of the developmental process. PMID:19530131

  2. Sensor Network Architectures for Monitoring Underwater Pipelines

    PubMed Central

    Mohamed, Nader; Jawhar, Imad; Al-Jaroodi, Jameela; Zhang, Liren

    2011-01-01

    This paper develops and compares different sensor network architecture designs that can be used for monitoring underwater pipeline infrastructures. These architectures are underwater wired sensor networks, underwater acoustic wireless sensor networks, RF (Radio Frequency) wireless sensor networks, integrated wired/acoustic wireless sensor networks, and integrated wired/RF wireless sensor networks. The paper also discusses the reliability challenges and enhancement approaches for these network architectures. The reliability evaluation, characteristics, advantages, and disadvantages among these architectures are discussed and compared. Three reliability factors are used for the discussion and comparison: the network connectivity, the continuity of power supply for the network, and the physical network security. In addition, the paper also develops and evaluates a hierarchical sensor network framework for underwater pipeline monitoring. PMID:22346669

  3. Sparse Regulatory Networks

    PubMed Central

    James, Gareth M.; Sabatti, Chiara; Zhou, Nengfeng; Zhu, Ji

    2011-01-01

    In many organisms the expression levels of each gene are controlled by the activation levels of known “Transcription Factors” (TF). A problem of considerable interest is that of estimating the “Transcription Regulation Networks” (TRN) relating the TFs and genes. While the expression levels of genes can be observed, the activation levels of the corresponding TFs are usually unknown, greatly increasing the difficulty of the problem. Based on previous experimental work, it is often the case that partial information about the TRN is available. For example, certain TFs may be known to regulate a given gene or in other cases a connection may be predicted with a certain probability. In general, the biology of the problem indicates there will be very few connections between TFs and genes. Several methods have been proposed for estimating TRNs. However, they all suffer from problems such as unrealistic assumptions about prior knowledge of the network structure or computational limitations. We propose a new approach that can directly utilize prior information about the network structure in conjunction with observed gene expression data to estimate the TRN. Our approach uses L1 penalties on the network to ensure a sparse structure. This has the advantage of being computationally efficient as well as making many fewer assumptions about the network structure. We use our methodology to construct the TRN for E. coli and show that the estimate is biologically sensible and compares favorably with previous estimates. PMID:21625366

  4. Bipartite memory network architectures for parallel processing

    SciTech Connect

    Smith, W.; Kale, L.V. . Dept. of Computer Science)

    1990-01-01

    Parallel architectures are boradly classified as either shared memory or distributed memory architectures. In this paper, the authors propose a third family of architectures, called bipartite memory network architectures. In this architecture, processors and memory modules constitute a bipartite graph, where each processor is allowed to access a small subset of the memory modules, and each memory module allows access from a small set of processors. The architecture is particularly suitable for computations requiring dynamic load balancing. The authors explore the properties of this architecture by examining the Perfect Difference set based topology for the graph. Extensions of this topology are also suggested.

  5. Plant Evolution: Evolving Antagonistic Gene Regulatory Networks.

    PubMed

    Cooper, Endymion D

    2016-06-20

    Developing a structurally complex phenotype requires a complex regulatory network. A new study shows how gene duplication provides a potential source of antagonistic interactions, an important component of gene regulatory networks. PMID:27326708

  6. Array processor architecture connection network

    NASA Technical Reports Server (NTRS)

    Barnes, George H. (Inventor); Lundstrom, Stephen F. (Inventor); Shafer, Philip E. (Inventor)

    1982-01-01

    A connection network is disclosed for use between a parallel array of processors and a parallel array of memory modules for establishing non-conflicting data communications paths between requested memory modules and requesting processors. The connection network includes a plurality of switching elements interposed between the processor array and the memory modules array in an Omega networking architecture. Each switching element includes a first and a second processor side port, a first and a second memory module side port, and control logic circuitry for providing data connections between the first and second processor ports and the first and second memory module ports. The control logic circuitry includes strobe logic for examining data arriving at the first and the second processor ports to indicate when the data arriving is requesting data from a requesting processor to a requested memory module. Further, connection circuitry is associated with the strobe logic for examining requesting data arriving at the first and the second processor ports for providing a data connection therefrom to the first and the second memory module ports in response thereto when the data connection so provided does not conflict with a pre-established data connection currently in use.

  7. The NASA Space Communications Data Networking Architecture

    NASA Technical Reports Server (NTRS)

    Israel, David J.; Hooke, Adrian J.; Freeman, Kenneth; Rush, John J.

    2006-01-01

    The NASA Space Communications Architecture Working Group (SCAWG) has recently been developing an integrated agency-wide space communications architecture in order to provide the necessary communication and navigation capabilities to support NASA's new Exploration and Science Programs. A critical element of the space communications architecture is the end-to-end Data Networking Architecture, which must provide a wide range of services required for missions ranging from planetary rovers to human spaceflight, and from sub-orbital space to deep space. Requirements for a higher degree of user autonomy and interoperability between a variety of elements must be accommodated within an architecture that necessarily features minimum operational complexity. The architecture must also be scalable and evolvable to meet mission needs for the next 25 years. This paper will describe the recommended NASA Data Networking Architecture, present some of the rationale for the recommendations, and will illustrate an application of the architecture to example NASA missions.

  8. ATMTN: a telemammography network architecture.

    PubMed

    Sheybani, Ehsan O; Sankar, Ravi

    2002-12-01

    One of the goals of the National Cancer Institute (NCI) to reach more than 80% of eligible women in mammography screening by the year 2000 yet remains as a challenge. In fact, a recent medical report reveals that while other types of cancer are experiencing negative growth, breast cancer has been the only one with a positive growth rate over the last few years. This is primarily due to the fact that 1) examination process is a complex and lengthy one and 2) it is not available to the majority of women who live in remote sites. Currently for mammography screening, women have to go to doctors or cancer centers/hospitals annually while high-risk patients may have to visit more often. One way to resolve these problems is by the use of advanced networking technologies and signal processing algorithms. On one hand, software modules can help detect, with high precision, true negatives (TN), while marking true positives (TP) for further investigation. Unavoidably, in this process some false negatives (FN) will be generated that are potentially life threatening; however, inclusion of the detection software improves the TP detection and, hence, reduces FNs drastically. Since TNs are the majority of examinations on a randomly selected population, this first step reduces the load on radiologists by a tremendous amount. On the other hand, high-speed networking equipment can accelerate the required clinic-lab connection and make detection, segmentation, and image enhancement algorithms readily available to the radiologists. This will bring the breast cancer care, caregiver, and the facilities to the patients and expand diagnostics and treatment to the remote sites. This research describes asynchronous transfer mode telemammography network (ATMTN) architecture for real-time, online screening, detection and diagnosis of breast cancer. ATMTN is a unique high-speed network integrated with automatic robust computer-assisted diagnosis-detection/digital signal processing (CAD

  9. Robustness and Accuracy in Sea Urchin Developmental Gene Regulatory Networks

    PubMed Central

    Ben-Tabou de-Leon, Smadar

    2016-01-01

    Developmental gene regulatory networks robustly control the timely activation of regulatory and differentiation genes. The structure of these networks underlies their capacity to buffer intrinsic and extrinsic noise and maintain embryonic morphology. Here I illustrate how the use of specific architectures by the sea urchin developmental regulatory networks enables the robust control of cell fate decisions. The Wnt-βcatenin signaling pathway patterns the primary embryonic axis while the BMP signaling pathway patterns the secondary embryonic axis in the sea urchin embryo and across bilateria. Interestingly, in the sea urchin in both cases, the signaling pathway that defines the axis controls directly the expression of a set of downstream regulatory genes. I propose that this direct activation of a set of regulatory genes enables a uniform regulatory response and a clear cut cell fate decision in the endoderm and in the dorsal ectoderm. The specification of the mesodermal pigment cell lineage is activated by Delta signaling that initiates a triple positive feedback loop that locks down the pigment specification state. I propose that the use of compound positive feedback circuitry provides the endodermal cells enough time to turn off mesodermal genes and ensures correct mesoderm vs. endoderm fate decision. Thus, I argue that understanding the control properties of repeatedly used regulatory architectures illuminates their role in embryogenesis and provides possible explanations to their resistance to evolutionary change. PMID:26913048

  10. A Communications Network Architecture for Future Mars Missions

    NASA Astrophysics Data System (ADS)

    Gilstrap, R.; Alena, R.; Stone, T.

    2012-06-01

    We propose a Mars communications network architecture incorporating the Internet Protocol, small communications relay satellites, laser communications, delay tolerant networking, mobile ad hoc networking, and wireless sensor networks.

  11. Evolution of Cis-Regulatory Elements and Regulatory Networks in Duplicated Genes of Arabidopsis1[OPEN

    PubMed Central

    Guo, Xu Qiu; Adams, Keith L.

    2015-01-01

    Plant genomes contain large numbers of duplicated genes that contribute to the evolution of new functions. Following duplication, genes can exhibit divergence in their coding sequence and their expression patterns. Changes in the cis-regulatory element landscape can result in changes in gene expression patterns. High-throughput methods developed recently can identify potential cis-regulatory elements on a genome-wide scale. Here, we use a recent comprehensive data set of DNase I sequencing-identified cis-regulatory binding sites (footprints) at single-base-pair resolution to compare binding sites and network connectivity in duplicated gene pairs in Arabidopsis (Arabidopsis thaliana). We found that duplicated gene pairs vary greatly in their cis-regulatory element architecture, resulting in changes in regulatory network connectivity. Whole-genome duplicates (WGDs) have approximately twice as many footprints in their promoters left by potential regulatory proteins than do tandem duplicates (TDs). The WGDs have a greater average number of footprint differences between paralogs than TDs. The footprints, in turn, result in more regulatory network connections between WGDs and other genes, forming denser, more complex regulatory networks than shown by TDs. When comparing regulatory connections between duplicates, WGDs had more pairs in which the two genes are either partially or fully diverged in their network connections, but fewer genes with no network connections than the TDs. There is evidence of younger TDs and WGDs having fewer unique connections compared with older duplicates. This study provides insights into cis-regulatory element evolution and network divergence in duplicated genes. PMID:26474639

  12. Regulatory modules controlling maize inflorescence architecture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Genetic control of branching is a primary determinant of yield, regulating seed number and harvesting ability, yet little is known about the molecular networks that shape grain-bearing inflorescences of cereal crops. Here, we used the maize (Zea mays) inflorescence to investigate gene networks that...

  13. Scalable Network Emulator Architecture for IP Optical Network Management

    NASA Astrophysics Data System (ADS)

    Oki, Eiji; Kitsuwan, Nattapong; Tsunoda, Shunichi; Miyamura, Takashi; Masuda, Akeo; Shiomoto, Kohei

    This letter proposes a scalable network emulator architecture to support IP optical network management. The network emulator uses the same router interfaces to communicate with the IP optical TE server as the actual IP optical network, and behaves as an actual IP optical network between the interfaces. The network emulator mainly consists of databases and three modules: interface module, resource simulator module, and traffic generator module. To make the network emulator scalable in terms of network size, we employ TCP/IP socket communications between the modules. The proposed network emulator has the benefit that its implementation is not strongly dependent on hardware limitations. We develop a prototype of the network emulator based on the proposed architecture. Our design and experiments show that the proposed architecture is effective.

  14. Hybrid architecture for building secure sensor networks

    NASA Astrophysics Data System (ADS)

    Owens, Ken R., Jr.; Watkins, Steve E.

    2012-04-01

    Sensor networks have various communication and security architectural concerns. Three approaches are defined to address these concerns for sensor networks. The first area is the utilization of new computing architectures that leverage embedded virtualization software on the sensor. Deploying a small, embedded virtualization operating system on the sensor nodes that is designed to communicate to low-cost cloud computing infrastructure in the network is the foundation to delivering low-cost, secure sensor networks. The second area focuses on securing the sensor. Sensor security components include developing an identification scheme, and leveraging authentication algorithms and protocols that address security assurance within the physical, communication network, and application layers. This function will primarily be accomplished through encrypting the communication channel and integrating sensor network firewall and intrusion detection/prevention components to the sensor network architecture. Hence, sensor networks will be able to maintain high levels of security. The third area addresses the real-time and high priority nature of the data that sensor networks collect. This function requires that a quality-of-service (QoS) definition and algorithm be developed for delivering the right data at the right time. A hybrid architecture is proposed that combines software and hardware features to handle network traffic with diverse QoS requirements.

  15. Circuitry and dynamics of human transcription factor regulatory networks

    PubMed Central

    Neph, Shane; Stergachis, Andrew B.; Reynolds, Alex; Sandstrom, Richard; Borenstein, Elhanan; Stamatoyannopoulos, John A.

    2012-01-01

    SUMMARY The combinatorial cross-regulation of hundreds of sequence-specific transcription factors defines a regulatory network that underlies cellular identity and function. Here we use genome-wide maps of in vivo DNaseI footprints to assemble an extensive core human regulatory network comprising connections among 475 sequence-specific transcription factors, and to analyze the dynamics of these connections across 41 diverse cell and tissue types. We find that human transcription factor networks are highly cell-selective and are driven by cohorts of factors that include regulators with previously unrecognized roles in control of cellular identity. Moreover, we identify many widely expressed factors that impact transcriptional regulatory networks in a cell-selective manner. Strikingly, in spite of their inherent diversity, all cell type regulatory networks independently converge on a common architecture that closely resembles the topology of living neuronal networks. Together, our results provide the first description of the circuitry, dynamics, and organizing principles of the human transcription factor regulatory network. PMID:22959076

  16. Advancements in metro optical network architectures

    NASA Astrophysics Data System (ADS)

    Paraschis, Loukas

    2005-02-01

    This paper discusses the innovation in network architectures, and optical transport, that enables metropolitan networks to cost-effectively scale to hundreds Gb/s of capacity, and to hundreds km of reach, and to also meet the diverse service needs of enterprise and residential applications. A converged metro network, where Ethernet/IP services, and traditional TDM traffic operate over an intelligent WDM transport layer is increasingly becoming the most attractive architecture addressing the primary need of network operators for significantly improved capital and operational network cost. At the same time, this converged network has to leverage advanced technology, and introduce intelligence in order to significantly improve the deployment and manageability of WDM transport. The most important system advancements and the associated technology innovations that enhance the cost-effectiveness of metropolitan optical networks are being reviewed.

  17. The Functional Consequences of Mutualistic Network Architecture

    PubMed Central

    Gómez, José M.; Perfectti, Francisco; Jordano, Pedro

    2011-01-01

    The architecture and properties of many complex networks play a significant role in the functioning of the systems they describe. Recently, complex network theory has been applied to ecological entities, like food webs or mutualistic plant-animal interactions. Unfortunately, we still lack an accurate view of the relationship between the architecture and functioning of ecological networks. In this study we explore this link by building individual-based pollination networks from eight Erysimum mediohispanicum (Brassicaceae) populations. In these individual-based networks, each individual plant in a population was considered a node, and was connected by means of undirected links to conspecifics sharing pollinators. The architecture of these unipartite networks was described by means of nestedness, connectivity and transitivity. Network functioning was estimated by quantifying the performance of the population described by each network as the number of per-capita juvenile plants produced per population. We found a consistent relationship between the topology of the networks and their functioning, since variation across populations in the average per-capita production of juvenile plants was positively and significantly related with network nestedness, connectivity and clustering. Subtle changes in the composition of diverse pollinator assemblages can drive major consequences for plant population performance and local persistence through modifications in the structure of the inter-plant pollination networks. PMID:21283583

  18. Network architecture functional description and design

    SciTech Connect

    Stans, L.; Bencoe, M.; Brown, D.; Kelly, S.; Pierson, L.; Schaldach, C.

    1989-05-25

    This report provides a top level functional description and design for the development and implementation of the central network to support the next generation of SNL, Albuquerque supercomputer in a UNIX{reg sign} environment. It describes the network functions and provides an architecture and topology.

  19. A security architecture for health information networks.

    PubMed

    Kailar, Rajashekar; Muralidhar, Vinod

    2007-01-01

    Health information network security needs to balance exacting security controls with practicality, and ease of implementation in today's healthcare enterprise. Recent work on 'nationwide health information network' architectures has sought to share highly confidential data over insecure networks such as the Internet. Using basic patterns of health network data flow and trust models to support secure communication between network nodes, we abstract network security requirements to a core set to enable secure inter-network data sharing. We propose a minimum set of security controls that can be implemented without needing major new technologies, but yet realize network security and privacy goals of confidentiality, integrity and availability. This framework combines a set of technology mechanisms with environmental controls, and is shown to be sufficient to counter commonly encountered network security threats adequately. PMID:18693862

  20. Satellite ATM Networks: Architectures and Guidelines Developed

    NASA Technical Reports Server (NTRS)

    vonDeak, Thomas C.; Yegendu, Ferit

    1999-01-01

    An important element of satellite-supported asynchronous transfer mode (ATM) networking will involve support for the routing and rerouting of active connections. Work published under the auspices of the Telecommunications Industry Association (http://www.tiaonline.org), describes basic architectures and routing protocol issues for satellite ATM (SATATM) networks. The architectures and issues identified will serve as a basis for further development of technical specifications for these SATATM networks. Three ATM network architectures for bent pipe satellites and three ATM network architectures for satellites with onboard ATM switches were developed. The architectures differ from one another in terms of required level of mobility, supported data rates, supported terrestrial interfaces, and onboard processing and switching requirements. The documentation addresses low-, middle-, and geosynchronous-Earth-orbit satellite configurations. The satellite environment may require real-time routing to support the mobility of end devices and nodes of the ATM network itself. This requires the network to be able to reroute active circuits in real time. In addition to supporting mobility, rerouting can also be used to (1) optimize network routing, (2) respond to changing quality-of-service requirements, and (3) provide a fault tolerance mechanism. Traffic management and control functions are necessary in ATM to ensure that the quality-of-service requirements associated with each connection are not violated and also to provide flow and congestion control functions. Functions related to traffic management were identified and described. Most of these traffic management functions will be supported by on-ground ATM switches, but in a hybrid terrestrial-satellite ATM network, some of the traffic management functions may have to be supported by the onboard satellite ATM switch. Future work is planned to examine the tradeoffs of placing traffic management functions onboard a satellite as

  1. Regulatory architecture determines optimal regulation of gene expression in metabolic pathways

    PubMed Central

    Chubukov, Victor; Zuleta, Ignacio A.; Li, Hao

    2012-01-01

    In response to environmental changes, the connections (“arrows”) in gene regulatory networks determine which genes modulate their expression, but the quantitative parameters of the network (“the numbers on the arrows”) are equally important in determining the resulting phenotype. What are the objectives and constraints by which evolution determines these parameters? We explore these issues by analyzing gene expression changes in a number of yeast metabolic pathways in response to nutrient depletion. We find that a striking pattern emerges that couples the regulatory architecture of the pathway to the gene expression response. In particular, we find that pathways controlled by the intermediate metabolite activation (IMA) architecture, in which an intermediate metabolite activates transcription of pathway genes, exhibit the following response: the enzyme immediately downstream of the regulatory metabolite is under the strongest transcriptional control, whereas the induction of the enzymes upstream of the regulatory intermediate is relatively weak. This pattern of responses is absent in pathways not controlled by an IMA architecture. The observation can be explained by the constraint imposed by the fundamental feedback structure of the network, which places downstream enzymes under a negative feedback loop and upstream ones under a positive feedback loop. This general design principle for transcriptional control of a metabolic pathway can be derived from a simple cost/benefit model of gene expression, in which the observed pattern is an optimal solution. Our results suggest that the parameters regulating metabolic enzyme expression are optimized by evolution, under the strong constraint of the underlying regulatory architecture. PMID:22416120

  2. Architecture and Connectivity Govern Actin Network Contractility.

    PubMed

    Ennomani, Hajer; Letort, Gaëlle; Guérin, Christophe; Martiel, Jean-Louis; Cao, Wenxiang; Nédélec, François; De La Cruz, Enrique M; Théry, Manuel; Blanchoin, Laurent

    2016-03-01

    Actomyosin contractility plays a central role in a wide range of cellular processes, including the establishment of cell polarity, cell migration, tissue integrity, and morphogenesis during development. The contractile response is variable and depends on actomyosin network architecture and biochemical composition. To determine how this coupling regulates actomyosin-driven contraction, we used a micropatterning method that enables the spatial control of actin assembly. We generated a variety of actin templates and measured how defined actin structures respond to myosin-induced forces. We found that the same actin filament crosslinkers either enhance or inhibit the contractility of a network, depending on the organization of actin within the network. Numerical simulations unified the roles of actin filament branching and crosslinking during actomyosin contraction. Specifically, we introduce the concept of "network connectivity" and show that the contractions of distinct actin architectures are described by the same master curve when considering their degree of connectivity. This makes it possible to predict the dynamic response of defined actin structures to transient changes in connectivity. We propose that, depending on the connectivity and the architecture, network contraction is dominated by either sarcomeric-like or buckling mechanisms. More generally, this study reveals how actin network contractility depends on its architecture under a defined set of biochemical conditions. PMID:26898468

  3. Modeling of hysteresis in gene regulatory networks.

    PubMed

    Hu, J; Qin, K R; Xiang, C; Lee, T H

    2012-08-01

    Hysteresis, observed in many gene regulatory networks, has a pivotal impact on biological systems, which enhances the robustness of cell functions. In this paper, a general model is proposed to describe the hysteretic gene regulatory network by combining the hysteresis component and the transient dynamics. The Bouc-Wen hysteresis model is modified to describe the hysteresis component in the mammalian gene regulatory networks. Rigorous mathematical analysis on the dynamical properties of the model is presented to ensure the bounded-input-bounded-output (BIBO) stability and demonstrates that the original Bouc-Wen model can only generate a clockwise hysteresis loop while the modified model can describe both clockwise and counter clockwise hysteresis loops. Simulation studies have shown that the hysteresis loops from our model are consistent with the experimental observations in three mammalian gene regulatory networks and two E.coli gene regulatory networks, which demonstrate the ability and accuracy of the mathematical model to emulate natural gene expression behavior with hysteresis. A comparison study has also been conducted to show that this model fits the experiment data significantly better than previous ones in the literature. The successful modeling of the hysteresis in all the five hysteretic gene regulatory networks suggests that the new model has the potential to be a unified framework for modeling hysteresis in gene regulatory networks and provide better understanding of the general mechanism that drives the hysteretic function. PMID:22588784

  4. Integrated Network Architecture for NASA's Orion Missions

    NASA Technical Reports Server (NTRS)

    Bhasin, Kul B.; Hayden, Jeffrey L.; Sartwell, Thomas; Miller, Ronald A.; Hudiburg, John J.

    2008-01-01

    NASA is planning a series of short and long duration human and robotic missions to explore the Moon and then Mars. The series of missions will begin with a new crew exploration vehicle (called Orion) that will initially provide crew exchange and cargo supply support to the International Space Station (ISS) and then become a human conveyance for travel to the Moon. The Orion vehicle will be mounted atop the Ares I launch vehicle for a series of pre-launch tests and then launched and inserted into low Earth orbit (LEO) for crew exchange missions to the ISS. The Orion and Ares I comprise the initial vehicles in the Constellation system of systems that later includes Ares V, Earth departure stage, lunar lander, and other lunar surface systems for the lunar exploration missions. These key systems will enable the lunar surface exploration missions to be initiated in 2018. The complexity of the Constellation system of systems and missions will require a communication and navigation infrastructure to provide low and high rate forward and return communication services, tracking services, and ground network services. The infrastructure must provide robust, reliable, safe, sustainable, and autonomous operations at minimum cost while maximizing the exploration capabilities and science return. The infrastructure will be based on a network of networks architecture that will integrate NASA legacy communication, modified elements, and navigation systems. New networks will be added to extend communication, navigation, and timing services for the Moon missions. Internet protocol (IP) and network management systems within the networks will enable interoperability throughout the Constellation system of systems. An integrated network architecture has developed based on the emerging Constellation requirements for Orion missions. The architecture, as presented in this paper, addresses the early Orion missions to the ISS with communication, navigation, and network services over five

  5. Improving neural network performance on SIMD architectures

    NASA Astrophysics Data System (ADS)

    Limonova, Elena; Ilin, Dmitry; Nikolaev, Dmitry

    2015-12-01

    Neural network calculations for the image recognition problems can be very time consuming. In this paper we propose three methods of increasing neural network performance on SIMD architectures. The usage of SIMD extensions is a way to speed up neural network processing available for a number of modern CPUs. In our experiments, we use ARM NEON as SIMD architecture example. The first method deals with half float data type for matrix computations. The second method describes fixed-point data type for the same purpose. The third method considers vectorized activation functions implementation. For each method we set up a series of experiments for convolutional and fully connected networks designed for image recognition task.

  6. Satellite Networks: Architectures, Applications, and Technologies

    NASA Technical Reports Server (NTRS)

    Bhasin, Kul (Compiler)

    1998-01-01

    Since global satellite networks are moving to the forefront in enhancing the national and global information infrastructures due to communication satellites' unique networking characteristics, a workshop was organized to assess the progress made to date and chart the future. This workshop provided the forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. Presentations on overview, state-of-the-art in research, development, deployment and applications and future trends on satellite networks are assembled.

  7. A Layered Approach To Pacs Network Architecture

    NASA Astrophysics Data System (ADS)

    Hegde, Shankar S.; Prewitt, Judith M.

    1984-08-01

    Although the functions performed by the different nodes on the PACS network are many, it is possible to formulate a minimum set of service primitives such that the application software residing at the nodes can utilize those primitives to perform the functions. These primitives define the framework for the communication interface. The question of how these primitives fit into the concept of a layered network architecture is explored in this paper. The OSI model as applicable to the PACS network is described, the areas that need standardization are briefly mentioned, and the ongoing standardization efforts are addressed from the OSI perspective.

  8. Fast notification architecture for wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Hahk

    2013-03-01

    In an emergency, since it is vital to transmit the message to the users immediately after analysing the data to prevent disaster, this article presents the deployment of a fast notification architecture for a wireless sensor network. The sensor nodes of the proposed architecture can monitor an emergency situation periodically and transmit the sensing data, immediately to the sink node. We decide on the grade of fire situation according to the decision rule using the sensing values of temperature, CO, smoke density and temperature increasing rate. On the other hand, to estimate the grade of air pollution, the sensing data, such as dust, formaldehyde, NO2, CO2, is applied to the given knowledge model. Since the sink node in the architecture has a ZigBee interface, it can transmit the alert messages in real time according to analysed results received from the host server to the terminals equipped with a SIM card-type ZigBee module. Also, the host server notifies the situation to the registered users who have cellular phone through short message service server of the cellular network. Thus, the proposed architecture can adapt an emergency situation dynamically compared to the conventional architecture using video processing. In the testbed, after generating air pollution and fire data, the terminal receives the message in less than 3 s. In the test results, this system can also be applied to buildings and public areas where many people gather together, to prevent unexpected disasters in urban settings.

  9. The architecture of the climate network

    NASA Astrophysics Data System (ADS)

    Tsonis, A. A.; Roebber, P. J.

    2004-02-01

    We consider climate as a network of many dynamical systems and apply ideas from graph theory to a global data set to study its collective behavior. We find that the network has properties of ‘small-world’ networks (Nature 393 (1999) 440). A detailed investigation of the coupling architecture of this network reveals that the overall dynamics emerge from the interaction of two interweaved subnetworks. One subnetwork operates in the tropics and the other at higher latitudes with the equatorial one acting as an agent that establishes links between the two hemispheres. Both subsystems are ‘small-world’ networks, but there are distinct differences between the two subsystems. The tropical one is an almost fully connected network, whereas the mid-latitude one is more like a scale-free network characterized by dominant super nodes, and multifractal properties. This unique architecture may lead to new insights not only about the dynamics of the climate system but of other spatially extended complex systems with a large number of degrees of freedom.

  10. GREAT: a web portal for Genome Regulatory Architecture Tools.

    PubMed

    Bouyioukos, Costas; Bucchini, François; Elati, Mohamed; Képès, François

    2016-07-01

    GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading. PMID:27151196

  11. GREAT: a web portal for Genome Regulatory Architecture Tools

    PubMed Central

    Bouyioukos, Costas; Bucchini, François; Elati, Mohamed; Képès, François

    2016-01-01

    GREAT (Genome REgulatory Architecture Tools) is a novel web portal for tools designed to generate user-friendly and biologically useful analysis of genome architecture and regulation. The online tools of GREAT are freely accessible and compatible with essentially any operating system which runs a modern browser. GREAT is based on the analysis of genome layout -defined as the respective positioning of co-functional genes- and its relation with chromosome architecture and gene expression. GREAT tools allow users to systematically detect regular patterns along co-functional genomic features in an automatic way consisting of three individual steps and respective interactive visualizations. In addition to the complete analysis of regularities, GREAT tools enable the use of periodicity and position information for improving the prediction of transcription factor binding sites using a multi-view machine learning approach. The outcome of this integrative approach features a multivariate analysis of the interplay between the location of a gene and its regulatory sequence. GREAT results are plotted in web interactive graphs and are available for download either as individual plots, self-contained interactive pages or as machine readable tables for downstream analysis. The GREAT portal can be reached at the following URL https://absynth.issb.genopole.fr/GREAT and each individual GREAT tool is available for downloading. PMID:27151196

  12. LINCS: Livermore's network architecture. [Octopus computing network

    SciTech Connect

    Fletcher, J.G.

    1982-01-01

    Octopus, a local computing network that has been evolving at the Lawrence Livermore National Laboratory for over fifteen years, is currently undergoing a major revision. The primary purpose of the revision is to consolidate and redefine the variety of conventions and formats, which have grown up over the years, into a single standard family of protocols, the Livermore Interactive Network Communication Standard (LINCS). This standard treats the entire network as a single distributed operating system such that access to a computing resource is obtained in a single way, whether that resource is local (on the same computer as the accessing process) or remote (on another computer). LINCS encompasses not only communication but also such issues as the relationship of customer to server processes and the structure, naming, and protection of resources. The discussion includes: an overview of the Livermore user community and computing hardware, the functions and structure of each of the seven layers of LINCS protocol, the reasons why we have designed our own protocols and why we are dissatisfied by the directions that current protocol standards are taking.

  13. Propagation of genetic variation in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Plahte, Erik; Gjuvsland, Arne B.; Omholt, Stig W.

    2013-08-01

    A future quantitative genetics theory should link genetic variation to phenotypic variation in a causally cohesive way based on how genes actually work and interact. We provide a theoretical framework for predicting and understanding the manifestation of genetic variation in haploid and diploid regulatory networks with arbitrary feedback structures and intra-locus and inter-locus functional dependencies. Using results from network and graph theory, we define propagation functions describing how genetic variation in a locus is propagated through the network, and show how their derivatives are related to the network’s feedback structure. Similarly, feedback functions describe the effect of genotypic variation of a locus on itself, either directly or mediated by the network. A simple sign rule relates the sign of the derivative of the feedback function of any locus to the feedback loops involving that particular locus. We show that the sign of the phenotypically manifested interaction between alleles at a diploid locus is equal to the sign of the dominant feedback loop involving that particular locus, in accordance with recent results for a single locus system. Our results provide tools by which one can use observable equilibrium concentrations of gene products to disclose structural properties of the network architecture. Our work is a step towards a theory capable of explaining the pleiotropy and epistasis features of genetic variation in complex regulatory networks as functions of regulatory anatomy and functional location of the genetic variation.

  14. Architectures of fiber optic network in telecommunications

    NASA Astrophysics Data System (ADS)

    Vasile, Irina B.; Vasile, Alexandru; Filip, Luminita E.

    2005-08-01

    The operators of telecommunications have targeted their efforts towards realizing applications using broad band fiber optics systems in the access network. Thus, a new concept related to the implementation of fiber optic transmission systems, named FITL (Fiber In The Loop) has appeared. The fiber optic transmission systems have been extensively used for realizing the transport and intercommunication of the public telecommunication network, as well as for assuring the access to the telecommunication systems of the great corporations. Still, the segment of the residential users and small corporations did not benefit on large scale of this technology implementation. For the purpose of defining fiber optic applications, more types of architectures were conceived, like: bus, ring, star, tree. In the case of tree-like networks passive splitters (that"s where the name of PON comes from - Passive Optical Network-), which reduce significantly the costs of the fiber optic access, by separating the costs of the optical electronic components. That's why the passive fiber optics architectures (PON represent a viable solution for realizing the access at the user's loop. The main types of fiber optics architectures included in this work are: FTTC (Fiber To The Curb); FTTB (Fiber To The Building); FTTH (Fiber To The Home).

  15. Mutational Robustness of Gene Regulatory Networks

    PubMed Central

    van Dijk, Aalt D. J.; van Mourik, Simon; van Ham, Roeland C. H. J.

    2012-01-01

    Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor – target gene interactions) but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive). In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence. PMID:22295094

  16. The influence of promoter architectures and regulatory motifs on gene expression in Escherichia coli.

    PubMed

    Rydenfelt, Mattias; Garcia, Hernan G; Cox, Robert Sidney; Phillips, Rob

    2014-01-01

    The ability to regulate gene expression is of central importance for the adaptability of living organisms to changes in their external and internal environment. At the transcriptional level, binding of transcription factors (TFs) in the promoter region can modulate the transcription rate, hence making TFs central players in gene regulation. For some model organisms, information about the locations and identities of discovered TF binding sites have been collected in continually updated databases, such as RegulonDB for the well-studied case of E. coli. In order to reveal the general principles behind the binding-site arrangement and function of these regulatory architectures we propose a random promoter architecture model that preserves the overall abundance of binding sites to identify overrepresented binding site configurations. This model is analogous to the random network model used in the study of genetic network motifs, where regulatory motifs are identified through their overrepresentation with respect to a "randomly connected" genetic network. Using our model we identify TF pairs which coregulate operons in an overrepresented fashion, or individual TFs which act at multiple binding sites per promoter by, for example, cooperative binding, DNA looping, or through multiple binding domains. We furthermore explore the relationship between promoter architecture and gene expression, using three different genome-wide protein copy number censuses. Perhaps surprisingly, we find no systematic correlation between the number of activator and repressor binding sites regulating a gene and the level of gene expression. A position-weight-matrix model used to estimate the binding affinity of RNA polymerase (RNAP) to the promoters of activated and repressed genes suggests that this lack of correlation might in part be due to differences in basal transcription levels, with repressed genes having a higher basal activity level. This quantitative catalogue relating promoter

  17. Genomic analysis of regulatory network dynamics reveals large topological changes

    NASA Astrophysics Data System (ADS)

    Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

    2004-09-01

    Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

  18. Reconstructing transcriptional regulatory networks through genomics data

    PubMed Central

    Sun, Ning; Zhao, Hongyu

    2013-01-01

    One central problem in biology is to understand how gene expression is regulated under different conditions. Microarray gene expression data and other high throughput data have made it possible to dissect transcriptional regulatory networks at the genomics level. Owing to the very large number of genes that need to be studied, the relatively small number of data sets available, the noise in the data and the different natures of the distinct data types, network inference presents great challenges. In this article, we review statistical and computational methods that have been developed in the last decade in response to genomics data for inferring transcriptional regulatory networks. PMID:20048387

  19. Autonomous Boolean modeling of gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Socolar, Joshua; Sun, Mengyang; Cheng, Xianrui

    2014-03-01

    In cases where the dynamical properties of gene regulatory networks are important, a faithful model must include three key features: a network topology; a functional response of each element to its inputs; and timing information about the transmission of signals across network links. Autonomous Boolean network (ABN) models are efficient representations of these elements and are amenable to analysis. We present an ABN model of the gene regulatory network governing cell fate specification in the early sea urchin embryo, which must generate three bands of distinct tissue types after several cell divisions, beginning from an initial condition with only two distinct cell types. Analysis of the spatial patterning problem and the dynamics of a network constructed from available experimental results reveals that a simple mechanism is at work in this case. Supported by NSF Grant DMS-10-68602

  20. Complete subunit architecture of the proteasome regulatory particle

    PubMed Central

    Lander, Gabriel C.; Estrin, Eric; Matyskiela, Mary E.; Bashore, Charlene; Nogales, Eva; Martin, Andreas

    2011-01-01

    The proteasome is the major ATP-dependent protease in eukaryotic cells, but limited structural information strongly restricts a mechanistic understanding of its activities. The proteasome regulatory particle, consisting of the lid and base subcomplexes, recognizes and processes poly-ubiquitinated substrates. We used electron microscopy and a newly-developed heterologous expression system for the lid to delineate the complete subunit architecture of the regulatory particle. Our studies reveal the spatial arrangement of ubiquitin receptors, deubiquitinating enzymes, and the protein unfolding machinery at subnanometer resolution, outlining the substrate’s path to degradation. Unexpectedly, the ATPase subunits within the base unfoldase are arranged in a spiral staircase, providing insight into potential mechanisms for substrate translocation through the central pore. Large conformational rearrangements of the lid upon holoenzyme formation suggest allosteric regulation of deubiquitination. We provide a structural basis for the ability of the proteasome to degrade a diverse set of substrates and thus regulate vital cellular processes. PMID:22237024

  1. Stabilizing gene regulatory networks through feedforward loops

    NASA Astrophysics Data System (ADS)

    Kadelka, C.; Murrugarra, D.; Laubenbacher, R.

    2013-06-01

    The global dynamics of gene regulatory networks are known to show robustness to perturbations in the form of intrinsic and extrinsic noise, as well as mutations of individual genes. One molecular mechanism underlying this robustness has been identified as the action of so-called microRNAs that operate via feedforward loops. We present results of a computational study, using the modeling framework of stochastic Boolean networks, which explores the role that such network motifs play in stabilizing global dynamics. The paper introduces a new measure for the stability of stochastic networks. The results show that certain types of feedforward loops do indeed buffer the network against stochastic effects.

  2. Re-engineering Nascom's network management architecture

    NASA Astrophysics Data System (ADS)

    Drake, Brian C.; Messent, David

    1994-11-01

    The development of Nascom systems for ground communications began in 1958 with Project Vanguard. The low-speed systems (rates less than 9.6 Kbs) were developed following existing standards; but, there were no comparable standards for high-speed systems. As a result, these systems were developed using custom protocols and custom hardware. Technology has made enormous strides since the ground support systems were implemented. Standards for computer equipment, software, and high-speed communications exist and the performance of current workstations exceeds that of the mainframes used in the development of the ground systems. Nascom is in the process of upgrading its ground support systems and providing additional services. The Message Switching System (MSS), Communications Address Processor (CAP), and Multiplexer/Demultiplexer (MDM) Automated Control System (MACS) are all examples of Nascom systems developed using standards such as, X-windows, Motif, and Simple Network Management Protocol (SNMP). Also, the Earth Observing System (EOS) Communications (Ecom) project is stressing standards as an integral part of its network. The move towards standards has produced a reduction in development, maintenance, and interoperability costs, while providing operational quality improvement. The Facility and Resource Manager (FARM) project has been established to integrate the Nascom networks and systems into a common network management architecture. The maximization of standards and implementation of computer automation in the architecture will lead to continued cost reductions and increased operational efficiency. The first step has been to derive overall Nascom requirements and identify the functionality common to all the current management systems. The identification of these common functions will enable the reuse of processes in the management architecture and promote increased use of automation throughout the Nascom network. The MSS, CAP, MACS, and Ecom projects have indicated

  3. Re-engineering Nascom's network management architecture

    NASA Technical Reports Server (NTRS)

    Drake, Brian C.; Messent, David

    1994-01-01

    The development of Nascom systems for ground communications began in 1958 with Project Vanguard. The low-speed systems (rates less than 9.6 Kbs) were developed following existing standards; but, there were no comparable standards for high-speed systems. As a result, these systems were developed using custom protocols and custom hardware. Technology has made enormous strides since the ground support systems were implemented. Standards for computer equipment, software, and high-speed communications exist and the performance of current workstations exceeds that of the mainframes used in the development of the ground systems. Nascom is in the process of upgrading its ground support systems and providing additional services. The Message Switching System (MSS), Communications Address Processor (CAP), and Multiplexer/Demultiplexer (MDM) Automated Control System (MACS) are all examples of Nascom systems developed using standards such as, X-windows, Motif, and Simple Network Management Protocol (SNMP). Also, the Earth Observing System (EOS) Communications (Ecom) project is stressing standards as an integral part of its network. The move towards standards has produced a reduction in development, maintenance, and interoperability costs, while providing operational quality improvement. The Facility and Resource Manager (FARM) project has been established to integrate the Nascom networks and systems into a common network management architecture. The maximization of standards and implementation of computer automation in the architecture will lead to continued cost reductions and increased operational efficiency. The first step has been to derive overall Nascom requirements and identify the functionality common to all the current management systems. The identification of these common functions will enable the reuse of processes in the management architecture and promote increased use of automation throughout the Nascom network. The MSS, CAP, MACS, and Ecom projects have indicated

  4. NATO Human View Architecture and Human Networks

    NASA Technical Reports Server (NTRS)

    Handley, Holly A. H.; Houston, Nancy P.

    2010-01-01

    The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.

  5. Navigation Architecture for a Space Mobile Network

    NASA Technical Reports Server (NTRS)

    Valdez, Jennifer E.; Ashman, Benjamin; Gramling, Cheryl; Heckler, Gregory W.; Carpenter, Russell

    2016-01-01

    The Tracking and Data Relay Satellite System (TDRSS) Augmentation Service for Satellites (TASS) is a proposed beacon service to provide a global, space based GPS augmentation service based on the NASA Global Differential GPS (GDGPS) System. The TASS signal will be tied to the GPS time system and usable as an additional ranging and Doppler radiometric source. Additionally, it will provide data vital to autonomous navigation in the near Earth regime, including space weather information, TDRS ephemerides, Earth Orientation Parameters (EOP), and forward commanding capability. TASS benefits include enhancing situational awareness, enabling increased autonomy, and providing near real-time command access for user platforms. As NASA Headquarters' Space Communication and Navigation Office (SCaN) begins to move away from a centralized network architecture and towards a Space Mobile Network (SMN) that allows for user initiated services, autonomous navigation will be a key part of such a system. This paper explores how a TASS beacon service enables the Space Mobile Networking paradigm, what a typical user platform would require, and provides an in-depth analysis of several navigation scenarios and operations concepts. This paper provides an overview of the TASS beacon and its role within the SMN and user community. Supporting navigation analysis is presented for two user mission scenarios: an Earth observing spacecraft in low earth orbit (LEO), and a highly elliptical spacecraft in a lunar resonance orbit. These diverse flight scenarios indicate the breadth of applicability of the TASS beacon for upcoming users within the current network architecture and in the SMN.

  6. The architecture of complex weighted networks

    PubMed Central

    Barrat, A.; Barthélemy, M.; Pastor-Satorras, R.; Vespignani, A.

    2004-01-01

    Networked structures arise in a wide array of different contexts such as technological and transportation infrastructures, social phenomena, and biological systems. These highly interconnected systems have recently been the focus of a great deal of attention that has uncovered and characterized their topological complexity. Along with a complex topological structure, real networks display a large heterogeneity in the capacity and intensity of the connections. These features, however, have mainly not been considered in past studies where links are usually represented as binary states, i.e., either present or absent. Here, we study the scientific collaboration network and the world-wide air-transportation network, which are representative examples of social and large infrastructure systems, respectively. In both cases it is possible to assign to each edge of the graph a weight proportional to the intensity or capacity of the connections among the various elements of the network. We define appropriate metrics combining weighted and topological observables that enable us to characterize the complex statistical properties and heterogeneity of the actual strength of edges and vertices. This information allows us to investigate the correlations among weighted quantities and the underlying topological structure of the network. These results provide a better description of the hierarchies and organizational principles at the basis of the architecture of weighted networks. PMID:15007165

  7. Splitting strategy for simulating genetic regulatory networks.

    PubMed

    You, Xiong; Liu, Xueping; Musa, Ibrahim Hussein

    2014-01-01

    The splitting approach is developed for the numerical simulation of genetic regulatory networks with a stable steady-state structure. The numerical results of the simulation of a one-gene network, a two-gene network, and a p53-mdm2 network show that the new splitting methods constructed in this paper are remarkably more effective and more suitable for long-term computation with large steps than the traditional general-purpose Runge-Kutta methods. The new methods have no restriction on the choice of stepsize due to their infinitely large stability regions. PMID:24624223

  8. Deep Space Network information system architecture study

    NASA Technical Reports Server (NTRS)

    Beswick, C. A.; Markley, R. W. (Editor); Atkinson, D. J.; Cooper, L. P.; Tausworthe, R. C.; Masline, R. C.; Jenkins, J. S.; Crowe, R. A.; Thomas, J. L.; Stoloff, M. J.

    1992-01-01

    The purpose of this article is to describe an architecture for the Deep Space Network (DSN) information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990s. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies, such as the following: computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

  9. Probabilistic logic modeling of network reliability for hybrid network architectures

    SciTech Connect

    Wyss, G.D.; Schriner, H.K.; Gaylor, T.R.

    1996-10-01

    Sandia National Laboratories has found that the reliability and failure modes of current-generation network technologies can be effectively modeled using fault tree-based probabilistic logic modeling (PLM) techniques. We have developed fault tree models that include various hierarchical networking technologies and classes of components interconnected in a wide variety of typical and atypical configurations. In this paper we discuss the types of results that can be obtained from PLMs and why these results are of great practical value to network designers and analysts. After providing some mathematical background, we describe the `plug-and-play` fault tree analysis methodology that we have developed for modeling connectivity and the provision of network services in several current- generation network architectures. Finally, we demonstrate the flexibility of the method by modeling the reliability of a hybrid example network that contains several interconnected ethernet, FDDI, and token ring segments. 11 refs., 3 figs., 1 tab.

  10. Development of the Brain's Functional Network Architecture

    PubMed Central

    Power, Jonathan D.; Petersen, Steven E.; Schlaggar, Bradley L.

    2013-01-01

    A full understanding of the development of the brain's functional network architecture requires not only an understanding of developmental changes in neural processing in individual brain regions but also an understanding of changes in inter-regional interactions. Resting state functional connectivity MRI (rs-fcMRI) is increasingly being used to study functional interactions between brain regions in both adults and children. We briefly review methods used to study functional interactions and networks with rs-fcMRI and how these methods have been used to define developmental changes in network functional connectivity. The developmental rs-fcMRI studies to date have found two general properties. First, regional interactions change from being predominately anatomically local in children to interactions spanning longer cortical distances in young adults. Second, this developmental change in functional connectivity occurs, in general, via mechanisms of segregation of local regions and integration of distant regions into disparate subnetworks. PMID:20976563

  11. Conservation of trans-acting networks during mammalian regulatory evolution

    PubMed Central

    Stergachis, Andrew B.; Neph, Shane; Sandstrom, Richard; Haugen, Eric; Reynolds, Alex P.; Zhang, Miaohua; Byron, Rachel; Canfield, Theresa; Stelhing-Sun, Sandra; Lee, Kristen; Thurman, Robert E.; Vong, Shinny; Bates, Daniel; Neri, Fidencio; Diegel, Morgan; Giste, Erika; Dunn, Douglas; Hansen, R. Scott; Johnson, Audra K.; Sabo, Peter J.; Wilken, Matthew S.; Reh, Thomas A.; Treuting, Piper M.; Kaul, Rajinder; Groudine, Mark; Bender, M.A.; Borenstein, Elhanan; Stamatoyannopoulos, John A.

    2014-01-01

    The fundamental body plan and major physiological axes have been highly conserved during mammalian evolution, despite constraint of only a fraction of the human genome sequence. To quantify cis- vs. trans-regulatory contributions to mammalian regulatory evolution, we performed genomic DNase I footprinting of the mouse genome across 25 cell and tissue types, collectively defining >8.6 million TF occupancy sites at nucleotide resolution. Here we show that mouse TF footprints encode a regulatory lexicon of >600 motifs that is >95% similar with that recognized in vivo by human TFs. However, only ~20% of mouse TF footprints have human orthologues. Despite substantial turnover of the cis-regulatory landscape around each TF gene, nearly half of all pairwise regulatory interactions connecting mouse TF genes have been maintained in orthologous human cell types through evolutionary innovation of TF recognition sequences. Strikingly, the higher-level organization of mouse TF-to-TF connections into cellular network architectures is nearly identical with human. Our results suggest that evolutionary selection on mammalian gene regulation is targeted chiefly at the level of trans-regulatory circuitry. PMID:25409825

  12. Genetic architecture of regulatory variation in Arabidopsis thaliana.

    PubMed

    Zhang, Xu; Cal, Andrew J; Borevitz, Justin O

    2011-05-01

    Studying the genetic regulation of expression variation is a key method to dissect complex phenotypic traits. To examine the genetic architecture of regulatory variation in Arabidopsis thaliana, we performed genome-wide association (GWA) mapping of gene expression in an F(1) hybrid diversity panel. At a genome-wide false discovery rate (FDR) of 0.2, an associated single nucleotide polymorphism (SNP) explains >38% of trait variation. In comparison with SNPs that are distant from the genes to which they were associated, locally associated SNPs are preferentially found in regions with extended linkage disequilibrium (LD) and have distinct population frequencies of the derived alleles (where Arabidopsis lyrata has the ancestral allele), suggesting that different selective forces are acting. Locally associated SNPs tend to have additive inheritance, whereas distantly associated SNPs are primarily dominant. In contrast to results from mapping of expression quantitative trait loci (eQTL) in linkage studies, we observe extensive allelic heterogeneity for local regulatory loci in our diversity panel. By association mapping of allele-specific expression (ASE), we detect a significant enrichment for cis-acting variation in local regulatory variation. In addition to gene expression variation, association mapping of splicing variation reveals both local and distant genetic regulation for intron and exon level traits. Finally, we identify candidate genes for 59 diverse phenotypic traits that were mapped to eQTL. PMID:21467266

  13. Network architecture for global biomedical monitoring service.

    PubMed

    Lopez-Casado, Carmen; Tejero-Calado, Juan; Bernal-Martin, Antonio; Lopez-Gomez, Miguel; Romero-Romero, Marco; Quesada, Guillermo; Lorca, Julio; Garcia, Eugenia

    2005-01-01

    Most of the patients who are in hospitals and, increasingly, patients controlled remotely from their homes, at-home monitoring, are continuously monitored in order to control their evolution. The medical devices used up to now, force the sanitary staff to go to the patients' room to control the biosignals that are being monitored, although in many cases, patients are in perfect conditions. If patient is at home, it is he or she who has to go to the hospital to take the record of the monitored signal. New wireless technologies, such as BlueTooth and WLAN, make possible the deployment of systems that allow the display and storage of those signals in any place where the hospital intranet is accessible. In that way, unnecessary displacements are avoided. This paper presents a network architecture that allows the identification of the biosignal acquisition device as IP network nodes. The system is based on a TCP/IP architecture which is scalable and avoids the deployment of a specific purpose network. PMID:17282729

  14. A swarm intelligence framework for reconstructing gene networks: searching for biologically plausible architectures.

    PubMed

    Kentzoglanakis, Kyriakos; Poole, Matthew

    2012-01-01

    In this paper, we investigate the problem of reverse engineering the topology of gene regulatory networks from temporal gene expression data. We adopt a computational intelligence approach comprising swarm intelligence techniques, namely particle swarm optimization (PSO) and ant colony optimization (ACO). In addition, the recurrent neural network (RNN) formalism is employed for modeling the dynamical behavior of gene regulatory systems. More specifically, ACO is used for searching the discrete space of network architectures and PSO for searching the corresponding continuous space of RNN model parameters. We propose a novel solution construction process in the context of ACO for generating biologically plausible candidate architectures. The objective is to concentrate the search effort into areas of the structure space that contain architectures which are feasible in terms of their topological resemblance to real-world networks. The proposed framework is initially applied to the reconstruction of a small artificial network that has previously been studied in the context of gene network reverse engineering. Subsequently, we consider an artificial data set with added noise for reconstructing a subnetwork of the genetic interaction network of S. cerevisiae (yeast). Finally, the framework is applied to a real-world data set for reverse engineering the SOS response system of the bacterium Escherichia coli. Results demonstrate the relative advantage of utilizing problem-specific knowledge regarding biologically plausible structural properties of gene networks over conducting a problem-agnostic search in the vast space of network architectures. PMID:21576756

  15. Scalable Architecture for Multihop Wireless ad Hoc Networks

    NASA Technical Reports Server (NTRS)

    Arabshahi, Payman; Gray, Andrew; Okino, Clayton; Yan, Tsun-Yee

    2004-01-01

    A scalable architecture for wireless digital data and voice communications via ad hoc networks has been proposed. Although the details of the architecture and of its implementation in hardware and software have yet to be developed, the broad outlines of the architecture are fairly clear: This architecture departs from current commercial wireless communication architectures, which are characterized by low effective bandwidth per user and are not well suited to low-cost, rapid scaling in large metropolitan areas. This architecture is inspired by a vision more akin to that of more than two dozen noncommercial community wireless networking organizations established by volunteers in North America and several European countries.

  16. Deep Space Network information system architecture study

    NASA Technical Reports Server (NTRS)

    Beswick, C. A.; Markley, R. W. (Editor); Atkinson, D. J.; Cooper, L. P.; Tausworthe, R. C.; Masline, R. C.; Jenkins, J. S.; Crowe, R. A.; Thomas, J. L.; Stoloff, M. J.

    1992-01-01

    The purpose of this article is to describe an architecture for the DSN information system in the years 2000-2010 and to provide guidelines for its evolution during the 1990's. The study scope is defined to be from the front-end areas at the antennas to the end users (spacecraft teams, principal investigators, archival storage systems, and non-NASA partners). The architectural vision provides guidance for major DSN implementation efforts during the next decade. A strong motivation for the study is an expected dramatic improvement in information-systems technologies--i.e., computer processing, automation technology (including knowledge-based systems), networking and data transport, software and hardware engineering, and human-interface technology. The proposed Ground Information System has the following major features: unified architecture from the front-end area to the end user; open-systems standards to achieve interoperability; DSN production of level 0 data; delivery of level 0 data from the Deep Space Communications Complex, if desired; dedicated telemetry processors for each receiver; security against unauthorized access and errors; and highly automated monitor and control.

  17. Modeling Emergence in Neuroprotective Regulatory Networks

    SciTech Connect

    Sanfilippo, Antonio P.; Haack, Jereme N.; McDermott, Jason E.; Stevens, S.L.; Stenzel-Poore, Mary

    2013-01-05

    The use of predictive modeling in the analysis of gene expression data can greatly accelerate the pace of scientific discovery in biomedical research by enabling in silico experimentation to test disease triggers and potential drug therapies. Techniques that focus on modeling emergence, such as agent-based modeling and multi-agent simulations, are of particular interest as they support the discovery of pathways that may have never been observed in the past. Thus far, these techniques have been primarily applied at the multi-cellular level, or have focused on signaling and metabolic networks. We present an approach where emergence modeling is extended to regulatory networks and demonstrate its application to the discovery of neuroprotective pathways. An initial evaluation of the approach indicates that emergence modeling provides novel insights for the analysis of regulatory networks that can advance the discovery of acute treatments for stroke and other diseases.

  18. Reverse-engineering human regulatory networks

    PubMed Central

    Lefebvre, Celine; Rieckhof, Gabrielle; Califano, Andrea

    2014-01-01

    The explosion of genomic, transcriptomic, proteomic, metabolomic, and other omics data is challenging the research community to develop rational models for their organization and interpretation to generate novel biological knowledge. The development and use of gene regulatory networks to mechanistically interpret this data is an important development in molecular biology, usually captured under the banner of systems biology. As a result, the repertoire of methods for the reconstruction of comprehensive and cell-context-specific maps of regulatory interactions, or interactomes, has also exploded in the past few years. In this review, we focus on Network Biology and more specifically on methods for reverse engineering transcriptional, post-transcriptional, and post-translational human interaction networks and show how their interrogation is starting to impact our understanding of cellular pathophysiology and one’s ability to predict cellular phenotypes from genome-wide molecular observations. PMID:22246697

  19. Gene regulatory networks and the underlying biology of developmental toxicity

    EPA Science Inventory

    Embryonic cells are specified by large-scale networks of functionally linked regulatory genes. Knowledge of the relevant gene regulatory networks is essential for understanding phenotypic heterogeneity that emerges from disruption of molecular functions, cellular processes or sig...

  20. Networks: A Review of Their Technology, Architecture, and Implementation.

    ERIC Educational Resources Information Center

    Learn, Larry L.

    1988-01-01

    This overview of network-related technologies covers network elements, analog and digital signals, transmission media and their characteristics, equipment certification, multiplexing, network types, access technologies, network architectures local-area network technologies and attributes, protocols, internetworking, fiber optics versus satellites,…

  1. Establishment of a Spaceport Network Architecture

    NASA Technical Reports Server (NTRS)

    Larson, Wiley J.; Gill, Tracy R.; Mueller, Robert P.; Brink, Jeffrey S.

    2012-01-01

    Since the beginning of the space age, the main actors in space exploration have been governmental agencies, enabling a privileged access to space, but with very restricted and rare missions. The last decade has seen the rise of space tourism, and the founding of ambitious private space mining companies, showing the beginnings of a new exploration era, that is based on a more generalized and regular access to space and which is not limited to the Earth's vicinity. However, the cost of launching sufficient mass into orbit to sustain these inspiring challenges is prohibitive, and the necessary infrastructures to support these missions is still lacking. To provide easy and affordable access into orbital and deep space destinations, there is the need to create a network of spaceports via specific waypoint locations coupled with the use of natural resources, or In Situ Resource Utilization (ISRU), to provide a more economical solution. As part of the International Space University Space Studies Program 2012, the international and intercultural team of Operations and Service Infrastructure for Space (OASIS) proposes an interdisciplinary answer to the problem of economical space access and transportation. This paper presents a summary of a detailed report [1] of the different phases of a project for developing a network of spaceports throughout the Solar System in a timeframe of 50 years. The requirements, functions, critical technologies and mission architecture of this network of spaceports are outlined in a roadmap of the important steps and phases. The economic and financial aspects are emphasized in order to allow a sustainable development of the network in a public-private partnership via the formation of an International Spaceport Authority (ISPA). The approach includes engineering, scientific, financial, legal, policy, and societal aspects. Team OASIS intends to provide guidelines to make the development of space transportation via a spaceports logistics network

  2. MSAT signalling and network management architectures

    NASA Technical Reports Server (NTRS)

    Garland, Peter; Keelty, J. Malcolm

    1989-01-01

    Spar Aerospace has been active in the design and definition of Mobile Satellite Systems since the mid 1970's. In work sponsored by the Canadian Department of Communications, various payload configurations have evolved. In addressing the payload configuration, the requirements of the mobile user, the service provider and the satellite operator have always been the most important consideration. The current Spar 11 beam satellite design is reviewed, and its capabilities to provide flexibility and potential for network growth within the WARC87 allocations are explored. To enable the full capabilities of the payload to be realized, a large amount of ground based Switching and Network Management infrastructure will be required, when space segment becomes available. Early indications were that a single custom designed Demand Assignment Multiple Access (DAMA) switch should be implemented to provide efficient use of the space segment. As MSAT has evolved into a multiple service concept, supporting many service providers, this architecture should be reviewed. Some possible signalling and Network Management solutions are explored.

  3. Navigation Architecture For A Space Mobile Network

    NASA Technical Reports Server (NTRS)

    Valdez, Jennifer E.; Ashman, Benjamin; Gramling, Cheryl; Heckler, Gregory W.; Carpenter, Russell

    2016-01-01

    The Tracking and Data Relay Satellite System (TDRSS) Augmentation Service for Satellites (TASS) is a proposed beacon service to provide a global, space-based GPS augmentation service based on the NASA Global Differential GPS (GDGPS) System. The TASS signal will be tied to the GPS time system and usable as an additional ranging and Doppler radiometric source. Additionally, it will provide data vital to autonomous navigation in the near Earth regime, including space weather information, TDRS ephemerides, Earth Orientation Parameters (EOP), and forward commanding capability. TASS benefits include enhancing situational awareness, enabling increased autonomy, and providing near real-time command access for user platforms. As NASA Headquarters Space Communication and Navigation Office (SCaN) begins to move away from a centralized network architecture and towards a Space Mobile Network (SMN) that allows for user initiated services, autonomous navigation will be a key part of such a system. This paper explores how a TASS beacon service enables the Space Mobile Networking paradigm, what a typical user platform would require, and provides an in-depth analysis of several navigation scenarios and operations concepts.

  4. A provisional regulatory gene network for specification of endomesoderm in the sea urchin embryo

    NASA Technical Reports Server (NTRS)

    Davidson, Eric H.; Rast, Jonathan P.; Oliveri, Paola; Ransick, Andrew; Calestani, Cristina; Yuh, Chiou-Hwa; Minokawa, Takuya; Amore, Gabriele; Hinman, Veronica; Arenas-Mena, Cesar; Otim, Ochan; Brown, C. Titus; Livi, Carolina B.; Lee, Pei Yun; Revilla, Roger; Schilstra, Maria J.; Clarke, Peter J C.; Rust, Alistair G.; Pan, Zhengjun; Arnone, Maria I.; Rowen, Lee; Cameron, R. Andrew; McClay, David R.; Hood, Leroy; Bolouri, Hamid

    2002-01-01

    We present the current form of a provisional DNA sequence-based regulatory gene network that explains in outline how endomesodermal specification in the sea urchin embryo is controlled. The model of the network is in a continuous process of revision and growth as new genes are added and new experimental results become available; see http://www.its.caltech.edu/mirsky/endomeso.htm (End-mes Gene Network Update) for the latest version. The network contains over 40 genes at present, many newly uncovered in the course of this work, and most encoding DNA-binding transcriptional regulatory factors. The architecture of the network was approached initially by construction of a logic model that integrated the extensive experimental evidence now available on endomesoderm specification. The internal linkages between genes in the network have been determined functionally, by measurement of the effects of regulatory perturbations on the expression of all relevant genes in the network. Five kinds of perturbation have been applied: (1) use of morpholino antisense oligonucleotides targeted to many of the key regulatory genes in the network; (2) transformation of other regulatory factors into dominant repressors by construction of Engrailed repressor domain fusions; (3) ectopic expression of given regulatory factors, from genetic expression constructs and from injected mRNAs; (4) blockade of the beta-catenin/Tcf pathway by introduction of mRNA encoding the intracellular domain of cadherin; and (5) blockade of the Notch signaling pathway by introduction of mRNA encoding the extracellular domain of the Notch receptor. The network model predicts the cis-regulatory inputs that link each gene into the network. Therefore, its architecture is testable by cis-regulatory analysis. Strongylocentrotus purpuratus and Lytechinus variegatus genomic BAC recombinants that include a large number of the genes in the network have been sequenced and annotated. Tests of the cis-regulatory predictions of

  5. Regulatory Snapshots: integrative mining of regulatory modules from expression time series and regulatory networks.

    PubMed

    Gonçalves, Joana P; Aires, Ricardo S; Francisco, Alexandre P; Madeira, Sara C

    2012-01-01

    Explaining regulatory mechanisms is crucial to understand complex cellular responses leading to system perturbations. Some strategies reverse engineer regulatory interactions from experimental data, while others identify functional regulatory units (modules) under the assumption that biological systems yield a modular organization. Most modular studies focus on network structure and static properties, ignoring that gene regulation is largely driven by stimulus-response behavior. Expression time series are key to gain insight into dynamics, but have been insufficiently explored by current methods, which often (1) apply generic algorithms unsuited for expression analysis over time, due to inability to maintain the chronology of events or incorporate time dependency; (2) ignore local patterns, abundant in most interesting cases of transcriptional activity; (3) neglect physical binding or lack automatic association of regulators, focusing mainly on expression patterns; or (4) limit the discovery to a predefined number of modules. We propose Regulatory Snapshots, an integrative mining approach to identify regulatory modules over time by combining transcriptional control with response, while overcoming the above challenges. Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time. Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data. Custom graphics are finally depicted to expose the regulatory activity in a module at consecutive time points (snapshots). Regulatory Snapshots successfully unraveled modules underlying yeast response to heat shock and human epithelial-to-mesenchymal transition, based on regulations documented in the YEASTRACT and JASPAR databases, respectively, and available expression data. Regulatory players involved in functionally enriched

  6. Adaptation by Plasticity of Genetic Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Brenner, Naama

    2007-03-01

    Genetic regulatory networks have an essential role in adaptation and evolution of cell populations. This role is strongly related to their dynamic properties over intermediate-to-long time scales. We have used the budding yeast as a model Eukaryote to study the long-term dynamics of the genetic regulatory system and its significance in evolution. A continuous cell growth technique (chemostat) allows us to monitor these systems over long times under controlled condition, enabling a quantitative characterization of dynamics: steady states and their stability, transients and relaxation. First, we have demonstrated adaptive dynamics in the GAL system, a classic model for a Eukaryotic genetic switch, induced and repressed by different carbon sources in the environment. We found that both induction and repression are only transient responses; over several generations, the system converges to a single robust steady state, independent of external conditions. Second, we explored the functional significance of such plasticity of the genetic regulatory network in evolution. We used genetic engineering to mimic the natural process of gene recruitment, placing the gene HIS3 under the regulation of the GAL system. Such genetic rewiring events are important in the evolution of gene regulation, but little is known about the physiological processes supporting them and the dynamics of their assimilation in a cell population. We have shown that cells carrying the rewired genome adapted to a demanding change of environment and stabilized a population, maintaining the adaptive state for hundreds of generations. Using genome-wide expression arrays we showed that underlying the observed adaptation is a global transcriptional programming that allowed tuning expression of the recruited gene to demands. Our results suggest that non-specific properties reflecting the natural plasticity of the regulatory network support adaptation of cells to novel challenges and enhance their evolvability.

  7. Population Dynamics of Genetic Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Braun, Erez

    2005-03-01

    Unlike common objects in physics, a biological cell processes information. The cell interprets its genome and transforms the genomic information content, through the action of genetic regulatory networks, into proteins which in turn dictate its metabolism, functionality and morphology. Understanding the dynamics of a population of biological cells presents a unique challenge. It requires to link the intracellular dynamics of gene regulation, through the mechanism of cell division, to the level of the population. We present experiments studying adaptive dynamics of populations of genetically homogeneous microorganisms (yeast), grown for long durations under steady conditions. We focus on population dynamics that do not involve random genetic mutations. Our experiments follow the long-term dynamics of the population distributions and allow to quantify the correlations among generations. We focus on three interconnected issues: adaptation of genetically homogeneous populations following environmental changes, selection processes on the population and population variability and expression distributions. We show that while the population exhibits specific short-term responses to environmental inputs, it eventually adapts to a robust steady-state, largely independent of external conditions. Cycles of medium-switch show that the adapted state is imprinted in the population and that this memory is maintained for many generations. To further study population adaptation, we utilize the process of gene recruitment whereby a gene naturally regulated by a specific promoter is placed under a different regulatory system. This naturally occurring process has been recognized as a major driving force in evolution. We have recruited an essential gene to a foreign regulatory network and followed the population long-term dynamics. Rewiring of the regulatory network allows us to expose their complex dynamics and phase space structure.

  8. Consensus gene regulatory networks: combining multiple microarray gene expression datasets

    NASA Astrophysics Data System (ADS)

    Peeling, Emma; Tucker, Allan

    2007-09-01

    In this paper we present a method for modelling gene regulatory networks by forming a consensus Bayesian network model from multiple microarray gene expression datasets. Our method is based on combining Bayesian network graph topologies and does not require any special pre-processing of the datasets, such as re-normalisation. We evaluate our method on a synthetic regulatory network and part of the yeast heat-shock response regulatory network using publicly available yeast microarray datasets. Results are promising; the consensus networks formed provide a broader view of the potential underlying network, obtaining an increased true positive rate over networks constructed from a single data source.

  9. Generation of oscillating gene regulatory network motifs

    NASA Astrophysics Data System (ADS)

    van Dorp, M.; Lannoo, B.; Carlon, E.

    2013-07-01

    Using an improved version of an evolutionary algorithm originally proposed by François and Hakim [Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.0304532101 101, 580 (2004)], we generated small gene regulatory networks in which the concentration of a target protein oscillates in time. These networks may serve as candidates for oscillatory modules to be found in larger regulatory networks and protein interaction networks. The algorithm was run for 105 times to produce a large set of oscillating modules, which were systematically classified and analyzed. The robustness of the oscillations against variations of the kinetic rates was also determined, to filter out the least robust cases. Furthermore, we show that the set of evolved networks can serve as a database of models whose behavior can be compared to experimentally observed oscillations. The algorithm found three smallest (core) oscillators in which nonlinearities and number of components are minimal. Two of those are two-gene modules: the mixed feedback loop, already discussed in the literature, and an autorepressed gene coupled with a heterodimer. The third one is a single gene module which is competitively regulated by a monomer and a dimer. The evolutionary algorithm also generated larger oscillating networks, which are in part extensions of the three core modules and in part genuinely new modules. The latter includes oscillators which do not rely on feedback induced by transcription factors, but are purely of post-transcriptional type. Analysis of post-transcriptional mechanisms of oscillation may provide useful information for circadian clock research, as recent experiments showed that circadian rhythms are maintained even in the absence of transcription.

  10. Transformation of legacy network management system to service oriented architecture

    NASA Astrophysics Data System (ADS)

    Sathyan, Jithesh; Shenoy, Krishnananda

    2007-09-01

    Service providers today are facing the challenge of operating and maintaining multiple networks, based on multiple technologies. Network Management System (NMS) solutions are being used to manage these networks. However the NMS is tightly coupled with Element or the Core network components. Hence there are multiple NMS solutions for heterogeneous networks. Current network management solutions are targeted at a variety of independent networks. The wide spread popularity of IP Multimedia Subsystem (IMS) is a clear indication that all of these independent networks will be integrated into a single IP-based infrastructure referred to as Next Generation Networks (NGN) in the near future. The services, network architectures and traffic pattern in NGN will dramatically differ from the current networks. The heterogeneity and complexity in NGN including concepts like Fixed Mobile Convergence will bring a number of challenges to network management. The high degree of complexity accompanying the network element technology necessitates network management systems (NMS) which can utilize this technology to provide more service interfaces while hiding the inherent complexity. As operators begin to add new networks and expand existing networks to support new technologies and products, the necessity of scalable, flexible and functionally rich NMS systems arises. Another important factor influencing NMS architecture is mergers and acquisitions among the key vendors. Ease of integration is a key impediment in the traditional hierarchical NMS architecture. These requirements trigger the need for an architectural framework that will address the NGNM (Next Generation Network Management) issues seamlessly. This paper presents a unique perspective of bringing service orientated architecture (SOA) to legacy network management systems (NMS). It advocates a staged approach in transforming a legacy NMS to SOA. The architecture at each stage is detailed along with the technical advantages and

  11. Inference of Gene Regulatory Network Based on Local Bayesian Networks

    PubMed Central

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Chen, Luonan

    2016-01-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  12. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    PubMed

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  13. RMOD: a tool for regulatory motif detection in signaling network.

    PubMed

    Kim, Jinki; Yi, Gwan-Su

    2013-01-01

    Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod. PMID:23874612

  14. Genetic regulatory networks that count to 3.

    PubMed

    Lehmann, Malte; Sneppen, Kim

    2013-07-21

    Sensing a graded input and differentiating between its different levels is at the core of many developmental decisions. Here, we want to examine how this can be realized for a simple system. We model gene regulatory circuits that reach distinct states when setting the underlying gene copy number to 1, 2 and 3. This distinction can be considered as counting the copy number. We explore different circuits that allow for counting and keeping memory of the count after resetting the copy number to 1. For this purpose, we sample different architectures and parameters, only considering circuits that contain repressive links, which we model by Michaelis-Menten terms. Interestingly, we find that counting to 3 does not require a hierarchy in Hill coefficients, in contrast to counting to 2, which is known from lambda phage. Furthermore, we find two main circuit architectures: one design also found in the vertebrate neural tube in a development governed by the sonic hedgehog morphogen and the more robust design of a repressilator supplemented with a weak repressilator acting in the opposite direction. PMID:23567648

  15. Intersecting transcription networks constrain gene regulatory evolution.

    PubMed

    Sorrells, Trevor R; Booth, Lauren N; Tuch, Brian B; Johnson, Alexander D

    2015-07-16

    Epistasis-the non-additive interactions between different genetic loci-constrains evolutionary pathways, blocking some and permitting others. For biological networks such as transcription circuits, the nature of these constraints and their consequences are largely unknown. Here we describe the evolutionary pathways of a transcription network that controls the response to mating pheromone in yeast. A component of this network, the transcription regulator Ste12, has evolved two different modes of binding to a set of its target genes. In one group of species, Ste12 binds to specific DNA binding sites, while in another lineage it occupies DNA indirectly, relying on a second transcription regulator to recognize DNA. We show, through the construction of various possible evolutionary intermediates, that evolution of the direct mode of DNA binding was not directly accessible to the ancestor. Instead, it was contingent on a lineage-specific change to an overlapping transcription network with a different function, the specification of cell type. These results show that analysing and predicting the evolution of cis-regulatory regions requires an understanding of their positions in overlapping networks, as this placement constrains the available evolutionary pathways. PMID:26153861

  16. Intersecting transcription networks constrain gene regulatory evolution

    PubMed Central

    Sorrells, Trevor R; Booth, Lauren N; Tuch, Brian B; Johnson, Alexander D

    2015-01-01

    Epistasis—the non-additive interactions between different genetic loci—constrains evolutionary pathways, blocking some and permitting others1–8. For biological networks such as transcription circuits, the nature of these constraints and their consequences are largely unknown. Here we describe the evolutionary pathways of a transcription network that controls the response to mating pheromone in yeasts9. A component of this network, the transcription regulator Ste12, has evolved two different modes of binding to a set of its target genes. In one group of species, Ste12 binds to specific DNA binding sites, while in another lineage it occupies DNA indirectly, relying on a second transcription regulator to recognize DNA. We show, through the construction of various possible evolutionary intermediates, that evolution of the direct mode of DNA binding was not directly accessible to the ancestor. Instead, it was contingent on a lineage-specific change to an overlapping transcription network with a different function, the specification of cell type. These results show that analyzing and predicting the evolution of cis-regulatory regions requires an understanding of their positions in overlapping networks, as this placement constrains the available evolutionary pathways. PMID:26153861

  17. Genetic Regulatory Networks in Embryogenesis and Evolution

    NASA Technical Reports Server (NTRS)

    1998-01-01

    The article introduces a series of papers that were originally presented at a workshop titled Genetic Regulatory Network in Embryogenesis and Evaluation. Contents include the following: evolution of cleavage programs in relationship to axial specification and body plan evolution, changes in cell lineage specification elucidate evolutionary relations in spiralia, axial patterning in the leech: developmental mechanisms and evolutionary implications, hox genes in arthropod development and evolution, heterochronic genes in development and evolution, a common theme for LIM homeobox gene function across phylogeny, and mechanisms of specification in ascidian embryos.

  18. Eric Davidson: Steps to a gene regulatory network for development.

    PubMed

    Rothenberg, Ellen V

    2016-04-15

    Eric Harris Davidson was a unique and creative intellectual force who grappled with the diversity of developmental processes used by animal embryos and wrestled them into an intelligible set of principles, then spent his life translating these process elements into molecularly definable terms through the architecture of gene regulatory networks. He took speculative risks in his theoretical writing but ran a highly organized, rigorous experimental program that yielded an unprecedentedly full characterization of a developing organism. His writings created logical order and a framework for mechanism from the complex phenomena at the heart of advanced multicellular organism development. This is a reminiscence of intellectual currents in his work as observed by the author through the last 30-35 years of Davidson's life. PMID:26825392

  19. Space Mobile Network: A Near Earth Communication and Navigation Architecture

    NASA Technical Reports Server (NTRS)

    Israel, Dave J.; Heckler, Greg; Menrad, Robert J.

    2016-01-01

    This paper describes a Space Mobile Network architecture, the result of a recently completed NASA study exploring architectural concepts to produce a vision for the future Near Earth communications and navigation systems. The Space Mobile Network (SMN) incorporates technologies, such as Disruption Tolerant Networking (DTN) and optical communications, and new operations concepts, such as User Initiated Services, to provide user services analogous to a terrestrial smartphone user. The paper will describe the SMN Architecture, envisioned future operations concepts, opportunities for industry and international collaboration and interoperability, and technology development areas and goals.

  20. Security Aspects of an Enterprise-Wide Network Architecture.

    ERIC Educational Resources Information Center

    Loew, Robert; Stengel, Ingo; Bleimann, Udo; McDonald, Aidan

    1999-01-01

    Presents an overview of two projects that concern local area networks and the common point between networks as they relate to network security. Discusses security architectures based on firewall components, packet filters, application gateways, security-management components, an intranet solution, user registration by Web form, and requests for…

  1. Stability analysis of genetic regulatory networks with multiple time delays.

    PubMed

    Wu, Fang-Xiang

    2007-01-01

    A genetic regulatory network is a dynamic system to describe interactions among genes (mRNA) and its products (proteins). From the statistic thermodynamics and biochemical reaction principle, a genetic regulatory network can be described by a group of nonlinear differential equations with time delays. Stability is one of interesting properties for genetic regulatory network. Previous studies have investigated stability of genetic regulatory networks with a single time delay. In this paper, we investigate properties of genetic regulatory networks with multiple time delays in the notion of delay-independent stability. We present necessary and sufficient condition for the local delay-independent stability of genetic regulatory network with multiple time delays which are independent or commensurate. PMID:18002223

  2. Predicate calculus for an architecture of multiple neural networks

    NASA Astrophysics Data System (ADS)

    Consoli, Robert H.

    1990-08-01

    Future projects with neural networks will require multiple individual network components. Current efforts along these lines are ad hoc. This paper relates the neural network to a classical device and derives a multi-part architecture from that model. Further it provides a Predicate Calculus variant for describing the location and nature of the trainings and suggests Resolution Refutation as a method for determining the performance of the system as well as the location of needed trainings for specific proofs. 2. THE NEURAL NETWORK AND A CLASSICAL DEVICE Recently investigators have been making reports about architectures of multiple neural networksL234. These efforts are appearing at an early stage in neural network investigations they are characterized by architectures suggested directly by the problem space. Touretzky and Hinton suggest an architecture for processing logical statements1 the design of this architecture arises from the syntax of a restricted class of logical expressions and exhibits syntactic limitations. In similar fashion a multiple neural netword arises out of a control problem2 from the sequence learning problem3 and from the domain of machine learning. 4 But a general theory of multiple neural devices is missing. More general attempts to relate single or multiple neural networks to classical computing devices are not common although an attempt is made to relate single neural devices to a Turing machines and Sun et a!. develop a multiple neural architecture that performs pattern classification.

  3. A modular architecture for wireless sensor network nodes

    NASA Astrophysics Data System (ADS)

    Davis, Jesse; Berry, Nina

    2004-09-01

    The system level hardware architecture of individual nodes in a wireless distributed sensor network has not received adequate attention. A large portion of the development work in wireless sensor networks has been devoted to the networking layer or the network communications, but considering the tight integration required between the hardware and software on each node can result in major benefits in power, performance, and usability as well. A novel hardware architecture based on the concept of task specific modular computing provides both the high flexibility and power efficiency required for effective distributed sensing solutions. A comparative power analysis with a traditional, centralized architecture gives a justifying motivation for pursuing the modular architecture. Finally, three decentralized module self-control mechanisms developed to minimize total system power will be presented and explained in detail.

  4. ROADM architectures and technologies for agile optical networks

    NASA Astrophysics Data System (ADS)

    Eldada, Louay A.

    2007-02-01

    We review the different optoelectronic component and module technologies that have been developed for use in ROADM subsystems, and describe their principles of operation, designs, features, advantages, and challenges. We also describe the various needs for reconfigurable optical add/drop switching in agile optical networks. For each network need, we present the different ROADM subsystem architecture options with their pros and cons, and describe the optoelectronic technologies supporting each architecture.

  5. Topological origin of global attractors in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Zhang, YunJun; Ouyang, Qi; Geng, Zhi

    2015-02-01

    Fixed-point attractors with global stability manifest themselves in a number of gene regulatory networks. This property indicates the stability of regulatory networks against small state perturbations and is closely related to other complex dynamics. In this paper, we aim to reveal the core modules in regulatory networks that determine their global attractors and the relationship between these core modules and other motifs. This work has been done via three steps. Firstly, inspired by the signal transmission in the regulation process, we extract the model of chain-like network from regulation networks. We propose a module of "ideal transmission chain (ITC)", which is proved sufficient and necessary (under certain condition) to form a global fixed-point in the context of chain-like network. Secondly, by examining two well-studied regulatory networks (i.e., the cell-cycle regulatory networks of Budding yeast and Fission yeast), we identify the ideal modules in true regulation networks and demonstrate that the modules have a superior contribution to network stability (quantified by the relative size of the biggest attraction basin). Thirdly, in these two regulation networks, we find that the double negative feedback loops, which are the key motifs of forming bistability in regulation, are connected to these core modules with high network stability. These results have shed new light on the connection between the topological feature and the dynamic property of regulatory networks.

  6. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

    PubMed Central

    2014-01-01

    It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the network estimation as a target tracking problem. We overcome the limited number of observations (small n large p problem) by performing tracking in a compressed domain. Assuming linear dynamics, we derive the LASSO-Kalman smoother, which recursively computes the minimum mean-square sparse estimate of the network connectivity at each time point. The LASSO operator, motivated by the sparsity of the genetic regulatory networks, allows simultaneous signal recovery and compression, thereby reducing the amount of required observations. The smoothing improves the estimation by incorporating all observations. We track the time-varying networks during the life cycle of the Drosophila melanogaster. The recovered networks show that few genes are permanent, whereas most are transient, acting only during specific developmental phases of the organism. PMID:24517200

  7. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother.

    PubMed

    Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

    2014-01-01

    : It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the network estimation as a target tracking problem. We overcome the limited number of observations (small n large p problem) by performing tracking in a compressed domain. Assuming linear dynamics, we derive the LASSO-Kalman smoother, which recursively computes the minimum mean-square sparse estimate of the network connectivity at each time point. The LASSO operator, motivated by the sparsity of the genetic regulatory networks, allows simultaneous signal recovery and compression, thereby reducing the amount of required observations. The smoothing improves the estimation by incorporating all observations. We track the time-varying networks during the life cycle of the Drosophila melanogaster. The recovered networks show that few genes are permanent, whereas most are transient, acting only during specific developmental phases of the organism. PMID:24517200

  8. NASA Integrated Network Monitor and Control Software Architecture

    NASA Technical Reports Server (NTRS)

    Shames, Peter; Anderson, Michael; Kowal, Steve; Levesque, Michael; Sindiy, Oleg; Donahue, Kenneth; Barnes, Patrick

    2012-01-01

    The National Aeronautics and Space Administration (NASA) Space Communications and Navigation office (SCaN) has commissioned a series of trade studies to define a new architecture intended to integrate the three existing networks that it operates, the Deep Space Network (DSN), Space Network (SN), and Near Earth Network (NEN), into one integrated network that offers users a set of common, standardized, services and interfaces. The integrated monitor and control architecture utilizes common software and common operator interfaces that can be deployed at all three network elements. This software uses state-of-the-art concepts such as a pool of re-programmable equipment that acts like a configurable software radio, distributed hierarchical control, and centralized management of the whole SCaN integrated network. For this trade space study a model-based approach using SysML was adopted to describe and analyze several possible options for the integrated network monitor and control architecture. This model was used to refine the design and to drive the costing of the four different software options. This trade study modeled the three existing self standing network elements at point of departure, and then described how to integrate them using variations of new and existing monitor and control system components for the different proposed deployments under consideration. This paper will describe the trade space explored, the selected system architecture, the modeling and trade study methods, and some observations on useful approaches to implementing such model based trade space representation and analysis.

  9. Modeling Evolution of Regulatory Networks in Artificial Organisms

    NASA Astrophysics Data System (ADS)

    Sánchez-Dehesa, Yolanda; Beslon, Guillaume; Peña, José-María

    2007-09-01

    Regulatory networks are not randomly connected. They are modular, scale-free networks and some motifs distribution is clearly different from random distribution. However, the evolutionary causes and consequences of this specific connectivity are mainly unknown. In this paper we propose Raevol, an integrative model to study the evolution of regulatory networks. While most existing models consider direct evolution of the regulatory network, Raevol integrates a realistic genotype-phenotype mapping where the genome undergo mutations that indirectly modify the genetic network. Moreover, the organisms are selected at the phenotype level (which is produced by the genome via the regulation network). Thus, in Raevol, the network only indirectly evolve and it can only be selected if its activity influences the phenotype. We plan to use this model to better understand the network evolution and to study the influence of networks topology on evolution.

  10. On-board processing satellite network architectures for broadband ISDN

    NASA Technical Reports Server (NTRS)

    Inukai, Thomas; Faris, Faris; Shyy, Dong-Jye

    1992-01-01

    Onboard baseband processing architectures for future satellite broadband integrated services digital networks (B-ISDN's) are addressed. To assess the feasibility of implementing satellite B-ISDN services, critical design issues, such as B-ISDN traffic characteristics, transmission link design, and a trade-off between onboard circuit and fast packet switching, are analyzed. Examples of the two types of switching mechanisms and potential onboard network control functions are presented. A sample network architecture is also included to illustrate a potential onboard processing system.

  11. Metabolic Constraint-Based Refinement of Transcriptional Regulatory Networks

    PubMed Central

    Chandrasekaran, Sriram; Price, Nathan D.

    2013-01-01

    There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10−172), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10−14) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework

  12. Metabolic constraint-based refinement of transcriptional regulatory networks.

    PubMed

    Chandrasekaran, Sriram; Price, Nathan D

    2013-01-01

    There is a strong need for computational frameworks that integrate different biological processes and data-types to unravel cellular regulation. Current efforts to reconstruct transcriptional regulatory networks (TRNs) focus primarily on proximal data such as gene co-expression and transcription factor (TF) binding. While such approaches enable rapid reconstruction of TRNs, the overwhelming combinatorics of possible networks limits identification of mechanistic regulatory interactions. Utilizing growth phenotypes and systems-level constraints to inform regulatory network reconstruction is an unmet challenge. We present our approach Gene Expression and Metabolism Integrated for Network Inference (GEMINI) that links a compendium of candidate regulatory interactions with the metabolic network to predict their systems-level effect on growth phenotypes. We then compare predictions with experimental phenotype data to select phenotype-consistent regulatory interactions. GEMINI makes use of the observation that only a small fraction of regulatory network states are compatible with a viable metabolic network, and outputs a regulatory network that is simultaneously consistent with the input genome-scale metabolic network model, gene expression data, and TF knockout phenotypes. GEMINI preferentially recalls gold-standard interactions (p-value = 10(-172)), significantly better than using gene expression alone. We applied GEMINI to create an integrated metabolic-regulatory network model for Saccharomyces cerevisiae involving 25,000 regulatory interactions controlling 1597 metabolic reactions. The model quantitatively predicts TF knockout phenotypes in new conditions (p-value = 10(-14)) and revealed potential condition-specific regulatory mechanisms. Our results suggest that a metabolic constraint-based approach can be successfully used to help reconstruct TRNs from high-throughput data, and highlights the potential of using a biochemically-detailed mechanistic framework to

  13. Differential network analysis reveals dysfunctional regulatory networks in gastric carcinogenesis.

    PubMed

    Cao, Mu-Shui; Liu, Bing-Ya; Dai, Wen-Tao; Zhou, Wei-Xin; Li, Yi-Xue; Li, Yuan-Yuan

    2015-01-01

    Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing

  14. Differential network analysis reveals dysfunctional regulatory networks in gastric carcinogenesis

    PubMed Central

    Cao, Mu-Shui; Liu, Bing-Ya; Dai, Wen-Tao; Zhou, Wei-Xin; Li, Yi-Xue; Li, Yuan-Yuan

    2015-01-01

    Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing

  15. Self-sustained oscillations of complex genomic regulatory networks

    NASA Astrophysics Data System (ADS)

    Ye, Weiming; Huang, Xiaodong; Huang, Xuhui; Li, Pengfei; Xia, Qinzhi; Hu, Gang

    2010-05-01

    Recently, self-sustained oscillations in complex networks consisting of non-oscillatory nodes have attracted great interest in diverse natural and social fields. Oscillatory genomic regulatory networks are one of the most typical examples of this kind. Given an oscillatory genomic network, it is important to reveal the central structure generating the oscillation. However, if the network consists of large numbers of genes and interactions, the oscillation generator is deeply hidden in the complicated interactions. We apply the dominant phase-advanced driving path method proposed in Qian et al. (2010) [1] to reduce complex genomic regulatory networks to one-dimensional and unidirectionally linked network graphs where negative regulatory loops are explored to play as the central generators of the oscillations, and oscillation propagation pathways in the complex networks are clearly shown by tree branches radiating from the loops. Based on the above understanding we can control oscillations of genomic networks with high efficiency.

  16. Unstructured Peer-to-Peer Network Architectures

    NASA Astrophysics Data System (ADS)

    Jin, Xing; Chan, S.-H. Gary

    With the rapid growth of the Internet, peer-to-peer P2P networks have been widely studied and deployed. According to CacheLogic Research, P2P traffic has dominated the Internet traffic in 2006, by accounting for over 72% Internet traffic. In this chapter, we focus on unstructured P2P networks, one key type of P2P networks. We first present several unstructured P2P networks for the file sharing application, and then investigate some advanced issues in the network design. We also study two other important applications, i.e., media streaming and voice over Internet Protocol (VoIP). Finally, we discuss unstructured P2P networks over wireless networks.

  17. Neural-network algorithms and architectures for pattern classification

    SciTech Connect

    Mao, Weidong.

    1991-01-01

    The study of the artificial neural networks is an integrated research field that involves the disciplines of applied mathematics, physics, neurobiology, computer science, information, control, parallel processing and VLSI. This dissertation deals with a number of topics from a broad spectrum of neural network research in models, algorithms, applications and VLSI architectures. Specifically, this dissertation is aimed at studying neural network algorithms and architectures for pattern classification tasks. The work presented in this dissertation has a wide range of applications including speech recognition, image recognition, and high level knowledge processing. Supervised neural networks, such as the back-propagation network, can be used for classification tasks as the result of approximating an input/output mapping. They are the approximation-based classifiers. The original gradient descent back propagation learning algorithm exhibits slow convergence speed. Fast algorithms such as the conjugate gradient and quasi-Newton algorithms can be adopted. The main emphasis on neural network classifiers in this dissertation is the competition-based classifiers. Due to the rapid advance in VLSI technology, parallel processing, and computer aided design (CAD), application-specific VLSI systems are becoming more and more powerful and feasible. In particular, VLSI array processors offer high speed and efficiency through their massive parallelism and pipelining, regularity, modularity, and local communication. A unified VLSI array architecture can be used for implementing neural networks and Hidden Markov Models. He also proposes a pipeline interleaving approach to design VLSI array architectures for real-time image and video signal processing.

  18. The architecture of a network level intrusion detection system

    SciTech Connect

    Heady, R.; Luger, G.; Maccabe, A.; Servilla, M.

    1990-08-15

    This paper presents the preliminary architecture of a network level intrusion detection system. The proposed system will monitor base level information in network packets (source, destination, packet size, and time), learning the normal patterns and announcing anomalies as they occur. The goal of this research is to determine the applicability of current intrusion detection technology to the detection of network level intrusions. In particular, the authors are investigating the possibility of using this technology to detect and react to worm programs.

  19. An intelligent service-based network architecture for wearable robots.

    PubMed

    Lee, Ka Keung; Zhang, Ping; Xu, Yangsheng; Liang, Bin

    2004-08-01

    We are developing a novel robot concept called the wearable robot. Wearable robots are mobile information devices capable of supporting remote communication and intelligent interaction between networked entities. In this paper, we explore the possible functions of such a robotic network and will present a distributed network architecture based on service components. In order to support the interaction and communication between the components in the wearable robot system, we have developed an intelligent network architecture. This service-based architecture involves three major mechanisms. The first mechanism involves the use of a task coordinator service such that the execution of the services can be managed using a priority queue. The second mechanism enables the system to automatically push the required service proxy to the client intelligently based on certain system-related conditions. In the third mechanism, we allow the system to automatically deliver services based on contextual information. Using a fuzzy-logic-based decision making system, the matching service can determine whether the service should be automatically delivered utilizing the information provided by the service, client, lookup service, and context sensors. An application scenario has been implemented to demonstrate the feasibility of this distributed service-based robot architecture. The architecture is implemented as extensions to the Jini network model. PMID:15462452

  20. Chaotic Gene Regulatory Networks Can Be Robust Against Mutations and Noise

    NASA Astrophysics Data System (ADS)

    Sevim, Volkan; Rikvold, Per Arne

    2008-03-01

    Robustness to mutations and noise has been shown to evolve through stabilizing selection for optimal phenotypes in model gene regulatory networks. The ability to evolve robust mutants is known to depend on the network architecture. How do the state-space structures of networks with high and low robustness differ? Here we present large-scale computer simulations of a Random Threshold Network model of gene regulatory networks undergoing biological evolution. We show using damage propagation analysis and an extensive statistical analysis of state spaces of these model gene networks that the change in their dynamical properties due to stabilizing selection is very small. Therefore, conventional measures of stability do not provide much information about robustness in model gene regulatory networks. Interestingly, the networks that are most robust to both mutations and noise are highly chaotic. Chaotic networks are able to produce large attractor basins, which can be useful for maintaining a stable gene-expression pattern.[1] V. Sevim and P. A. Rikvold (2007), e-print arXiv:0708.2244.[2] V. Sevim and P. A. Rikvold (2007), e-print arXiv:0711.1522.

  1. Operational Concepts for a Generic Space Exploration Communication Network Architecture

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Vaden, Karl R.; Jones, Robert E.; Roberts, Anthony M.

    2015-01-01

    This document is one of three. It describes the Operational Concept (OpsCon) for a generic space exploration communication architecture. The purpose of this particular document is to identify communication flows and data types. Two other documents accompany this document, a security policy profile and a communication architecture document. The operational concepts should be read first followed by the security policy profile and then the architecture document. The overall goal is to design a generic space exploration communication network architecture that is affordable, deployable, maintainable, securable, evolvable, reliable, and adaptable. The architecture should also require limited reconfiguration throughout system development and deployment. System deployment includes: subsystem development in a factory setting, system integration in a laboratory setting, launch preparation, launch, and deployment and operation in space.

  2. An OSI architecture for the Deep Space Network

    NASA Technical Reports Server (NTRS)

    Heuser, W. R.

    1992-01-01

    This article presents an Open Systems Interconnection (OSI) architecture developed for the Deep Space Network. An historical review is provided to establish the context for current United States Government policy on interprocessor communication standards. An introduction to the OSI architecture, its seven-layer approach, and an overview of application service entities are furnished as a tutorial. Finally, the results of a prototype system developed for monitor and control of a Deep Space Station are also presented.

  3. Reverse engineering of gene regulatory networks.

    PubMed

    Cho, K H; Choo, S M; Jung, S H; Kim, J R; Choi, H S; Kim, J

    2007-05-01

    Systems biology is a multi-disciplinary approach to the study of the interactions of various cellular mechanisms and cellular components. Owing to the development of new technologies that simultaneously measure the expression of genetic information, systems biological studies involving gene interactions are increasingly prominent. In this regard, reconstructing gene regulatory networks (GRNs) forms the basis for the dynamical analysis of gene interactions and related effects on cellular control pathways. Various approaches of inferring GRNs from gene expression profiles and biological information, including machine learning approaches, have been reviewed, with a brief introduction of DNA microarray experiments as typical tools for measuring levels of messenger ribonucleic acid (mRNA) expression. In particular, the inference methods are classified according to the required input information, and the main idea of each method is elucidated by comparing its advantages and disadvantages with respect to the other methods. In addition, recent developments in this field are introduced and discussions on the challenges and opportunities for future research are provided. PMID:17591174

  4. Distributed control architecture of high-speed networks

    NASA Astrophysics Data System (ADS)

    Cidon, Israel; Gopal, Inder; Kaplan, Marc A.; Kutten, Shay

    1995-05-01

    A control architecture for a high-speed packet-switched network is described. The architecture was designed and implemented as part of the PARIS (subsequently plaNET and BBNS) networking project at IBM. This high bandwidth network for integrated communication (data, voice, video) is currently operational as a laboratory prototype. It will also be deployed within the AURORA Testbed that is part of the NSF/DARPA gigabit networking program. The high bandwidth dictates the need for specialized hardware to support faster packet handling for both point-to-point and multicast connections. A faster and more efficient network control is also required in order to support the increased number of connections and their changing requirements with time. The new network control architecture presented exploits specialized hardware, thereby enabling tasks to be performed faster and with less computation overhead. In particular, since control information can be distributed quickly using hardware packet handling mechanisms, decisions can be made based upon more complete and accurate information. In some respects, this has the effect of having the benefits of centralized control (e.g., easier bandwidth resource allocation to connections), while retaining the fault tolerance and scalability of a distributed architecture.

  5. Architectural and Markovian factors of echo state networks.

    PubMed

    Gallicchio, Claudio; Micheli, Alessio

    2011-06-01

    Echo State Networks (ESNs) constitute an emerging approach for efficiently modeling Recurrent Neural Networks (RNNs). In this paper we investigate some of the main aspects that can be accounted for the success and limitations of this class of models. In particular, we propose complementary classes of factors related to contractivity and architecture of reservoirs and we study their relative relevance. First, we show the existence of a class of tasks for which ESN performance is independent of the architectural design. The effect of the Markovian factor, characterizing a significant class within these cases, is shown by introducing instances of easy/hard tasks for ESNs featured by contractivity of reservoir dynamics. In the complementary cases, for which architectural design is effective, we investigate and decompose the aspects of network design that allow a larger reservoir to progressively improve the predictive performance. In particular, we introduce four key architectural factors: input variability, multiple time-scales dynamics, non-linear interactions among units and regression in an augmented feature space. To investigate the quantitative effects of the different architectural factors within this class of tasks successfully approached by ESNs, variants of the basic ESN model are proposed and tested on instances of datasets of different nature and difficulty. Experimental evidences confirm the role of the Markovian factor and show that all the identified key architectural factors have a major role in determining ESN performances. PMID:21376531

  6. A spiking neural network architecture for nonlinear function approximation.

    PubMed

    Iannella, N; Back, A D

    2001-01-01

    Multilayer perceptrons have received much attention in recent years due to their universal approximation capabilities. Normally, such models use real valued continuous signals, although they are loosely based on biological neuronal networks that encode signals using spike trains. Spiking neural networks are of interest both from a biological point of view and in terms of a method of robust signaling in particularly noisy or difficult environments. It is important to consider networks based on spike trains. A basic question that needs to be considered however, is what type of architecture can be used to provide universal function approximation capabilities in spiking networks? In this paper, we propose a spiking neural network architecture using both integrate-and-fire units as well as delays, that is capable of approximating a real valued function mapping to within a specified degree of accuracy. PMID:11665783

  7. Neural network based architectures for aerospace applications

    NASA Technical Reports Server (NTRS)

    Ricart, Richard

    1987-01-01

    A brief history of the field of neural networks research is given and some simple concepts are described. In addition, some neural network based avionics research and development programs are reviewed. The need for the United States Air Force and NASA to assume a leadership role in supporting this technology is stressed.

  8. Design Guidelines for New Generation Network Architecture

    NASA Astrophysics Data System (ADS)

    Harai, Hiroaki; Fujikawa, Kenji; Kafle, Ved P.; Miyazawa, Takaya; Murata, Masayuki; Ohnishi, Masaaki; Ohta, Masataka; Umezawa, Takeshi

    Limitations are found in the recent Internet because a lot of functions and protocols are patched to the original suite of layered protocols without considering global optimization. This reveals that end-to-end argument in the original Internet was neither sufficient for the current societal network and nor for a sustainable network of the future. In this position paper, we present design guidelines for a future network, which we call the New Generation Network, which provides the inclusion of diverse human requirements, reliable connection between the real-world and virtual network space, and promotion of social potentiality for human emergence. The guidelines consist of the crystal synthesis, the reality connection, and the sustainable & evolutional guidelines.

  9. Power, Avionics and Software Communication Network Architecture

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Sands, Obed S.; Bakula, Casey J.; Oldham, Daniel R.; Wright, Ted; Bradish, Martin A.; Klebau, Joseph M.

    2014-01-01

    This document describes the communication architecture for the Power, Avionics and Software (PAS) 2.0 subsystem for the Advanced Extravehicular Mobile Unit (AEMU). The following systems are described in detail: Caution Warn- ing and Control System, Informatics, Storage, Video, Audio, Communication, and Monitoring Test and Validation. This document also provides some background as well as the purpose and goals of the PAS project at Glenn Research Center (GRC).

  10. Convolutional neural network architectures for predicting DNA–protein binding

    PubMed Central

    Zeng, Haoyang; Edwards, Matthew D.; Liu, Ge; Gifford, David K.

    2016-01-01

    Motivation: Convolutional neural networks (CNN) have outperformed conventional methods in modeling the sequence specificity of DNA–protein binding. Yet inappropriate CNN architectures can yield poorer performance than simpler models. Thus an in-depth understanding of how to match CNN architecture to a given task is needed to fully harness the power of CNNs for computational biology applications. Results: We present a systematic exploration of CNN architectures for predicting DNA sequence binding using a large compendium of transcription factor datasets. We identify the best-performing architectures by varying CNN width, depth and pooling designs. We find that adding convolutional kernels to a network is important for motif-based tasks. We show the benefits of CNNs in learning rich higher-order sequence features, such as secondary motifs and local sequence context, by comparing network performance on multiple modeling tasks ranging in difficulty. We also demonstrate how careful construction of sequence benchmark datasets, using approaches that control potentially confounding effects like positional or motif strength bias, is critical in making fair comparisons between competing methods. We explore how to establish the sufficiency of training data for these learning tasks, and we have created a flexible cloud-based framework that permits the rapid exploration of alternative neural network architectures for problems in computational biology. Availability and Implementation: All the models analyzed are available at http://cnn.csail.mit.edu. Contact: gifford@mit.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27307608

  11. On-board processing satellite network architecture and control study

    NASA Technical Reports Server (NTRS)

    Campanella, S. Joseph; Pontano, Benjamin A.; Chalmers, Harvey

    1987-01-01

    The market for telecommunications services needs to be segmented into user classes having similar transmission requirements and hence similar network architectures. Use of the following transmission architecture was considered: satellite switched TDMA; TDMA up, TDM down; scanning (hopping) beam TDMA; FDMA up, TDM down; satellite switched MF/TDMA; and switching Hub earth stations with double hop transmission. A candidate network architecture will be selected that: comprises multiple access subnetworks optimized for each user; interconnects the subnetworks by means of a baseband processor; and optimizes the marriage of interconnection and access techniques. An overall network control architecture will be provided that will serve the needs of the baseband and satellite switched RF interconnected subnetworks. The results of the studies shall be used to identify elements of network architecture and control that require the greatest degree of technology development to realize an operational system. This will be specified in terms of: requirements of the enabling technology; difference from the current available technology; and estimate of the development requirements needed to achieve an operational system. The results obtained for each of these tasks are presented.

  12. C. elegans Metabolic Gene Regulatory Networks Govern the Cellular Economy

    PubMed Central

    Watson, Emma; Walhout, Albertha J.M.

    2014-01-01

    Diet greatly impacts metabolism in health and disease. In response to the presence or absence of specific nutrients, metabolic gene regulatory networks sense the metabolic state of the cell and regulate metabolic flux accordingly, for instance by the transcriptional control of metabolic enzymes. Here we discuss recent insights regarding metazoan metabolic regulatory networks using the nematode Caenorhabditis elegans as a model, including the modular organization of metabolic gene regulatory networks, the prominent impact of diet on the transcriptome and metabolome, specialized roles of nuclear hormone receptors in responding to dietary conditions, regulation of metabolic genes and metabolic regulators by microRNAs, and feedback between metabolic genes and their regulators. PMID:24731597

  13. Determining Regulatory Networks Governing the Differentiation of Embryonic Stem Cells to Pancreatic Lineage

    NASA Astrophysics Data System (ADS)

    Banerjee, Ipsita

    2009-03-01

    Knowledge of pathways governing cellular differentiation to specific phenotype will enable generation of desired cell fates by careful alteration of the governing network by adequate manipulation of the cellular environment. With this aim, we have developed a novel method to reconstruct the underlying regulatory architecture of a differentiating cell population from discrete temporal gene expression data. We utilize an inherent feature of biological networks, that of sparsity, in formulating the network reconstruction problem as a bi-level mixed-integer programming problem. The formulation optimizes the network topology at the upper level and the network connectivity strength at the lower level. The method is first validated by in-silico data, before applying it to the complex system of embryonic stem (ES) cell differentiation. This formulation enables efficient identification of the underlying network topology which could accurately predict steps necessary for directing differentiation to subsequent stages. Concurrent experimental verification demonstrated excellent agreement with model prediction.

  14. The Inferred Cardiogenic Gene Regulatory Network in the Mammalian Heart

    PubMed Central

    Li, Xing; Thiagarajan, Raghuram; Nelson, Timothy J.; Tomita-Mitchell, Aoy; Beard, Daniel A.

    2014-01-01

    Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from the developing mouse heart. Approximately 200 genes of interest were input into the algorithm to generate putative network topologies that are capable of explaining the experimental data via model simulation. To cull specious network interactions, thousands of putative networks are merged and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene interactions and used to predict regulatory pathways important for the developing mammalian heart. Area under the precision-recall curve and receiver operator characteristic curve are 9% and 58%, respectively. Of the top 10 ranked predicted interactions, 4 have already been validated. The algorithm is further tested using a network enriched with known interactions and another depleted of them. The inferred networks contained more interactions for the enriched network versus the depleted network. In all test cases, maximum performance of the algorithm was achieved when the purely data-driven method of network inference was combined with a data-independent, functional-based association method. Lastly, the network generated from the list of approximately 200 genes of interest was expanded using gene-profile uniqueness metrics to include approximately 900 additional known mouse genes and to form the most likely cardiogenic gene regulatory network. The resultant network supports known regulatory interactions and contains several novel cardiogenic regulatory interactions. The method outlined herein provides an informative approach to network inference and leads to clear testable hypotheses related to gene regulation. PMID:24971943

  15. Modular architecture of protein structures and allosteric communications: potential implications for signaling proteins and regulatory linkages

    PubMed Central

    del Sol, Antonio; Araúzo-Bravo, Marcos J; Amoros, Dolors; Nussinov, Ruth

    2007-01-01

    Background Allosteric communications are vital for cellular signaling. Here we explore a relationship between protein architectural organization and shortcuts in signaling pathways. Results We show that protein domains consist of modules interconnected by residues that mediate signaling through the shortest pathways. These mediating residues tend to be located at the inter-modular boundaries, which are more rigid and display a larger number of long-range interactions than intra-modular regions. The inter-modular boundaries contain most of the residues centrally conserved in the protein fold, which may be crucial for information transfer between amino acids. Our approach to modular decomposition relies on a representation of protein structures as residue-interacting networks, and removal of the most central residue contacts, which are assumed to be crucial for allosteric communications. The modular decomposition of 100 multi-domain protein structures indicates that modules constitute the building blocks of domains. The analysis of 13 allosteric proteins revealed that modules characterize experimentally identified functional regions. Based on the study of an additional functionally annotated dataset of 115 proteins, we propose that high-modularity modules include functional sites and are the basic functional units. We provide examples (the Gαs subunit and P450 cytochromes) to illustrate that the modular architecture of active sites is linked to their functional specialization. Conclusion Our method decomposes protein structures into modules, allowing the study of signal transmission between functional sites. A modular configuration might be advantageous: it allows signaling proteins to expand their regulatory linkages and may elicit a broader range of control mechanisms either via modular combinations or through modulation of inter-modular linkages. PMID:17531094

  16. Construction of gene regulatory networks using biclustering and bayesian networks

    PubMed Central

    2011-01-01

    Background Understanding gene interactions in complex living systems can be seen as the ultimate goal of the systems biology revolution. Hence, to elucidate disease ontology fully and to reduce the cost of drug development, gene regulatory networks (GRNs) have to be constructed. During the last decade, many GRN inference algorithms based on genome-wide data have been developed to unravel the complexity of gene regulation. Time series transcriptomic data measured by genome-wide DNA microarrays are traditionally used for GRN modelling. One of the major problems with microarrays is that a dataset consists of relatively few time points with respect to the large number of genes. Dimensionality is one of the interesting problems in GRN modelling. Results In this paper, we develop a biclustering function enrichment analysis toolbox (BicAT-plus) to study the effect of biclustering in reducing data dimensions. The network generated from our system was validated via available interaction databases and was compared with previous methods. The results revealed the performance of our proposed method. Conclusions Because of the sparse nature of GRNs, the results of biclustering techniques differ significantly from those of previous methods. PMID:22018164

  17. Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

    PubMed

    Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

    2010-05-18

    The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems. PMID:20439753

  18. Network architectures in support of digital subscriber line (DSL) deployment

    NASA Astrophysics Data System (ADS)

    Peuch, Bruno

    1998-09-01

    DSL technology enables very high bandwidth transmission in a point-to-point fashion from a customer's premises to a central office (CO), wiring center, or other logical point of traffic aggregation. Unlike many technologies that enable broadband Internet access, DSL technology does not determine a specific architecture to be deployed at either the customer's premises or in the service/access provider's network. In fact, DSL technology can be used in conjunction with a variety of network architectures. While being agnostic regarding to higher-layer protocols, there are still several critical 'protocol specific' issues that need to be addressed when deploying DSL as a solution for IP (Internet/intrAnet) access. This paper will address these issues and present a range of network architectures that incorporate DSL technology. This paper will only focus on those architectures that enable IP access. These architectures are divided into three categories: Traditional Dialled Model (TDM), frame-based (Frame Relay/Ethernet), and cell-based (ATM).

  19. Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks

    PubMed Central

    Koschützki, Dirk; Schreiber, Falk

    2008-01-01

    The structural analysis of biological networks includes the ranking of the vertices based on the connection structure of a network. To support this analysis we discuss centrality measures which indicate the importance of vertices, and demonstrate their applicability on a gene regulatory network. We show that common centrality measures result in different valuations of the vertices and that novel measures tailored to specific biological investigations are useful for the analysis of biological networks, in particular gene regulatory networks. PMID:19787083

  20. An OSI architecture for the deep space network

    NASA Technical Reports Server (NTRS)

    Heuser, W. Randy; Cooper, Lynne P.

    1993-01-01

    The flexibility and robustness of a monitor and control system are a direct result of the underlying inter-processor communications architecture. A new architecture for monitor & Control at the Deep Space Network Communications Complexes has been developed based on the Open System Interconnection (OSI) standards. The suitability of OSI standards for DSN M&C has been proven in the laboratory. The laboratory success has resulted in choosing an OSI-based architecture for DSS-13 M&C. DSS-13 is the DSN experimental station and is not part of the 'operational' DSN; it's role is to provide an environment to test new communications concepts can be tested and conduct unique science experiments. Therefore, DSS-13 must be robust enough to support operational activities, while also being flexible enough to enable experimentation. This paper describes the M&C architecture developed for DSS-13 and the results from system and operational testing.

  1. Nitrogen modulation of legume root architecture signaling pathways involves phytohormones and small regulatory molecules

    PubMed Central

    Mohd-Radzman, Nadiatul A.; Djordjevic, Michael A.; Imin, Nijat

    2013-01-01

    Nitrogen, particularly nitrate is an important yield determinant for crops. However, current agricultural practice with excessive fertilizer usage has detrimental effects on the environment. Therefore, legumes have been suggested as a sustainable alternative for replenishing soil nitrogen. Legumes can uniquely form nitrogen-fixing nodules through symbiotic interaction with specialized soil bacteria. Legumes possess a highly plastic root system which modulates its architecture according to the nitrogen availability in the soil. Understanding how legumes regulate root development in response to nitrogen availability is an important step to improving root architecture. The nitrogen-mediated root development pathway starts with sensing soil nitrogen level followed by subsequent signal transduction pathways involving phytohormones, microRNAs and regulatory peptides that collectively modulate the growth and shape of the root system. This review focuses on the current understanding of nitrogen-mediated legume root architecture including local and systemic regulations by different N-sources and the modulations by phytohormones and small regulatory molecules. PMID:24098303

  2. Convergence Analysis of a Cascade Architecture Neural Network

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.; Stubberub, Allen R.; Daud, Taher; Thakoor, Anil

    1997-01-01

    In this paper, we present a mathematical foundation, including a convergence analysis, for cascading architecture neural networks. From this, a mathematical foundation for the casade correlation learning algorithm can also be found. Furthermore, it becomes apparent that the cascade correlation scheme is a special case of an efficient hardware learning algorithm called Cascade Error Projection.

  3. Integrated network architecture for sustained human and robotic exploration

    NASA Technical Reports Server (NTRS)

    Noreen, Gary K.; Cesarone, Robert; Deutsch, Leslie; Edwards, Charlie; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazzolla, Sabino; Hastrup, Rolf; Abraham, Douglas

    2005-01-01

    The National Aeronautics and Space Administration (NASA) Exploration Systems Mission Directorate is planning a series of human and robotic missions to the Earth's moon and to Mars. These missions will require telecommunication and navigation services. This paper sets forth presumed requirements for such services and presents strawman lunar and Mars telecommunications network architectures to satisfy the presumed requirements.

  4. Large-Scale Networked Virtual Environments: Architecture and Applications

    ERIC Educational Resources Information Center

    Lamotte, Wim; Quax, Peter; Flerackers, Eddy

    2008-01-01

    Purpose: Scalability is an important research topic in the context of networked virtual environments (NVEs). This paper aims to describe the ALVIC (Architecture for Large-scale Virtual Interactive Communities) approach to NVE scalability. Design/methodology/approach: The setup and results from two case studies are shown: a 3-D learning environment…

  5. Investigation of network architecture development and properties in thermoset matrices

    NASA Astrophysics Data System (ADS)

    Swanson, Jeremy Owen

    Matrices employed in composite materials directly influence overall composite properties. In all thermoset materials, molecular level interactions and transformations during cure result in heterogeneous architecture. Variability in connectivity results from the often dramatic spatial and topological changes that occur during the crosslinking process. Compatibility (fillers, pigments, additives), temperature gradients and reactivity differences in the precursors only serve to increase the complexity of network formation. The objective of the research herein is to characterize and understand the relationships between cure conditions, conversion, connectivity, network architecture and properties in glassy thermosetting matrix resins. In this research, epoxy and vinyl ester resins (VERs) were characterized to identify controlling factors in the development of network architecture and understand how they affect the mechanical properties. VERs cure under low temperature conditions (< 50°C) via redox catalysis resulted in vitrification limiting conversion with resulting glass transition temperatures (Tgs) approximately 15°C above the cure temperature. Subsequently, in situ ligand exchange altered the activity of the metal catalyst, and the reduced connectivity of the resulting networks translated into a 30% reduction in stiffness above Tg. Network architecture was further manipulated by changing the chemical composition of the backbone. Incorporation of POSS nanoparticles into VERs resulted in changes to initial network development, with higher levels of conversion prior to vitrification. 3,3'-DDS was cured with a variety of epoxies and examined for conversion, connectivity and mechanical properties. Comparison with 4,4'-DDS revealed significant correlations between molecular level structure and properties. The research established relationships between cure conditions, conversion, connectivity and properties in glassy thermosetting matrix resins. Specifically, the

  6. ReNE: A Cytoscape Plugin for Regulatory Network Enhancement

    PubMed Central

    Politano, Gianfranco; Benso, Alfredo; Savino, Alessandro; Di Carlo, Stefano

    2014-01-01

    One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by Re

  7. ReNE: a cytoscape plugin for regulatory network enhancement.

    PubMed

    Politano, Gianfranco; Benso, Alfredo; Savino, Alessandro; Di Carlo, Stefano

    2014-01-01

    One of the biggest challenges in the study of biological regulatory mechanisms is the integration, americanmodeling, and analysis of the complex interactions which take place in biological networks. Despite post transcriptional regulatory elements (i.e., miRNAs) are widely investigated in current research, their usage and visualization in biological networks is very limited. Regulatory networks are commonly limited to gene entities. To integrate networks with post transcriptional regulatory data, researchers are therefore forced to manually resort to specific third party databases. In this context, we introduce ReNE, a Cytoscape 3.x plugin designed to automatically enrich a standard gene-based regulatory network with more detailed transcriptional, post transcriptional, and translational data, resulting in an enhanced network that more precisely models the actual biological regulatory mechanisms. ReNE can automatically import a network layout from the Reactome or KEGG repositories, or work with custom pathways described using a standard OWL/XML data format that the Cytoscape import procedure accepts. Moreover, ReNE allows researchers to merge multiple pathways coming from different sources. The merged network structure is normalized to guarantee a consistent and uniform description of the network nodes and edges and to enrich all integrated data with additional annotations retrieved from genome-wide databases like NCBI, thus producing a pathway fully manageable through the Cytoscape environment. The normalized network is then analyzed to include missing transcription factors, miRNAs, and proteins. The resulting enhanced network is still a fully functional Cytoscape network where each regulatory element (transcription factor, miRNA, gene, protein) and regulatory mechanism (up-regulation/down-regulation) is clearly visually identifiable, thus enabling a better visual understanding of its role and the effect in the network behavior. The enhanced network produced by Re

  8. Robust Networking Architecture and Secure Communication Scheme for Heterogeneous Wireless Sensor Networks

    ERIC Educational Resources Information Center

    McNeal, McKenzie, III.

    2012-01-01

    Current networking architectures and communication protocols used for Wireless Sensor Networks (WSNs) have been designed to be energy efficient, low latency, and long network lifetime. One major issue that must be addressed is the security in data communication. Due to the limited capabilities of low cost and small sized sensor nodes, designing…

  9. Building and measuring a high performance network architecture

    SciTech Connect

    Kramer, William T.C.; Toole, Timothy; Fisher, Chuck; Dugan, Jon; Wheeler, David; Wing, William R; Nickless, William; Goddard, Gregory; Corbato, Steven; Love, E. Paul; Daspit, Paul; Edwards, Hal; Mercer, Linden; Koester, David; Decina, Basil; Dart, Eli; Paul Reisinger, Paul; Kurihara, Riki; Zekauskas, Matthew J; Plesset, Eric; Wulf, Julie; Luce, Douglas; Rogers, James; Duncan, Rex; Mauth, Jeffery

    2001-04-20

    Once a year, the SC conferences present a unique opportunity to create and build one of the most complex and highest performance networks in the world. At SC2000, large-scale and complex local and wide area networking connections were demonstrated, including large-scale distributed applications running on different architectures. This project was designed to use the unique opportunity presented at SC2000 to create a testbed network environment and then use that network to demonstrate and evaluate high performance computational and communication applications. This testbed was designed to incorporate many interoperable systems and services and was designed for measurement from the very beginning. The end results were key insights into how to use novel, high performance networking technologies and to accumulate measurements that will give insights into the networks of the future.

  10. Neural network architectures to analyze OPAD data

    NASA Technical Reports Server (NTRS)

    Whitaker, Kevin W.

    1992-01-01

    A prototype Optical Plume Anomaly Detection (OPAD) system is now installed on the space shuttle main engine (SSME) Technology Test Bed (TTB) at MSFC. The OPAD system requirements dictate the need for fast, efficient data processing techniques. To address this need of the OPAD system, a study was conducted into how artificial neural networks could be used to assist in the analysis of plume spectral data.

  11. The development of brain network architecture.

    PubMed

    Wierenga, Lara M; van den Heuvel, Martijn P; van Dijk, Sarai; Rijks, Yvonne; de Reus, Marcel A; Durston, Sarah

    2016-02-01

    Brain connectivity shows protracted development throughout childhood and adolescence, and, as such, the topology of brain networks changes during this period. The complexity of these changes with development is reflected by regional differences in maturation. This study explored age-related changes in network topology and regional developmental patterns during childhood and adolescence. We acquired two sets of Diffusion Weighted Imaging-scans and anatomical T1-weighted scans. The first dataset included 85 typically developing individuals (53 males; 32 females), aged between 7 and 23 years and was acquired on a Philips Achieva 1.5 Tesla scanner. A second dataset (N = 38) was acquired on a different (but identical) 1.5 T scanner and was used for independent replication of our results. We reconstructed whole brain networks using tractography. We operationalized fiber tract development as changes in mean diffusivity and radial diffusivity with age. Most fibers showed maturational changes in mean and radial diffusivity values throughout childhood and adolescence, likely reflecting increasing white matter integrity. The largest age-related changes were observed in association fibers within and between the frontal and parietal lobes. Furthermore, there was a simultaneous age-related decrease in average path length (P < 0.0001), increase in node strength (P < 0.0001) as well as network clustering (P = 0.001), which may reflect fine-tuning of topological organization. These results suggest a sequential maturational model where connections between unimodal regions strengthen in childhood, followed by connections from these unimodal regions to association regions, while adolescence is characterized by the strengthening of connections between association regions within the frontal and parietal cortex. Hum Brain Mapp 37:717-729, 2016. © 2015 Wiley Periodicals, Inc. PMID:26595445

  12. High-speed parallel-processing networks for advanced architectures

    SciTech Connect

    Morgan, D.R.

    1988-06-01

    This paper describes various parallel-processing architecture networks that are candidates for eventual airborne use. An attempt at projecting which type of network is suitable or optimum for specific metafunction or stand-alone applications is made. However, specific algorithms will need to be developed and bench marks executed before firm conclusions can be drawn. Also, a conceptual projection of how these processors can be built in small, flyable units through the use of wafer-scale integration is offered. The use of the PAVE PILLAR system architecture to provide system level support for these tightly coupled networks is described. The author concludes that: (1) extremely high processing speeds implemented in flyable hardware is possible through parallel-processing networks if development programs are pursued; (2) dramatic speed enhancements through parallel processing requires an excellent match between the algorithm and computer-network architecture; (3) matching several high speed parallel oriented algorithms across the aircraft system to a limited set of hardware modules may be the most cost-effective approach to achieving speed enhancements; and (4) software-development tools and improved operating systems will need to be developed to support efficient parallel-processor use.

  13. An optimization methodology for neural network weights and architectures.

    PubMed

    Ludermir, Teresa B; Yamazaki, Akio; Zanchettin, Cleber

    2006-11-01

    This paper introduces a methodology for neural network global optimization. The aim is the simultaneous optimization of multilayer perceptron (MLP) network weights and architectures, in order to generate topologies with few connections and high classification performance for any data sets. The approach combines the advantages of simulated annealing, tabu search and the backpropagation training algorithm in order to generate an automatic process for producing networks with high classification performance and low complexity. Experimental results obtained with four classification problems and one prediction problem has shown to be better than those obtained by the most commonly used optimization techniques. PMID:17131660

  14. Development of the network architecture of the Canadian MSAT system

    NASA Technical Reports Server (NTRS)

    Davies, N. George; Shoamanesh, Alireza; Leung, Victor C. M.

    1988-01-01

    A description is given of the present concept for the Canadian Mobile Satellite (MSAT) System and the development of the network architecture which will accommodate the planned family of three categories of service: a mobile radio service (MRS), a mobile telephone service (MTS), and a mobile data service (MDS). The MSAT satellite will have cross-strapped L-band and Ku-band transponders to provide communications services between L-band mobile terminals and fixed base stations supporting dispatcher-type MRS, gateway stations supporting MTS interconnections to the public telephone network, data hub stations supporting the MDS, and the network control center. The currently perceived centralized architecture with demand assignment multiple access for the circuit switched MRS, MTS and permanently assigned channels for the packet switched MDS is discussed.

  15. Network architecture in a converged optical + IP network

    NASA Astrophysics Data System (ADS)

    Wakim, Walid; Zottmann, Harald

    2012-01-01

    As demands on Provider Networks continue to grow at exponential rates, providers are forced to evaluate how to continue to grow the network while increasing service velocity, enhancing resiliency while decreasing the total cost of ownership (TCO). The bandwidth growth that networks are experiencing is in the form packet based multimedia services such as video, video conferencing, gaming, etc... mixed with Over the Top (OTT) content providers such as Netflix, and the customer's expectations that best effort is not enough you end up with a situation that forces the provider to analyze how to gain more out of the network with less cost. In this paper we will discuss changes in the network that are driving us to a tighter integration between packet and optical layers and how to improve on today's multi - layer inefficiencies to drive down network TCO and provide for a fully integrated and dynamic network that will decrease time to revenue.

  16. What explains regulatory failure? Analysing the architecture of health care regulation in two Indian states.

    PubMed

    Sheikh, Kabir; Saligram, Prasanna S; Hort, Krishna

    2015-02-01

    Regulating health care is a pre-eminent policy challenge in many low- and middle-income countries (LMIC), particularly those with a strong private health sector. Yet, the regulatory approaches instituted in these countries have often been reported to be ineffective-India being exemplary. There is limited empirical research on the architecture and processes of health care regulation in LMIC that would explain these regulatory failures. We undertook a research study in two Indian states, with the aims of (1) mapping the organizations engaged with, and the written policies focused on health care regulation, (2) identifying gaps in the design and implementation of policies for health care regulation and (3) investigating underlying reasons for the identified gaps. We adopted a stepped research approach and applied a framework of basic regulatory functions for health care, to assess prevailing gaps in policy design and implementation. Qualitative research methods were employed including in-depth interviews with 32 representatives of regulatory organizations and document review. Several gaps in policy design were observed across both states, with a number of basic regulatory functions not underwritten in law, nor assigned to a regulatory organization to enact. In some instances the contents of regulatory policies had been weakened or diluted, rendering them less effective. Implementation gaps were also extensively reported in both states. Regulatory gaps were underpinned by human resource constraints, ambivalence in the roles of regulatory organizations, ineffective co-ordination between regulatory groups and extensive contestation of regulatory policies by private stakeholders. The findings are instructive that prevailing arrangements for health care regulation are ill equipped to enact several basic functions, and further that the performance of regulatory organizations is subject to pressures and distortions similar to those characterizing the wider health system

  17. Resting state networks' corticotopy: the dual intertwined rings architecture.

    PubMed

    Mesmoudi, Salma; Perlbarg, Vincent; Rudrauf, David; Messe, Arnaud; Pinsard, Basile; Hasboun, Dominique; Cioli, Claudia; Marrelec, Guillaume; Toro, Roberto; Benali, Habib; Burnod, Yves

    2013-01-01

    How does the brain integrate multiple sources of information to support normal sensorimotor and cognitive functions? To investigate this question we present an overall brain architecture (called "the dual intertwined rings architecture") that relates the functional specialization of cortical networks to their spatial distribution over the cerebral cortex (or "corticotopy"). Recent results suggest that the resting state networks (RSNs) are organized into two large families: 1) a sensorimotor family that includes visual, somatic, and auditory areas and 2) a large association family that comprises parietal, temporal, and frontal regions and also includes the default mode network. We used two large databases of resting state fMRI data, from which we extracted 32 robust RSNs. We estimated: (1) the RSN functional roles by using a projection of the results on task based networks (TBNs) as referenced in large databases of fMRI activation studies; and (2) relationship of the RSNs with the Brodmann Areas. In both classifications, the 32 RSNs are organized into a remarkable architecture of two intertwined rings per hemisphere and so four rings linked by homotopic connections. The first ring forms a continuous ensemble and includes visual, somatic, and auditory cortices, with interspersed bimodal cortices (auditory-visual, visual-somatic and auditory-somatic, abbreviated as VSA ring). The second ring integrates distant parietal, temporal and frontal regions (PTF ring) through a network of association fiber tracts which closes the ring anatomically and ensures a functional continuity within the ring. The PTF ring relates association cortices specialized in attention, language and working memory, to the networks involved in motivation and biological regulation and rhythms. This "dual intertwined architecture" suggests a dual integrative process: the VSA ring performs fast real-time multimodal integration of sensorimotor information whereas the PTF ring performs multi

  18. A network architecture for Petaflops supercomputers.

    SciTech Connect

    DeBenedictis, Erik P.

    2003-09-01

    If we are to build a supercomputer with a speed of 10{sup 15} floating operations per second (1 PetaFLOPS), interconnect technology will need to be improved considerably over what it is today. In this report, we explore one possible interconnect design for such a network. The guiding principle in this design is the optimization of all components for the finiteness of the speed of light. To achieve a linear speedup in time over well-tested supercomputers of todays' designs will require scaling up of processor power and bandwidth and scaling down of latency. Latency scaling is the most challenging: it requires a 100 ns user-to-user latency for messages traveling the full diameter of the machine. To meet this constraint requires simultaneously minimizing wire length through 3D packaging, new low-latency electrical signaling mechanisms, extremely fast routers, and new network interfaces. In this report, we outline approaches and implementations that will meet the requirements when implemented as a system. No technology breakthroughs are required.

  19. Changes in cis-regulatory elements of a key floral regulator are associated with divergence of inflorescence architectures.

    PubMed

    Kusters, Elske; Della Pina, Serena; Castel, Rob; Souer, Erik; Koes, Ronald

    2015-08-15

    Higher plant species diverged extensively with regard to the moment (flowering time) and position (inflorescence architecture) at which flowers are formed. This seems largely caused by variation in the expression patterns of conserved genes that specify floral meristem identity (FMI), rather than changes in the encoded proteins. Here, we report a functional comparison of the promoters of homologous FMI genes from Arabidopsis, petunia, tomato and Antirrhinum. Analysis of promoter-reporter constructs in petunia and Arabidopsis, as well as complementation experiments, showed that the divergent expression of leafy (LFY) and the petunia homolog aberrant leaf and flower (ALF) results from alterations in the upstream regulatory network rather than cis-regulatory changes. The divergent expression of unusual floral organs (UFO) from Arabidopsis, and the petunia homolog double top (DOT), however, is caused by the loss or gain of cis-regulatory promoter elements, which respond to trans-acting factors that are expressed in similar patterns in both species. Introduction of pUFO:UFO causes no obvious defects in Arabidopsis, but in petunia it causes the precocious and ectopic formation of flowers. This provides an example of how a change in a cis-regulatory region can account for a change in the plant body plan. PMID:26220938

  20. A fault-tolerant network architecture for integrated avionics

    NASA Technical Reports Server (NTRS)

    Butler, Bryan; Adams, Stuart

    1991-01-01

    The Army Fault-Tolerant Architecture (AFTA) under construction at the Charles Stark Draper Laboratory is an example of a highly integrated critical avionics system. The AFTA system must connect to other redundant and nonredundant systems, as well as to input/output devices. A fault-tolerant data bus (FTDB) is being developed to provide highly reliable communication between the AFTA computer and other network stations. The FTDB is being designed for Byzantine resilience and is probably capable of tolerating any single arbitrary fault. The author describes a prototype architecture for the fault-tolerant data bus.

  1. Towards a predictive theory for genetic regulatory networks

    NASA Astrophysics Data System (ADS)

    Tkacik, Gasper

    When cells respond to changes in the environment by regulating the expression levels of their genes, we often draw parallels between these biological processes and engineered information processing systems. One can go beyond this qualitative analogy, however, by analyzing information transmission in biochemical ``hardware'' using Shannon's information theory. Here, gene regulation is viewed as a transmission channel operating under restrictive constraints set by the resource costs and intracellular noise. We present a series of results demonstrating that a theory of information transmission in genetic regulatory circuits feasibly yields non-trivial, testable predictions. These predictions concern strategies by which individual gene regulatory elements, e.g., promoters or enhancers, read out their signals; as well as strategies by which small networks of genes, independently or in spatially coupled settings, respond to their inputs. These predictions can be quantitatively compared to the known regulatory networks and their function, and can elucidate how reproducible biological processes, such as embryonic development, can be orchestrated by networks built out of noisy components. Preliminary successes in the gap gene network of the fruit fly Drosophila indicate that a full ab initio theoretical prediction of a regulatory network is possible, a feat that has not yet been achieved for any real regulatory network. We end by describing open challenges on the path towards such a prediction.

  2. Time-Delayed Models of Gene Regulatory Networks

    PubMed Central

    Parmar, K.; Blyuss, K. B.; Kyrychko, Y. N.; Hogan, S. J.

    2015-01-01

    We discuss different mathematical models of gene regulatory networks as relevant to the onset and development of cancer. After discussion of alternative modelling approaches, we use a paradigmatic two-gene network to focus on the role played by time delays in the dynamics of gene regulatory networks. We contrast the dynamics of the reduced model arising in the limit of fast mRNA dynamics with that of the full model. The review concludes with the discussion of some open problems. PMID:26576197

  3. Phenotype accessibility and noise in random threshold gene regulatory networks.

    PubMed

    Pinho, Ricardo; Garcia, Victor; Feldman, Marcus W

    2014-01-01

    Evolution requires phenotypic variation in a population of organisms for selection to function. Gene regulatory processes involved in organismal development affect the phenotypic diversity of organisms. Since only a fraction of all possible phenotypes are predicted to be accessed by the end of development, organisms may evolve strategies to use environmental cues and noise-like fluctuations to produce additional phenotypic diversity, and hence to enhance the speed of adaptation. We used a generic model of organismal development --gene regulatory networks-- to investigate how different levels of noise on gene expression states (i.e. phenotypes) may affect access to new, unique phenotypes, thereby affecting phenotypic diversity. We studied additional strategies that organisms might adopt to attain larger phenotypic diversity: either by augmenting their genome or the number of gene expression states. This was done for different types of gene regulatory networks that allow for distinct levels of regulatory influence on gene expression or are more likely to give rise to stable phenotypes. We found that if gene expression is binary, increasing noise levels generally decreases phenotype accessibility for all network types studied. If more gene expression states are considered, noise can moderately enhance the speed of discovery if three or four gene expression states are allowed, and if there are enough distinct regulatory networks in the population. These results were independent of the network types analyzed, and were robust to different implementations of noise. Hence, for noise to increase the number of accessible phenotypes in gene regulatory networks, very specific conditions need to be satisfied. If the number of distinct regulatory networks involved in organismal development is large enough, and the acquisition of more genes or fine tuning of their expression states proves costly to the organism, noise can be useful in allowing access to more unique phenotypes

  4. Phenotype Accessibility and Noise in Random Threshold Gene Regulatory Networks

    PubMed Central

    Feldman, Marcus W.

    2015-01-01

    Evolution requires phenotypic variation in a population of organisms for selection to function. Gene regulatory processes involved in organismal development affect the phenotypic diversity of organisms. Since only a fraction of all possible phenotypes are predicted to be accessed by the end of development, organisms may evolve strategies to use environmental cues and noise-like fluctuations to produce additional phenotypic diversity, and hence to enhance the speed of adaptation. We used a generic model of organismal development --gene regulatory networks-- to investigate how different levels of noise on gene expression states (i.e. phenotypes) may affect access to new, unique phenotypes, thereby affecting phenotypic diversity. We studied additional strategies that organisms might adopt to attain larger phenotypic diversity: either by augmenting their genome or the number of gene expression states. This was done for different types of gene regulatory networks that allow for distinct levels of regulatory influence on gene expression or are more likely to give rise to stable phenotypes. We found that if gene expression is binary, increasing noise levels generally decreases phenotype accessibility for all network types studied. If more gene expression states are considered, noise can moderately enhance the speed of discovery if three or four gene expression states are allowed, and if there are enough distinct regulatory networks in the population. These results were independent of the network types analyzed, and were robust to different implementations of noise. Hence, for noise to increase the number of accessible phenotypes in gene regulatory networks, very specific conditions need to be satisfied. If the number of distinct regulatory networks involved in organismal development is large enough, and the acquisition of more genes or fine tuning of their expression states proves costly to the organism, noise can be useful in allowing access to more unique phenotypes

  5. A Review of Modeling Techniques for Genetic Regulatory Networks

    PubMed Central

    Yaghoobi, Hanif; Haghipour, Siyamak; Hamzeiy, Hossein; Asadi-Khiavi, Masoud

    2012-01-01

    Understanding the genetic regulatory networks, the discovery of interactions between genes and understanding regulatory processes in a cell at the gene level are the major goals of system biology and computational biology. Modeling gene regulatory networks and describing the actions of the cells at the molecular level are used in medicine and molecular biology applications such as metabolic pathways and drug discovery. Modeling these networks is also one of the important issues in genomic signal processing. After the advent of microarray technology, it is possible to model these networks using time–series data. In this paper, we provide an extensive review of methods that have been used on time–series data and represent the features, advantages and disadvantages of each. Also, we classify these methods according to their nature. A parallel study of these methods can lead to the discovery of new synthetic methods or improve previous methods. PMID:23493097

  6. Architectural Exploration and Design Methodologies of Photonic Interconnection Networks

    NASA Astrophysics Data System (ADS)

    Chan, Jong Wu

    Photonic technology is becoming an increasingly attractive solution to the problems facing today's electronic chip-scale interconnection networks. Recent progress in silicon photonics research has enabled the demonstration of all the necessary optical building blocks for creating extremely high-bandwidth density and energy-efficient links for on- and off-chip communications. From the feasibility and architecture perspective however, photonics represents a dramatic paradigm shift from traditional electronic network designs due to fundamental differences in how electronics and photonics function and behave. As a result of these differences, new modeling and analysis methods must be employed in order to properly realize a functional photonic chip-scale interconnect design. In this work, we present a methodology for characterizing and modeling fundamental photonic building blocks which can subsequently be combined to form full photonic network architectures. We also describe a set of tools which can be utilized to assess the physical-layer and system-level performance properties of a photonic network. The models and tools are integrated in a novel open-source design and simulation environment called PhoenixSim. Next, we leverage PhoenixSim for the study of chip-scale photonic networks. We examine several photonic networks through the synergistic study of both physical-layer metrics and system-level metrics. This holistic analysis method enables us to provide deeper insight into architecture scalability since it considers insertion loss, crosstalk, and power dissipation. In addition to these novel physical-layer metrics, traditional system-level metrics of bandwidth and latency are also obtained. Lastly, we propose a novel routing architecture known as wavelength-selective spatial routing. This routing architecture is analogous to electronic virtual channels since it enables the transmission of multiple logical optical channels through a single physical plane (i.e. the

  7. An Architecture for Dynamic Trust Monitoring in Mobile Networks

    NASA Astrophysics Data System (ADS)

    Onolaja, Olufunmilola; Bahsoon, Rami; Theodoropoulos, Georgios

    Collusion attacks remain a major problem of reputation and trust models, in mobile ad hoc networks. By covering up malicious behaviour of one another from the remaining part of the network, two or more malicious nodes may collaborate to cause damage to or disrupt the network. A number of models exist, which have been proposed to address this issue. Despite these however, the assurance of trusted communication still remains a challenge in these networks. We present a dynamic trust model that detects malicious behaviour at runtime and prevents collusion attacks. Our proposed model employs a novel approach that has the advantage of predicting the future trustworthiness of nodes, based on historical and online behaviour of nodes. This is achieved by an architecture that applies the paradigm of Dynamic Data Driven Application Systems, in solving the problem of collusion attacks in mobile networks.

  8. Elastic Optical Path Network Architecture: Framework for Spectrally-Efficient and Scalable Future Optical Networks

    NASA Astrophysics Data System (ADS)

    Jinno, Masahiko; Takara, Hidehiko; Sone, Yoshiaki; Yonenaga, Kazushige; Hirano, Akira

    This paper presents an elastic optical path network architecture as a novel networking framework to address the looming capacity crunch problem in internet protocol (IP) and optical networks. The basic idea is to introduce elasticity and adaptation into the optical domain to yield spectrally-efficient optical path accommodation, heightened network scalability through IP traffic offloading to the elastic optical layer, and enhanced survivability for serious disasters.

  9. Gene regulatory networks modelling using a dynamic evolutionary hybrid

    PubMed Central

    2010-01-01

    Background Inference of gene regulatory networks is a key goal in the quest for understanding fundamental cellular processes and revealing underlying relations among genes. With the availability of gene expression data, computational methods aiming at regulatory networks reconstruction are facing challenges posed by the data's high dimensionality, temporal dynamics or measurement noise. We propose an approach based on a novel multi-layer evolutionary trained neuro-fuzzy recurrent network (ENFRN) that is able to select potential regulators of target genes and describe their regulation type. Results The recurrent, self-organizing structure and evolutionary training of our network yield an optimized pool of regulatory relations, while its fuzzy nature avoids noise-related problems. Furthermore, we are able to assign scores for each regulation, highlighting the confidence in the retrieved relations. The approach was tested by applying it to several benchmark datasets of yeast, managing to acquire biologically validated relations among genes. Conclusions The results demonstrate the effectiveness of the ENFRN in retrieving biologically valid regulatory relations and providing meaningful insights for better understanding the dynamics of gene regulatory networks. The algorithms and methods described in this paper have been implemented in a Matlab toolbox and are available from: http://bioserver-1.bioacademy.gr/DataRepository/Project_ENFRN_GRN/. PMID:20298548

  10. Inferring slowly-changing dynamic gene-regulatory networks

    PubMed Central

    2015-01-01

    Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experiments are designed in order to tease out temporal changes in the underlying network. It is typically reasonable to assume that changes in genomic networks are few, because biological systems tend to be stable. We introduce a new model for estimating slow changes in dynamic gene-regulatory networks, which is suitable for high-dimensional data, e.g. time-course microarray data. Our aim is to estimate a dynamically changing genomic network based on temporal activity measurements of the genes in the network. Our method is based on the penalized likelihood with ℓ1-norm, that penalizes conditional dependencies between genes as well as differences between conditional independence elements across time points. We also present a heuristic search strategy to find optimal tuning parameters. We re-write the penalized maximum likelihood problem into a standard convex optimization problem subject to linear equality constraints. We show that our method performs well in simulation studies. Finally, we apply the proposed model to a time-course T-cell dataset. PMID:25917062

  11. High-performance, scalable optical network-on-chip architectures

    NASA Astrophysics Data System (ADS)

    Tan, Xianfang

    The rapid advance of technology enables a large number of processing cores to be integrated into a single chip which is called a Chip Multiprocessor (CMP) or a Multiprocessor System-on-Chip (MPSoC) design. The on-chip interconnection network, which is the communication infrastructure for these processing cores, plays a central role in a many-core system. With the continuously increasing complexity of many-core systems, traditional metallic wired electronic networks-on-chip (NoC) became a bottleneck because of the unbearable latency in data transmission and extremely high energy consumption on chip. Optical networks-on-chip (ONoC) has been proposed as a promising alternative paradigm for electronic NoC with the benefits of optical signaling communication such as extremely high bandwidth, negligible latency, and low power consumption. This dissertation focus on the design of high-performance and scalable ONoC architectures and the contributions are highlighted as follow: 1. A micro-ring resonator (MRR)-based Generic Wavelength-routed Optical Router (GWOR) is proposed. A method for developing any sized GWOR is introduced. GWOR is a scalable non-blocking ONoC architecture with simple structure, low cost and high power efficiency compared to existing ONoC designs. 2. To expand the bandwidth and improve the fault tolerance of the GWOR, a redundant GWOR architecture is designed by cascading different type of GWORs into one network. 3. The redundant GWOR built with MRR-based comb switches is proposed. Comb switches can expand the bandwidth while keep the topology of GWOR unchanged by replacing the general MRRs with comb switches. 4. A butterfly fat tree (BFT)-based hybrid optoelectronic NoC (HONoC) architecture is developed in which GWORs are used for global communication and electronic routers are used for local communication. The proposed HONoC uses less numbers of electronic routers and links than its counterpart of electronic BFT-based NoC. It takes the advantages of

  12. Genomic reconstruction of transcriptional regulatory networks in lactic acid bacteria

    PubMed Central

    2013-01-01

    Background Genome scale annotation of regulatory interactions and reconstruction of regulatory networks are the crucial problems in bacterial genomics. The Lactobacillales order of bacteria collates various microorganisms having a large economic impact, including both human and animal pathogens and strains used in the food industry. Nonetheless, no systematic genome-wide analysis of transcriptional regulation has been previously made for this taxonomic group. Results A comparative genomics approach was used for reconstruction of transcriptional regulatory networks in 30 selected genomes of lactic acid bacteria. The inferred networks comprise regulons for 102 orthologous transcription factors (TFs), including 47 novel regulons for previously uncharacterized TFs. Numerous differences between regulatory networks of the Streptococcaceae and Lactobacillaceae groups were described on several levels. The two groups are characterized by substantially different sets of TFs encoded in their genomes. Content of the inferred regulons and structure of their cognate TF binding motifs differ for many orthologous TFs between the two groups. Multiple cases of non-orthologous displacements of TFs that control specific metabolic pathways were reported. Conclusions The reconstructed regulatory networks substantially expand the existing knowledge of transcriptional regulation in lactic acid bacteria. In each of 30 studied genomes the obtained regulatory network contains on average 36 TFs and 250 target genes that are mostly involved in carbohydrate metabolism, stress response, metal homeostasis and amino acids biosynthesis. The inferred networks can be used for genetic experiments, functional annotations of genes, metabolic reconstruction and evolutionary analysis. All reconstructed regulons are captured within the Streptococcaceae and Lactobacillaceae collections in the RegPrecise database (http://regprecise.lbl.gov). PMID:23398941

  13. Integrated Network Architecture for Sustained Human and Robotic Exploration

    NASA Technical Reports Server (NTRS)

    Noreen, Gary; Cesarone, Robert; Deutsch, Leslie; Edwards, Charles; Soloff, Jason; Ely, Todd; Cook, Brian; Morabito, David; Hemmati, Hamid; Piazolla, Sabino; Hastrup, Rolf; Abraham, Douglas; Miles, Sue; Manshadi, Farzin

    2005-01-01

    The National Aeronautics and Space Administration (NASA) Exploration Systems Enterprise is planning a series of human and robotic missions to the Earth's moon and to Mars. These missions will require communication and navigation services. This paper1 sets forth presumed requirements for such services and concepts for lunar and Mars telecommunications network architectures to satisfy the presumed requirements. The paper suggests that an inexpensive ground network would suffice for missions to the near-side of the moon. A constellation of three Lunar Telecommunications Orbiters connected to an inexpensive ground network could provide continuous redundant links to a polar lunar base and its vicinity. For human and robotic missions to Mars, a pair of areostationary satellites could provide continuous redundant links between Earth and a mid-latitude Mars base in conjunction with the Deep Space Network augmented by large arrays of 12-m antennas on Earth.

  14. A Multi-Agent System Architecture for Sensor Networks

    PubMed Central

    Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

    2009-01-01

    The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172

  15. A multi-agent system architecture for sensor networks.

    PubMed

    Fuentes-Fernández, Rubén; Guijarro, María; Pajares, Gonzalo

    2009-01-01

    The design of the control systems for sensor networks presents important challenges. Besides the traditional problems about how to process the sensor data to obtain the target information, engineers need to consider additional aspects such as the heterogeneity and high number of sensors, and the flexibility of these networks regarding topologies and the sensors in them. Although there are partial approaches for resolving these issues, their integration relies on ad hoc solutions requiring important development efforts. In order to provide an effective approach for this integration, this paper proposes an architecture based on the multi-agent system paradigm with a clear separation of concerns. The architecture considers sensors as devices used by an upper layer of manager agents. These agents are able to communicate and negotiate services to achieve the required functionality. Activities are organized according to roles related with the different aspects to integrate, mainly sensor management, data processing, communication and adaptation to changes in the available devices and their capabilities. This organization largely isolates and decouples the data management from the changing network, while encouraging reuse of solutions. The use of the architecture is facilitated by a specific modelling language developed through metamodelling. A case study concerning a generic distributed system for fire fighting illustrates the approach and the comparison with related work. PMID:22303172

  16. Efficient experimental design for uncertainty reduction in gene regulatory networks

    PubMed Central

    2015-01-01

    Background An accurate understanding of interactions among genes plays a major role in developing therapeutic intervention methods. Gene regulatory networks often contain a significant amount of uncertainty. The process of prioritizing biological experiments to reduce the uncertainty of gene regulatory networks is called experimental design. Under such a strategy, the experiments with high priority are suggested to be conducted first. Results The authors have already proposed an optimal experimental design method based upon the objective for modeling gene regulatory networks, such as deriving therapeutic interventions. The experimental design method utilizes the concept of mean objective cost of uncertainty (MOCU). MOCU quantifies the expected increase of cost resulting from uncertainty. The optimal experiment to be conducted first is the one which leads to the minimum expected remaining MOCU subsequent to the experiment. In the process, one must find the optimal intervention for every gene regulatory network compatible with the prior knowledge, which can be prohibitively expensive when the size of the network is large. In this paper, we propose a computationally efficient experimental design method. This method incorporates a network reduction scheme by introducing a novel cost function that takes into account the disruption in the ranking of potential experiments. We then estimate the approximate expected remaining MOCU at a lower computational cost using the reduced networks. Conclusions Simulation results based on synthetic and real gene regulatory networks show that the proposed approximate method has close performance to that of the optimal method but at lower computational cost. The proposed approximate method also outperforms the random selection policy significantly. A MATLAB software implementing the proposed experimental design method is available at http://gsp.tamu.edu/Publications/supplementary/roozbeh15a/. PMID:26423515

  17. Insights into the organization of biochemical regulatory networks using graph theory analyses.

    PubMed

    Ma'ayan, Avi

    2009-02-27

    Graph theory has been a valuable mathematical modeling tool to gain insights into the topological organization of biochemical networks. There are two types of insights that may be obtained by graph theory analyses. The first provides an overview of the global organization of biochemical networks; the second uses prior knowledge to place results from multivariate experiments, such as microarray data sets, in the context of known pathways and networks to infer regulation. Using graph analyses, biochemical networks are found to be scale-free and small-world, indicating that these networks contain hubs, which are proteins that interact with many other molecules. These hubs may interact with many different types of proteins at the same time and location or at different times and locations, resulting in diverse biological responses. Groups of components in networks are organized in recurring patterns termed network motifs such as feedback and feed-forward loops. Graph analysis revealed that negative feedback loops are less common and are present mostly in proximity to the membrane, whereas positive feedback loops are highly nested in an architecture that promotes dynamical stability. Cell signaling networks have multiple pathways from some input receptors and few from others. Such topology is reminiscent of a classification system. Signaling networks display a bow-tie structure indicative of funneling information from extracellular signals and then dispatching information from a few specific central intracellular signaling nexuses. These insights show that graph theory is a valuable tool for gaining an understanding of global regulatory features of biochemical networks. PMID:18940806

  18. Bayesian Nonlinear Model Selection for Gene Regulatory Networks

    PubMed Central

    Ni, Yang; Stingo, Francesco C.; Baladandayuthapani, Veerabhadran

    2015-01-01

    Summary Gene regulatory networks represent the regulatory relationships between genes and their products and are important for exploring and defining the underlying biological processes of cellular systems. We develop a novel framework to recover the structure of nonlinear gene regulatory networks using semiparametric spline-based directed acyclic graphical models. Our use of splines allows the model to have both flexibility in capturing nonlinear dependencies as well as control of overfitting via shrinkage, using mixed model representations of penalized splines. We propose a novel discrete mixture prior on the smoothing parameter of the splines that allows for simultaneous selection of both linear and nonlinear functional relationships as well as inducing sparsity in the edge selection. Using simulation studies, we demonstrate the superior performance of our methods in comparison with several existing approaches in terms of network reconstruction and functional selection. We apply our methods to a gene expression dataset in glioblastoma multiforme, which reveals several interesting and biologically relevant nonlinear relationships. PMID:25854759

  19. Fiber-Optic Network Architectures for Onboard Avionics Applications Investigated

    NASA Technical Reports Server (NTRS)

    Nguyen, Hung D.; Ngo, Duc H.

    2003-01-01

    This project is part of a study within the Advanced Air Transportation Technologies program undertaken at the NASA Glenn Research Center. The main focus of the program is the improvement of air transportation, with particular emphasis on air transportation safety. Current and future advances in digital data communications between an aircraft and the outside world will require high-bandwidth onboard communication networks. Radiofrequency (RF) systems, with their interconnection network based on coaxial cables and waveguides, increase the complexity of communication systems onboard modern civil and military aircraft with respect to weight, power consumption, and safety. In addition, safety and reliability concerns from electromagnetic interference between the RF components embedded in these communication systems exist. A simple, reliable, and lightweight network that is free from the effects of electromagnetic interference and capable of supporting the broadband communications needs of future onboard digital avionics systems cannot be easily implemented using existing coaxial cable-based systems. Fiber-optical communication systems can meet all these challenges of modern avionics applications in an efficient, cost-effective manner. The objective of this project is to present a number of optical network architectures for onboard RF signal distribution. Because of the emergence of a number of digital avionics devices requiring high-bandwidth connectivity, fiber-optic RF networks onboard modern aircraft will play a vital role in ensuring a low-noise, highly reliable RF communication system. Two approaches are being used for network architectures for aircraft onboard fiber-optic distribution systems: a hybrid RF-optical network and an all-optical wavelength division multiplexing (WDM) network.

  20. Random Evolution of Idiotypic Networks: Dynamics and Architecture

    NASA Astrophysics Data System (ADS)

    Brede, Markus; Behn, Ulrich

    The paper deals with modelling a subsystem of the immune system, the so-called idiotypic network (INW). INWs, conceived by N.K. Jerne in 1974, are functional networks of interacting antibodies and B cells. In principle, Jernes' framework provides solutions to many issues in immunology, such as immunological memory, mechanisms for antigen recognition and self/non-self discrimination. Explaining the interconnection between the elementary components, local dynamics, network formation and architecture, and possible modes of global system function appears to be an ideal playground of statistical mechanics. We present a simple cellular automaton model, based on a graph representation of the system. From a simplified description of idiotypic interactions, rules for the random evolution of networks of occupied and empty sites on these graphs are derived. In certain biologically relevant parameter ranges the resultant dynamics leads to stationary states. A stationary state is found to correspond to a specific pattern of network organization. It turns out that even these very simple rules give rise to a multitude of different kinds of patterns. We characterize these networks by classifying `static' and `dynamic' network-patterns. A type of `dynamic' network is found to display many features of real INWs.

  1. A compendium of Caenhorabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks

    PubMed Central

    Reece-Hoyes, John S; Deplancke, Bart; Shingles, Jane; Grove, Christian A; Hope, Ian A; Walhout, Albertha JM

    2005-01-01

    Background Transcription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes. Results By computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks. Conclusion wTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function

  2. Architecture, Infrastructure, and Broadband Civic Network Design: An Institutional View

    NASA Astrophysics Data System (ADS)

    Venkatesh, Murali; Chango, Mawaki

    Cultural values frame architectures, and architectures motivate infrastructures — by which we mean the foundational telecommunications and Internet access services that software applications depend on. Design is the social process that realizes architectural elements in an infrastructure. This process is often a conflicted one where transformative visions confront the realities of entrenched power, where innovation confronts pressure from institutionalized interests and practices working to resist change and reproduce the status quo in the design outcome. We use this viewpoint to discuss design aspects of the Urban-net, a broadband civic networking case. Civic networks are embodiments of distinctive technological configurations and forms of social order. In choosing some technological configurations over others, designers are favoring some social structural configurations over alternatives. To the extent that a civic network sets out to reconfigure the prevailing social order (as was the case in the Urban-net project considered here), the design process becomes the arena where challengers of the prevailing order encounter its defenders. In this case, the defenders prevailed and the design that emerged was conservative and reproduced the status quo. What steps can stakeholders take so that the project’s future development is in line with the original aim of structural change? We outline two strategies. We argue the importance of articulating cultural desiderata in an architecture that stakeholders can use to open up the infrastructure to new constituents and incremental change. Next, we argue the importance of designing the conditions of design. The climate in which social interactions occur can powerfully shape design outcomes, but this does not usually figure in stakeholders’ design concerns.

  3. Software Defined Networking (SDN) controlled all optical switching networks with multi-dimensional switching architecture

    NASA Astrophysics Data System (ADS)

    Zhao, Yongli; Ji, Yuefeng; Zhang, Jie; Li, Hui; Xiong, Qianjin; Qiu, Shaofeng

    2014-08-01

    Ultrahigh throughout capacity requirement is challenging the current optical switching nodes with the fast development of data center networks. Pbit/s level all optical switching networks need to be deployed soon, which will cause the high complexity of node architecture. How to control the future network and node equipment together will become a new problem. An enhanced Software Defined Networking (eSDN) control architecture is proposed in the paper, which consists of Provider NOX (P-NOX) and Node NOX (N-NOX). With the cooperation of P-NOX and N-NOX, the flexible control of the entire network can be achieved. All optical switching network testbed has been experimentally demonstrated with efficient control of enhanced Software Defined Networking (eSDN). Pbit/s level all optical switching nodes in the testbed are implemented based on multi-dimensional switching architecture, i.e. multi-level and multi-planar. Due to the space and cost limitation, each optical switching node is only equipped with four input line boxes and four output line boxes respectively. Experimental results are given to verify the performance of our proposed control and switching architecture.

  4. Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks

    PubMed Central

    Eddy, James A.; Papin, Jason A.

    2008-01-01

    Extracellular cues affect signaling, metabolic, and regulatory processes to elicit cellular responses. Although intracellular signaling, metabolic, and regulatory networks are highly integrated, previous analyses have largely focused on independent processes (e.g., metabolism) without considering the interplay that exists among them. However, there is evidence that many diseases arise from multifunctional components with roles throughout signaling, metabolic, and regulatory networks. Therefore, in this study, we propose a flux balance analysis (FBA)–based strategy, referred to as integrated dynamic FBA (idFBA), that dynamically simulates cellular phenotypes arising from integrated networks. The idFBA framework requires an integrated stoichiometric reconstruction of signaling, metabolic, and regulatory processes. It assumes quasi-steady-state conditions for “fast” reactions and incorporates “slow” reactions into the stoichiometric formalism in a time-delayed manner. To assess the efficacy of idFBA, we developed a prototypic integrated system comprising signaling, metabolic, and regulatory processes with network features characteristic of actual systems and incorporating kinetic parameters based on typical time scales observed in literature. idFBA was applied to the prototypic system, which was evaluated for different environments and gene regulatory rules. In addition, we applied the idFBA framework in a similar manner to a representative module of the single-cell eukaryotic organism Saccharomyces cerevisiae. Ultimately, idFBA facilitated quantitative, dynamic analysis of systemic effects of extracellular cues on cellular phenotypes and generated comparable time-course predictions when contrasted with an equivalent kinetic model. Since idFBA solves a linear programming problem and does not require an exhaustive list of detailed kinetic parameters, it may be efficiently scaled to integrated intracellular systems that incorporate signaling, metabolic, and

  5. A New Integrated Neural Network Architecture for Streamflow Forecasting

    NASA Astrophysics Data System (ADS)

    Teegavarapu, R. S.

    2005-12-01

    Streamflow time series often provide valuable insights into the underlying physical processes that govern response of any watershed. Patterns derived from time series based on repeated structures within these series can be beneficial for developing new or improved data-driven forecasting models. Data-driven models, artificial neural networks (ANN), are developed in the current study for streamflow prediction using input structures that are classified into geometrically similar patterns. The number of patterns that are identified in a series depends on the lagged values of streamflows used in the input structures of the ANN model. A new modular and integrated ANN architecture that combines several ANN models, referred to as pattern-classified neural network (PCNN), is proposed, developed and investigated in this study. The ANN models are used for one step-ahead prediction of streamflows for Reed Creek and Little River, Virginia. Results obtained from this study suggest that the use of these patterns in the process of training has improved the performance of the neural networks in prediction. The improved performance of the ANN models can be attributed to prior classification of data, which in a way has complimented and enhanced the already existing classification abilities of the neural networks. The PCNN architecture also provides the benefit of better generalization of a data-driven model by developing several independent models instead of one global data-driven prediction model for the entire data.

  6. Cortical network architecture for context processing in primate brain

    PubMed Central

    Chao, Zenas C; Nagasaka, Yasuo; Fujii, Naotaka

    2015-01-01

    Context is information linked to a situation that can guide behavior. In the brain, context is encoded by sensory processing and can later be retrieved from memory. How context is communicated within the cortical network in sensory and mnemonic forms is unknown due to the lack of methods for high-resolution, brain-wide neuronal recording and analysis. Here, we report the comprehensive architecture of a cortical network for context processing. Using hemisphere-wide, high-density electrocorticography, we measured large-scale neuronal activity from monkeys observing videos of agents interacting in situations with different contexts. We extracted five context-related network structures including a bottom-up network during encoding and, seconds later, cue-dependent retrieval of the same network with the opposite top-down connectivity. These findings show that context is represented in the cortical network as distributed communication structures with dynamic information flows. This study provides a general methodology for recording and analyzing cortical network neuronal communication during cognition. DOI: http://dx.doi.org/10.7554/eLife.06121.001 PMID:26416139

  7. An open, interoperable, and scalable prehospital information technology network architecture.

    PubMed

    Landman, Adam B; Rokos, Ivan C; Burns, Kevin; Van Gelder, Carin M; Fisher, Roger M; Dunford, James V; Cone, David C; Bogucki, Sandy

    2011-01-01

    Some of the most intractable challenges in prehospital medicine include response time optimization, inefficiencies at the emergency medical services (EMS)-emergency department (ED) interface, and the ability to correlate field interventions with patient outcomes. Information technology (IT) can address these and other concerns by ensuring that system and patient information is received when and where it is needed, is fully integrated with prior and subsequent patient information, and is securely archived. Some EMS agencies have begun adopting information technologies, such as wireless transmission of 12-lead electrocardiograms, but few agencies have developed a comprehensive plan for management of their prehospital information and integration with other electronic medical records. This perspective article highlights the challenges and limitations of integrating IT elements without a strategic plan, and proposes an open, interoperable, and scalable prehospital information technology (PHIT) architecture. The two core components of this PHIT architecture are 1) routers with broadband network connectivity to share data between ambulance devices and EMS system information services and 2) an electronic patient care report to organize and archive all electronic prehospital data. To successfully implement this comprehensive PHIT architecture, data and technology requirements must be based on best available evidence, and the system must adhere to health data standards as well as privacy and security regulations. Recent federal legislation prioritizing health information technology may position federal agencies to help design and fund PHIT architectures. PMID:21294627

  8. Biologically relevant neural network architectures for support vector machines.

    PubMed

    Jändel, Magnus

    2014-01-01

    Neural network architectures that implement support vector machines (SVM) are investigated for the purpose of modeling perceptual one-shot learning in biological organisms. A family of SVM algorithms including variants of maximum margin, 1-norm, 2-norm and ν-SVM is considered. SVM training rules adapted for neural computation are derived. It is found that competitive queuing memory (CQM) is ideal for storing and retrieving support vectors. Several different CQM-based neural architectures are examined for each SVM algorithm. Although most of the sixty-four scanned architectures are unconvincing for biological modeling four feasible candidates are found. The seemingly complex learning rule of a full ν-SVM implementation finds a particularly simple and natural implementation in bisymmetric architectures. Since CQM-like neural structures are thought to encode skilled action sequences and bisymmetry is ubiquitous in motor systems it is speculated that trainable pattern recognition in low-level perception has evolved as an internalized motor programme. PMID:24126252

  9. Dynamical properties of gene regulatory networks involved in long-term potentiation

    PubMed Central

    Nido, Gonzalo S.; Ryan, Margaret M.; Benuskova, Lubica; Williams, Joanna M.

    2015-01-01

    The long-lasting enhancement of synaptic effectiveness known as long-term potentiation (LTP) is considered to be the cellular basis of long-term memory. LTP elicits changes at the cellular and molecular level, including temporally specific alterations in gene networks. LTP can be seen as a biological process in which a transient signal sets a new homeostatic state that is “remembered” by cellular regulatory systems. Previously, we have shown that early growth response (Egr) transcription factors are of fundamental importance to gene networks recruited early after LTP induction. From a systems perspective, we hypothesized that these networks will show less stable architecture, while networks recruited later will exhibit increased stability, being more directly related to LTP consolidation. Using random Boolean network (RBN) simulations we found that the network derived at 24 h was markedly more stable than those derived at 20 min or 5 h post-LTP. This temporal effect on the vulnerability of the networks is mirrored by what is known about the vulnerability of LTP and memory itself. Differential gene co-expression analysis further highlighted the importance of the Egr family and found a rapid enrichment in connectivity at 20 min, followed by a systematic decrease, providing a potential explanation for the down-regulation of gene expression at 24 h documented in our preceding studies. We also found that the architecture exhibited by a control and the 24 h LTP co-expression networks fit well to a scale-free distribution, known to be robust against perturbations. By contrast the 20 min and 5 h networks showed more truncated distributions. These results suggest that a new homeostatic state is achieved 24 h post-LTP. Together, these data present an integrated view of the genomic response following LTP induction by which the stability of the networks regulated at different times parallel the properties observed at the synapse. PMID:26300724

  10. SDN architecture for optical packet and circuit integrated networks

    NASA Astrophysics Data System (ADS)

    Furukawa, Hideaki; Miyazawa, Takaya

    2016-02-01

    We have been developing an optical packet and circuit integrated (OPCI) network, which realizes dynamic optical path, high-density packet multiplexing, and flexible wavelength resource allocation. In the OPCI networks, a best-effort service and a QoS-guaranteed service are provided by employing optical packet switching (OPS) and optical circuit switching (OCS) respectively, and users can select these services. Different wavelength resources are assigned for OPS and OCS links, and the amount of their wavelength resources are dynamically changed in accordance with the service usage conditions. To apply OPCI networks into wide-area (core/metro) networks, we have developed an OPCI node with a distributed control mechanism. Moreover, our OPCI node works with a centralized control mechanism as well as a distributed one. It is therefore possible to realize SDN-based OPCI networks, where resource requests and a centralized configuration are carried out. In this paper, we show our SDN architecture for an OPS system that configures mapping tables between IP addresses and optical packet addresses and switching tables according to the requests from multiple users via a web interface. While OpenFlow-based centralized control protocol is coming into widespread use especially for single-administrative, small-area (LAN/data-center) networks. Here, we also show an interworking mechanism between OpenFlow-based networks (OFNs) and the OPCI network for constructing a wide-area network, and a control method of wavelength resource selection to automatically transfer diversified flows from OFNs to the OPCI network.

  11. An efficient optical architecture for sparsely connected neural networks

    NASA Technical Reports Server (NTRS)

    Hine, Butler P., III; Downie, John D.; Reid, Max B.

    1990-01-01

    An architecture for general-purpose optical neural network processor is presented in which the interconnections and weights are formed by directing coherent beams holographically, thereby making use of the space-bandwidth products of the recording medium for sparsely interconnected networks more efficiently that the commonly used vector-matrix multiplier, since all of the hologram area is in use. An investigation is made of the use of computer-generated holograms recorded on such updatable media as thermoplastic materials, in order to define the interconnections and weights of a neural network processor; attention is given to limits on interconnection densities, diffraction efficiencies, and weighing accuracies possible with such an updatable thin film holographic device.

  12. Modeling genomic regulatory networks with big data.

    PubMed

    Bolouri, Hamid

    2014-05-01

    High-throughput sequencing, large-scale data generation projects, and web-based cloud computing are changing how computational biology is performed, who performs it, and what biological insights it can deliver. I review here the latest developments in available data, methods, and software, focusing on the modeling and analysis of the gene regulatory interactions in cells. Three key findings are: (i) although sophisticated computational resources are increasingly available to bench biologists, tailored ongoing education is necessary to avoid the erroneous use of these resources. (ii) Current models of the regulation of gene expression are far too simplistic and need updating. (iii) Integrative computational analysis of large-scale datasets is becoming a fundamental component of molecular biology. I discuss current and near-term opportunities and challenges related to these three points. PMID:24630831

  13. Disrupted Brain Functional Network Architecture in Chronic Tinnitus Patients

    PubMed Central

    Chen, Yu-Chen; Feng, Yuan; Xu, Jin-Jing; Mao, Cun-Nan; Xia, Wenqing; Ren, Jun; Yin, Xindao

    2016-01-01

    Purpose: Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated the disruptions of multiple brain networks in tinnitus patients. Nonetheless, several studies found no differences in network processing between tinnitus patients and healthy controls (HCs). Its neural bases are poorly understood. To identify aberrant brain network architecture involved in chronic tinnitus, we compared the resting-state fMRI (rs-fMRI) patterns of tinnitus patients and HCs. Materials and Methods: Chronic tinnitus patients (n = 24) with normal hearing thresholds and age-, sex-, education- and hearing threshold-matched HCs (n = 22) participated in the current study and underwent the rs-fMRI scanning. We used degree centrality (DC) to investigate functional connectivity (FC) strength of the whole-brain network and Granger causality to analyze effective connectivity in order to explore directional aspects involved in tinnitus. Results: Compared to HCs, we found significantly increased network centrality in bilateral superior frontal gyrus (SFG). Unidirectionally, the left SFG revealed increased effective connectivity to the left middle orbitofrontal cortex (OFC), left posterior lobe of cerebellum (PLC), left postcentral gyrus, and right middle occipital gyrus (MOG) while the right SFG exhibited enhanced effective connectivity to the right supplementary motor area (SMA). In addition, the effective connectivity from the bilateral SFG to the OFC and SMA showed positive correlations with tinnitus distress. Conclusions: Rs-fMRI provides a new and novel method for identifying aberrant brain network architecture. Chronic tinnitus patients have disrupted FC strength and causal connectivity mostly in non-auditory regions, especially the prefrontal cortex (PFC). The current findings will provide a new perspective for understanding the neuropathophysiological mechanisms in chronic tinnitus. PMID:27458377

  14. Resting State Networks' Corticotopy: The Dual Intertwined Rings Architecture

    PubMed Central

    Mesmoudi, Salma; Perlbarg, Vincent; Rudrauf, David; Messe, Arnaud; Pinsard, Basile; Hasboun, Dominique; Cioli, Claudia; Marrelec, Guillaume; Toro, Roberto; Benali, Habib; Burnod, Yves

    2013-01-01

    How does the brain integrate multiple sources of information to support normal sensorimotor and cognitive functions? To investigate this question we present an overall brain architecture (called “the dual intertwined rings architecture”) that relates the functional specialization of cortical networks to their spatial distribution over the cerebral cortex (or “corticotopy”). Recent results suggest that the resting state networks (RSNs) are organized into two large families: 1) a sensorimotor family that includes visual, somatic, and auditory areas and 2) a large association family that comprises parietal, temporal, and frontal regions and also includes the default mode network. We used two large databases of resting state fMRI data, from which we extracted 32 robust RSNs. We estimated: (1) the RSN functional roles by using a projection of the results on task based networks (TBNs) as referenced in large databases of fMRI activation studies; and (2) relationship of the RSNs with the Brodmann Areas. In both classifications, the 32 RSNs are organized into a remarkable architecture of two intertwined rings per hemisphere and so four rings linked by homotopic connections. The first ring forms a continuous ensemble and includes visual, somatic, and auditory cortices, with interspersed bimodal cortices (auditory-visual, visual-somatic and auditory-somatic, abbreviated as VSA ring). The second ring integrates distant parietal, temporal and frontal regions (PTF ring) through a network of association fiber tracts which closes the ring anatomically and ensures a functional continuity within the ring. The PTF ring relates association cortices specialized in attention, language and working memory, to the networks involved in motivation and biological regulation and rhythms. This “dual intertwined architecture” suggests a dual integrative process: the VSA ring performs fast real-time multimodal integration of sensorimotor information whereas the PTF ring performs multi

  15. Charting gene regulatory networks: strategies, challenges and perspectives

    PubMed Central

    2004-01-01

    One of the foremost challenges in the post-genomic era will be to chart the gene regulatory networks of cells, including aspects such as genome annotation, identification of cis-regulatory elements and transcription factors, information on protein–DNA and protein–protein interactions, and data mining and integration. Some of these broad sets of data have already been assembled for building networks of gene regulation. Even though these datasets are still far from comprehensive, and the approach faces many important and difficult challenges, some strategies have begun to make connections between disparate regulatory events and to foster new hypotheses. In this article we review several different genomics and proteomics technologies, and present bioinformatics methods for exploring these data in order to make novel discoveries. PMID:15080794

  16. Motif for controllable toggle switch in gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Zhao, Chen; Bin, Ao; Ye, Weiming; Fan, Ying; Di, Zengru

    2015-02-01

    Toggle switch as a common phenomenon in gene regulatory networks has been recognized important for biological functions. Despite much effort dedicated to understanding the toggle switch and designing synthetic biology circuit to achieve the biological function, we still lack a comprehensive understanding of the intrinsic dynamics behind such phenomenon and the minimum structure that is imperative for producing toggle switch. In this paper, we discover a minimum structure, a motif that enables a controllable toggle switch. In particular, the motif consists of a transformative double negative feedback loop (DNFL) that is regulated by an additional driver node. By enumerating all possible regulatory configurations from the driver node, we identify two types of motifs associated with the toggle switch that is captured by the existence of bistable states. The toggle switch is controllable in the sense that the gap between the bistable states is adjustable as determined by the regulatory strength from the driver nodes. We test the effect of the motifs in self-oscillating gene regulatory network (SON) with respect to the interplay between the motifs and the other genes, and find that the switching dynamics of the whole network can be successfully controlled insofar as the network contains a single motif. Our findings are important to uncover the underlying nonlinear dynamics of controllable toggle switch and can have implications in devising biology circuit in the field of synthetic biology.

  17. Compartmentalized gene regulatory network of the pathogenic fungus Fusarium graminearum

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Head blight caused by Fusarium graminearum (Fg) is a major limiting factor of wheat production with both yield loss and mycotoxin contamination. Here we report a model for global Fg gene regulatory networks (GRNs) inferred from a large collection of transcriptomic data using a machine-learning appro...

  18. SATRAT: Staphylococcus aureus transcript regulatory network analysis tool

    PubMed Central

    Nagarajan, Vijayaraj; Elasri, Mohamed O.

    2015-01-01

    Staphylococcus aureus is a commensal organism that primarily colonizes the nose of healthy individuals. S. aureus causes a spectrum of infections that range from skin and soft-tissue infections to fatal invasive diseases. S. aureus uses a large number of virulence factors that are regulated in a coordinated fashion. The complex regulatory mechanisms have been investigated in numerous high-throughput experiments. Access to this data is critical to studying this pathogen. Previously, we developed a compilation of microarray experimental data to enable researchers to search, browse, compare, and contrast transcript profiles. We have substantially updated this database and have built a novel exploratory tool—SATRAT—the S. aureus transcript regulatory network analysis tool, based on the updated database. This tool is capable of performing deep searches using a query and generating an interactive regulatory network based on associations among the regulators of any query gene. We believe this integrated regulatory network analysis tool would help researchers explore the missing links and identify novel pathways that regulate virulence in S. aureus. Also, the data model and the network generation code used to build this resource is open sourced, enabling researchers to build similar resources for other bacterial systems. PMID:25653902

  19. The brain's functional network architecture reveals human motives.

    PubMed

    Hein, Grit; Morishima, Yosuke; Leiberg, Susanne; Sul, Sunhae; Fehr, Ernst

    2016-03-01

    Goal-directed human behaviors are driven by motives. Motives are, however, purely mental constructs that are not directly observable. Here, we show that the brain's functional network architecture captures information that predicts different motives behind the same altruistic act with high accuracy. In contrast, mere activity in these regions contains no information about motives. Empathy-based altruism is primarily characterized by a positive connectivity from the anterior cingulate cortex (ACC) to the anterior insula (AI), whereas reciprocity-based altruism additionally invokes strong positive connectivity from the AI to the ACC and even stronger positive connectivity from the AI to the ventral striatum. Moreover, predominantly selfish individuals show distinct functional architectures compared to altruists, and they only increase altruistic behavior in response to empathy inductions, but not reciprocity inductions. PMID:26941317

  20. Correlation Between Channel Profile and Plan View Drainage Network Architecture

    NASA Astrophysics Data System (ADS)

    Shelef, E.; Hilley, G. E.

    2011-12-01

    This research explores the relationship between the plan-view network and profile geometry of channels using high-resolution digital topography and numerical models. In particular, we study the relations between plan-view morphometrics of the channel network and the mechanics of land-shaping processes as reflected by channel profile concavity. This analysis addresses one of the long-standing questions in geomorphology relating to the mechanistic significance of various plan-view channel network geometry measures. Statistically based studies suggest that Hortonian measures of channel network architecture (e.g. bifurcation ratio, area ratio, and length ratio) describe virtually all possible network geometries, and hence are not diagnostic when evaluating the origins of the geometry of a particular network. Our analyses of high resolution DEMs that capture different channel profile concavities (i.e debris flow vs. fluvial flows), as well as the topography of landscapes produced by process-based numerical models affirms this conclusion and indicates that Hortonian measures, as well as Hack exponent, are insensitive to channel concavity. In contrast, channel frequency (number of channel segments per area) appears to provide a measure that is sensitive to channel concavity. As such, channel frequency appears to discern between landscapes dominated by different land-shaping processes that produce different channel profile concavities. In the context of headword growing networks, the observed relations between concavity and channel frequency can be modeled through the coupled effect of concavity and surface roughness on the competition between headword growing channels. Our results suggest that the plan-view geometry of channel networks does not simply arise from random deflection of channels that once joined, cannot separate, but rather reflects the underlying processes that incise through rock and transport mass through the channel network

  1. A solution for parallel network architectures applied to network defense appliances and sensors

    NASA Astrophysics Data System (ADS)

    Naber, Eric C.; Velez, Paul G.; Johal, Amanpreet S.

    2012-06-01

    Network defense has more technologies available for purchase today than ever before. As the number of threats increase, organizations are deploying multiple defense technologies to defend their networks. For instance, an enterprise network boundary often implements multiple network defense appliances, some with overlapping capabilities (e.g., firewalls, IDS/IPS, DNS Defense). These appliances are applied in a serial fashion to create a chain of network processing specifically designed to drop bad traffic from the network. In these architectures, once a packet is dropped by an appliance subsequent appliances do not process it. This introduces significant limitations; (1) Stateful appliances will maintain an internal state which differs from network reality; (2) The network manager cannot determine, or unit test, how each appliance would have treated each packet; (3) The appliance "votes" cannot be combined to achieve higherlevel functionality. To address these limitations, we have developed a novel, backwards-compatible Parallel Architecture for Network Defense Appliances (PANDA). Our approach allows every appliance to process all network traffic and cast a vote to drop or allow each packet. This "crowd-sourcing" approach allows the network designer to take full advantage of each appliance, understand how each appliance is behaving, and achieve new collaborative appliance behavior.

  2. Signalling design and architecture for a proposed mobile satellite network

    NASA Technical Reports Server (NTRS)

    Yan, T.-Y.; Cheng, U.; Wang, C.

    1990-01-01

    In a frequency-division/demand-assigned multiple-access (FD/DAMA) architecture, each mobile subscriber must make a connection request to the Network Management Center before transmission for either open-end or closed-end services. Open-end services are for voice calls and long file transfer and are processed on a blocked-call-cleared basis. Closed-end services are for transmitting burst data and are processed on a first-come first-served basis. This paper presents the signalling design and architecture for non-voice services of an FD/DAMA mobile satellite network. The connection requests are made through the recently proposed multiple channel collision resolution scheme which provides a significantly higher throughput than the traditional slotted ALOHA scheme. For non-voice services, it is well known that retransmissions are necessary to ensure the delivery of a message in its entirety from the source to destination. Retransmission protocols for open-end and closed-end data transfer are investigated. The signal structure for the proposed network is derived from X-25 standards with appropriate modifications. The packet types and their usages are described in this paper.

  3. Network architecture underlying maximal separation of neuronal representations

    PubMed Central

    Jortner, Ron A.

    2011-01-01

    One of the most basic and general tasks faced by all nervous systems is extracting relevant information from the organism's surrounding world. While physical signals available to sensory systems are often continuous, variable, overlapping, and noisy, high-level neuronal representations used for decision-making tend to be discrete, specific, invariant, and highly separable. This study addresses the question of how neuronal specificity is generated. Inspired by experimental findings on network architecture in the olfactory system of the locust, I construct a highly simplified theoretical framework which allows for analytic solution of its key properties. For generalized feed-forward systems, I show that an intermediate range of connectivity values between source- and target-populations leads to a combinatorial explosion of wiring possibilities, resulting in input spaces which are, by their very nature, exquisitely sparsely populated. In particular, connection probability ½, as found in the locust antennal-lobe–mushroom-body circuit, serves to maximize separation of neuronal representations across the target Kenyon cells (KCs), and explains their specific and reliable responses. This analysis yields a function expressing response specificity in terms of lower network parameters; together with appropriate gain control this leads to a simple neuronal algorithm for generating arbitrarily sparse and selective codes and linking network architecture and neural coding. I suggest a straightforward way to construct ecologically meaningful representations from this code. PMID:23316159

  4. Randomly evolving idiotypic networks: Structural properties and architecture

    NASA Astrophysics Data System (ADS)

    Schmidtchen, Holger; Thüne, Mario; Behn, Ulrich

    2012-07-01

    We consider a minimalistic dynamic model of the idiotypic network of B lymphocytes. A network node represents a population of B lymphocytes of the same specificity (idiotype), which is encoded by a bit string. The links of the network connect nodes with complementary and nearly complementary bit strings, allowing for a few mismatches. A node is occupied if a lymphocyte clone of the corresponding idiotype exists; otherwise it is empty. There is a continuous influx of new B lymphocytes of random idiotype from the bone marrow. B lymphocytes are stimulated by cross-linking their receptors with complementary structures. If there are too many complementary structures, steric hindrance prevents cross-linking. Stimulated cells proliferate and secrete antibodies of the same idiotype as their receptors; unstimulated lymphocytes die. Depending on few parameters, the autonomous system evolves randomly towards patterns of highly organized architecture, where the nodes can be classified into groups according to their statistical properties. We observe and describe analytically the building principles of these patterns, which make it possible to calculate number and size of the node groups and the number of links between them. The architecture of all patterns observed so far in simulations can be explained this way. A tool for real-time pattern identification is proposed.

  5. Genomic analysis of the hierarchical structure of regulatory networks

    PubMed Central

    Yu, Haiyuan; Gerstein, Mark

    2006-01-01

    A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

  6. EXAMINE: a computational approach to reconstructing gene regulatory networks.

    PubMed

    Deng, Xutao; Geng, Huimin; Ali, Hesham

    2005-08-01

    Reverse-engineering of gene networks using linear models often results in an underdetermined system because of excessive unknown parameters. In addition, the practical utility of linear models has remained unclear. We address these problems by developing an improved method, EXpression Array MINing Engine (EXAMINE), to infer gene regulatory networks from time-series gene expression data sets. EXAMINE takes advantage of sparse graph theory to overcome the excessive-parameter problem with an adaptive-connectivity model and fitting algorithm. EXAMINE also guarantees that the most parsimonious network structure will be found with its incremental adaptive fitting process. Compared to previous linear models, where a fully connected model is used, EXAMINE reduces the number of parameters by O(N), thereby increasing the chance of recovering the underlying regulatory network. The fitting algorithm increments the connectivity during the fitting process until a satisfactory fit is obtained. We performed a systematic study to explore the data mining ability of linear models. A guideline for using linear models is provided: If the system is small (3-20 elements), more than 90% of the regulation pathways can be determined correctly. For a large-scale system, either clustering is needed or it is necessary to integrate information in addition to expression profile. Coupled with the clustering method, we applied EXAMINE to rat central nervous system development (CNS) data with 112 genes. We were able to efficiently generate regulatory networks with statistically significant pathways that have been predicted previously. PMID:15951103

  7. Integrating heterogeneous gene expression data for gene regulatory network modelling.

    PubMed

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

    2012-06-01

    Gene regulatory networks (GRNs) are complex biological systems that have a large impact on protein levels, so that discovering network interactions is a major objective of systems biology. Quantitative GRN models have been inferred, to date, from time series measurements of gene expression, but at small scale, and with limited application to real data. Time series experiments are typically short (number of time points of the order of ten), whereas regulatory networks can be very large (containing hundreds of genes). This creates an under-determination problem, which negatively influences the results of any inferential algorithm. Presented here is an integrative approach to model inference, which has not been previously discussed to the authors' knowledge. Multiple heterogeneous expression time series are used to infer the same model, and results are shown to be more robust to noise and parameter perturbation. Additionally, a wavelet analysis shows that these models display limited noise over-fitting within the individual datasets. PMID:21948152

  8. Cross-fertilization between connectionist networks and highly parallel architectures

    NASA Technical Reports Server (NTRS)

    Barnden, John; Srinivas, Kankanahalli

    1989-01-01

    The theoretical and practical connections between connectionist schemes such as neural-network computers and traditional symbolic processing architectures involving a high degree of parallelism are explored, reviewing the results of recent investigations. Topics addressed include data flow, data structure, and control flow; conventional pointers; associative addressing; hashing and reduced representations; the problem of binding values to variables; and levels of parallelism. It is concluded that connectionism is more closely related to traditional computer science and technology than is generally admitted; more cooperation between followers of the two approaches is recommended.

  9. Implicit methods for qualitative modeling of gene regulatory networks.

    PubMed

    Garg, Abhishek; Mohanram, Kartik; De Micheli, Giovanni; Xenarios, Ioannis

    2012-01-01

    Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments. PMID:21938638

  10. A hybrid 802.16/802.11 network architecture for a United States coastal area network

    NASA Astrophysics Data System (ADS)

    Burbank, Jack L.; Kasch, William T.; Andrusenko, Julia; Haberman, Brian K.; Nichols, Robert; Zheng, Harold

    2007-04-01

    This paper presents a concept for a United States Coastal Area Network (U-SCAN) that is comprised of IEEE 802.11, 802.16, and satellite communications technologies. The Office of Naval Research (ONR) on behalf of the National Oceanographic Partnership Program (NOPP) has tasked The Johns Hopkins University Applied Physics Laboratory (JHU/APL) to perform an architectural study into the establishment of a United States Coastal Area Network (U-SCAN). The goal of this study is to define a wireless network architecture that can be deployed to enable contiguous coastal area network coverage for scientific, commercial, and homeland security (e.g. Coast Guard) applications within the United States Exclusive Economic Zone (EEZ), in a manner that is flexible, manageable, and affordable. The JHU/APL study will ultimately provide recommendations to NOPP regarding potential network architectures and technologies that could provide the desired capability, with a particular focus on commercial (both existing and emerging) technologies. This paper presents the envisioned U-SCAN architecture, and presents the envisioned technical capabilities and shortcomings of the component candidate technologies.

  11. Multivariate analysis of noise in genetic regulatory networks.

    PubMed

    Tomioka, Ryota; Kimura, Hidenori; J Kobayashi, Tetsuya; Aihara, Kazuyuki

    2004-08-21

    Stochasticity is an intrinsic property of genetic regulatory networks due to the low copy numbers of the major molecular species, such as, DNA, mRNA, and regulatory proteins. Therefore, investigation of the mechanisms that reduce the stochastic noise is essential in understanding the reproducible behaviors of real organisms and is also a key to design synthetic genetic regulatory networks that can reliably work. We use an analytical and systematic method, the linear noise approximation of the chemical master equation along with the decoupling of a stoichiometric matrix. In the analysis of fluctuations of multiple molecular species, the covariance is an important measure of noise. However, usually the representation of a covariance matrix in the natural coordinate system, i.e. the copy numbers of the molecular species, is intractably complicated because reactions change copy numbers of more than one molecular species simultaneously. Decoupling of a stoichiometric matrix, which is a transformation of variables, significantly simplifies the representation of a covariance matrix and elucidates the mechanisms behind the observed fluctuations in the copy numbers. We apply our method to three types of fundamental genetic regulatory networks, that is, a single-gene autoregulatory network, a two-gene autoregulatory network, and a mutually repressive network. We have found that there are multiple noise components differently originating. Each noise component produces fluctuation in the characteristic direction. The resulting fluctuations in the copy numbers of the molecular species are the sum of these fluctuations. In the examples, the limitation of the negative feedback in noise reduction and the trade-off of fluctuations in multiple molecular species are clearly explained. The analytical representations show the full parameter dependence. Additionally, the validity of our method is tested by stochastic simulations. PMID:15246787

  12. Global Analysis of Photosynthesis Transcriptional Regulatory Networks

    PubMed Central

    Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.

    2014-01-01

    Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis. PMID:25503406

  13. Global analysis of photosynthesis transcriptional regulatory networks.

    PubMed

    Imam, Saheed; Noguera, Daniel R; Donohue, Timothy J

    2014-12-01

    Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis. PMID:25503406

  14. Gene Regulatory Networks Elucidating Huanglongbing Disease Mechanisms

    PubMed Central

    Martinelli, Federico; Reagan, Russell L.; Uratsu, Sandra L.; Phu, My L.; Albrecht, Ute; Zhao, Weixiang; Davis, Cristina E.; Bowman, Kim D.; Dandekar, Abhaya M.

    2013-01-01

    Next-generation sequencing was exploited to gain deeper insight into the response to infection by Candidatus liberibacter asiaticus (CaLas), especially the immune disregulation and metabolic dysfunction caused by source-sink disruption. Previous fruit transcriptome data were compared with additional RNA-Seq data in three tissues: immature fruit, and young and mature leaves. Four categories of orchard trees were studied: symptomatic, asymptomatic, apparently healthy, and healthy. Principal component analysis found distinct expression patterns between immature and mature fruits and leaf samples for all four categories of trees. A predicted protein – protein interaction network identified HLB-regulated genes for sugar transporters playing key roles in the overall plant responses. Gene set and pathway enrichment analyses highlight the role of sucrose and starch metabolism in disease symptom development in all tissues. HLB-regulated genes (glucose-phosphate-transporter, invertase, starch-related genes) would likely determine the source-sink relationship disruption. In infected leaves, transcriptomic changes were observed for light reactions genes (downregulation), sucrose metabolism (upregulation), and starch biosynthesis (upregulation). In parallel, symptomatic fruits over-expressed genes involved in photosynthesis, sucrose and raffinose metabolism, and downregulated starch biosynthesis. We visualized gene networks between tissues inducing a source-sink shift. CaLas alters the hormone crosstalk, resulting in weak and ineffective tissue-specific plant immune responses necessary for bacterial clearance. Accordingly, expression of WRKYs (including WRKY70) was higher in fruits than in leaves. Systemic acquired responses were inadequately activated in young leaves, generally considered the sites where most new infections occur. PMID:24086326

  15. Using Distributed Sensor Network Architecture to Link Heterogeneous Astronomical Assets

    NASA Astrophysics Data System (ADS)

    White, R.; Evans, S.; Pergande, J.; Vestrand, W.; Wozniak, P.; Wren, J.

    The internet has brought about great change in the astronomical community, but this interconnectivity is just starting to be exploited for use in this type of instrumentation. Here we present the Telescope ALert Operations Network System (TALONS), a network software suite that allows intercommunication between external and internal astronomical resources and controls the distribution of information to each of the resources. TALONS is an fundamental element of the Thinking Telescopes System, in operation at Los Alamos National Laboratory, and has been enabling great science for the past four years. The system allows a distributed network of telescopes to perform more efficiently in synchronous operation than as individual instruments. TALONS is designed as a merger between a standard server/client architecture and a Distributed Sensor Network (DSN). It can dynamically regulate its client base, allowing any number of heterogeneous resources to be linked together and communicate. TALONS couples that capability with collaborative analysis and maintenance modules so that it can respond quickly to external requests and changing network environments. TALONS clients connect via an intelligent agent, which acts in proxy for the scientist, allowing the telescope to analyze incoming information and respond autonomously. TALONS has a proven track record of effectively supporting the instruments at Los Alamos and other astronomical resources around the world.

  16. Differential Regulatory Analysis Based on Coexpression Network in Cancer Research.

    PubMed

    Li, Junyi; Li, Yi-Xue; Li, Yuan-Yuan

    2016-01-01

    With rapid development of high-throughput techniques and accumulation of big transcriptomic data, plenty of computational methods and algorithms such as differential analysis and network analysis have been proposed to explore genome-wide gene expression characteristics. These efforts are aiming to transform underlying genomic information into valuable knowledges in biological and medical research fields. Recently, tremendous integrative research methods are dedicated to interpret the development and progress of neoplastic diseases, whereas differential regulatory analysis (DRA) based on gene coexpression network (GCN) increasingly plays a robust complement to regular differential expression analysis in revealing regulatory functions of cancer related genes such as evading growth suppressors and resisting cell death. Differential regulatory analysis based on GCN is prospective and shows its essential role in discovering the system properties of carcinogenesis features. Here we briefly review the paradigm of differential regulatory analysis based on GCN. We also focus on the applications of differential regulatory analysis based on GCN in cancer research and point out that DRA is necessary and extraordinary to reveal underlying molecular mechanism in large-scale carcinogenesis studies. PMID:27597964

  17. Differential Regulatory Analysis Based on Coexpression Network in Cancer Research

    PubMed Central

    2016-01-01

    With rapid development of high-throughput techniques and accumulation of big transcriptomic data, plenty of computational methods and algorithms such as differential analysis and network analysis have been proposed to explore genome-wide gene expression characteristics. These efforts are aiming to transform underlying genomic information into valuable knowledges in biological and medical research fields. Recently, tremendous integrative research methods are dedicated to interpret the development and progress of neoplastic diseases, whereas differential regulatory analysis (DRA) based on gene coexpression network (GCN) increasingly plays a robust complement to regular differential expression analysis in revealing regulatory functions of cancer related genes such as evading growth suppressors and resisting cell death. Differential regulatory analysis based on GCN is prospective and shows its essential role in discovering the system properties of carcinogenesis features. Here we briefly review the paradigm of differential regulatory analysis based on GCN. We also focus on the applications of differential regulatory analysis based on GCN in cancer research and point out that DRA is necessary and extraordinary to reveal underlying molecular mechanism in large-scale carcinogenesis studies. PMID:27597964

  18. Automated Identification of Core Regulatory Genes in Human Gene Regulatory Networks

    PubMed Central

    Singhal, Amit; Kumar, Pavanish; de Libero, Gennaro; Poidinger, Michael; Monterola, Christopher

    2015-01-01

    Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript. PMID:26393364

  19. An architecture for designing fuzzy logic controllers using neural networks

    NASA Technical Reports Server (NTRS)

    Berenji, Hamid R.

    1991-01-01

    Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

  20. A gene regulatory network armature for T-lymphocyte specification

    SciTech Connect

    Fung, Elizabeth-sharon

    2008-01-01

    Choice of a T-lymphoid fate by hematopoietic progenitor cells depends on sustained Notch-Delta signaling combined with tightly-regulated activities of multiple transcription factors. To dissect the regulatory network connections that mediate this process, we have used high-resolution analysis of regulatory gene expression trajectories from the beginning to the end of specification; tests of the short-term Notchdependence of these gene expression changes; and perturbation analyses of the effects of overexpression of two essential transcription factors, namely PU.l and GATA-3. Quantitative expression measurements of >50 transcription factor and marker genes have been used to derive the principal components of regulatory change through which T-cell precursors progress from primitive multipotency to T-lineage commitment. Distinct parts of the path reveal separate contributions of Notch signaling, GATA-3 activity, and downregulation of PU.l. Using BioTapestry, the results have been assembled into a draft gene regulatory network for the specification of T-cell precursors and the choice of T as opposed to myeloid dendritic or mast-cell fates. This network also accommodates effects of E proteins and mutual repression circuits of Gfil against Egr-2 and of TCF-l against PU.l as proposed elsewhere, but requires additional functions that remain unidentified. Distinctive features of this network structure include the intense dose-dependence of GATA-3 effects; the gene-specific modulation of PU.l activity based on Notch activity; the lack of direct opposition between PU.l and GATA-3; and the need for a distinct, late-acting repressive function or functions to extinguish stem and progenitor-derived regulatory gene expression.

  1. On-board processing satellite network architecture and control study

    NASA Technical Reports Server (NTRS)

    Campanella, S. Joseph; Pontano, B.; Chalmers, H.

    1987-01-01

    For satellites to remain a vital part of future national and international communications, system concepts that use their inherent advantages to the fullest must be created. Network architectures that take maximum advantage of satellites equipped with onboard processing are explored. Satellite generations must accommodate various services for which satellites constitute the preferred vehicle of delivery. Such services tend to be those that are widely dispersed and present thin to medium loads to the system. Typical systems considered are thin and medium route telephony, maritime, land and aeronautical radio, VSAT data, low bit rate video teleconferencing, and high bit rate broadcast of high definition video. Delivery of services by TDMA and FDMA multiplexing techniques and combinations of the two for individual and mixed service types are studied. The possibilities offered by onboard circuit switched and packet switched architectures are examined and the results strongly support a preference for the latter. A detailed design architecture encompassing the onboard packet switch and its control, the related demand assigned TDMA burst structures, and destination packet protocols for routing traffic are presented. Fundamental onboard hardware requirements comprising speed, memory size, chip count, and power are estimated. The study concludes with identification of key enabling technologies and identifies a plan to develop a POC model.

  2. Space Mobile Network: A Near Earth Communications and Navigation Architecture

    NASA Technical Reports Server (NTRS)

    Israel, David J.; Heckler, Gregory W.; Menrad, Robert J.

    2016-01-01

    This paper shares key findings of NASA's Earth Regime Network Evolution Study (ERNESt) team resulting from its 18-month effort to define a wholly new architecture-level paradigm for the exploitation of space by civil space and commercial sector organizations. Since the launch of Sputnik in October 1957 spaceflight missions have remained highly scripted activities from launch through disposal. The utilization of computer technology has enabled dramatic increases in mission complexity; but, the underlying premise that the diverse actions necessary to meet mission goals requires minute-by-minute scripting, defined weeks in advance of execution, for the life of the mission has remained. This archetype was appropriate for a "new frontier" but now risks overtly constraining the potential market-based opportunities for the innovation considered necessary to efficiently address the complexities associated with meeting communications and navigation requirements projected to be characteristics of the next era of space exploration: a growing number of missions in simultaneous execution, increased variance of mission types and growth in location/orbital regime diversity. The resulting ERNESt architectural cornerstone - the Space Mobile Network (SMN) - was envisioned as critical to creating an environment essential to meeting these future challenges in political, programmatic, technological and budgetary terms. The SMN incorporates technologies such as: Disruption Tolerant Networking (DTN) and optical communications, as well as new operations concepts such as User Initiated Services (UIS) to provide user services analogous to today's terrestrial mobile network user. Results developed in collaboration with NASA's Space Communications and Navigation (SCaN) Division and field centers are reported on. Findings have been validated via briefings to external focus groups and initial ground-based demonstrations. The SMN opens new niches for exploitation by the marketplace of mission

  3. Exploring the miRNA Regulatory Network Using Evolutionary Correlations

    PubMed Central

    Obermayer, Benedikt; Levine, Erel

    2014-01-01

    Post-transcriptional regulation by miRNAs is a widespread and highly conserved phenomenon in metazoans, with several hundreds to thousands of conserved binding sites for each miRNA, and up to two thirds of all genes under miRNA regulation. At the same time, the effect of miRNA regulation on mRNA and protein levels is usually quite modest and associated phenotypes are often weak or subtle. This has given rise to the notion that the highly interconnected miRNA regulatory network exerts its function less through any individual link and more via collective effects that lead to a functional interdependence of network links. We present a Bayesian framework to quantify conservation of miRNA target sites using vertebrate whole-genome alignments. The increased statistical power of our phylogenetic model allows detection of evolutionary correlation in the conservation patterns of site pairs. Such correlations could result from collective functions in the regulatory network. For instance, co-conservation of target site pairs supports a selective benefit of combinatorial regulation by multiple miRNAs. We find that some miRNA families are under pronounced co-targeting constraints, indicating a high connectivity in the regulatory network, while others appear to function in a more isolated way. By analyzing coordinated targeting of different curated gene sets, we observe distinct evolutionary signatures for protein complexes and signaling pathways that could reflect differences in control strategies. Our method is easily scalable to analyze upcoming larger data sets, and readily adaptable to detect high-level selective constraints between other genomic loci. We thus provide a proof-of-principle method to understand regulatory networks from an evolutionary perspective. PMID:25299225

  4. The nucleosome landscape of Plasmodium falciparum reveals chromatin architecture and dynamics of regulatory sequences

    PubMed Central

    Kensche, Philip Reiner; Hoeijmakers, Wieteke Anna Maria; Toenhake, Christa Geeke; Bras, Maaike; Chappell, Lia; Berriman, Matthew; Bártfai, Richárd

    2016-01-01

    In eukaryotes, the chromatin architecture has a pivotal role in regulating all DNA-associated processes and it is central to the control of gene expression. For Plasmodium falciparum, a causative agent of human malaria, the nucleosome positioning profile of regulatory regions deserves particular attention because of their extreme AT-content. With the aid of a highly controlled MNase-seq procedure we reveal how positioning of nucleosomes provides a structural and regulatory framework to the transcriptional unit by demarcating landmark sites (transcription/translation start and end sites). In addition, our analysis provides strong indications for the function of positioned nucleosomes in splice site recognition. Transcription start sites (TSSs) are bordered by a small nucleosome-depleted region, but lack the stereotypic downstream nucleosome arrays, highlighting a key difference in chromatin organization compared to model organisms. Furthermore, we observe transcription-coupled eviction of nucleosomes on strong TSSs during intraerythrocytic development and demonstrate that nucleosome positioning and dynamics can be predictive for the functionality of regulatory DNA elements. Collectively, the strong nucleosome positioning over splice sites and surrounding putative transcription factor binding sites highlights the regulatory capacity of the nucleosome landscape in this deadly human pathogen. PMID:26578577

  5. Shifts in the architecture of the Nationwide Health Information Network

    PubMed Central

    Sundwall, David; Lenert, Michael Edward

    2012-01-01

    In the midst of a US $30 billion USD investment in the Nationwide Health Information Network (NwHIN) and electronic health records systems, a significant change in the architecture of the NwHIN is taking place. Prior to 2010, the focus of information exchange in the NwHIN was the Regional Health Information Organization (RHIO). Since 2010, the Office of the National Coordinator (ONC) has been sponsoring policies that promote an internet-like architecture that encourages point to-point information exchange and private health information exchange networks. The net effect of these activities is to undercut the limited business model for RHIOs, decreasing the likelihood of their success, while making the NwHIN dependent on nascent technologies for community level functions such as record locator services. These changes may impact the health of patients and communities. Independent, scientifically focused debate is needed on the wisdom of ONC's proposed changes in its strategy for the NwHIN. PMID:22268218

  6. Engineered skeletal muscle tissue networks with controllable architecture

    PubMed Central

    Bian, Weining; Bursac, Nenad

    2009-01-01

    The engineering of functional skeletal muscle tissue substitutes holds promise for the treatment of various muscular diseases and injuries. However, no tissue fabrication technology currently exists for the generation of a relatively large and thick bioartificial muscle made of densely packed, uniformly aligned, and differentiated myofibers. In this study, we describe a versatile cell/hydrogel micromolding approach where polydimethylsiloxane (PDMS) molds containing an array of elongated posts were used to fabricate relatively large neonatal rat skeletal muscle tissue networks with reproducible and controllable architecture. By combining cell-mediated fibrin gel compaction and precise microfabrication of mold dimensions including the length and height of the PDMS posts, we were able to simultaneously support high cell viability, guide cell alignment along the microfabricated tissue pores, and reproducibly control the overall tissue porosity, size, and thickness. The interconnected muscle bundles within the porous tissue networks were composed of densely packed, aligned, and highly differentiated myofibers. The formed myofibers expressed myogenin, developed abundant cross-striations, and generated spontaneous tissue contractions at the macroscopic spatial scale. The proliferation of non-muscle cells was significantly reduced compared to monolayer cultures. The more complex muscle tissue architectures were fabricated by controlling the spatial distribution and direction of the PDMS posts. PMID:19070360

  7. Interactions between Distant ceRNAs in Regulatory Networks

    PubMed Central

    Nitzan, Mor; Steiman-Shimony, Avital; Altuvia, Yael; Biham, Ofer; Margalit, Hanah

    2014-01-01

    Competing endogenous RNAs (ceRNAs) were recently introduced as RNA transcripts that affect each other’s expression level through competition for their microRNA (miRNA) coregulators. This stems from the bidirectional effects between miRNAs and their target RNAs, where a change in the expression level of one target affects the level of the miRNA regulator, which in turn affects the level of other targets. By the same logic, miRNAs that share targets compete over binding to their common targets and therefore also exhibit ceRNA-like behavior. Taken together, perturbation effects could propagate in the posttranscriptional regulatory network through a path of coregulated targets and miRNAs that share targets, suggesting the existence of distant ceRNAs. Here we study the prevalence of distant ceRNAs and their effect in cellular networks. Analyzing the network of miRNA-target interactions deciphered experimentally in HEK293 cells, we show that it is a dense, intertwined network, suggesting that many nodes can act as distant ceRNAs of one another. Indeed, using gene expression data from a perturbation experiment, we demonstrate small, yet statistically significant, changes in gene expression caused by distant ceRNAs in that network. We further characterize the magnitude of the propagated perturbation effect and the parameters affecting it by mathematical modeling and simulations. Our results show that the magnitude of the effect depends on the generation and degradation rates of involved miRNAs and targets, their interaction rates, the distance between the ceRNAs and the topology of the network. Although demonstrated for a miRNA-mRNA regulatory network, our results offer what to our knowledge is a new view on various posttranscriptional cellular networks, expanding the concept of ceRNAs and implying possible distant cross talk within the network, with consequences for the interpretation of indirect effects of gene perturbation. PMID:24853754

  8. Firewall Architectures for High-Speed Networks: Final Report

    SciTech Connect

    Errin W. Fulp

    2007-08-20

    Firewalls are a key component for securing networks that are vital to government agencies and private industry. They enforce a security policy by inspecting and filtering traffic arriving or departing from a secure network. While performing these critical security operations, firewalls must act transparent to legitimate users, with little or no effect on the perceived network performance (QoS). Packets must be inspected and compared against increasingly complex rule sets and tables, which is a time-consuming process. As a result, current firewall systems can introduce significant delays and are unable to maintain QoS guarantees. Furthermore, firewalls are susceptible to Denial of Service (DoS) attacks that merely overload/saturate the firewall with illegitimate traffic. Current firewall technology only offers a short-term solution that is not scalable; therefore, the \\textbf{objective of this DOE project was to develop new firewall optimization techniques and architectures} that meet these important challenges. Firewall optimization concerns decreasing the number of comparisons required per packet, which reduces processing time and delay. This is done by reorganizing policy rules via special sorting techniques that maintain the original policy integrity. This research is important since it applies to current and future firewall systems. Another method for increasing firewall performance is with new firewall designs. The architectures under investigation consist of multiple firewalls that collectively enforce a security policy. Our innovative distributed systems quickly divide traffic across different levels based on perceived threat, allowing traffic to be processed in parallel (beyond current firewall sandwich technology). Traffic deemed safe is transmitted to the secure network, while remaining traffic is forwarded to lower levels for further examination. The result of this divide-and-conquer strategy is lower delays for legitimate traffic, higher throughput

  9. Cis-regulatory architecture of a brain signaling center predates the origin of chordates.

    PubMed

    Yao, Yao; Minor, Paul J; Zhao, Ying-Tao; Jeong, Yongsu; Pani, Ariel M; King, Anna N; Symmons, Orsolya; Gan, Lin; Cardoso, Wellington V; Spitz, François; Lowe, Christopher J; Epstein, Douglas J

    2016-05-01

    Genomic approaches have predicted hundreds of thousands of tissue-specific cis-regulatory sequences, but the determinants critical to their function and evolutionary history are mostly unknown. Here we systematically decode a set of brain enhancers active in the zona limitans intrathalamica (zli), a signaling center essential for vertebrate forebrain development via the secreted morphogen Sonic hedgehog (Shh). We apply a de novo motif analysis tool to identify six position-independent sequence motifs together with their cognate transcription factors that are essential for zli enhancer activity and Shh expression in the mouse embryo. Using knowledge of this regulatory lexicon, we discover new Shh zli enhancers in mice and a functionally equivalent element in hemichordates, indicating an ancient origin of the Shh zli regulatory network that predates the chordate phylum. These findings support a strategy for delineating functionally conserved enhancers in the absence of overt sequence homologies and over extensive evolutionary distances. PMID:27064252

  10. MicroRNA Regulatory Networks in Cardiovascular Development

    PubMed Central

    Liu, Ning; Olson, Eric N.

    2010-01-01

    The heart, more than any other organ, requires precise function on a second-to-second basis throughout the lifespan of the organism. Even subtle perturbations in cardiac structure or function have catastrophic consequences, resulting in lethal forms of congenital and adult heart disease. Such intolerance of the heart to variability necessitates especially robust regulatory mechanisms to govern cardiac gene expression. Recent studies have revealed central roles for microRNAs (miRNAs) as governors of gene expression during cardiovascular development and disease. The integration of miRNAs into the genetic circuitry of the heart provides a rich and robust array of regulatory interactions to control cardiac gene expression. miRNA regulatory networks also offer opportunities for therapeutically modulating cardiac function through the manipulation of pathogenic and protective miRNAs. We discuss the roles of miRNAs as regulators of cardiac form and function, unresolved questions in the field, and issues for the future. PMID:20412767

  11. Proposal of a multi-layer network architecture for OBS/GMPLS network interworking

    NASA Astrophysics Data System (ADS)

    Guo, Hongxiang; Tsuritani, Takehiro; Yin, Yawei; Otani, Tomohiro; Wu, Jian

    2007-11-01

    In order to enable the existing optical circuit switching (OCS) network to support both wavelength and subwavelength granularities, this paper proposes overlay-based multi-layer network architecture for interworking the generalized multi-protocol label switching (GMPLS) controlled OCS network with optical burst switching (OBS) networks. A dedicated GMPLS border controller with necessary GMPLS extensions, including group label switching path (LSP) provisioning, node capability advertisement, and standard wavelength label as well as wavelength availability advertisement, is introduced in this multi-layer network to enable a simple but flexible interworking operation. The feasibility of this proposal is experimentally confirmed by demonstrating an OBS/GMPLS testbed, in which the extended node capability advertisement and group LSP functions successfully enabled the burst header packet (BHP) and data burst (DB) to transmit over a GMPLS-controlled transparent OCS network.

  12. Master Regulators, Regulatory Networks, and Pathways of Glioblastoma Subtypes

    PubMed Central

    Bozdag, Serdar; Li, Aiguo; Baysan, Mehmet; Fine, Howard A

    2014-01-01

    Glioblastoma multiforme (GBM) is the most common malignant brain tumor. GBM samples are classified into subtypes based on their transcriptomic and epigenetic profiles. Despite numerous studies to better characterize GBM biology, a comprehensive study to identify GBM subtype- specific master regulators, gene regulatory networks, and pathways is missing. Here, we used FastMEDUSA to compute master regulators and gene regulatory networks for each GBM subtype. We also ran Gene Set Enrichment Analysis and Ingenuity Pathway Analysis on GBM expression dataset from The Cancer Genome Atlas Project to compute GBM- and GBM subtype-specific pathways. Our analysis was able to recover some of the known master regulators and pathways in GBM as well as some putative novel regulators and pathways, which will aide in our understanding of the unique biology of GBM subtypes. PMID:25368508

  13. Identification of Neurodegenerative Factors Using Translatome-Regulatory Network Analysis

    PubMed Central

    Brichta, Lars; Shin, William; Jackson-Lewis, Vernice; Blesa, Javier; Yap, Ee-Lynn; Walker, Zachary; Zhang, Jack; Roussarie, Jean-Pierre; Alvarez, Mariano J.; Califano, Andrea; Przedborski, Serge; Greengard, Paul

    2016-01-01

    For degenerative disorders of the central nervous system, the major obstacle to therapeutic advancement has been the challenge of identifying the key molecular mechanisms underlying neuronal loss. We developed a combinatorial approach including translational profiling and brain regulatory network analysis to search for key determinants of neuronal survival or death. Following the generation of transgenic mice for cell type-specific profiling of midbrain dopaminergic neurons, we established and compared translatome libraries reflecting the molecular signature of these cells at baseline or under degenerative stress. Analysis of these libraries by interrogating a context-specific brain regulatory network led to the identification of a repertoire of intrinsic upstream regulators that drive the dopaminergic stress response. The altered activity of these regulators was not associated with changes in their expression levels. This strategy can be generalized for the elucidation of novel molecular determinants involved in the degeneration of other classes of neurons. PMID:26214373

  14. Modeling Regulatory Networks to Understand Plant Development: Small Is Beautiful

    PubMed Central

    Middleton, Alistair M.; Farcot, Etienne; Owen, Markus R.; Vernoux, Teva

    2012-01-01

    We now have unprecedented capability to generate large data sets on the myriad genes and molecular players that regulate plant development. Networks of interactions between systems components can be derived from that data in various ways and can be used to develop mathematical models of various degrees of sophistication. Here, we discuss why, in many cases, it is productive to focus on small networks. We provide a brief and accessible introduction to relevant mathematical and computational approaches to model regulatory networks and discuss examples of small network models that have helped generate new insights into plant biology (where small is beautiful), such as in circadian rhythms, hormone signaling, and tissue patterning. We conclude by outlining some of the key technical and modeling challenges for the future. PMID:23110896

  15. Modeling regulatory networks to understand plant development: small is beautiful.

    PubMed

    Middleton, Alistair M; Farcot, Etienne; Owen, Markus R; Vernoux, Teva

    2012-10-01

    We now have unprecedented capability to generate large data sets on the myriad genes and molecular players that regulate plant development. Networks of interactions between systems components can be derived from that data in various ways and can be used to develop mathematical models of various degrees of sophistication. Here, we discuss why, in many cases, it is productive to focus on small networks. We provide a brief and accessible introduction to relevant mathematical and computational approaches to model regulatory networks and discuss examples of small network models that have helped generate new insights into plant biology (where small is beautiful), such as in circadian rhythms, hormone signaling, and tissue patterning. We conclude by outlining some of the key technical and modeling challenges for the future. PMID:23110896

  16. Multicolor labeling in developmental gene regulatory network analysis.

    PubMed

    Sethi, Aditya J; Angerer, Robert C; Angerer, Lynne M

    2014-01-01

    The sea urchin embryo is an important model system for developmental gene regulatory network (GRN) analysis. This chapter describes the use of multicolor fluorescent in situ hybridization (FISH) as well as a combination of FISH and immunohistochemistry in sea urchin embryonic GRN studies. The methods presented here can be applied to a variety of experimental settings where accurate spatial resolution of multiple gene products is required for constructing a developmental GRN. PMID:24567220

  17. An algebra-based method for inferring gene regulatory networks

    PubMed Central

    2014-01-01

    Background The inference of gene regulatory networks (GRNs) from experimental observations is at the heart of systems biology. This includes the inference of both the network topology and its dynamics. While there are many algorithms available to infer the network topology from experimental data, less emphasis has been placed on methods that infer network dynamics. Furthermore, since the network inference problem is typically underdetermined, it is essential to have the option of incorporating into the inference process, prior knowledge about the network, along with an effective description of the search space of dynamic models. Finally, it is also important to have an understanding of how a given inference method is affected by experimental and other noise in the data used. Results This paper contains a novel inference algorithm using the algebraic framework of Boolean polynomial dynamical systems (BPDS), meeting all these requirements. The algorithm takes as input time series data, including those from network perturbations, such as knock-out mutant strains and RNAi experiments. It allows for the incorporation of prior biological knowledge while being robust to significant levels of noise in the data used for inference. It uses an evolutionary algorithm for local optimization with an encoding of the mathematical models as BPDS. The BPDS framework allows an effective representation of the search space for algebraic dynamic models that improves computational performance. The algorithm is validated with both simulated and experimental microarray expression profile data. Robustness to noise is tested using a published mathematical model of the segment polarity gene network in Drosophila melanogaster. Benchmarking of the algorithm is done by comparison with a spectrum of state-of-the-art network inference methods on data from the synthetic IRMA network to demonstrate that our method has good precision and recall for the network reconstruction task, while also

  18. ARACNe-based inference, using curated microarray data, of Arabidopsis thaliana root transcriptional regulatory networks

    PubMed Central

    2014-01-01

    Background Uncovering the complex transcriptional regulatory networks (TRNs) that underlie plant and animal development remains a challenge. However, a vast amount of data from public microarray experiments is available, which can be subject to inference algorithms in order to recover reliable TRN architectures. Results In this study we present a simple bioinformatics methodology that uses public, carefully curated microarray data and the mutual information algorithm ARACNe in order to obtain a database of transcriptional interactions. We used data from Arabidopsis thaliana root samples to show that the transcriptional regulatory networks derived from this database successfully recover previously identified root transcriptional modules and to propose new transcription factors for the SHORT ROOT/SCARECROW and PLETHORA pathways. We further show that these networks are a powerful tool to integrate and analyze high-throughput expression data, as exemplified by our analysis of a SHORT ROOT induction time-course microarray dataset, and are a reliable source for the prediction of novel root gene functions. In particular, we used our database to predict novel genes involved in root secondary cell-wall synthesis and identified the MADS-box TF XAL1/AGL12 as an unexpected participant in this process. Conclusions This study demonstrates that network inference using carefully curated microarray data yields reliable TRN architectures. In contrast to previous efforts to obtain root TRNs, that have focused on particular functional modules or tissues, our root transcriptional interactions provide an overview of the transcriptional pathways present in Arabidopsis thaliana roots and will likely yield a plethora of novel hypotheses to be tested experimentally. PMID:24739361

  19. Phase transitions in the evolution of gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Skanata, Antun; Kussell, Edo

    The role of gene regulatory networks is to respond to environmental conditions and optimize growth of the cell. A typical example is found in bacteria, where metabolic genes are activated in response to nutrient availability, and are subsequently turned off to conserve energy when their specific substrates are depleted. However, in fluctuating environmental conditions, regulatory networks could experience strong evolutionary pressures not only to turn the right genes on and off, but also to respond optimally under a wide spectrum of fluctuation timescales. The outcome of evolution is predicted by the long-term growth rate, which differentiates between optimal strategies. Here we present an analytic computation of the long-term growth rate in randomly fluctuating environments, by using mean-field and higher order expansion in the environmental history. We find that optimal strategies correspond to distinct regions in the phase space of fluctuations, separated by first and second order phase transitions. The statistics of environmental randomness are shown to dictate the possible evolutionary modes, which either change the structure of the regulatory network abruptly, or gradually modify and tune the interactions between its components.

  20. Gap Gene Regulatory Dynamics Evolve along a Genotype Network

    PubMed Central

    Crombach, Anton; Wotton, Karl R.; Jiménez-Guri, Eva; Jaeger, Johannes

    2016-01-01

    Developmental gene networks implement the dynamic regulatory mechanisms that pattern and shape the organism. Over evolutionary time, the wiring of these networks changes, yet the patterning outcome is often preserved, a phenomenon known as “system drift.” System drift is illustrated by the gap gene network—involved in segmental patterning—in dipteran insects. In the classic model organism Drosophila melanogaster and the nonmodel scuttle fly Megaselia abdita, early activation and placement of gap gene expression domains show significant quantitative differences, yet the final patterning output of the system is essentially identical in both species. In this detailed modeling analysis of system drift, we use gene circuits which are fit to quantitative gap gene expression data in M. abdita and compare them with an equivalent set of models from D. melanogaster. The results of this comparative analysis show precisely how compensatory regulatory mechanisms achieve equivalent final patterns in both species. We discuss the larger implications of the work in terms of “genotype networks” and the ways in which the structure of regulatory networks can influence patterns of evolutionary change (evolvability). PMID:26796549

  1. Non-coding RNAs and a layered architecture of genetic networks

    NASA Astrophysics Data System (ADS)

    Zhdanov, Vladimir

    2010-12-01

    In eukaryotic cells, protein-coding sequences constitute a relatively small part of the genome. The rest of the genome is transcribed to non-coding RNAs (ncRNAs). Such RNAs form the cornerstone of a regulatory network that operates in parallel with the protein network. Their biological functions are based primarily on the ability to pair with and deactivate target messenger RNAs (mRNAs). To clarify the likely role of ncRNAs in complex genetic networks, we present and comprehensively analyze a kinetic model of one of the key counterparts of the network architectures. Specifically, the genes transcribed to ncRNAs are considered to interplay with a hierarchical two-layer set of genes transcribed to mRNAs. The genes forming the bottom layer are regulated from the top and negatively self-regulated. If the former regulation is positive, the dependence of the RNA populations on the governing parameters is found to be often non-monotonous. Specifically, the model predicts bistability. If the regulation is negative, the dependence of the RNA populations on the governing parameters is monotonous. In particular, the population of the mRNAs, corresponding to the genes forming the bottom layer, is nearly constant.

  2. Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

    NASA Technical Reports Server (NTRS)

    Liang, Shoudan; Fuhrman, Stefanie; Somogyi, Roland

    1998-01-01

    Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

  3. Modularity and evolutionary constraints in a baculovirus gene regulatory network

    PubMed Central

    2013-01-01

    Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates

  4. Architecture of the Florida power grid as a complex network

    NASA Astrophysics Data System (ADS)

    Xu, Yan; Gurfinkel, Aleks Jacob; Rikvold, Per Arne

    2014-05-01

    We study the Florida high-voltage power grid as a technological network embedded in space. Measurements of geographical lengths of transmission lines, the mixing of generators and loads, the weighted clustering coefficient, as well as the organization of edge conductance weights show a complex architecture quite different from random-graph models usually considered. In particular, we introduce a parametrized mixing matrix to characterize the mixing pattern of generators and loads in the Florida Grid, which is intermediate between the random mixing case and the semi-bipartite case where generator-generator transmission lines are forbidden. Our observations motivate an investigation of optimization (design) principles leading to the structural organization of power grids. We thus propose two network optimization models for the Florida Grid as a case study. Our results show that the Florida Grid is optimized not only by reducing the construction cost (measured by the total length of power lines), but also through reducing the total pairwise edge resistance in the grid, which increases the robustness of power transmission between generators and loads against random line failures. We then embed our models in spatial areas of different aspect ratios and study how this geometric factor affects the network structure, as well as the box-counting fractal dimension of the grids generated by our models.

  5. An architecture for distributed video applications based on declarative networking

    NASA Astrophysics Data System (ADS)

    Wang, Xiping; Gonzales, Cesar; Lobo, Jorge; Calo, Seraphin; Verma, Dinesh

    2012-06-01

    Video surveillance applications are examples of complex distributed coalition tasks. Real-time capture and analysis of image sensor data is one of the most important tasks in a number of military critical decision making scenarios. In complex battlefield situations, there is a need to coordinate the operation of distributed image sensors and the analysis of their data as transmitted over a heterogeneous wireless network where bandwidth, power, and computational capabilities are constrained. There is also a need to automate decision making based on the results of the analysis of video data. Declarative Networking is a promising technology for controlling complex video surveillance applications in this sort of environment. This paper presents a flexible and extensible architecture for deploying distributed video surveillance applications using the declarative networking paradigm, which allows us to dynamically connect and manage distributed image sensors and deploy various modules for the analysis of video data to satisfy a variety of video surveillance requirements. With declarative computing, it becomes possible for us not only to express the program control structure in a declarative fashion, but also to simplify the management of distributed video surveillance applications.

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

    NASA Technical Reports Server (NTRS)

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

    1992-01-01

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

  7. An architecture for transmit beamforming for rapidly deployable radio networks

    SciTech Connect

    Prescott, G.E.; Sparks, C.A.; Sivaprakasam, S.

    1997-01-01

    Beamforming Technology will be an essential element in tactical battlefield communication systems of the next generation. Only with beamforming will the demands of communication quality, network access and covertness be jointly achieved. This paper focuses on the signal processing features of one element of this technology-transmitter beamforming. A flexible beamforming architecture such as the one described here will facilitate ongoing research into the development of a high speed ATM-based wireless communication system currently being investigated at the University of Kansas. This system provides for spatial frequency reuse by allowing multiple transmit beams to be steered to mobile end users. The modulation and the steering angles of the beams adapt under software control in response to the demands of the communications environment and the user{close_quote}s {ital requirements}. {copyright} {ital 1997 American Institute of Physics.}

  8. Controlled architecture for improved macromolecular memory within polymer networks.

    PubMed

    DiPasquale, Stephen A; Byrne, Mark E

    2016-08-01

    This brief review analyzes recent developments in the field of living/controlled polymerization and the potential of this technique for creating imprinted polymers with highly structured architecture with macromolecular memory. As a result, it is possible to engineer polymers at the molecular level with increased homogeneity relating to enhanced template binding and transport. Only recently has living/controlled polymerization been exploited to decrease heterogeneity and substantially improve the efficiency of the imprinting process for both highly and weakly crosslinked imprinted polymers. Living polymerization can be utilized to create imprinted networks that are vastly more efficient than similar polymers produced using conventional free radical polymerization, and these improvements increase the role that macromolecular memory can play in the design and engineering of new drug delivery and sensing platforms. PMID:27322505

  9. A recursive network approach can identify constitutive regulatory circuits in gene expression data

    NASA Astrophysics Data System (ADS)

    Blasi, Monica Francesca; Casorelli, Ida; Colosimo, Alfredo; Blasi, Francesco Simone; Bignami, Margherita; Giuliani, Alessandro

    2005-03-01

    The activity of the cell is often coordinated by the organisation of proteins into regulatory circuits that share a common function. Genome-wide expression profiles might contain important information on these circuits. Current approaches for the analysis of gene expression data include clustering the individual expression measurements and relating them to biological functions as well as modelling and simulation of gene regulation processes by additional computer tools. The identification of the regulative programmes from microarray experiments is limited, however, by the intrinsic difficulty of linear methods to detect low-variance signals and by the sensitivity of the different approaches. Here we face the problem of recognising invariant patterns of correlations among gene expression reminiscent of regulation circuits. We demonstrate that a recursive neural network approach can identify genetic regulation circuits from expression data for ribosomal and genome stability genes. The proposed method, by greatly enhancing the sensitivity of microarray studies, allows the identification of important aspects of genetic regulation networks and might be useful for the discrimination of the different players involved in regulation circuits. Our results suggest that the constitutive regulatory networks involved in the generic organisation of the cell display a high degree of clustering depending on a modular architecture.

  10. Negative Feedback and Transcriptional Overshooting in a Regulatory Network for Horizontal Gene Transfer

    PubMed Central

    Fernandez-Lopez, Raul; del Campo, Irene; Revilla, Carlos; Cuevas, Ana; de la Cruz, Fernando

    2014-01-01

    Horizontal gene transfer (HGT) is a major force driving bacterial evolution. Because of their ability to cross inter-species barriers, bacterial plasmids are essential agents for HGT. This ability, however, poses specific requisites on plasmid physiology, in particular the need to overcome a multilevel selection process with opposing demands. We analyzed the transcriptional network of plasmid R388, one of the most promiscuous plasmids in Proteobacteria. Transcriptional analysis by fluorescence expression profiling and quantitative PCR revealed a regulatory network controlled by six transcriptional repressors. The regulatory network relied on strong promoters, which were tightly repressed in negative feedback loops. Computational simulations and theoretical analysis indicated that this architecture would show a transcriptional burst after plasmid conjugation, linking the magnitude of the feedback gain with the intensity of the transcriptional burst. Experimental analysis showed that transcriptional overshooting occurred when the plasmid invaded a new population of susceptible cells. We propose that transcriptional overshooting allows genome rebooting after horizontal gene transfer, and might have an adaptive role in overcoming the opposing demands of multilevel selection. PMID:24586200

  11. Distributed Prognostics and Health Management with a Wireless Network Architecture

    NASA Technical Reports Server (NTRS)

    Goebel, Kai; Saha, Sankalita; Sha, Bhaskar

    2013-01-01

    A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the

  12. Dynamical modeling and analysis of large cellular regulatory networks

    NASA Astrophysics Data System (ADS)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  13. Noise Control in Gene Regulatory Networks with Negative Feedback.

    PubMed

    Hinczewski, Michael; Thirumalai, D

    2016-07-01

    Genes and proteins regulate cellular functions through complex circuits of biochemical reactions. Fluctuations in the components of these regulatory networks result in noise that invariably corrupts the signal, possibly compromising function. Here, we create a practical formalism based on ideas introduced by Wiener and Kolmogorov (WK) for filtering noise in engineered communications systems to quantitatively assess the extent to which noise can be controlled in biological processes involving negative feedback. Application of the theory, which reproduces the previously proven scaling of the lower bound for noise suppression in terms of the number of signaling events, shows that a tetracycline repressor-based negative-regulatory gene circuit behaves as a WK filter. For the class of Hill-like nonlinear regulatory functions, this type of filter provides the optimal reduction in noise. Our theoretical approach can be readily combined with experimental measurements of response functions in a wide variety of genetic circuits, to elucidate the general principles by which biological networks minimize noise. PMID:27095600

  14. Genomic Reconstruction of the Transcriptional Regulatory Network in Bacillus subtilis

    PubMed Central

    Leyn, Semen A.; Kazanov, Marat D.; Sernova, Natalia V.; Ermakova, Ekaterina O.; Novichkov, Pavel S.

    2013-01-01

    The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Bacillales species. For transcription factor (TF) regulons, we combined the available information from the DBTBS database and the literature with bioinformatics tools, allowing inference of TF binding sites (TFBSs), comparative analysis of the genomic context of predicted TFBSs, functional assignment of target genes, and effector prediction. For RNA regulons, we used known RNA regulatory motifs collected in the Rfam database to scan genomes and analyze the genomic context of new RNA sites. The inferred TRN in B. subtilis comprises regulons for 129 TFs and 24 regulatory RNA families. First, we analyzed 66 TF regulons with previously known TFBSs in B. subtilis and projected them to other Bacillales genomes, resulting in refinement of TFBS motifs and identification of novel regulon members. Second, we inferred motifs and described regulons for 28 experimentally studied TFs with previously unknown TFBSs. Third, we discovered novel motifs and reconstructed regulons for 36 previously uncharacterized TFs. The inferred collection of regulons is available in the RegPrecise database (http://regprecise.lbl.gov/) and can be used in genetic experiments, metabolic modeling, and evolutionary analysis. PMID:23504016

  15. Genomic reconstruction of the transcriptional regulatory network in Bacillus subtilis.

    PubMed

    Leyn, Semen A; Kazanov, Marat D; Sernova, Natalia V; Ermakova, Ekaterina O; Novichkov, Pavel S; Rodionov, Dmitry A

    2013-06-01

    The adaptation of microorganisms to their environment is controlled by complex transcriptional regulatory networks (TRNs), which are still only partially understood even for model species. Genome scale annotation of regulatory features of genes and TRN reconstruction are challenging tasks of microbial genomics. We used the knowledge-driven comparative-genomics approach implemented in the RegPredict Web server to infer TRN in the model Gram-positive bacterium Bacillus subtilis and 10 related Bacillales species. For transcription factor (TF) regulons, we combined the available information from the DBTBS database and the literature with bioinformatics tools, allowing inference of TF binding sites (TFBSs), comparative analysis of the genomic context of predicted TFBSs, functional assignment of target genes, and effector prediction. For RNA regulons, we used known RNA regulatory motifs collected in the Rfam database to scan genomes and analyze the genomic context of new RNA sites. The inferred TRN in B. subtilis comprises regulons for 129 TFs and 24 regulatory RNA families. First, we analyzed 66 TF regulons with previously known TFBSs in B. subtilis and projected them to other Bacillales genomes, resulting in refinement of TFBS motifs and identification of novel regulon members. Second, we inferred motifs and described regulons for 28 experimentally studied TFs with previously unknown TFBSs. Third, we discovered novel motifs and reconstructed regulons for 36 previously uncharacterized TFs. The inferred collection of regulons is available in the RegPrecise database (http://regprecise.lbl.gov/) and can be used in genetic experiments, metabolic modeling, and evolutionary analysis. PMID:23504016

  16. Regulatory Compliance in Multi-Tier Supplier Networks

    NASA Technical Reports Server (NTRS)

    Goossen, Emray R.; Buster, Duke A.

    2014-01-01

    Over the years, avionics systems have increased in complexity to the point where 1st tier suppliers to an aircraft OEM find it financially beneficial to outsource designs of subsystems to 2nd tier and at times to 3rd tier suppliers. Combined with challenging schedule and budgetary pressures, the environment in which safety-critical systems are being developed introduces new hurdles for regulatory agencies and industry. This new environment of both complex systems and tiered development has raised concerns in the ability of the designers to ensure safety considerations are fully addressed throughout the tier levels. This has also raised questions about the sufficiency of current regulatory guidance to ensure: proper flow down of safety awareness, avionics application understanding at the lower tiers, OEM and 1st tier oversight practices, and capabilities of lower tier suppliers. Therefore, NASA established a research project to address Regulatory Compliance in a Multi-tier Supplier Network. This research was divided into three major study efforts: 1. Describe Modern Multi-tier Avionics Development 2. Identify Current Issues in Achieving Safety and Regulatory Compliance 3. Short-term/Long-term Recommendations Toward Higher Assurance Confidence This report presents our findings of the risks, weaknesses, and our recommendations. It also includes a collection of industry-identified risks, an assessment of guideline weaknesses related to multi-tier development of complex avionics systems, and a postulation of potential modifications to guidelines to close the identified risks and weaknesses.

  17. Implementing wireless sensor networks for architectural heritage conservation

    NASA Astrophysics Data System (ADS)

    Martínez-Garrido, M. I.; Aparicio, S.; Fort, R.; Izquierdo, M. A. G.; Anaya, J. J.

    2012-04-01

    Preventive conservation in architectural heritage is one of the most important aims for the development and implementation of new techniques to assess decay, lending to reduce damage before it has occurred and reducing costs in the long term. For that purpose, it is necessary to know all aspects influencing in decay evolution depending on the material under study and its internal and external conditions. Wireless sensor networks are an emerging technology and a minimally invasive technique. The use of these networks facilitates data acquisition and monitoring of a large number of variables that could provoke material damages, such as presence of harmful compounds like salts, dampness, etc. The current project presents different wireless sensors networks (WSN) and sensors used to fulfill the requirements for a complete analysis of main decay agents in a Renaissance church of the 16th century in Madrid (Spain). Current typologies and wireless technologies are studied establishing the most suitable system and the convenience of each one. Firstly, it is very important to consider that microclimate is in close correlation with material deterioration. Therefore a temperature(T) and relative humidity (RH)/moisture network has been developed, using ZigBee wireless communications protocols, and monitoring different points along the church surface. These points are recording RH/T differences depending on the height and the sensor location (inside the material or on the surface). On the other hand, T/RH button sensors have been used, minimizing aesthetical interferences, and concluding which is the most advisable way for monitoring these specific parameters. Due to the fact that microclimate is a complex phenomenon, it is necessary to examine spatial distribution and time evolution at the same time. This work shows both studies since the development expects a long term monitoring. A different wireless network has been deployed to study the effects of pollution caused by other

  18. State-dependent architecture of thalamic reticular sub-networks

    PubMed Central

    Halassa, Michael M.; Chen, Zhe; Wimmer, Ralf D.; Brunetti, Philip M.; Zhao, Shengli; Zikopoulos, Basilis; Wang, Fan; Brown, Emery N.; Wilson, Matthew A.

    2014-01-01

    Behavioral state is known to influence interactions between thalamus and cortex, which are important for sensation, action and cognition. The thalamic reticular nucleus (TRN) is hypothesized to regulate thalamo-cortical transmission, but the underlying functional architecture of this process and its state-dependence are unknown. By combining the first TRN ensemble recording with psychophysics and connectivity-based optogenetic tagging, we find that the TRN is composed of distinct sub-networks. While activity of limbic-projecting TRN neurons correlates with arousal, sensory-projecting neurons participate in spindles and show elevated synchrony by slow waves during sleep. Conversely, sensory-projecting neurons are suppressed by attentional states, demonstrating common microcircuit mechanisms of sensory processing in sleep and attention. Bidirectional manipulation of attentional performance was achieved through optogenetic manipulation of these TRN sub-networks. Our findings provide evidence for differential regulation of thalamic inhibition across brain states, suggesting that the TRN separately controls external stimulus processing and internally-generated computations, a basic determinant of cognitive function. PMID:25126786

  19. Hybrid Network Architectures for the Next Generation NAS

    NASA Technical Reports Server (NTRS)

    Madubata, Christian

    2003-01-01

    To meet the needs of the 21st Century NAS, an integrated, network-centric infrastructure is essential that is characterized by secure, high bandwidth, digital communication systems that support precision navigation capable of reducing position errors for all aircraft to within a few meters. This system will also require precision surveillance systems capable of accurately locating all aircraft, and automatically detecting any deviations from an approved path within seconds and be able to deliver high resolution weather forecasts - critical to create 4- dimensional (space and time) profiles for up to 6 hours for all atmospheric conditions affecting aviation, including wake vortices. The 21st Century NAS will be characterized by highly accurate digital data bases depicting terrain, obstacle, and airport information no matter what visibility conditions exist. This research task will be to perform a high-level requirements analysis of the applications, information and services required by the next generation National Airspace System. The investigation and analysis is expected to lead to the development and design of several national network-centric communications architectures that would be capable of supporting the Next Generation NAS.

  20. Overview of the Smart Network Element Architecture and Recent Innovations

    NASA Technical Reports Server (NTRS)

    Perotti, Jose M.; Mata, Carlos T.; Oostdyk, Rebecca L.

    2008-01-01

    In industrial environments, system operators rely on the availability and accuracy of sensors to monitor processes and detect failures of components and/or processes. The sensors must be networked in such a way that their data is reported to a central human interface, where operators are tasked with making real-time decisions based on the state of the sensors and the components that are being monitored. Incorporating health management functions at this central location aids the operator by automating the decision-making process to suggest, and sometimes perform, the action required by current operating conditions. Integrated Systems Health Management (ISHM) aims to incorporate data from many sources, including real-time and historical data and user input, and extract information and knowledge from that data to diagnose failures and predict future failures of the system. By distributing health management processing to lower levels of the architecture, there is less bandwidth required for ISHM, enhanced data fusion, make systems and processes more robust, and improved resolution for the detection and isolation of failures in a system, subsystem, component, or process. The Smart Network Element (SNE) has been developed at NASA Kennedy Space Center to perform intelligent functions at sensors and actuators' level in support of ISHM.

  1. Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation

    PubMed Central

    Goode, Debbie K.; Obier, Nadine; Vijayabaskar, M.S.; Lie-A-Ling, Michael; Lilly, Andrew J.; Hannah, Rebecca; Lichtinger, Monika; Batta, Kiran; Florkowska, Magdalena; Patel, Rahima; Challinor, Mairi; Wallace, Kirstie; Gilmour, Jane; Assi, Salam A.; Cauchy, Pierre; Hoogenkamp, Maarten; Westhead, David R.; Lacaud, Georges; Kouskoff, Valerie; Göttgens, Berthold; Bonifer, Constanze

    2016-01-01

    Summary Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue-specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell-derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome-wide data uncovered a stage-specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development. PMID:26923725

  2. Dynamic Gene Regulatory Networks Drive Hematopoietic Specification and Differentiation.

    PubMed

    Goode, Debbie K; Obier, Nadine; Vijayabaskar, M S; Lie-A-Ling, Michael; Lilly, Andrew J; Hannah, Rebecca; Lichtinger, Monika; Batta, Kiran; Florkowska, Magdalena; Patel, Rahima; Challinor, Mairi; Wallace, Kirstie; Gilmour, Jane; Assi, Salam A; Cauchy, Pierre; Hoogenkamp, Maarten; Westhead, David R; Lacaud, Georges; Kouskoff, Valerie; Göttgens, Berthold; Bonifer, Constanze

    2016-03-01

    Metazoan development involves the successive activation and silencing of specific gene expression programs and is driven by tissue-specific transcription factors programming the chromatin landscape. To understand how this process executes an entire developmental pathway, we generated global gene expression, chromatin accessibility, histone modification, and transcription factor binding data from purified embryonic stem cell-derived cells representing six sequential stages of hematopoietic specification and differentiation. Our data reveal the nature of regulatory elements driving differential gene expression and inform how transcription factor binding impacts on promoter activity. We present a dynamic core regulatory network model for hematopoietic specification and demonstrate its utility for the design of reprogramming experiments. Functional studies motivated by our genome-wide data uncovered a stage-specific role for TEAD/YAP factors in mammalian hematopoietic specification. Our study presents a powerful resource for studying hematopoiesis and demonstrates how such data advance our understanding of mammalian development. PMID:26923725

  3. Inferring the role of transcription factors in regulatory networks

    PubMed Central

    Veber, Philippe; Guziolowski, Carito; Le Borgne, Michel; Radulescu, Ovidiu; Siegel, Anne

    2008-01-01

    Background Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple organisms up to higher eukaryotes. Admittedly, a key ingredient in developing a reconstruction method is its ability to integrate heterogeneous sources of information, as well as to comply with practical observability issues: measurements can be scarce or noisy. In this work, we show how to combine a network of genetic regulations with a set of expression profiles, in order to infer the functional effect of the regulations, as inducer or repressor. Our approach is based on a consistency rule between a network and the signs of variation given by expression arrays. Results We evaluate our approach in several settings of increasing complexity. First, we generate artificial expression data on a transcriptional network of E. coli extracted from the literature (1529 nodes and 3802 edges), and we estimate that 30% of the regulations can be annotated with about 30 profiles. We additionally prove that at most 40.8% of the network can be inferred using our approach. Second, we use this network in order to validate the predictions obtained with a compendium of real expression profiles. We describe a filtering algorithm that generates particularly reliable predictions. Finally, we apply our inference approach to S. cerevisiae transcriptional network (2419 nodes and 4344 interactions), by combining ChIP-chip data and 15 expression profiles. We are able to detect and isolate inconsistencies between the expression profiles and a significant portion of the model (15% of all the interactions). In addition, we report predictions for 14.5% of all interactions. Conclusion Our approach does not require accurate expression levels nor times series. Nevertheless, we show on both data, real and artificial, that a relatively small number of perturbation experiments are enough to determine a significant portion of

  4. Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

    DOE PAGESBeta

    Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; Novichkov, Pavel

    2015-06-01

    The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond thosemore » of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.« less

  5. Topological effects of data incompleteness of gene regulatory networks

    PubMed Central

    2012-01-01

    Background The topological analysis of biological networks has been a prolific topic in network science during the last decade. A persistent problem with this approach is the inherent uncertainty and noisy nature of the data. One of the cases in which this situation is more marked is that of transcriptional regulatory networks (TRNs) in bacteria. The datasets are incomplete because regulatory pathways associated to a relevant fraction of bacterial genes remain unknown. Furthermore, direction, strengths and signs of the links are sometimes unknown or simply overlooked. Finally, the experimental approaches to infer the regulations are highly heterogeneous, in a way that induces the appearance of systematic experimental-topological correlations. And yet, the quality of the available data increases constantly. Results In this work we capitalize on these advances to point out the influence of data (in)completeness and quality on some classical results on topological analysis of TRNs, specially regarding modularity at different levels. Conclusions In doing so, we identify the most relevant factors affecting the validity of previous findings, highlighting important caveats to future prokaryotic TRNs topological analysis. PMID:22920968

  6. Large Scale Comparative Visualisation of Regulatory Networks with TRNDiff

    SciTech Connect

    Chua, Xin-Yi; Buckingham, Lawrence; Hogan, James M.; Novichkov, Pavel

    2015-06-01

    The advent of Next Generation Sequencing (NGS) technologies has seen explosive growth in genomic datasets, and dense coverage of related organisms, supporting study of subtle, strain-specific variations as a determinant of function. Such data collections present fresh and complex challenges for bioinformatics, those of comparing models of complex relationships across hundreds and even thousands of sequences. Transcriptional Regulatory Network (TRN) structures document the influence of regulatory proteins called Transcription Factors (TFs) on associated Target Genes (TGs). TRNs are routinely inferred from model systems or iterative search, and analysis at these scales requires simultaneous displays of multiple networks well beyond those of existing network visualisation tools [1]. In this paper we describe TRNDiff, an open source system supporting the comparative analysis and visualization of TRNs (and similarly structured data) from many genomes, allowing rapid identification of functional variations within species. The approach is demonstrated through a small scale multiple TRN analysis of the Fur iron-uptake system of Yersinia, suggesting a number of candidate virulence factors; and through a larger study exploiting integration with the RegPrecise database (http://regprecise.lbl.gov; [2]) - a collection of hundreds of manually curated and predicted transcription factor regulons drawn from across the entire spectrum of prokaryotic organisms.

  7. Deciphering the importance of the palindromic architecture of the immunoglobulin heavy-chain 3' regulatory region.

    PubMed

    Saintamand, Alexis; Vincent-Fabert, Christelle; Garot, Armand; Rouaud, Pauline; Oruc, Zeliha; Magnone, Virginie; Cogné, Michel; Denizot, Yves

    2016-01-01

    The IgH 3' regulatory region (3'RR) controls class switch recombination (CSR) and somatic hypermutation (SHM) in B cells. The mouse 3'RR contains four enhancer elements with hs1,2 flanked by inverted repeated sequences and the centre of a 25-kb palindrome bounded by two hs3 enhancer inverted copies (hs3a and hs3b). hs4 lies downstream of the palindrome. In mammals, evolution maintained this unique palindromic arrangement, suggesting that it is functionally significant. Here we report that deconstructing the palindromic IgH 3'RR strongly affects its function even when enhancers are preserved. CSR and IgH transcription appear to be poorly dependent on the 3'RR architecture and it is more or less preserved, provided 3'RR enhancers are present. By contrast, a 'palindromic effect' significantly lowers VH germline transcription, AID recruitment and SHM. In conclusion, this work indicates that the IgH 3'RR does not simply pile up enhancer units but also optimally exposes them into a functional architecture of crucial importance. PMID:26883548

  8. Deciphering the importance of the palindromic architecture of the immunoglobulin heavy-chain 3' regulatory region

    PubMed Central

    Saintamand, Alexis; Vincent-Fabert, Christelle; Garot, Armand; Rouaud, Pauline; Oruc, Zeliha; Magnone, Virginie; Cogné, Michel; Denizot, Yves

    2016-01-01

    The IgH 3' regulatory region (3'RR) controls class switch recombination (CSR) and somatic hypermutation (SHM) in B cells. The mouse 3'RR contains four enhancer elements with hs1,2 flanked by inverted repeated sequences and the centre of a 25-kb palindrome bounded by two hs3 enhancer inverted copies (hs3a and hs3b). hs4 lies downstream of the palindrome. In mammals, evolution maintained this unique palindromic arrangement, suggesting that it is functionally significant. Here we report that deconstructing the palindromic IgH 3'RR strongly affects its function even when enhancers are preserved. CSR and IgH transcription appear to be poorly dependent on the 3'RR architecture and it is more or less preserved, provided 3'RR enhancers are present. By contrast, a ‘palindromic effect' significantly lowers VH germline transcription, AID recruitment and SHM. In conclusion, this work indicates that the IgH 3'RR does not simply pile up enhancer units but also optimally exposes them into a functional architecture of crucial importance. PMID:26883548

  9. Criteria for Evaluating Alternative Network and Link Layer Protocols for the NASA Constellation Program Communication Architecture

    NASA Technical Reports Server (NTRS)

    Benbenek, Daniel; Soloff, Jason; Lieb, Erica

    2010-01-01

    Selecting a communications and network architecture for future manned space flight requires an evaluation of the varying goals and objectives of the program, development of communications and network architecture evaluation criteria, and assessment of critical architecture trades. This paper uses Cx Program proposed exploration activities as a guideline; lunar sortie, outpost, Mars, and flexible path options are described. A set of proposed communications network architecture criteria are proposed and described. They include: interoperability, security, reliability, and ease of automating topology changes. Finally a key set of architecture options are traded including (1) multiplexing data at a common network layer vs. at the data link layer, (2) implementing multiple network layers vs. a single network layer, and (3) the use of a particular network layer protocol, primarily IPv6 vs. Delay Tolerant Networking (DTN). In summary, the protocol options are evaluated against the proposed exploration activities and their relative performance with respect to the criteria are assessed. An architectural approach which includes (a) the capability of multiplexing at both the network layer and the data link layer and (b) a single network layer for operations at each program phase, as these solutions are best suited to respond to the widest array of program needs and meet each of the evaluation criteria.

  10. Compartmentalized gene regulatory network of the pathogenic fungus Fusarium graminearum.

    PubMed

    Guo, Li; Zhao, Guoyi; Xu, Jin-Rong; Kistler, H Corby; Gao, Lixin; Ma, Li-Jun

    2016-07-01

    Head blight caused by Fusarium graminearum threatens world-wide wheat production, resulting in both yield loss and mycotoxin contamination. We reconstructed the global F. graminearum gene regulatory network (GRN) from a large collection of transcriptomic data using Bayesian network inference, a machine-learning algorithm. This GRN reveals connectivity between key regulators and their target genes. Focusing on key regulators, this network contains eight distinct but interwoven modules. Enriched for unique functions, such as cell cycle, DNA replication, transcription, translation and stress responses, each module exhibits distinct expression profiles. Evolutionarily, the F. graminearum genome can be divided into core regions shared with closely related species and variable regions harboring genes that are unique to F. graminearum and perform species-specific functions. Interestingly, the inferred top regulators regulate genes that are significantly enriched from the same genomic regions (P < 0.05), revealing a compartmentalized network structure that may reflect network rewiring related to specific adaptation of this plant pathogen. This first-ever reconstructed filamentous fungal GRN primes our understanding of pathogenicity at the systems biology level and provides enticing prospects for novel disease control strategies involving the targeting of master regulators in pathogens. The program can be used to construct GRNs of other plant pathogens. PMID:26990214

  11. Advanced optical network architecture for integrated digital avionics

    NASA Astrophysics Data System (ADS)

    Morgan, D. Reed

    1996-12-01

    For the first time in the history of avionics, the network designer now has a choice in selecting the media that interconnects the sources and sinks of digital data on aircraft. Electrical designs are already giving way to photonics in application areas where the data rate times distance product is large or where special design requirements such as low weight or EMI considerations are critical. Future digital avionic architectures will increasingly favor the use of photonic interconnects as network data rates of one gigabit/second and higher are needed to support real-time operation of high-speed integrated digital processing. As the cost of optical network building blocks is reduced and as temperature-rugged laser sources are matured, metal interconnects will be forced to retreat to applications spanning shorter and shorter distances. Although the trend is already underway, the widespread use of digital optics will first occur at the system level, where gigabit/second, real-time interconnects between sensors, processors, mass memories and displays separated by a least of few meters will be required. The application of photonic interconnects for inter-printed wiring board signalling across the backplane will eventually find application for gigabit/second applications since signal degradation over copper traces occurs before one gigabit/second and 0.5 meters are reached. For the foreseeable future however, metal interconnects will continue to be used to interconnect devices on printed wiring boards since 5 gigabit/second signals can be sent over metal up to around 15 centimeters. Current-day applications of optical interconnects at the system level are described and a projection of how advanced optical interconnect technology will be driven by the use of high speed integrated digital processing on future aircraft is presented. The recommended advanced network for application in the 2010 time frame is a fiber-based system with a signalling speed of around 2

  12. Control of Metastatic Progression by microRNA Regulatory Networks

    PubMed Central

    Pencheva, Nora; Tavazoie, Sohail F.

    2015-01-01

    Aberrant microRNA (miRNA) expression is a defining feature of human malignancy. Specific miRNAs have been identified as promoters or suppressors of metastatic progression. These miRNAs control metastasis through divergent or convergent regulation of metastatic gene pathways. Some miRNA regulatory networks govern cell-autonomous cancer phenotypes, while others modulate the cell-extrinsic composition of the metastatic microenvironment. The use of small RNAs as probes into the molecular and cellular underpinnings of metastasis holds promise for the identification of candidate genes for potential therapeutic intervention. PMID:23728460

  13. Control of metastatic progression by microRNA regulatory networks.

    PubMed

    Pencheva, Nora; Tavazoie, Sohail F

    2013-06-01

    Aberrant microRNA (miRNA) expression is a defining feature of human malignancy. Specific miRNAs have been identified as promoters or suppressors of metastatic progression. miRNAs control metastasis through divergent or convergent regulation of metastatic gene pathways. Some miRNA regulatory networks govern cell-autonomous cancer phenotypes, whereas others modulate the cell-extrinsic composition of the metastatic microenvironment. The use of small RNAs as probes into the molecular and cellular underpinnings of metastasis holds promise for the identification of candidate genes for potential therapeutic intervention. PMID:23728460

  14. Neural network architecture for cognitive navigation in dynamic environments.

    PubMed

    Villacorta-Atienza, José Antonio; Makarov, Valeri A

    2013-12-01

    Navigation in time-evolving environments with moving targets and obstacles requires cognitive abilities widely demonstrated by even simplest animals. However, it is a long-standing challenging problem for artificial agents. Cognitive autonomous robots coping with this problem must solve two essential tasks: 1) understand the environment in terms of what may happen and how I can deal with this and 2) learn successful experiences for their further use in an automatic subconscious way. The recently introduced concept of compact internal representation (CIR) provides the ground for both the tasks. CIR is a specific cognitive map that compacts time-evolving situations into static structures containing information necessary for navigation. It belongs to the class of global approaches, i.e., it finds trajectories to a target when they exist but also detects situations when no solution can be found. Here we extend the concept of situations with mobile targets. Then using CIR as a core, we propose a closed-loop neural network architecture consisting of conscious and subconscious pathways for efficient decision-making. The conscious pathway provides solutions to novel situations if the default subconscious pathway fails to guide the agent to a target. Employing experiments with roving robots and numerical simulations, we show that the proposed architecture provides the robot with cognitive abilities and enables reliable and flexible navigation in realistic time-evolving environments. We prove that the subconscious pathway is robust against uncertainty in the sensory information. Thus if a novel situation is similar but not identical to the previous experience (because of, e.g., noisy perception) then the subconscious pathway is able to provide an effective solution. PMID:24805224

  15. The exploration of network motifs as potential drug targets from post-translational regulatory networks.

    PubMed

    Zhang, Xiao-Dong; Song, Jiangning; Bork, Peer; Zhao, Xing-Ming

    2016-01-01

    Phosphorylation and proteolysis are among the most common post-translational modifications (PTMs), and play critical roles in various biological processes. More recent discoveries imply that the crosstalks between these two PTMs are involved in many diseases. In this work, we construct a post-translational regulatory network (PTRN) consists of phosphorylation and proteolysis processes, which enables us to investigate the regulatory interplays between these two PTMs. With the PTRN, we identify some functional network motifs that are significantly enriched with drug targets, some of which are further found to contain multiple proteins targeted by combinatorial drugs. These findings imply that the network motifs may be used to predict targets when designing new drugs. Inspired by this, we propose a novel computational approach called NetTar for predicting drug targets using the identified network motifs. Benchmarking results on real data indicate that our approach can be used for accurate prediction of novel proteins targeted by known drugs. PMID:26853265

  16. The exploration of network motifs as potential drug targets from post-translational regulatory networks

    PubMed Central

    Zhang, Xiao-Dong; Song, Jiangning; Bork, Peer; Zhao, Xing-Ming

    2016-01-01

    Phosphorylation and proteolysis are among the most common post-translational modifications (PTMs), and play critical roles in various biological processes. More recent discoveries imply that the crosstalks between these two PTMs are involved in many diseases. In this work, we construct a post-translational regulatory network (PTRN) consists of phosphorylation and proteolysis processes, which enables us to investigate the regulatory interplays between these two PTMs. With the PTRN, we identify some functional network motifs that are significantly enriched with drug targets, some of which are further found to contain multiple proteins targeted by combinatorial drugs. These findings imply that the network motifs may be used to predict targets when designing new drugs. Inspired by this, we propose a novel computational approach called NetTar for predicting drug targets using the identified network motifs. Benchmarking results on real data indicate that our approach can be used for accurate prediction of novel proteins targeted by known drugs. PMID:26853265

  17. Regulatory network rewiring for secondary metabolism in Arabidopsis thaliana under various conditions

    PubMed Central

    2014-01-01

    Background Plant secondary metabolites are critical to various biological processes. However, the regulations of these metabolites are complex because of regulatory rewiring or crosstalk. To unveil how regulatory behaviors on secondary metabolism reshape biological processes, we constructed and analyzed a dynamic regulatory network of secondary metabolic pathways in Arabidopsis. Results The dynamic regulatory network was constructed through integrating co-expressed gene pairs and regulatory interactions. Regulatory interactions were either predicted by conserved transcription factor binding sites (TFBSs) or proved by experiments. We found that integrating two data (co-expression and predicted regulatory interactions) enhanced the number of highly confident regulatory interactions by over 10% compared with using single data. The dynamic changes of regulatory network systematically manifested regulatory rewiring to explain the mechanism of regulation, such as in terpenoids metabolism, the regulatory crosstalk of RAV1 (AT1G13260) and ATHB1 (AT3G01470) on HMG1 (hydroxymethylglutaryl-CoA reductase, AT1G76490); and regulation of RAV1 on epoxysqualene biosynthesis and sterol biosynthesis. Besides, we investigated regulatory rewiring with expression, network topology and upstream signaling pathways. Regulatory rewiring was revealed by the variability of genes’ expression: pathway genes and transcription factors (TFs) were significantly differentially expressed under different conditions (such as terpenoids biosynthetic genes in tissue experiments and E2F/DP family members in genotype experiments). Both network topology and signaling pathways supported regulatory rewiring. For example, we discovered correlation among the numbers of pathway genes, TFs and network topology: one-gene pathways (such as δ-carotene biosynthesis) were regulated by a fewer TFs, and were not critical to metabolic network because of their low degrees in topology. Upstream signaling pathways of 50

  18. Quantum perceptron over a field and neural network architecture selection in a quantum computer.

    PubMed

    da Silva, Adenilton José; Ludermir, Teresa Bernarda; de Oliveira, Wilson Rosa

    2016-04-01

    In this work, we propose a quantum neural network named quantum perceptron over a field (QPF). Quantum computers are not yet a reality and the models and algorithms proposed in this work cannot be simulated in actual (or classical) computers. QPF is a direct generalization of a classical perceptron and solves some drawbacks found in previous models of quantum perceptrons. We also present a learning algorithm named Superposition based Architecture Learning algorithm (SAL) that optimizes the neural network weights and architectures. SAL searches for the best architecture in a finite set of neural network architectures with linear time over the number of patterns in the training set. SAL is the first learning algorithm to determine neural network architectures in polynomial time. This speedup is obtained by the use of quantum parallelism and a non-linear quantum operator. PMID:26878722

  19. Asymmetric Regulation of Peripheral Genes by Two Transcriptional Regulatory Networks

    PubMed Central

    Li, Jing-Ru; Suzuki, Takahiro; Nishimura, Hajime; Kishima, Mami; Maeda, Shiori; Suzuki, Harukazu

    2016-01-01

    Transcriptional regulatory network (TRN) reconstitution and deconstruction occur simultaneously during reprogramming; however, it remains unclear how the starting and targeting TRNs regulate the induction and suppression of peripheral genes. Here we analyzed the regulation using direct cell reprogramming from human dermal fibroblasts to monocytes as the platform. We simultaneously deconstructed fibroblastic TRN and reconstituted monocytic TRN; monocytic and fibroblastic gene expression were analyzed in comparison with that of fibroblastic TRN deconstruction only or monocytic TRN reconstitution only. Global gene expression analysis showed cross-regulation of TRNs. Detailed analysis revealed that knocking down fibroblastic TRN positively affected half of the upregulated monocytic genes, indicating that intrinsic fibroblastic TRN interfered with the expression of induced genes. In contrast, reconstitution of monocytic TRN showed neutral effects on the majority of fibroblastic gene downregulation. This study provides an explicit example that demonstrates how two networks together regulate gene expression during cell reprogramming processes and contributes to the elaborate exploration of TRNs. PMID:27483142

  20. Applying a service-based architecture to autonomous distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Patrone, David M.; Patrone, Dennis S.; Wenstrand, Doug S.; Smith, Dexter G.

    2004-04-01

    Traditional distributed architectures are not sufficient when developing an autonomous, distributed sensor network. In order to be truly autonomous, a distributed sensor network must be able to survive and reconfigure in-the-field without manual intervention. A limitation of traditional distributed architectures, such as client/server or peer-to-peer, within an autonomous network is that the distributed devices and applications are tightly coupled by their communication protocols prior to implementation and deployment. The introduction of new devices and applications in the field is difficult due to this coupling. Also, autonomous reconfiguration of the devices on the network due to faults or addition of new devices is extremely difficult unless the devices are homogeneous. A service-based architecture is proposed as an alternative architecture for creating autonomous, distributed sensor networks. The service-based approach provides the ability to create a scalable, self-configuring, and self-healing network for building and maintaining large, emerging and ad-hoc virtual networks of devices and applications. New devices can be automatically discovered by current devices on the network and automatically integrated into the system without manual intervention. This paper will explain the benefits and limitations of applying a service-based architecture to autonomous, distributed sensor networks and compare this approach with traditional architectures such as client/server and peer-to-peer. A description will be given of a prototype system developed using service-enabled seismic, acoustic, and visual sensors.

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

    NASA Astrophysics Data System (ADS)

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

    2015-11-01

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

  2. Potential unsatisfiability of cyclic constraints on stochastic biological networks biases selection towards hierarchical architectures

    PubMed Central

    Smith, Cameron; Pechuan, Ximo; Puzio, Raymond S.; Biro, Daniel; Bergman, Aviv

    2015-01-01

    Constraints placed upon the phenotypes of organisms result from their interactions with the environment. Over evolutionary time scales, these constraints feed back onto smaller molecular subnetworks comprising the organism. The evolution of biological networks is studied by considering a network of a few nodes embedded in a larger context. Taking into account this fact that any network under study is actually embedded in a larger context, we define network architecture, not on the basis of physical interactions alone, but rather as a specification of the manner in which constraints are placed upon the states of its nodes. We show that such network architectures possessing cycles in their topology, in contrast to those that do not, may be subjected to unsatisfiable constraints. This may be a significant factor leading to selection biased against those network architectures where such inconsistent constraints are more likely to arise. We proceed to quantify the likelihood of inconsistency arising as a function of network architecture finding that, in the absence of sampling bias over the space of possible constraints and for a given network size, networks with a larger number of cycles are more likely to have unsatisfiable constraints placed upon them. Our results identify a constraint that, at least in isolation, would contribute to a bias in the evolutionary process towards more hierarchical -modular versus completely connected network architectures. Together, these results highlight the context dependence of the functionality of biological networks. PMID:26040595

  3. A dynamic and intricate regulatory network determines Pseudomonas aeruginosa virulence

    PubMed Central

    Balasubramanian, Deepak; Schneper, Lisa; Kumari, Hansi; Mathee, Kalai

    2013-01-01

    Pseudomonas aeruginosa is a metabolically versatile bacterium that is found in a wide range of biotic and abiotic habitats. It is a major human opportunistic pathogen causing numerous acute and chronic infections. The critical traits contributing to the pathogenic potential of P. aeruginosa are the production of a myriad of virulence factors, formation of biofilms and antibiotic resistance. Expression of these traits is under stringent regulation, and it responds to largely unidentified environmental signals. This review is focused on providing a global picture of virulence gene regulation in P. aeruginosa. In addition to key regulatory pathways that control the transition from acute to chronic infection phenotypes, some regulators have been identified that modulate multiple virulence mechanisms. Despite of a propensity for chaotic behaviour, no chaotic motifs were readily observed in the P. aeruginosa virulence regulatory network. Having a ‘birds-eye’ view of the regulatory cascades provides the forum opportunities to pose questions, formulate hypotheses and evaluate theories in elucidating P. aeruginosa pathogenesis. Understanding the mechanisms involved in making P. aeruginosa a successful pathogen is essential in helping devise control strategies. PMID:23143271

  4. An approach to evaluate the topological significance of motifs and other patterns in regulatory networks

    PubMed Central

    Goemann, Björn; Wingender, Edgar; Potapov, Anatolij P

    2009-01-01

    Background The identification of network motifs as statistically over-represented topological patterns has become one of the most promising topics in the analysis of complex networks. The main focus is commonly made on how they operate by means of their internal organization. Yet, their contribution to a network's global architecture is poorly understood. However, this requires switching from the abstract view of a topological pattern to the level of its instances. Here, we show how a recently proposed metric, the pairwise disconnectivity index, can be adapted to survey if and which kind of topological patterns and their instances are most important for sustaining the connectivity within a network. Results The pairwise disconnectivity index of a pattern instance quantifies the dependency of the pairwise connections between vertices in a network on the presence of this pattern instance. Thereby, it particularly considers how the coherence between the unique constituents of a pattern instance relates to the rest of a network. We have applied the method exemplarily to the analysis of 3-vertex topological pattern instances in the transcription networks of a bacteria (E. coli), a unicellular eukaryote (S. cerevisiae) and higher eukaryotes (human, mouse, rat). We found that in these networks only very few pattern instances break lots of the pairwise connections between vertices upon the removal of an instance. Among them network motifs do not prevail. Rather, those patterns that are shared by the three networks exhibit a conspicuously enhanced pairwise disconnectivity index. Additionally, these are often located in close vicinity to each other or are even overlapping, since only a small number of genes are repeatedly present in most of them. Moreover, evidence has gathered that the importance of these pattern instances is due to synergistic rather than merely additive effects between their constituents. Conclusion A new method has been proposed that enables to evaluate

  5. Epidermal differentiation gene regulatory networks controlled by MAF and MAFB.

    PubMed

    Labott, Andrew T; Lopez-Pajares, Vanessa

    2016-06-01

    Numerous regulatory factors in epidermal differentiation and their role in regulating different cell states have been identified in recent years. However, the genetic interactions between these regulators over the dynamic course of differentiation have not been studied. In this Extra-View article, we review recent work by Lopez-Pajares et al. that explores a new regulatory network in epidermal differentiation. They analyze the changing transcriptome throughout epidermal regeneration to identify 3 separate gene sets enriched in the progenitor, early and late differentiation states. Using expression module mapping, MAF along with MAFB, are identified as transcription factors essential for epidermal differentiation. Through double knock-down of MAF:MAFB using siRNA and CRISPR/Cas9-mediated knockout, epidermal differentiation was shown to be impaired both in-vitro and in-vivo, confirming MAF:MAFB's role to activate genes that drive differentiation. Lopez-Pajares and collaborators integrated 42 published regulator gene sets and the MAF:MAFB gene set into the dynamic differentiation gene expression landscape and found that lncRNAs TINCR and ANCR act as upstream regulators of MAF:MAFB. Furthermore, ChIP-seq analysis of MAF:MAFB identified key transcription factor genes linked to epidermal differentiation as downstream effectors. Combined, these findings illustrate a dynamically regulated network with MAF:MAFB as a crucial link for progenitor gene repression and differentiation gene activation. PMID:27097296

  6. Branching of the PIF3 regulatory network in Arabidopsis

    PubMed Central

    Sentandreu, Maria; Leivar, Pablo; Martín, Guiomar; Monte, Elena

    2012-01-01

    Plants need to accurately adjust their development after germination in the underground darkness to ensure survival of the seedling, both in the dark and in the light upon reaching the soil surface. Recent studies have established that the photoreceptors phytochromes and the bHLH phytochrome interacting factors PIFs regulate seedling development to adjust it to the prevailing light environment during post-germinative growth. However, complete understanding of the downstream regulatory network implementing these developmental responses is still lacking. In a recent work, published in The Plant Cell, we report a subset of PIF3-regulated genes in dark-grown seedlings that we have named MIDAs (MISREGULATED IN DARK). Analysis of their functional relevance using mutants showed that four of them present phenotypic alterations in the dark, and that each affected a particular facet of seedling development, suggesting organ-specific branching in the signal that PIF3 relays downstream. Furthermore, our results also showed an altered response to light in seedlings with an impaired PIF3/MIDA regulatory network, indicating that these factors might also be essential to initiate and optimize the developmental adjustment of the seedling to the light environment. PMID:22499182

  7. Form, Function, and Information Processing in Stochastic Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Wiggins, Chris

    2009-03-01

    The ability of a biological network to transduce signals, e.g., from chemical information about the abundance of small molecules into regulatory information about the rate of mRNA expression, is thwarted by numerous sources of noise. A great amount has been learned and conjectured in the last decade about the extent to which the form of a network --- specified by the connectivity and sign of regulation --- constrains or guides the networks function --- the particular noisy input-output relation(s) the network is capable of executing. In parallel, a great amount of research has sought to elucidate the role of inescapable or 'intrinsic' noise arising from the finite copy number of the participating molecules, which sets physical limits on information processing in small cells. I'll discuss how information theory may help illuminate these topics by providing a framework for quantifying function which does not rely on specifying the particular task to be performed a priori, as well as by providing a measure for the extent to which form follows function. En route I hope to show how stochastic chemical kinetics, modeled by the (linear) master equation describing the probability of copy counts for all reactants, benefits from the same spectral approaches fundamental to solving the (linear) diffusion equation.

  8. Optical packet switch architectures for ultrahigh-speed networks

    NASA Astrophysics Data System (ADS)

    O'Mahony, M. J.; Klonidis, Dimitris; Politi, Christina; Negabati, Reza; Simeonidou, Dimitra

    2005-11-01

    Optical packet switching is commonly considered as a possible technology for future telecommunication networks, due to its compatibility with bursty traffic, eg Internet protocol (IP), and efficient use of wavelength channels. Current transport networks are voice-optimised and connection oriented, however the amount of data traffic is rapidly increasing, resulting in a continuous increase of average traffic through major exchanges exceeding 30% per annum (in Europe). Thus optical packet switching is seen as a future technology that will support diverse traffic profiles and give more efficient bandwidth utilisation through its ability to provide multiplexing at the packet level. In recent years the significance of optical packet switching as an emerging technology has been identified and researched by a number of research groups. Earlier optical packet switching demonstrators presented switching of mainly ATM compatible synchronously transmitted packets at bit rates up to 2.5b/s with the optical header encoded either in series or in parallel to the payload using the sub-carrier modulation technique. More recent projects have demonstrated switching capabilities at 10Gb/s using more advanced approaches with special encoding schemes for header and header detection, together with sophisticated control mechanisms for contention resolution. The capability of switching optical packets at bit rates up to 160Gb/s has recently been demonstrated. This paper discusses the architectures currently proposed for high speed optical packet switching, including the key techniques of header processing and payload switching. The focus is on a high speed demonstrator [OPSnet] capable of operation at rates >100 Gb/s.

  9. How difficult is inference of mammalian causal gene regulatory networks?

    PubMed

    Djordjevic, Djordje; Yang, Andrian; Zadoorian, Armella; Rungrugeecharoen, Kevin; Ho, Joshua W K

    2014-01-01

    Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart) and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect), which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference methods for

  10. Visual pattern recognition network: its training algorithm and its optoelectronic architecture

    NASA Astrophysics Data System (ADS)

    Wang, Ning; Liu, Liren

    1996-07-01

    A visual pattern recognition network and its training algorithm are proposed. The network constructed of a one-layer morphology network and a two-layer modified Hamming net. This visual network can implement invariant pattern recognition with respect to image translation and size projection. After supervised learning takes place, the visual network extracts image features and classifies patterns much the same as living beings do. Moreover we set up its optoelectronic architecture for real-time pattern recognition.

  11. Beyond antioxidant genes in the ancient NRF2 regulatory network

    PubMed Central

    Lacher, Sarah E.; Lee, Joslynn S.; Wang, Xuting; Campbell, Michelle R.; Bell, Douglas A.; Slattery, Matthew

    2016-01-01

    NRF2, a basic leucine zipper transcription factor encoded by the gene NFE2L2, is a master regulator of the transcriptional response to oxidative stress. NRF2 is structurally and functionally conserved from insects to humans, and it heterodimerizes with the small MAF transcription factors to bind a consensus DNA sequence (the antioxidant response element, or ARE) and regulate gene expression. We have used genome-wide chromatin immunoprecipitation (ChIP-seq) and gene expression data to identify direct NRF2 target genes in Drosophila and humans. These data have allowed us to construct the deeply conserved ancient NRF2 regulatory network – target genes that are conserved from Drosophila to human. The ancient network consists of canonical antioxidant genes, as well as genes related to proteasomal pathways, metabolism, and a number of less expected genes. We have also used enhancer reporter assays and electrophoretic mobility shift assays to confirm NRF2-mediated regulation of ARE (antioxidant response element) activity at a number of these novel target genes. Interestingly, the ancient network also highlights a prominent negative feedback loop; this, combined with the finding that and NRF2-mediated regulatory output is tightly linked to the quality of the ARE it is targeting, suggests that precise regulation of nuclear NRF2 concentration is necessary to achieve proper quantitative regulation of distinct gene sets. Together, these findings highlight the importance of balance in the NRF2-ARE pathway, and indicate that NRF2-mediated regulation of xenobiotic metabolism, glucose metabolism, and proteostasis have been central to this pathway since its inception. PMID:26163000

  12. The transcriptional regulatory repertoire of Corynebacterium glutamicum: reconstruction of the network controlling pathways involved in lysine and glutamate production.

    PubMed

    Brinkrolf, Karina; Schröder, Jasmin; Pühler, Alfred; Tauch, Andreas

    2010-09-01

    Corynebacterium glutamicum is one of the best studied organisms of the high G+C branch of Gram-positive bacteria and an emerging model system for the suborder Corynebacterineae. To gain insights into the regulatory gene composition and architecture of the transcriptional regulatory network of C. glutamicum, components of the transcriptional regulatory repertoire were intensively studied by many scientific groups in recent years. In this mini-review, we summarize the present knowledge about the deduced transcriptional regulatory repertoire of C. glutamicum and the current status of transcriptional regulatory network reconstruction with regard to the genome-wide detection of transcriptional regulations, coregulatory interactions and hierarchical cross-regulations. Moreover, we provide an overview of those regulators and their transcriptional regulations controlling genes involved in the conversion of the carbon sources glucose, fructose and sucrose into the industrially relevant products l-lysine and l-glutamate. This data will contribute to our understanding of l-lysine and l-glutamate production by C. glutamicum from the perspective of systems biology and may provide the basis for computational modeling of the respective biotechnologically important metabolic pathways. PMID:19963020

  13. The middleware architecture supports heterogeneous network systems for module-based personal robot system

    NASA Astrophysics Data System (ADS)

    Choo, Seongho; Li, Vitaly; Choi, Dong Hee; Jung, Gi Deck; Park, Hong Seong; Ryuh, Youngsun

    2005-12-01

    On developing the personal robot system presently, the internal architecture is every module those occupy separated functions are connected through heterogeneous network system. This module-based architecture supports specialization and division of labor at not only designing but also implementation, as an effect of this architecture, it can reduce developing times and costs for modules. Furthermore, because every module is connected among other modules through network systems, we can get easy integrations and synergy effect to apply advanced mutual functions by co-working some modules. In this architecture, one of the most important technologies is the network middleware that takes charge communications among each modules connected through heterogeneous networks systems. The network middleware acts as the human nerve system inside of personal robot system; it relays, transmits, and translates information appropriately between modules that are similar to human organizations. The network middleware supports various hardware platform, heterogeneous network systems (Ethernet, Wireless LAN, USB, IEEE 1394, CAN, CDMA-SMS, RS-232C). This paper discussed some mechanisms about our network middleware to intercommunication and routing among modules, methods for real-time data communication and fault-tolerant network service. There have designed and implemented a layered network middleware scheme, distributed routing management, network monitoring/notification technology on heterogeneous networks for these goals. The main theme is how to make routing information in our network middleware. Additionally, with this routing information table, we appended some features. Now we are designing, making a new version network middleware (we call 'OO M/W') that can support object-oriented operation, also are updating program sources itself for object-oriented architecture. It is lighter, faster, and can support more operation systems and heterogeneous network systems, but other general

  14. A hybrid behavioural rule of adaptation and drift explains the emergent architecture of antagonistic networks

    PubMed Central

    Nuwagaba, S.; Zhang, F.; Hui, C.

    2015-01-01

    Ecological processes that can realistically account for network architectures are central to our understanding of how species assemble and function in ecosystems. Consumer species are constantly selecting and adjusting which resource species are to be exploited in an antagonistic network. Here we incorporate a hybrid behavioural rule of adaptive interaction switching and random drift into a bipartite network model. Predictions are insensitive to the model parameters and the initial network structures, and agree extremely well with the observed levels of modularity, nestedness and node-degree distributions for 61 real networks. Evolutionary and community assemblage histories only indirectly affect network structure by defining the size and complexity of ecological networks, whereas adaptive interaction switching and random drift carve out the details of network architecture at the faster ecological time scale. The hybrid behavioural rule of both adaptation and drift could well be the key processes for structure emergence in real ecological networks. PMID:25925104

  15. A hybrid behavioural rule of adaptation and drift explains the emergent architecture of antagonistic networks.

    PubMed

    Nuwagaba, S; Zhang, F; Hui, C

    2015-05-22

    Ecological processes that can realistically account for network architectures are central to our understanding of how species assemble and function in ecosystems. Consumer species are constantly selecting and adjusting which resource species are to be exploited in an antagonistic network. Here we incorporate a hybrid behavioural rule of adaptive interaction switching and random drift into a bipartite network model. Predictions are insensitive to the model parameters and the initial network structures, and agree extremely well with the observed levels of modularity, nestedness and node-degree distributions for 61 real networks. Evolutionary and community assemblage histories only indirectly affect network structure by defining the size and complexity of ecological networks, whereas adaptive interaction switching and random drift carve out the details of network architecture at the faster ecological time scale. The hybrid behavioural rule of both adaptation and drift could well be the key processes for structure emergence in real ecological networks. PMID:25925104

  16. Ensemble Inference and Inferability of Gene Regulatory Networks

    PubMed Central

    Ud-Dean, S. M. Minhaz; Gunawan, Rudiyanto

    2014-01-01

    The inference of gene regulatory network (GRN) from gene expression data is an unsolved problem of great importance. This inference has been stated, though not proven, to be underdetermined implying that there could be many equivalent (indistinguishable) solutions. Motivated by this fundamental limitation, we have developed new framework and algorithm, called TRaCE, for the ensemble inference of GRNs. The ensemble corresponds to the inherent uncertainty associated with discriminating direct and indirect gene regulations from steady-state data of gene knock-out (KO) experiments. We applied TRaCE to analyze the inferability of random GRNs and the GRNs of E. coli and yeast from single- and double-gene KO experiments. The results showed that, with the exception of networks with very few edges, GRNs are typically not inferable even when the data are ideal (unbiased and noise-free). Finally, we compared the performance of TRaCE with top performing methods of DREAM4 in silico network inference challenge. PMID:25093509

  17. Pharyngeal mesoderm regulatory network controls cardiac and head muscle morphogenesis

    PubMed Central

    Harel, Itamar; Maezawa, Yoshiro; Avraham, Roi; Rinon, Ariel; Ma, Hsiao-Yen; Cross, Joe W.; Leviatan, Noam; Hegesh, Julius; Roy, Achira; Jacob-Hirsch, Jasmine; Rechavi, Gideon; Carvajal, Jaime; Tole, Shubha; Kioussi, Chrissa; Quaggin, Susan; Tzahor, Eldad

    2012-01-01

    The search for developmental mechanisms driving vertebrate organogenesis has paved the way toward a deeper understanding of birth defects. During embryogenesis, parts of the heart and craniofacial muscles arise from pharyngeal mesoderm (PM) progenitors. Here, we reveal a hierarchical regulatory network of a set of transcription factors expressed in the PM that initiates heart and craniofacial organogenesis. Genetic perturbation of this network in mice resulted in heart and craniofacial muscle defects, revealing robust cross-regulation between its members. We identified Lhx2 as a previously undescribed player during cardiac and pharyngeal muscle development. Lhx2 and Tcf21 genetically interact with Tbx1, the major determinant in the etiology of DiGeorge/velo-cardio-facial/22q11.2 deletion syndrome. Furthermore, knockout of these genes in the mouse recapitulates specific cardiac features of this syndrome. We suggest that PM-derived cardiogenesis and myogenesis are network properties rather than properties specific to individual PM members. These findings shed new light on the developmental underpinnings of congenital defects. PMID:23112163

  18. A novel ECDM-OFDM-PON architecture for next-generation optical access network.

    PubMed

    Zhang, Lijia; Xin, Xiangjun; Liu, Bo; Yu, Jianjun; Zhang, Qi

    2010-08-16

    This paper proposes a novel architecture for next-generation passive optical network (PON) based on electrical code division multiplexing orthogonal frequency division multiplexing (ECDM-OFDM) access. The feasibility of bidirectional transmission with the same wavelength has been experimentally demonstrated under this architecture. An error-free transmission of two PON channels has been successfully demonstrated in the experiment. PMID:20721227

  19. Uncovering Transcriptional Regulatory Networks by Sparse Bayesian Factor Model

    NASA Astrophysics Data System (ADS)

    Meng, Jia; Zhang, Jianqiu(Michelle); Qi, Yuan(Alan); Chen, Yidong; Huang, Yufei

    2010-12-01

    The problem of uncovering transcriptional regulation by transcription factors (TFs) based on microarray data is considered. A novel Bayesian sparse correlated rectified factor model (BSCRFM) is proposed that models the unknown TF protein level activity, the correlated regulations between TFs, and the sparse nature of TF-regulated genes. The model admits prior knowledge from existing database regarding TF-regulated target genes based on a sparse prior and through a developed Gibbs sampling algorithm, a context-specific transcriptional regulatory network specific to the experimental condition of the microarray data can be obtained. The proposed model and the Gibbs sampling algorithm were evaluated on the simulated systems, and results demonstrated the validity and effectiveness of the proposed approach. The proposed model was then applied to the breast cancer microarray data of patients with Estrogen Receptor positive ([InlineEquation not available: see fulltext.]) status and Estrogen Receptor negative ([InlineEquation not available: see fulltext.]) status, respectively.

  20. Transcriptional Regulatory Networks for CD4 T Cell Differentiation

    PubMed Central

    Zhu, Jinfang

    2015-01-01

    CD4+ T cells play a central role in controlling the adaptive immune response by secreting cytokines to activate target cells. Naïve CD4+ T cells differentiate into at least four subsets, Th1, Th2, Th17, and inducible regulatory T cells, each with unique functions for pathogen elimination. The differentiation of these subsets is induced in response to cytokine stimulation, which is translated into Stat activation, followed by induction of master regulator transcription factors. In addition to these factors, multiple other transcription factors, both subset specific and shared, are also involved in promoting subset differentiation. This review will focus on the network of transcription factors that control CD4+ T cell differentiation. PMID:24839135

  1. An Arabidopsis Gene Regulatory Network for Secondary Cell Wall Synthesis

    PubMed Central

    Taylor-Teeples, M; Lin, L; de Lucas, M; Turco, G; Toal, TW; Gaudinier, A; Young, NF; Trabucco, GM; Veling, MT; Lamothe, R; Handakumbura, PP; Xiong, G; Wang, C; Corwin, J; Tsoukalas, A; Zhang, L; Ware, D; Pauly, M; Kliebenstein, DJ; Dehesh, K; Tagkopoulos, I; Breton, G; Pruneda-Paz, JL; Ahnert, SE; Kay, SA; Hazen, SP; Brady, SM

    2014-01-01

    Summary The plant cell wall is an important factor for determining cell shape, function and response to the environment. Secondary cell walls, such as those found in xylem, are composed of cellulose, hemicelluloses and lignin and account for the bulk of plant biomass. The coordination between transcriptional regulation of synthesis for each polymer is complex and vital to cell function. A regulatory hierarchy of developmental switches has been proposed, although the full complement of regulators remains unknown. Here, we present a protein-DNA network between Arabidopsis transcription factors and secondary cell wall metabolic genes with gene expression regulated by a series of feed-forward loops. This model allowed us to develop and validate new hypotheses about secondary wall gene regulation under abiotic stress. Distinct stresses are able to perturb targeted genes to potentially promote functional adaptation. These interactions will serve as a foundation for understanding the regulation of a complex, integral plant component. PMID:25533953

  2. RegNetwork: an integrated database of transcriptional and post-transcriptional regulatory networks in human and mouse

    PubMed Central

    Liu, Zhi-Ping; Wu, Canglin; Miao, Hongyu; Wu, Hulin

    2015-01-01

    Transcriptional and post-transcriptional regulation of gene expression is of fundamental importance to numerous biological processes. Nowadays, an increasing amount of gene regulatory relationships have been documented in various databases and literature. However, to more efficiently exploit such knowledge for biomedical research and applications, it is necessary to construct a genome-wide regulatory network database to integrate the information on gene regulatory relationships that are widely scattered in many different places. Therefore, in this work, we build a knowledge-based database, named ‘RegNetwork’, of gene regulatory networks for human and mouse by collecting and integrating the documented regulatory interactions among transcription factors (TFs), microRNAs (miRNAs) and target genes from 25 selected databases. Moreover, we also inferred and incorporated potential regulatory relationships based on transcription factor binding site (TFBS) motifs into RegNetwork. As a result, RegNetwork contains a comprehensive set of experimentally observed or predicted transcriptional and post-transcriptional regulatory relationships, and the database framework is flexibly designed for potential extensions to include gene regulatory networks for other organisms in the future. Based on RegNetwork, we characterized the statistical and topological properties of genome-wide regulatory networks for human and mouse, we also extracted and interpreted simple yet important network motifs that involve the interplays between TF-miRNA and their targets. In summary, RegNetwork provides an integrated resource on the prior information for gene regulatory relationships, and it enables us to further investigate context-specific transcriptional and post-transcriptional regulatory interactions based on domain-specific experimental data. Database URL: http://www.regnetworkweb.org PMID:26424082

  3. Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions.

    PubMed

    Schep, Alicia N; Buenrostro, Jason D; Denny, Sarah K; Schwartz, Katja; Sherlock, Gavin; Greenleaf, William J

    2015-11-01

    Transcription factors canonically bind nucleosome-free DNA, making the positioning of nucleosomes within regulatory regions crucial to the regulation of gene expression. Using the assay of transposase accessible chromatin (ATAC-seq), we observe a highly structured pattern of DNA fragment lengths and positions around nucleosomes in Saccharomyces cerevisiae, and use this distinctive two-dimensional nucleosomal "fingerprint" as the basis for a new nucleosome-positioning algorithm called NucleoATAC. We show that NucleoATAC can identify the rotational and translational positions of nucleosomes with up to base-pair resolution and provide quantitative measures of nucleosome occupancy in S. cerevisiae, Schizosaccharomyces pombe, and human cells. We demonstrate the application of NucleoATAC to a number of outstanding problems in chromatin biology, including analysis of sequence features underlying nucleosome positioning, promoter chromatin architecture across species, identification of transient changes in nucleosome occupancy and positioning during a dynamic cellular response, and integrated analysis of nucleosome occupancy and transcription factor binding. PMID:26314830

  4. Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions

    PubMed Central

    Schep, Alicia N.; Buenrostro, Jason D.; Denny, Sarah K.; Schwartz, Katja; Sherlock, Gavin; Greenleaf, William J.

    2015-01-01

    Transcription factors canonically bind nucleosome-free DNA, making the positioning of nucleosomes within regulatory regions crucial to the regulation of gene expression. Using the assay of transposase accessible chromatin (ATAC-seq), we observe a highly structured pattern of DNA fragment lengths and positions around nucleosomes in Saccharomyces cerevisiae, and use this distinctive two-dimensional nucleosomal “fingerprint” as the basis for a new nucleosome-positioning algorithm called NucleoATAC. We show that NucleoATAC can identify the rotational and translational positions of nucleosomes with up to base-pair resolution and provide quantitative measures of nucleosome occupancy in S. cerevisiae, Schizosaccharomyces pombe, and human cells. We demonstrate the application of NucleoATAC to a number of outstanding problems in chromatin biology, including analysis of sequence features underlying nucleosome positioning, promoter chromatin architecture across species, identification of transient changes in nucleosome occupancy and positioning during a dynamic cellular response, and integrated analysis of nucleosome occupancy and transcription factor binding. PMID:26314830

  5. Integrated Approach to Reconstruction of Microbial Regulatory Networks

    SciTech Connect

    Rodionov, Dmitry A; Novichkov, Pavel S

    2013-11-04

    This project had the goal(s) of development of integrated bioinformatics platform for genome-scale inference and visualization of transcriptional regulatory networks (TRNs) in bacterial genomes. The work was done in Sanford-Burnham Medical Research Institute (SBMRI, P.I. D.A. Rodionov) and Lawrence Berkeley National Laboratory (LBNL, co-P.I. P.S. Novichkov). The developed computational resources include: (1) RegPredict web-platform for TRN inference and regulon reconstruction in microbial genomes, and (2) RegPrecise database for collection, visualization and comparative analysis of transcriptional regulons reconstructed by comparative genomics. These analytical resources were selected as key components in the DOE Systems Biology KnowledgeBase (SBKB). The high-quality data accumulated in RegPrecise will provide essential datasets of reference regulons in diverse microbes to enable automatic reconstruction of draft TRNs in newly sequenced genomes. We outline our progress toward the three aims of this grant proposal, which were: Develop integrated platform for genome-scale regulon reconstruction; Infer regulatory annotations in several groups of bacteria and building of reference collections of microbial regulons; and Develop KnowledgeBase on microbial transcriptional regulation.

  6. Modeling of a 3DTV service in the software-defined networking architecture

    NASA Astrophysics Data System (ADS)

    Wilczewski, Grzegorz

    2014-11-01

    In this article a newly developed concept towards modeling of a multimedia service offering stereoscopic motion imagery is presented. Proposed model is based on the approach of utilization of Software-defined Networking or Software Defined Networks architecture (SDN). The definition of 3D television service spanning SDN concept is identified, exposing basic characteristic of a 3DTV service in a modern networking organization layout. Furthermore, exemplary functionalities of the proposed 3DTV model are depicted. It is indicated that modeling of a 3DTV service in the Software-defined Networking architecture leads to multiplicity of improvements, especially towards flexibility of a service supporting heterogeneity of end user devices.

  7. Service-Transport Separated Network Architecture Using MPLS-TP Technologies

    NASA Astrophysics Data System (ADS)

    Sakamoto, Kenichi; Ashi, Yoshihiro; Takase, Akihiko

    We propose a next-generation service-transport separated network architecture that uses packet technology. The transport network is responsible for the high speed and reliable bit transfer, and the service network is responsible for many types of network services. This separation makes it possible for the next-generation network to achieve both rapid bandwidth spreading and the speedy installation of new services. We also propose a next-generation transport network using the multi-protocol label switching transport profile (MPLS-TP) and optical networking technologies.

  8. Access protocols and network architectures for very high-speed optical fiber local area networks

    NASA Astrophysics Data System (ADS)

    Ganti, Sudhaker N. M.

    1993-10-01

    The single mode optical fiber possesses an enormous bandwidth of more than 30 THz in the low-loss optical region of 1.3 and 1.5 microns. Through wavelength division multiplexing (WDM), the optical fiber bandwidth can be divided into a set of high-speed channels, where each channel is assigned its own unique wavelength. An M x M passive optical star coupler is a simple broadcast medium, in which light energy incident at any input is uniformly coupled (or distributed) to all the outputs. Thus, a passive star along with the WDM channels can be used to configure a local area network (LAN). In this LAN, users require tunable devices to access a complete or a partial set of the WDM channels. Due to these multiple channels, many concurrent packet transmissions corresponding to different user pairs are possible and thus the total system throughput can be much higher than the data rates of each individual channel. To fairly arbitrate the data channels among the users, media access protocols are needed. Depending upon the number of data channels and the number of users, two possible situations arise. In the first case, the number of users is much larger than the number of data channels and in the second, the number of users equals the number of channels. In both cases, data channel contention may arise if multiple users access the same given channel and must be resolved. This thesis proposes media access protocols for passive optical star networks. All the proposed protocols are slotted in nature, i.e., the time axis on each channel is divided into slots. The well known Slotted-ALOHA and Reservation ALOHA protocols are extended to the multichannel network environment. The thesis also proposes switching protocols (equal number of channels and users), contention-based reservation protocols for this network architecture. To interconnect these star networks, a multi-control channel protocol is also proposed along with two interconnecting techniques. Since there are multiple data

  9. A More Efficient COPE Architecture for Network Coding in Multihop Wireless Networks

    NASA Astrophysics Data System (ADS)

    Chi, Kaikai; Jiang, Xiaohong; Horiguchi, Susumu

    Recently, a promising packet forwarding architecture COPE was proposed to essentially improve the throughput of multihop wireless networks, where each network node can intelligently encode multiple packets together and forward them in a single transmission. However, COPE is still in its infancy and has the following limitations: (1) COPE adopts the FIFO packet scheduling and thus does not provide different priorities for different types of packets. (2) COPE simply classifies all packets destined to the same nexthop into small-size or large-size virtual queues and examines only the head packet of each virtual queue to find coding solutions. Such a queueing structure will lose some potential coding opportunities, because among packets destined to the same nexthop at most two packets (the head packets of small-size and large-size queues) will be examined in the coding process, regardless of the number of flows. (3) The coding algorithm adopted in COPE is fast but cannot always find good solutions. In order to address the above limitations, in this paper we first present a new queueing structure for COPE, which can provide more potential coding opportunities, and then propose a new packet scheduling algorithm for this queueing structure to assign different priorities to different types of packets. Finally, we propose an efficient coding algorithm to find appropriate packets for coding. Simulation results demonstrate that this new COPE architecture can further greatly improve the node transmission efficiency.

  10. Space Network IP Services (SNIS): An Architecture for Supporting Low Earth Orbiting IP Satellite Missions

    NASA Technical Reports Server (NTRS)

    Israel, David J.

    2005-01-01

    The NASA Space Network (SN) supports a variety of missions using the Tracking and Data Relay Satellite System (TDRSS), which includes ground stations in White Sands, New Mexico and Guam. A Space Network IP Services (SNIS) architecture is being developed to support future users with requirements for end-to-end Internet Protocol (IP) communications. This architecture will support all IP protocols, including Mobile IP, over TDRSS Single Access, Multiple Access, and Demand Access Radio Frequency (RF) links. This paper will describe this architecture and how it can enable Low Earth Orbiting IP satellite missions.

  11. Architectural and operational considerations emerging from hybrid RF-optical network loading simulations

    NASA Astrophysics Data System (ADS)

    Chen, Yijiang; Abraham, Douglas S.; Heckman, David P.; Kwok, Andrew; MacNeal, Bruce E.; Tran, Kristy; Wu, Janet P.

    2016-03-01

    A technology demonstration of free space optical communication at interplanetary distances is planned via one or more future NASA deep-space missions. Such demonstrations will "pave the way" for operational use of optical communications on future robotic/potential Human missions. Hence, the Deep Space Network architecture will need to evolve. Preliminary attempts to model the anticipated future mission set and simulate how well it loads onto assumed architectures with combinations of RF and optical apertures have been evaluated. This paper discusses the results of preliminary loading simulations for hybrid RF-optical network architectures and highlights key mission and ground infrastructure considerations that emerge.

  12. A neural network architecture for implementation of expert systems for real time monitoring

    NASA Technical Reports Server (NTRS)

    Ramamoorthy, P. A.

    1991-01-01

    Since neural networks have the advantages of massive parallelism and simple architecture, they are good tools for implementing real time expert systems. In a rule based expert system, the antecedents of rules are in the conjunctive or disjunctive form. We constructed a multilayer feedforward type network in which neurons represent AND or OR operations of rules. Further, we developed a translator which can automatically map a given rule base into the network. Also, we proposed a new and powerful yet flexible architecture that combines the advantages of both fuzzy expert systems and neural networks. This architecture uses the fuzzy logic concepts to separate input data domains into several smaller and overlapped regions. Rule-based expert systems for time critical applications using neural networks, the automated implementation of rule-based expert systems with neural nets, and fuzzy expert systems vs. neural nets are covered.

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

    PubMed Central

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

    2015-01-01

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

  14. Comprehensive Mapping of the Escherichia coli Flagellar Regulatory Network

    PubMed Central

    Fitzgerald, Devon M.; Bonocora, Richard P.; Wade, Joseph T.

    2014-01-01

    Flagellar synthesis is a highly regulated process in all motile bacteria. In Escherichia coli and related species, the transcription factor FlhDC is the master regulator of a multi-tiered transcription network. FlhDC activates transcription of a number of genes, including some flagellar genes and the gene encoding the alternative Sigma factor FliA. Genes whose expression is required late in flagellar assembly are primarily transcribed by FliA, imparting temporal regulation of transcription and coupling expression to flagellar assembly. In this study, we use ChIP-seq and RNA-seq to comprehensively map the E. coli FlhDC and FliA regulons. We define a surprisingly restricted FlhDC regulon, including two novel regulated targets and two binding sites not associated with detectable regulation of surrounding genes. In contrast, we greatly expand the known FliA regulon. Surprisingly, 30 of the 52 FliA binding sites are located inside genes. Two of these intragenic promoters are associated with detectable noncoding RNAs, while the others either produce highly unstable RNAs or are inactive under these conditions. Together, our data redefine the E. coli flagellar regulatory network, and provide new insight into the temporal orchestration of gene expression that coordinates the flagellar assembly process. PMID:25275371

  15. Complex Dynamic Behavior in Simple Gene Regulatory Networks

    NASA Astrophysics Data System (ADS)

    Santillán Zerón, Moisés

    2007-02-01

    Knowing the complete genome of a given species is just a piece of the puzzle. To fully unveil the systems behavior of an organism, an organ, or even a single cell, we need to understand the underlying gene regulatory dynamics. Given the complexity of the whole system, the ultimate goal is unattainable for the moment. But perhaps, by analyzing the most simple genetic systems, we may be able to develop the mathematical techniques and procedures required to tackle more complex genetic networks in the near future. In the present work, the techniques for developing mathematical models of simple bacterial gene networks, like the tryptophan and lactose operons are introduced. Despite all of the underlying assumptions, such models can provide valuable information regarding gene regulation dynamics. Here, we pay special attention to robustness as an emergent property. These notes are organized as follows. In the first section, the long historical relation between mathematics, physics, and biology is briefly reviewed. Recently, the multidisciplinary work in biology has received great attention in the form of systems biology. The main concepts of this novel science are discussed in the second section. A very slim introduction to the essential concepts of molecular biology is given in the third section. In the fourth section, a brief introduction to chemical kinetics is presented. Finally, in the fifth section, a mathematical model for the lactose operon is developed and analyzed..

  16. Cross-Tissue Regulatory Gene Networks in Coronary Artery Disease.

    PubMed

    Talukdar, Husain A; Foroughi Asl, Hassan; Jain, Rajeev K; Ermel, Raili; Ruusalepp, Arno; Franzén, Oscar; Kidd, Brian A; Readhead, Ben; Giannarelli, Chiara; Kovacic, Jason C; Ivert, Torbjörn; Dudley, Joel T; Civelek, Mete; Lusis, Aldons J; Schadt, Eric E; Skogsberg, Josefin; Michoel, Tom; Björkegren, Johan L M

    2016-03-23

    Inferring molecular networks can reveal how genetic perturbations interact with environmental factors to cause common complex diseases. We analyzed genetic and gene expression data from seven tissues relevant to coronary artery disease (CAD) and identified regulatory gene networks (RGNs) and their key drivers. By integrating data from genome-wide association studies, we identified 30 CAD-causal RGNs interconnected in vascular and metabolic tissues, and we validated them with corresponding data from the Hybrid Mouse Diversity Panel. As proof of concept, by targeting the key drivers AIP, DRAP1, POLR2I, and PQBP1 in a cross-species-validated, arterial-wall RGN involving RNA-processing genes, we re-identified this RGN in THP-1 foam cells and independent data from CAD macrophages and carotid lesions. This characterization of the molecular landscape in CAD will help better define the regulation of CAD candidate genes identified by genome-wide association studies and is a first step toward achieving the goals of precision medicine. PMID:27135365

  17. Regulatory Networks Controlling Plant Cold Acclimation or Low Temperature Regulatory Networks Controlling Cold Acclimation in Arabidopsis (2011 JGI User Meeting)

    ScienceCinema

    Thomashow, Mike

    2011-06-03

    The U.S. Department of Energy Joint Genome Institute (JGI) invited scientists interested in the application of genomics to bioenergy and environmental issues, as well as all current and prospective users and collaborators, to attend the annual DOE JGI Genomics of Energy & Environment Meeting held March 22-24, 2011 in Walnut Creek, Calif. The emphasis of this meeting was on the genomics of renewable energy strategies, carbon cycling, environmental gene discovery, and engineering of fuel-producing organisms. The meeting features presentations by leading scientists advancing these topics. Mike Thomashow of Michigan State University gives a presentation on on "Low Temperature Regulatory Networks Controlling Cold Acclimation in Arabidopsis" at the 6th annual Genomics of Energy & Environment Meeting on March 23, 2011. «

  18. Regulatory Networks Controlling Plant Cold Acclimation or Low Temperature Regulatory Networks Controlling Cold Acclimation in Arabidopsis (2011 JGI User Meeting)

    SciTech Connect

    Thomashow, Mike

    2011-03-23

    The U.S. Department of Energy Joint Genome Institute (JGI) invited scientists interested in the application of genomics to bioenergy and environmental issues, as well as all current and prospective users and collaborators, to attend the annual DOE JGI Genomics of Energy & Environment Meeting held March 22-24, 2011 in Walnut Creek, Calif. The emphasis of this meeting was on the genomics of renewable energy strategies, carbon cycling, environmental gene discovery, and engineering of fuel-producing organisms. The meeting features presentations by leading scientists advancing these topics. Mike Thomashow of Michigan State University gives a presentation on on "Low Temperature Regulatory Networks Controlling Cold Acclimation in Arabidopsis" at the 6th annual Genomics of Energy & Environment Meeting on March 23, 2011. «

  19. Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) Technology Infrastructure for a Distributed Data Network

    PubMed Central

    Schilling, Lisa M.; Kwan, Bethany M.; Drolshagen, Charles T.; Hosokawa, Patrick W.; Brandt, Elias; Pace, Wilson D.; Uhrich, Christopher; Kamerick, Michael; Bunting, Aidan; Payne, Philip R.O.; Stephens, William E.; George, Joseph M.; Vance, Mark; Giacomini, Kelli; Braddy, Jason; Green, Mika K.; Kahn, Michael G.

    2013-01-01

    Introduction: Distributed Data Networks (DDNs) offer infrastructure solutions for sharing electronic health data from across disparate data sources to support comparative effectiveness research. Data sharing mechanisms must address technical and governance concerns stemming from network security and data disclosure laws and best practices, such as HIPAA. Methods: The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) deploys TRIAD grid technology, a common data model, detailed technical documentation, and custom software for data harmonization to facilitate data sharing in collaboration with stakeholders in the care of safety net populations. Data sharing partners host TRIAD grid nodes containing harmonized clinical data within their internal or hosted network environments. Authorized users can use a central web-based query system to request analytic data sets. Discussion: SAFTINet DDN infrastructure achieved a number of data sharing objectives, including scalable and sustainable systems for ensuring harmonized data structures and terminologies and secure distributed queries. Initial implementation challenges were resolved through iterative discussions, development and implementation of technical documentation, governance, and technology solutions. PMID:25848567

  20. Rearrangements of the transcriptional regulatory networks of metabolic pathways in fungi

    PubMed Central

    Lavoie, Hugo; Hogues, Hervé; Whiteway, Malcolm

    2013-01-01

    Growing evidence suggests that transcriptional regulatory networks in many organisms are highly flexible. Here, we discuss the evolution of transcriptional regulatory networks governing the metabolic machinery of sequenced ascomycetes. In particular, recent work has shown that transcriptional rewiring is common in regulons controlling processes such as production of ribosome components and metabolism of carbohydrates and lipids. We note that dramatic rearrangements of the transcriptional regulatory components of metabolic functions have occurred among ascomycetes species. PMID:19875326

  1. Identifying Functional Gene Regulatory Network Phenotypes Underlying Single Cell Transcriptional Variability

    PubMed Central

    Park, James; Ogunnaike, Babatunde; Schwaber, James; Vadigepalli, Rajanikanth

    2014-01-01

    Summary/abstract Recent analysis of single-cell transcriptomic data has revealed a surprising organization of the transcriptional variability pervasive across individual neurons. In response to distinct combinations of synaptic input-type, a new organization of neuronal subtypes emerged based on transcriptional states that were aligned along a gradient of correlated gene expression. Individual neurons traverse across these transcriptional states in response to cellular inputs. However, the regulatory network interactions driving these changes remain unclear. Here we present a novel fuzzy logic-based approach to infer quantitative gene regulatory network models from highly variable single-cell gene expression data. Our approach involves developing an a priori regulatory network that is then trained against in vivo single-cell gene expression data in order to identify causal gene interactions and corresponding quantitative model parameters. Simulations of the inferred gene regulatory network response to experimentally observed stimuli levels mirrored the pattern and quantitative range of gene expression across individual neurons remarkably well. In addition, the network identification results revealed that distinct regulatory interactions, coupled with differences in the regulatory network stimuli, drive the variable gene expression patterns observed across the neuronal subtypes. We also identified a key difference between the neuronal subtype-specific networks with respect to negative feedback regulation, with the catecholaminergic subtype network lacking such interactions. Furthermore, by varying regulatory network stimuli over a wide range, we identified several cases in which divergent neuronal subtypes could be driven towards similar transcriptional states by distinct stimuli operating on subtype-specific regulatory networks. Based on these results, we conclude that heterogeneous single-cell gene expression profiles should be interpreted through a regulatory

  2. Genes under weaker stabilizing selection increase network evolvability and rapid regulatory adaptation to an environmental shift.

    PubMed

    Laarits, T; Bordalo, P; Lemos, B

    2016-08-01

    Regulatory networks play a central role in the modulation of gene expression, the control of cellular differentiation, and the emergence of complex phenotypes. Regulatory networks could constrain or facilitate evolutionary adaptation in gene expression levels. Here, we model the adaptation of regulatory networks and gene expression levels to a shift in the environment that alters the optimal expression level of a single gene. Our analyses show signatures of natural selection on regulatory networks that both constrain and facilitate rapid evolution of gene expression level towards new optima. The analyses are interpreted from the standpoint of neutral expectations and illustrate the challenge to making inferences about network adaptation. Furthermore, we examine the consequence of variable stabilizing selection across genes on the strength and direction of interactions in regulatory networks and in their subsequent adaptation. We observe that directional selection on a highly constrained gene previously under strong stabilizing selection was more efficient when the gene was embedded within a network of partners under relaxed stabilizing selection pressure. The observation leads to the expectation that evolutionarily resilient regulatory networks will contain optimal ratios of genes whose expression is under weak and strong stabilizing selection. Altogether, our results suggest that the variable strengths of stabilizing selection across genes within regulatory networks might itself contribute to the long-term adaptation of complex phenotypes. PMID:27213992

  3. Integrating Transcriptomic and Proteomic Data Using Predictive Regulatory Network Models of Host Response to Pathogens

    PubMed Central

    Chasman, Deborah; Walters, Kevin B.; Lopes, Tiago J. S.; Eisfeld, Amie J.; Kawaoka, Yoshihiro; Roy, Sushmita

    2016-01-01

    Mammalian host response to pathogenic infections is controlled by a complex regulatory network connecting regulatory proteins such as transcription factors and signaling proteins to target genes. An important challenge in infectious disease research is to understand molecular similarities and differences in mammalian host response to diverse sets of pathogens. Recently, systems biology studies have produced rich collections of omic profiles measuring host response to infectious agents such as influenza viruses at multiple levels. To gain a comprehensive understanding of the regulatory network driving host response to multiple infectious agents, we integrated host transcriptomes and proteomes using a network-based approach. Our approach combines expression-based regulatory network inference, structured-sparsity based regression, and network information flow to infer putative physical regulatory programs for expression modules. We applied our approach to identify regulatory networks, modules and subnetworks that drive host response to multiple influenza infections. The inferred regulatory network and modules are significantly enriched for known pathways of immune response and implicate apoptosis, splicing, and interferon signaling processes in the differential response of viral infections of different pathogenicities. We used the learned network to prioritize regulators and study virus and time-point specific networks. RNAi-based knockdown of predicted regulators had significant impact on viral replication and include several previously unknown regulators. Taken together, our integrated analysis identified novel module level patterns that capture strain and pathogenicity-specific patterns of expression and helped identify important regulators of host response to influenza infection. PMID:27403523

  4. Architecture and System Engineering Development Study of Space-Based Satellite Networks for NASA Missions

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.

    2003-01-01

    Traditional NASA missions, both near Earth and deep space, have been stovepipe in nature and point-to-point in architecture. Recently, NASA and others have conceptualized missions that required space-based networking. The notion of networks in space is a drastic shift in thinking and requires entirely new architectures, radio systems (antennas, modems, and media access), and possibly even new protocols. A full system engineering approach for some key mission architectures will occur that considers issues such as the science being performed, stationkeeping, antenna size, contact time, data rates, radio-link power requirements, media access techniques, and appropriate networking and transport protocols. This report highlights preliminary architecture concepts and key technologies that will be investigated.

  5. Autonomous Boolean models for logic, timing, and stability in regulatory networks

    NASA Astrophysics Data System (ADS)

    Socolar, Joshua E. S.

    2011-03-01

    The dynamics of gene expression in a cell is controlled by a dizzying array of biochemical processes. Natural selection, however, has created regulatory systems with a level of logical organization that can be modeled without detailed knowledge of the biochemistry. In cases where graded responses are not relevant, autonomous Boolean network (ABN) models can effectively represent the logic of gene regulation. These are models in which Boolean logic governs the output value of each node and the timing of updates is determined according to delay parameters associated with each link. An advantage of ABNs over synchronous or random asynchronous Boolean networks is that noise associated with molecular concentrations or transport times can be represented through fluctuations in the timing of updates. We have used ABN models to investigate the stability of oscillations in a model of transcriptional oscillations in yeast and the parameter constraints in a model of segment polarity maintenance in the fly embryo, and also to characterize chaotic dynamics observed in a free--running digital electronic circuit. The yeast study highlights architectural and dynamical features of oscillators that rely on pulse transmission rather than a frustrated feedback loop; the fly study reveals timing constraints that are hidden in ODE models; and the electronics study shows that Boolean chaos can occur if and only if time delays are history dependent. Joint work with V. Sevim, X. Gong, X. Cheng, M. Sun, D. Gauthier, H. Cavalcante, and R. Zhang. Supported by NSF Grant PHY-0417372 and NIH Grant P50-GM081883.

  6. Heterogeneous waveband switching in wavelength division multiplexed networks based on autonomous clustering architecture [Invited

    NASA Astrophysics Data System (ADS)

    Li, Mengke; Ramamurthy, Byrav

    2006-09-01

    Adopting waveband switching (WBS) in backbone wavelength division multiplexed (WDM) networks is promising since it can reduce the network operational cost and the call blocking probability. However, upgrading the existing optical switching architecture requires time and money. Thus heterogeneous waveband switching (HeteroWBS) architecture would be desirable in such a system, where some nodes can support WBS functions and some cannot. We study the performance of HeteroWBS networks in terms of call blocking probability and cost savings under dynamically arriving traffic requests. We first investigate the effects of optical component developments on waveband switching in WDM networks. Various connection managements are then listed and analyzed. Next, to assist in the designing of efficient WBS algorithms, an autonomous clustering-based HeteroWBS (AS-HeteroWBS) architecture is proposed. The AS-HeteroWBS architecture clusters the network into multiple autonomous systems (ASs). An AS may contain some specific nodes that provide WBS functions for all the nodes in the AS. Based on the architecture, three HeteroWBS algorithms are proposed, namely, the autonomous heterogeneous WBS algorithm (AS-WBS), the autonomous source-limited heterogeneous WBS algorithm (AS-S-WBS), and the shortest-path-based heterogeneous WBS algorithm (SH-WBS). Our simulation results show that the HeteroWBS algorithms can achieve optimal cost savings while maintaining the same network throughput compared with the algorithm without WBS.

  7. Learning a Markov Logic network for supervised gene regulatory network inference

    PubMed Central

    2013-01-01

    Background Gene regulatory network inference remains a challenging problem in systems biology despite the numerous approaches that have been proposed. When substantial knowledge on a gene regulatory network is already available, supervised network inference is appropriate. Such a method builds a binary classifier able to assign a class (Regulation/No regulation) to an ordered pair of genes. Once learnt, the pairwise classifier can be used to predict new regulations. In this work, we explore the framework of Markov Logic Networks (MLN) that combine features of probabilistic graphical models with the expressivity of first-order logic rules. Results We propose to learn a Markov Logic network, e.g. a set of weighted rules that conclude on the predicate “regulates”, starting from a known gene regulatory network involved in the switch proliferation/differentiation of keratinocyte cells, a set of experimental transcriptomic data and various descriptions of genes all encoded into first-order logic. As training data are unbalanced, we use asymmetric bagging to learn a set of MLNs. The prediction of a new regulation can then be obtained by averaging predictions of individual MLNs. As a side contribution, we propose three in silico tests to assess the performance of any pairwise classifier in various network inference tasks on real datasets. A first test consists of measuring the average performance on balanced edge prediction problem; a second one deals with the ability of the classifier, once enhanced by asymmetric bagging, to update a given network. Finally our main result concerns a third test that measures the ability of the method to predict regulations with a new set of genes. As expected, MLN, when provided with only numerical discretized gene expression data, does not perform as well as a pairwise SVM in terms of AUPR. However, when a more complete description of gene properties is provided by heterogeneous sources, MLN achieves the same performance as a black

  8. A Pan-Cancer Modular Regulatory Network Analysis to Identify Common and Cancer-Specific Network Components

    PubMed Central

    Knaack, Sara A; Siahpirani, Alireza Fotuhi; Roy, Sushmita

    2014-01-01

    Many human diseases including cancer are the result of perturbations to transcriptional regulatory networks that control context-specific expression of genes. A comparative approach across multiple cancer types is a powerful approach to illuminate the common and specific network features of this family of diseases. Recent efforts from The Cancer Genome Atlas (TCGA) have generated large collections of functional genomic data sets for multiple types of cancers. An emerging challenge is to devise computational approaches that systematically compare these genomic data sets across different cancer types that identify common and cancer-specific network components. We present a module- and network-based characterization of transcriptional patterns in six different cancers being studied in TCGA: breast, colon, rectal, kidney, ovarian, and endometrial. Our approach uses a recently developed regulatory network reconstruction algorithm, modular regulatory network learning with per gene information (MERLIN), within a stability selection framework to predict regulators for individual genes and gene modules. Our module-based analysis identifies a common theme of immune system processes in each cancer study, with modules statistically enriched for immune response processes as well as targets of key immune response regulators from the interferon regulatory factor (IRF) and signal transducer and activator of transcription (STAT) families. Comparison of the inferred regulatory networks from each cancer type identified a core regulatory network that included genes involved in chromatin remodeling, cell cycle, and immune response. Regulatory network hubs included genes with known roles in specific cancer types as well as genes with potentially novel roles in different cancer types. Overall, our integrated module and network analysis recapitulated known themes in cancer biology and additionally revealed novel regulatory hubs that suggest a complex interplay of immune response, cell

  9. Network-centric MFA tracking architecture based on soft-level data association

    NASA Astrophysics Data System (ADS)

    Novoselov, Roman; Gadaleta, Sabino; Poore, Aubrey

    2005-09-01

    This work presents a new network centric architecture for multiple frame assignment (MFA) tracking. The architecture improves on earlier network tracking schemes by allowing trackers to broadcast decisions about their local soft-level associations, via the Soft Associated Measurement Reports (SAMRs). The SAMR may be followed by an "Oops" message, if the soft association was incorrect and must be revoked. We show, however, that such revocations are very rare in most scenarios. This paper discusses the implementation of the new algorithm and presents simulation results. Considerable improvements in the consistency of the air picture are demonstrated, owing to the the reduced latency in transmission of measurement-to-track associations. The earlier network architectures, namely, the Centralized MFA, the Replicated Centralized MFA, and the Network MFA on Local and All Data, are also discussed in this work, as they form the foundation for the "Oops" algorithm.

  10. Sieve-based relation extraction of gene regulatory networks from biological literature

    PubMed Central

    2015-01-01

    Background Relation extraction is an essential procedure in literature mining. It focuses on extracting semantic relations between parts of text, called mentions. Biomedical literature includes an enormous amount of textual descriptions of biological entities, their interactions and results of related experiments. To extract them in an explicit, computer readable format, these relations were at first extracted manually from databases. Manual curation was later replaced with automatic or semi-automatic tools with natural language processing capabilities. The current challenge is the development of information extraction procedures that can directly infer more complex relational structures, such as gene regulatory networks. Results We develop a computational approach for extraction of gene regulatory networks from textual data. Our method is designed as a sieve-based system and uses linear-chain conditional random fields and rules for relation extraction. With this method we successfully extracted the sporulation gene regulation network in the bacterium Bacillus subtilis for the information extraction challenge at the BioNLP 2013 conference. To enable extraction of distant relations using first-order models, we transform the data into skip-mention sequences. We infer multiple models, each of which is able to extract different relationship types. Following the shared task, we conducted additional analysis using different system settings that resulted in reducing the reconstruction error of bacterial sporulation network from 0.73 to 0.68, measured as the slot error rate between the predicted and the reference network. We observe that all relation extraction sieves contribute to the predictive performance of the proposed approach. Also, features constructed by considering mention words and their prefixes and suffixes are the most important features for higher accuracy of extraction. Analysis of distances between different mention types in the text shows that our choice

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

    NASA Technical Reports Server (NTRS)

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

    1988-01-01

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

  12. An architecture for covert unmanned/unattended network discovery

    NASA Astrophysics Data System (ADS)

    Giallorenzi, Thomas R.; Hyer, Kevin L.; Reeder, W. Bruce; Sylvester, Randal R.

    2005-10-01

    A common problem in modern military communication networks is node discovery. In order to form a robust and efficient network each node needs to notify the network of its existence and, where security policies allow, to report its location. Furthermore, the process of fast and covert new node identification and recognition can help prevent friendly fire incidents. Once a network is established, new nodes often need to join the existing network, and they need a way to do this without compromising their own security, or the security of the network that they are joining. In addition, an established network requires a method of discovering the existence of another disjoint network that has migrated into communication range, so that a cross-link can be established between the networks in order to form a larger network. This process of nodes "discovering" each other is called node discovery, and this provides a capability that has many applications. A good node discovery scheme for military communication related applications has a number of properties including: fast and reliable network entry, covertness, secure and jam proof signaling, and range extension compared to the primary communications link itself. For the purposes of this paper the mechanism that provides node discovery will be called the Discovery Waveform. The Discovery Waveform has many applications such as terminal discovery for wireless communications, node discovery for establishing networking, and seemingly unrelated applications such as bursting time critical data.

  13. SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

    PubMed

    Wright, Adam; Sittig, Dean F

    2008-12-01

    In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are: PMID:18434256

  14. An integrated architecture of adaptive neural network control for dynamic systems

    SciTech Connect

    Ke, Liu; Tokar, R.; Mcvey, B.

    1994-07-01

    In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.

  15. In silico Transcriptional Regulatory Networks Involved in Tomato Fruit Ripening

    PubMed Central

    Arhondakis, Stilianos; Bita, Craita E.; Perrakis, Andreas; Manioudaki, Maria E.; Krokida, Afroditi; Kaloudas, Dimitrios; Kalaitzis, Panagiotis

    2016-01-01

    Tomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs) which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37, and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening. PMID:27625653

  16. In silico Transcriptional Regulatory Networks Involved in Tomato Fruit Ripening.

    PubMed

    Arhondakis, Stilianos; Bita, Craita E; Perrakis, Andreas; Manioudaki, Maria E; Krokida, Afroditi; Kaloudas, Dimitrios; Kalaitzis, Panagiotis

    2016-01-01

    Tomato fruit ripening is a complex developmental programme partly mediated by transcriptional regulatory networks. Several transcription factors (TFs) which are members of gene families such as MADS-box and ERF were shown to play a significant role in ripening through interconnections into an intricate network. The accumulation of large datasets of expression profiles corresponding to different stages of tomato fruit ripening and the availability of bioinformatics tools for their analysis provide an opportunity to identify TFs which might regulate gene clusters with similar co-expression patterns. We identified two TFs, a SlWRKY22-like and a SlER24 transcriptional activator which were shown to regulate modules by using the LeMoNe algorithm for the analysis of our microarray datasets representing four stages of fruit ripening, breaker, turning, pink and red ripe. The WRKY22-like module comprised a subgroup of six various calcium sensing transcripts with similar to the TF expression patterns according to real time PCR validation. A promoter motif search identified a cis acting element, the W-box, recognized by WRKY TFs that was present in the promoter region of all six calcium sensing genes. Moreover, publicly available microarray datasets of similar ripening stages were also analyzed with LeMoNe resulting in TFs such as SlERF.E1, SlERF.C1, SlERF.B2, SLERF.A2, SlWRKY24, SLWRKY37, and MADS-box/TM29 which might also play an important role in regulation of ripening. These results suggest that the SlWRKY22-like might be involved in the coordinated regulation of expression of the six calcium sensing genes. Conclusively the LeMoNe tool might lead to the identification of putative TF targets for further physiological analysis as regulators of tomato fruit ripening. PMID:27625653

  17. Transcriptional regulatory network during development in the olfactory epithelium

    PubMed Central

    Im, SeungYeong; Moon, Cheil

    2015-01-01

    Regeneration, a process of reconstitution of the entire tissue, occurs throughout life in the olfactory epithelium (OE). Regeneration of OE consists of several stages: proliferation of progenitors, cell fate determination between neuronal and non-neuronal lineages, their differentiation and maturation. How the differentiated cell types that comprise the OE are regenerated, is one of the central questions in olfactory developmental neurobiology. The past decade has witnessed considerable progress regarding the regulation of transcription factors (TFs) involved in the remarkable regenerative potential of OE. Here, we review current state of knowledge of the transcriptional regulatory networks that are powerful modulators of the acquisition and maintenance of developmental stages during regeneration in the OE. Advance in our understanding of regeneration will not only shed light on the basic principles of adult plasticity of cell identity, but may also lead to new approaches for using stem cells and reprogramming after injury or degenerative neurological diseases. [BMB Reports 2015; 48(11): 599-608] PMID:26303973

  18. Identification of a gene regulatory network associated with prion replication

    PubMed Central

    Marbiah, Masue M; Harvey, Anna; West, Billy T; Louzolo, Anais; Banerjee, Priya; Alden, Jack; Grigoriadis, Anita; Hummerich, Holger; Kan, Ho-Man; Cai, Ying; Bloom, George S; Jat, Parmjit; Collinge, John; Klöhn, Peter-Christian

    2014-01-01

    Prions consist of aggregates of abnormal conformers of the cellular prion protein (PrPC). They propagate by recruiting host-encoded PrPC although the critical interacting proteins and the reasons for the differences in susceptibility of distinct cell lines and populations are unknown. We derived a lineage of cell lines with markedly differing susceptibilities, unexplained by PrPC expression differences, to identify such factors. Transcriptome analysis of prion-resistant revertants, isolated from highly susceptible cells, revealed a gene expression signature associated with susceptibility and modulated by differentiation. Several of these genes encode proteins with a role in extracellular matrix (ECM) remodelling, a compartment in which disease-related PrP is deposited. Silencing nine of these genes significantly increased susceptibility. Silencing of Papss2 led to undersulphated heparan sulphate and increased PrPC deposition at the ECM, concomitantly with increased prion propagation. Moreover, inhibition of fibronectin 1 binding to integrin α8 by RGD peptide inhibited metalloproteinases (MMP)-2/9 whilst increasing prion propagation. In summary, we have identified a gene regulatory network associated with prion propagation at the ECM and governed by the cellular differentiation state. PMID:24843046

  19. Transcriptional regulatory network shapes the genome structure of Saccharomyces cerevisiae

    PubMed Central

    Li, Songling; Heermann, Dieter W.

    2013-01-01

    Among cellular processes gene transcription is central. More and more evidence is mounting that transcription is tightly connected with the spatial organization of the chromosomes. Spatial proximity of genes sharing transcriptional machinery is one of the consequences of this organization. Motivated by information on the physical relationship among genes identified via chromosomal conformation capture methods, we complement the spatial organization with the idea that genes under similar transcription factor control, but possible scattered throughout the genome, might be in physically proximity to facilitate the access of their commonly used transcription factors. Unlike the transcription factory model, “interacting” genes in our “Gene Proximity Model” are not necessarily immediate physical neighbors but are in spatial proximity. Considering the stochastic nature of TF-promoter binding, this local condensation mechanism could serve as a tie to recruit co-regulated genes to guarantee the swiftness of biological reactions. We tested this idea with a simple eukaryotic organism, Saccharomyces cerevisiae. Chromosomal interaction patterns and folding behavior generated by our model re-construct those obtained from experiments. We show that the transcriptional regulatory network has a close linkage with the genome organization in budding yeast, which is fundamental and instrumental to later studies on other more complex eukaryotes. PMID:23674068

  20. Transcriptional Regulatory Network for the Development of Innate Lymphoid Cells

    PubMed Central

    Zhong, Chao; Zhu, Jinfang

    2015-01-01

    Recent studies on innate lymphoid cells (ILCs) have expanded our knowledge about the innate arm of the immune system. Helper-like ILCs share both the “innate” feature of conventional natural killer (cNK) cells and the “helper” feature of CD4+ T helper (Th) cells. With this combination, helper-like ILCs are capable of initiating early immune responses similar to cNK cells, but via secretion of a set of effector cytokines similar to those produced by Th cells. Although many studies have revealed the functional similarity between helper-like ILCs and Th cells, some aspects of ILCs including the development of this lineage remain elusive. It is intriguing that the majority of transcription factors involved in multiple stages of T cell development, differentiation, and function also play critical roles during ILC development. Regulators such as Id2, GATA-3, Nfil3, TOX, and TCF-1 are expressed and function at various stages of ILC development. In this review, we will summarize the expression and functions of these transcription factors shared by ILCs and Th cells. We will also propose a complex transcriptional regulatory network for the lineage commitment of ILCs. PMID:26379372

  1. A Cluster-Based Architecture to Structure the Topology of Parallel Wireless Sensor Networks

    PubMed Central

    Lloret, Jaime; Garcia, Miguel; Bri, Diana; Diaz, Juan R.

    2009-01-01

    A wireless sensor network is a self-configuring network of mobile nodes connected by wireless links where the nodes have limited capacity and energy. In many cases, the application environment requires the design of an exclusive network topology for a particular case. Cluster-based network developments and proposals in existence have been designed to build a network for just one type of node, where all nodes can communicate with any other nodes in their coverage area. Let us suppose a set of clusters of sensor nodes where each cluster is formed by different types of nodes (e.g., they could be classified by the sensed parameter using different transmitting interfaces, by the node profile or by the type of device: laptops, PDAs, sensor etc.) and exclusive networks, as virtual networks, are needed with the same type of sensed data, or the same type of devices, or even the same type of profiles. In this paper, we propose an algorithm that is able to structure the topology of different wireless sensor networks to coexist in the same environment. It allows control and management of the topology of each network. The architecture operation and the protocol messages will be described. Measurements from a real test-bench will show that the designed protocol has low bandwidth consumption and also demonstrates the viability and the scalability of the proposed architecture. Our ccluster-based algorithm is compared with other algorithms reported in the literature in terms of architecture and protocol measurements. PMID:22303185

  2. Architecture for High Speed Learning of Neural Network using Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Yoshikawa, Masaya; Terai, Hidekazu

    This paper discusses the architecture for high speed learning of Neural Network (NN) using Genetic Algorithm (GA). The proposed architecture prevents local minimum by using the GA characteristic of holding several individual populations for a population-based search and achieves high speed processing adopting dedicated hardware. To keep general purpose equal software processing, the proposed architecture can be flexible genetic operations on GA and is introduced both Sigmoid function and Heaviside function on NN. Furthermore, the proposed architecture is not optimized only the pipeline at evaluation phase on NN, but also optimized hierarchic pipelines on the whole at evolutionary phase. We have done the simulation, verification and logic synthesis using library of 0.35μm CMOS standard cell. Simulation results evaluating the proposed architecture show to achieve 22 times speed on average compared with software processing.

  3. Construction of Gene Regulatory Networks Using Recurrent Neural Networks and Swarm Intelligence

    PubMed Central

    Khan, Abhinandan; Mandal, Sudip; Pal, Rajat Kumar; Saha, Goutam

    2016-01-01

    We have proposed a methodology for the reverse engineering of biologically plausible gene regulatory networks from temporal genetic expression data. We have used established information and the fundamental mathematical theory for this purpose. We have employed the Recurrent Neural Network formalism to extract the underlying dynamics present in the time series expression data accurately. We have introduced a new hybrid swarm intelligence framework for the accurate training of the model parameters. The proposed methodology has been first applied to a small artificial network, and the results obtained suggest that it can produce the best results available in the contemporary literature, to the best of our knowledge. Subsequently, we have implemented our proposed framework on experimental (in vivo) datasets. Finally, we have investigated two medium sized genetic networks (in silico) extracted from GeneNetWeaver, to understand how the proposed algorithm scales up with network size. Additionally, we have implemented our proposed algorithm with half the number of time points. The results indicate that a reduction of 50% in the number of time points does not have an effect on the accuracy of the proposed methodology significantly, with a maximum of just over 15% deterioration in the worst case. PMID:27298752

  4. Data- and knowledge-based modeling of gene regulatory networks: an update

    PubMed Central

    Linde, Jörg; Schulze, Sylvie; Henkel, Sebastian G.; Guthke, Reinhard

    2015-01-01

    Gene regulatory network inference is a systems biology approach which predicts interactions between genes with the help of high-throughput data. In this review, we present current and updated network inference methods focusing on novel techniques for data acquisition, network inference assessment, network inference for interacting species and the integration of prior knowledge. After the advance of Next-Generation-Sequencing of cDNAs derived from RNA samples (RNA-Seq) we discuss in detail its application to network inference. Furthermore, we present progress for large-scale or even full-genomic network inference as well as for small-scale condensed network inference and review advances in the evaluation of network inference methods by crowdsourcing. Finally, we reflect the current availability of data and prior knowledge sources and give an outlook for the inference of gene regulatory networks that reflect interacting species, in particular pathogen-host interactions. PMID:27047314

  5. The architecture of dynamic reservoir in the echo state network

    NASA Astrophysics Data System (ADS)

    Cui, Hongyan; Liu, Xiang; Li, Lixiang

    2012-09-01

    Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.

  6. The architecture of dynamic reservoir in the echo state network.

    PubMed

    Cui, Hongyan; Liu, Xiang; Li, Lixiang

    2012-09-01

    Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities. PMID:23020466

  7. A Study of Artificial Neural Network Architectures for Othello Evaluation Functions

    NASA Astrophysics Data System (ADS)

    Binkley, Kevin J.; Seehart, Ken; Hagiwara, Masafumi

    In this study, we use temporal difference learning (TDL) to investigate the ability of 20 different artificial neural network (ANN) architectures to learn othello game board evaluation functions. The ANN evaluation functions are applied to create a strong othello player using only 1-ply search. In addition to comparing many of the ANN architectures seen in the literature, we introduce several new architectures that consider the game board symmetry. Both embedding the game board symmetry into the network architecture through weight sharing and the outright removal of symmetry through symmetry removal are explored. Experiments varying the number of inputs per game board square from one to three, the number of hidden nodes, and number of hidden layers are also performed. We found it advantageous to consider game board symmetry in the form of symmetry by weight sharing; and that an input encoding of three inputs per square outperformed the one input per square encoding that is commonly seen in the literature. Furthermore, architectures with only one hidden layer were strongly outperformed by architectures with multiple hidden layers. A standard weighted-square board heuristic evaluation function from the literature was used to evaluate the quality of the trained ANN othello players. One of the ANN architectures introduced in this study, an ANN implementing weight sharing and consisting of three hidden layers, using only a 1-ply search, outperformed a weighted-square test heuristic player using a 6-ply minimax search.

  8. Utilising eduroam[TM] Architecture in Building Wireless Community Networks

    ERIC Educational Resources Information Center

    Huhtanen, Karri; Vatiainen, Heikki; Keski-Kasari, Sami; Harju, Jarmo

    2008-01-01

    Purpose: eduroam[TM] has already been proved to be a scalable, secure and feasible way for universities and research institutions to connect their wireless networks into a WLAN roaming community, but the advantages of eduroam[TM] have not yet been fully discovered in the wireless community networks aimed at regular consumers. This aim of this…

  9. The regulatory network of E. coli metabolism as a Boolean dynamical system exhibits both homeostasis and flexibility of response

    PubMed Central

    Samal, Areejit; Jain, Sanjay

    2008-01-01

    Background Elucidating the architecture and dynamics of large scale genetic regulatory networks of cells is an important goal in systems biology. We study the system level dynamical properties of the genetic network of Escherichia coli that regulates its metabolism, and show how its design leads to biologically useful cellular properties. Our study uses the database (Covert et al., Nature 2004) containing 583 genes and 96 external metabolites which describes not only the network connections but also the Boolean rule at each gene node that controls the switching on or off of the gene as a function of its inputs. Results We have studied how the attractors of the Boolean dynamical system constructed from this database depend on the initial condition of the genes and on various environmental conditions corresponding to buffered minimal media. We find that the system exhibits homeostasis in that its attractors, that turn out to be fixed points or low period cycles, are highly insensitive to initial conditions or perturbations of gene configurations for any given fixed environment. At the same time the attractors show a wide variation when external media are varied implying that the system mounts a highly flexible response to changed environmental conditions. The regulatory dynamics acts to enhance the cellular growth rate under changed media. Conclusion Our study shows that the reconstructed genetic network regulating metabolism in E. coli is hierarchical, modular, and largely acyclic, with environmental variables controlling the root of the hierarchy. This architecture makes the cell highly robust to perturbations of gene configurations as well as highly responsive to environmental changes. The twin properties of homeostasis and response flexibility are achieved by this dynamical system even though it is not close to the edge of chaos. PMID:18312613

  10. Network-Attached Solid-State Recorder Architecture

    NASA Technical Reports Server (NTRS)

    Cox, Brian

    2008-01-01

    A document discusses placing memory modules on the high-speed serial interconnect, which is used by a spacecraft s computer elements for inter-processor communications, to allow all multiple computer system architectures to access the spacecraft data storage at the same time. Each memory board is identical electrically and receives its bus ID upon connection to the system. The computer elements are configured in a similar fashion. The architecture allows for multiple memory boards to be accessed simultaneously by different computer elements, and results in a scalable, strong, fault-tolerant system. The IEEE-1393 ring bus can be routed so that multiple card failures can occur and the mass memory storage will still function.

  11. Experiments on neural network architectures for fuzzy logic

    NASA Technical Reports Server (NTRS)

    Keller, James M.

    1991-01-01

    The use of fuzzy logic to model and manage uncertainty in a rule-based system places high computational demands on an inference engine. In an earlier paper, the authors introduced a trainable neural network structure for fuzzy logic. These networks can learn and extrapolate complex relationships between possibility distributions for the antecedents and consequents in the rules. Here, the power of these networks is further explored. The insensitivity of the output to noisy input distributions (which are likely if the clauses are generated from real data) is demonstrated as well as the ability of the networks to internalize multiple conjunctive clause and disjunctive clause rules. Since different rules with the same variables can be encoded in a single network, this approach to fuzzy logic inference provides a natural mechanism for rule conflict resolution.

  12. Regulatory module network of basic/helix-loop-helix transcription factors in mouse brain

    PubMed Central

    Li, Jing; Liu, Zijing J; Pan, Yuchun C; Liu, Qi; Fu, Xing; Cooper, Nigel GF; Li, Yixue; Qiu, Mengsheng; Shi, Tieliu

    2007-01-01

    Background The basic/helix-loop-helix (bHLH) proteins are important components of the transcriptional regulatory network, controlling a variety of biological processes, especially the development of the central nervous system. Until now, reports describing the regulatory network of the bHLH transcription factor (TF) family have been scarce. In order to understand the regulatory mechanisms of bHLH TFs in mouse brain, we inferred their regulatory network from genome-wide gene expression profiles with the module networks method. Results A regulatory network comprising 15 important bHLH TFs and 153 target genes was constructed. The network was divided into 28 modules based on expression profiles. A regulatory-motif search shows the complexity and diversity of the network. In addition, 26 cooperative bHLH TF pairs were also detected in the network. This cooperation suggests possible physical interactions or genetic regulation between TFs. Interestingly, some TFs in the network regulate more than one module. A novel cross-repression between Neurod6 and Hey2 was identified, which may control various functions in different brain regions. The presence of TF binding sites (TFBSs) in the promoter regions of their target genes validates more than 70% of TF-target gene pairs of the network. Literature mining provides additional support for five modules. More importantly, the regulatory relationships among selected key components are all validated in mutant mice. Conclusion Our network is reliable and very informative for understanding the role of bHLH TFs in mouse brain development and function. It provides a framework for future experimental analyses. PMID:18021424

  13. Shadow Enhancers Are Pervasive Features of Developmental Regulatory Networks

    PubMed Central

    Cannavò, Enrico; Khoueiry, Pierre; Garfield, David A.; Geeleher, Paul; Zichner, Thomas; Gustafson, E. Hilary; Ciglar, Lucia; Korbel, Jan O.; Furlong, Eileen E.M.

    2016-01-01

    Summary Embryogenesis is remarkably robust to segregating mutations and environmental variation; under a range of conditions, embryos of a given species develop into stereotypically patterned organisms. Such robustness is thought to be conferred, in part, through elements within regulatory networks that perform similar, redundant tasks. Redundant enhancers (or “shadow” enhancers), for example, can confer precision and robustness to gene expression, at least at individual, well-studied loci. However, the extent to which enhancer redundancy exists and can thereby have a major impact on developmental robustness remains unknown. Here, we systematically assessed this, identifying over 1,000 predicted shadow enhancers during Drosophila mesoderm development. The activity of 23 elements, associated with five genes, was examined in transgenic embryos, while natural structural variation among individuals was used to assess their ability to buffer against genetic variation. Our results reveal three clear properties of enhancer redundancy within developmental systems. First, it is much more pervasive than previously anticipated, with 64% of loci examined having shadow enhancers. Their spatial redundancy is often partial in nature, while the non-overlapping function may explain why these enhancers are maintained within a population. Second, over 70% of loci do not follow the simple situation of having only two shadow enhancers—often there are three (rols), four (CadN and ade5), or five (Traf1), at least one of which can be deleted with no obvious phenotypic effects. Third, although shadow enhancers can buffer variation, patterns of segregating variation suggest that they play a more complex role in development than generally considered. PMID:26687625

  14. Shadow Enhancers Are Pervasive Features of Developmental Regulatory Networks.

    PubMed

    Cannavò, Enrico; Khoueiry, Pierre; Garfield, David A; Geeleher, Paul; Zichner, Thomas; Gustafson, E Hilary; Ciglar, Lucia; Korbel, Jan O; Furlong, Eileen E M

    2016-01-11

    Embryogenesis is remarkably robust to segregating mutations and environmental variation; under a range of conditions, embryos of a given species develop into stereotypically patterned organisms. Such robustness is thought to be conferred, in part, through elements within regulatory networks that perform similar, redundant tasks. Redundant enhancers (or "shadow" enhancers), for example, can confer precision and robustness to gene expression, at least at individual, well-studied loci. However, the extent to which enhancer redundancy exists and can thereby have a major impact on developmental robustness remains unknown. Here, we systematically assessed this, identifying over 1,000 predicted shadow enhancers during Drosophila mesoderm development. The activity of 23 elements, associated with five genes, was examined in transgenic embryos, while natural structural variation among individuals was used to assess their ability to buffer against genetic variation. Our results reveal three clear properties of enhancer redundancy within developmental systems. First, it is much more pervasive than previously anticipated, with 64% of loci examined having shadow enhancers. Their spatial redundancy is often partial in nature, while the non-overlapping function may explain why these enhancers are maintained within a population. Second, over 70% of loci do not follow the simple situation of having only two shadow enhancers-often there are three (rols), four (CadN and ade5), or five (Traf1), at least one of which can be deleted with no obvious phenotypic effects. Third, although shadow enhancers can buffer variation, patterns of segregating variation suggest that they play a more complex role in development than generally considered. PMID:26687625

  15. An Architectural Concept for Intrusion Tolerance in Air Traffic Networks

    NASA Technical Reports Server (NTRS)

    Maddalon, Jeffrey M.; Miner, Paul S.

    2003-01-01

    The goal of an intrusion tolerant network is to continue to provide predictable and reliable communication in the presence of a limited num ber of compromised network components. The behavior of a compromised network component ranges from a node that no longer responds to a nod e that is under the control of a malicious entity that is actively tr ying to cause other nodes to fail. Most current data communication ne tworks do not include support for tolerating unconstrained misbehavio r of components in the network. However, the fault tolerance communit y has developed protocols that provide both predictable and reliable communication in the presence of the worst possible behavior of a limited number of nodes in the system. One may view a malicious entity in a communication network as a node that has failed and is behaving in an arbitrary manner. NASA/Langley Research Center has developed one such fault-tolerant computing platform called SPIDER (Scalable Proces sor-Independent Design for Electromagnetic Resilience). The protocols and interconnection mechanisms of SPIDER may be adapted to large-sca le, distributed communication networks such as would be required for future Air Traffic Management systems. The predictability and reliabi lity guarantees provided by the SPIDER protocols have been formally v erified. This analysis can be readily adapted to similar network stru ctures.

  16. A Novel Approach to Noise-Filtering Based on a Gain-Scheduling Neural Network Architecture

    NASA Technical Reports Server (NTRS)

    Troudet, T.; Merrill, W.

    1994-01-01

    A gain-scheduling neural network architecture is proposed to enhance the noise-filtering efficiency of feedforward neural networks, in terms of both nominal performance and robustness. The synergistic benefits of the proposed architecture are demonstrated and discussed in the context of the noise-filtering of signals that are typically encountered in aerospace control systems. The synthesis of such a gain-scheduled neurofiltering provides the robustness of linear filtering, while preserving the nominal performance advantage of conventional nonlinear neurofiltering. Quantitative performance and robustness evaluations are provided for the signal processing of pitch rate responses to typical pilot command inputs for a modern fighter aircraft model.

  17. Discrete dynamical system modelling for gene regulatory networks of 5-hydroxymethylfural tolerance for ethanologenic yeast

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Composed of linear difference equations, a discrete dynamic system model was designed to reconstruct transcriptional regulations in gene regulatory networks in response to 5-hydroxymethylfurfural, a bioethanol conversion inhibitor for ethanologenic yeast Saccharomyces cerevisiae. The modeling aims ...

  18. Architectural Design for the Global Legal Information Network

    NASA Technical Reports Server (NTRS)

    Kalpakis, Konstantinos

    1999-01-01

    In this report, we provide a summary of our activities regarding the goals, requirements analysis, design, and prototype implementation for the Global Legal Information Network, a joint effort between the Law Library of Congress and NASA.

  19. Quantum cryptography on multi-user network architectures

    NASA Astrophysics Data System (ADS)

    Kumavor, Patrick D.; Beal, Alan C.; Yelin, Susanne; Donkor, Eric; Wang, Bing C.

    2006-05-01

    Quantum cryptography applies the uncertainty principle and the no-cloning theorem to allow to parties to share a secret key over an ultra-secure link. Present quantum cryptography technologies provide encryption key distribution only between two users. However, practical implementations of encryption key distribution schemes require establishing secure quantum communications amongst multiple users. This paper looks at some of the advantages and drawbacks of some common network topologies that could be used in sending cryptographic keys across a network consisting of multiple users. These topologies are the star, ring, and bus networks. Their performances are compared and analyzed using quantum bit error rate analysis. The paper also presents an experimental demonstration of a six-user quantum key distribution network implemented on a bus topology.

  20. RNA regulatory networks diversified through curvature of the PUF protein scaffold

    PubMed Central

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P.; Nevil, Markus; Campbell, Zachary T.; Tanaka Hall, Traci M.; Wickens, Marvin

    2015-01-01

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p–RNA complexes reveal that the protein scaffold presents an exceptionally flat and extended interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks. PMID:26364903

  1. RNA regulatory networks diversified through curvature of the PUF protein scaffold

    SciTech Connect

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P.; Nevil, Markus; Campbell, Zachary T.; Tanaka Hall, Traci M.; Wickens, Marvin

    2015-09-14

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p–RNA complexes reveal that the protein scaffold presents an exceptionally flat and extended interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks.

  2. RNA regulatory networks diversified through curvature of the PUF protein scaffold

    DOE PAGESBeta

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P.; Nevil, Markus; Campbell, Zachary T.; Tanaka Hall, Traci M.; Wickens, Marvin

    2015-09-14

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p–RNA complexes reveal that the protein scaffold presents an exceptionally flat and extendedmore » interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks.« less

  3. RNA regulatory networks diversified through curvature of the PUF protein scaffold.

    PubMed

    Wilinski, Daniel; Qiu, Chen; Lapointe, Christopher P; Nevil, Markus; Campbell, Zachary T; Tanaka Hall, Traci M; Wickens, Marvin

    2015-01-01

    Proteins bind and control mRNAs, directing their localization, translation and stability. Members of the PUF family of RNA-binding proteins control multiple mRNAs in a single cell, and play key roles in development, stem cell maintenance and memory formation. Here we identified the mRNA targets of a S. cerevisiae PUF protein, Puf5p, by ultraviolet-crosslinking-affinity purification and high-throughput sequencing (HITS-CLIP). The binding sites recognized by Puf5p are diverse, with variable spacer lengths between two specific sequences. Each length of site correlates with a distinct biological function. Crystal structures of Puf5p-RNA complexes reveal that the protein scaffold presents an exceptionally flat and extended interaction surface relative to other PUF proteins. In complexes with RNAs of different lengths, the protein is unchanged. A single PUF protein repeat is sufficient to induce broadening of specificity. Changes in protein architecture, such as alterations in curvature, may lead to evolution of mRNA regulatory networks. PMID:26364903

  4. Harnessing Diversity towards the Reconstructing of Large Scale Gene Regulatory Networks

    PubMed Central

    Yamanaka, Ryota; Kitano, Hiroaki

    2013-01-01

    Elucidating gene regulatory network (GRN) from large scale experimental data remains a central challenge in systems biology. Recently, numerous techniques, particularly consensus driven approaches combining different algorithms, have become a potentially promising strategy to infer accurate GRNs. Here, we develop a novel consensus inference algorithm, TopkNet that can integrate multiple algorithms to infer GRNs. Comprehensive performance benchmarking on a cloud computing framework demonstrated that (i) a simple strategy to combine many algorithms does not always lead to performance improvement compared to the cost of consensus and (ii) TopkNet integrating only high-performance algorithms provide significant performance improvement compared to the best individual algorithms and community prediction. These results suggest that a priori determination of high-performance algorithms is a key to reconstruct an unknown regulatory network. Similarity among gene-expression datasets can be useful to determine potential optimal algorithms for reconstruction of unknown regulatory networks, i.e., if expression-data associated with known regulatory network is similar to that with unknown regulatory network, optimal algorithms determined for the known regulatory network can be repurposed to infer the unknown regulatory network. Based on this observation, we developed a quantitative measure of similarity among gene-expression datasets and demonstrated that, if similarity between the two expression datasets is high, TopkNet integrating algorithms that are optimal for known dataset perform well on the unknown dataset. The consensus framework, TopkNet, together with the similarity measure proposed in this study provides a powerful strategy towards harnessing the wisdom of the crowds in reconstruction of unknown regulatory networks. PMID:24278007

  5. Robustness in Regulatory Interaction Networks. A Generic Approach with Applications at Different Levels: Physiologic, Metabolic and Genetic

    PubMed Central

    Demongeot, Jacques; Ben Amor, Hedi; Elena, Adrien; Gillois, Pierre; Noual, Mathilde; Sené, Sylvain

    2009-01-01

    Regulatory interaction networks are often studied on their dynamical side (existence of attractors, study of their stability). We focus here also on their robustness, that is their ability to offer the same spatiotemporal patterns and to resist to external perturbations such as losses of nodes or edges in the networks interactions architecture, changes in their environmental boundary conditions as well as changes in the update schedule (or updating mode) of the states of their elements (e.g., if these elements are genes, their synchronous coexpression mode versus their sequential expression). We define the generic notions of boundary, core, and critical vertex or edge of the underlying interaction graph of the regulatory network, whose disappearance causes dramatic changes in the number and nature of attractors (e.g., passage from a bistable behaviour to a unique periodic regime) or in the range of their basins of stability. The dynamic transition of states will be presented in the framework of threshold Boolean automata rules. A panorama of applications at different levels will be given: brain and plant morphogenesis, bulbar cardio-respiratory regulation, glycolytic/oxidative metabolic coupling, and eventually cell cycle and feather morphogenesis genetic control. PMID:20057955

  6. A Highly Coupled Network of Tertiary Interactions in the SAM-I Riboswitch and Their Role in Regulatory Tuning.

    PubMed

    Wostenberg, Christopher; Ceres, Pablo; Polaski, Jacob T; Batey, Robert T

    2015-11-01

    RNA folding in vivo is significantly influenced by transcription, which is not necessarily recapitulated by Mg(2+)-induced folding of the corresponding full-length RNA in vitro. Riboswitches that regulate gene expression at the transcriptional level are an ideal system for investigating this aspect of RNA folding as ligand-dependent termination is obligatorily co-transcriptional, providing a clear readout of the folding outcome. The folding of representative members of the SAM-I family of riboswitches has been extensively analyzed using approaches focusing almost exclusively upon Mg(2+) and/or S-adenosylmethionine (SAM)-induced folding of full-length transcripts of the ligand binding domain. To relate these findings to co-transcriptional regulatory activity, we have investigated a set of structure-guided mutations of conserved tertiary architectural elements of the ligand binding domain using an in vitro single-turnover transcriptional termination assay, complemented with phylogenetic analysis and isothermal titration calorimetry data. This analysis revealed a conserved internal loop adjacent to the SAM binding site that significantly affects ligand binding and regulatory activity. Conversely, most single point mutations throughout key conserved features in peripheral tertiary architecture supporting the SAM binding pocket have relatively little impact on riboswitch activity. Instead, a secondary structural element in the peripheral subdomain appears to be the key determinant in observed differences in regulatory properties across the SAM-I family. These data reveal a highly coupled network of tertiary interactions that promote high-fidelity co-transcriptional folding of the riboswitch but are only indirectly linked to regulatory tuning. PMID:26343759

  7. Form and function in gene regulatory networks: the structure of network motifs determines fundamental properties of their dynamical state space

    PubMed Central

    Ahnert, S. E.; Fink, T. M. A.

    2016-01-01

    Network motifs have been studied extensively over the past decade, and certain motifs, such as the feed-forward loop, play an important role in regulatory networks. Recent studies have used Boolean network motifs to explore the link between form and function in gene regulatory networks and have found that the structure of a motif does not strongly determine its function, if this is defined in terms of the gene expression patterns the motif can produce. Here, we offer a different, higher-level definition of the ‘function’ of a motif, in terms of two fundamental properties of its dynamical state space as a Boolean network. One is the basin entropy, which is a complexity measure of the dynamics of Boolean networks. The other is the diversity of cyclic attractor lengths that a given motif can produce. Using these two measures, we examine all 104 topologically distinct three-node motifs and show that the structural properties of a motif, such as the presence of feedback loops and feed-forward loops, predict fundamental characteristics of its dynamical state space, which in turn determine aspects of its functional versatility. We also show that these higher-level properties have a direct bearing on real regulatory networks, as both basin entropy and cycle length diversity show a close correspondence with the prevalence, in neural and genetic regulatory networks, of the 13 connected motifs without self-interactions that have been studied extensively in the literature. PMID:27440255

  8. Gene regulatory networks and developmental plasticity in the early sea urchin embryo: alternative deployment of the skeletogenic gene regulatory network.

    PubMed

    Ettensohn, Charles A; Kitazawa, Chisato; Cheers, Melani S; Leonard, Jennifer D; Sharma, Tara

    2007-09-01

    Cell fates in the sea urchin embryo are remarkably labile, despite the fact that maternal polarity and zygotic programs of differential gene expression pattern the embryo from the earliest stages. Recent work has focused on transcriptional gene regulatory networks (GRNs) deployed in specific embryonic territories during early development. The micromere-primary mesenchyme cell (PMC) GRN drives the development of the embryonic skeleton. Although normally deployed only by presumptive PMCs, every lineage of the early embryo has the potential to activate this pathway. Here, we focus on one striking example of regulative activation of the skeletogenic GRN; the transfating of non-skeletogenic mesoderm (NSM) cells to a PMC fate during gastrulation. We show that transfating is accompanied by the de novo expression of terminal, biomineralization-related genes in the PMC GRN, as well as genes encoding two upstream transcription factors, Lvalx1 and Lvtbr. We report that Lvalx1, a key component of the skeletogenic GRN in the PMC lineage, plays an essential role in the regulative pathway both in NSM cells and in animal blastomeres. MAPK signaling is required for the expression of Lvalx1 and downstream skeletogenic genes in NSM cells, mirroring its role in the PMC lineage. We also demonstrate that Lvalx1 regulates the signal from PMCs that normally suppresses NSM transfating. Significantly, misexpression of Lvalx1 in macromeres (the progenitors of NSM cells) is sufficient to activate the skeletogenic GRN. We suggest that NSM cells normally deploy a basal mesodermal pathway and require only an Lvalx1-mediated sub-program to express a PMC fate. Finally, we provide evidence that, in contrast to the normal pathway, activation of the skeletogenic GRN in NSM cells is independent of Lvpmar1. Our studies reveal that, although most features of the micromere-PMC GRN are recapitulated in transfating NSM cells, different inputs activate this GRN during normal and regulative development. PMID

  9. Using consensus bayesian network to model the reactive oxygen species regulatory pathway.

    PubMed

    Hu, Liangdong; Wang, Limin

    2013-01-01

    Bayesian network is one of the most successful graph models for representing the reactive oxygen species regulatory pathway. With the increasing number of microarray measurements, it is possible to construct the bayesian network from microarray data directly. Although large numbers of bayesian network learning algorithms have been developed, when applying them to learn bayesian networks from microarray data, the accuracies are low due to that the databases they used to learn bayesian networks contain too few microarray data. In this paper, we propose a consensus bayesian network which is constructed by combining bayesian networks from relevant literatures and bayesian networks learned from microarray data. It would have a higher accuracy than the bayesian networks learned from one database. In the experiment, we validated the bayesian network combination algorithm on several classic machine learning databases and used the consensus bayesian network to model the Escherichia coli's ROS pathway. PMID:23457624

  10. SANDS: A Service-Oriented Architecture for Clinical Decision Support in a National Health Information Network

    PubMed Central

    Wright, Adam; Sittig, Dean F.

    2008-01-01

    In this paper we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. PMID:18434256

  11. Genes and networks regulating root anatomy and architecture.

    PubMed

    Wachsman, Guy; Sparks, Erin E; Benfey, Philip N

    2015-10-01

    The root is an excellent model for studying developmental processes that underlie plant anatomy and architecture. Its modular structure, the lack of cell movement and relative accessibility to microscopic visualization facilitate research in a number of areas of plant biology. In this review, we describe several examples that demonstrate how cell type-specific developmental mechanisms determine cell fate and the formation of defined tissues with unique characteristics. In the last 10 yr, advances in genome-wide technologies have led to the sequencing of thousands of plant genomes, transcriptomes and proteomes. In parallel with the development of these high-throughput technologies, biologists have had to establish computational, statistical and bioinformatic tools that can deal with the wealth of data generated by them. These resources provide a foundation for posing more complex questions about molecular interactions, and have led to the discovery of new mechanisms that control phenotypic differences. Here we review several recent studies that shed new light on developmental processes, which are involved in establishing root anatomy and architecture. We highlight the power of combining large-scale experiments with classical techniques to uncover new pathways in root development. PMID:25989832

  12. Advancing Reversible Shape Memory by Tuning Network Architecture

    NASA Astrophysics Data System (ADS)

    Li, Qiaoxi; Zhou, Jing; Vatankhah Varnosfaderani, Mohammad; Nykypanchuk, Dmytro; Gang, Oleg; Sheiko, Sergei; University of north carolina at chapel hill Collaboration; Brookhaven National Lab-CFN Collaboration

    Recently, reversible shape memory (RSM) has been realized in conventional semi-crystalline elastomers without applying any external force and synthetic programming. The mechanism is ascribed to counteraction between thermodynamically driven relaxation of a strained polymer network and kinetically preferred self-seeding recrystallization of constrained network strands. In order to maximize RSM's performance in terms of (i) range of reversible strain, (ii) rate of strain recovery, and (iii) relaxation time of reversibility, we have designed a systematic series of networks with different topologies and crosslinking densities, including purposely introduced dangling chains and irregular meshes. Within a broad range of crosslink density ca. 50-1000 mol/m3, we have demonstrated that the RSM's properties improve significantly with increasing crosslink density, regardless of network topology. Actually, one of the most irregular networks with densest crosslinking allowed achieving up to 80% of the programmed strain being fully reversible, fast recovery rate up to 0.05 K-1, and less than 15% decrease of reversibility after hours of annealing at partial melt state. With this understanding and optimization of RSM, we pursue an idea of shape control through self-assembly of shape-memory particles. For this purpose, 3D printing has been employed to prepare large assemblies of particles possessing specific shapes and morphologies.

  13. Self-growing neural network architecture using crisp and fuzzy entropy

    NASA Technical Reports Server (NTRS)

    Cios, Krzysztof J.

    1992-01-01

    The paper briefly describes the self-growing neural network algorithm, CID3, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results for a real-life recognition problem of distinguishing defects in a glass ribbon, and for a benchmark problen of telling two spirals apart are shown and discussed.

  14. Self-growing neural network architecture using crisp and fuzzy entropy

    NASA Technical Reports Server (NTRS)

    Cios, Krzysztof J.

    1992-01-01

    The paper briefly describes the self-growing neural network algorithm, CID2, which makes decision trees equivalent to hidden layers of a neural network. The algorithm generates a feedforward architecture using crisp and fuzzy entropy measures. The results of a real-life recognition problem of distinguishing defects in a glass ribbon and of a benchmark problem of differentiating two spirals are shown and discussed.

  15. Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function.

    PubMed

    Martin, O C; Krzywicki, A; Zagorski, M

    2016-07-01

    Living cells can maintain their internal states, react to changing environments, grow, differentiate, divide, etc. All these processes are tightly controlled by what can be called a regulatory program. The logic of the underlying control can sometimes be guessed at by examining the network of influences amongst genetic components. Some associated gene regulatory networks have been studied in prokaryotes and eukaryotes, unveiling various structural features ranging from broad distributions of out-degrees to recurrent "motifs", that is small subgraphs having a specific pattern of interactions. To understand what factors may be driving such structuring, a number of groups have introduced frameworks to model the dynamics of gene regulatory networks. In that context, we review here such in silico approaches and show how selection for phenotypes, i.e., network function, can shape network structure. PMID:27365153

  16. Drivers of structural features in gene regulatory networks: From biophysical constraints to biological function

    NASA Astrophysics Data System (ADS)

    Martin, O. C.; Krzywicki, A.; Zagorski, M.

    2016-07-01

    Living cells can maintain their internal states, react to changing environments, grow, differentiate, divide, etc. All these processes are tightly controlled by what can be called a regulatory program. The logic of the underlying control can sometimes be guessed at by examining the network of influences amongst genetic components. Some associated gene regulatory networks have been studied in prokaryotes and eukaryotes, unveiling various structural features ranging from broad distributions of out-degrees to recurrent "motifs", that is small subgraphs having a specific pattern of interactions. To understand what factors may be driving such structuring, a number of groups have introduced frameworks to model the dynamics of gene regulatory networks. In that context, we review here such in silico approaches and show how selection for phenotypes, i.e., network function, can shape network structure.

  17. Architectures and economics for pervasive broadband satellite networks

    NASA Technical Reports Server (NTRS)

    Staelin, D. H.; Harvey, R. L.

    1979-01-01

    The size of a satellite network necessary to provide pervasive high-data-rate business communications is estimated, and one possible configuration is described which could interconnect most organizations in the United States. Within an order of magnitude, such a network might reasonably have a capacity equivalent to 10,000 simultaneous 3-Mbps channels, and rely primarily upon a cluster of approximately 3-5 satellites in a single orbital slot. Nominal prices for 3-6 Mbps video conference services might then be approximately $2000 monthly lease charge plus perhaps 70 cents per minute one way.

  18. WDS Knowledge Network Architecture in Support of International Science

    NASA Astrophysics Data System (ADS)

    Mokrane, M.; Minster, J. B. H.; Hugo, W.

    2014-12-01

    ICSU (International Council for Science) created the World Data System (WDS) as an interdisciplinary body at its General Assembly in Maputo in 2008, and since then the membership of the WDS has grown to include 86 members, of whom 56 are institutions or data centers focused on providing quality-assured data and services to the scientific community, and 10 more are entire networks of such data facilities and services. In addition to its objective of providing universal and equitable access to scientific data and services, WDS is also active in promoting stewardship, standards and conventions, and improved access to products derived from data and services. Whereas WDS is in process of aggregating and harmonizing the metadata collections of its membership, it is clear that additional benefits can be obtained by supplementing such traditional metadata sources with information about members, authors, and the coverages of the data, as well as metrics such as citation indices, quality indicators, and usability. Moreover, the relationships between the actors and systems that populate this metadata landscape can be seen as a knowledge network that describes a subset of global scientific endeavor. Such a knowledge network is useful in many ways, supporting both machine-based and human requests for contextual information related to a specific data set, institution, author, topic, or other entities in the network. Specific use cases that can be realized include decision and policy support for funding agencies, identification of collaborators, ranking of data sources, availability of data for specific coverages, and many more. The paper defines the scope of and conceptual background to such a knowledge network, discusses some initial work done by WDS to establish the network, and proposes an implementation model for rapid operationalization. In this model, established interests such as DataCite, ORCID, and CrossRef have well-defined roles, and the standards, services, and

  19. Reconfigurable middleware architectures for large scale sensor networks

    SciTech Connect

    Brennan, Sean M.

    2010-03-01

    Wireless sensor networks, in an e ffort to be energy efficient, typically lack the high-level abstractions of advanced programming languages. Though strong, the dichotomy between these two paradigms can be overcome. The SENSIX software framework, described in this dissertation, uniquely integrates constraint-dominated wireless sensor networks with the flexibility of object-oriented programming models, without violating the principles of either. Though these two computing paradigms are contradictory in many ways, SENSIX bridges them to yield a dynamic middleware abstraction unifying low-level resource-aware task recon figuration and high-level object recomposition.

  20. Phase transition of the microvascular network architecture in human pathologies.

    PubMed

    Bianciardi, Giorgio; Traversi, Claudio; Cattaneo, Ruggero; De Felice, Claudia; Monaco, Annalisa; Tosi, Gianmarco; Parrini, Stefano; Latini, Giuseppe

    2012-01-01

    We have investigated the microvascular pattern in acquired or genetic diseases in humans. The lower gingival and vestibular oral mucosa, as well as the optic nerve head, was chosen to characterize the vascular pattern complexity due to the simple accessibility and visibility Local fractal dimensions, fractal dimension of the minimum path and Lempel-Ziv complexity have been used as operational numerical tools to characterize the microvascular networks. In the normal healthy subjects microvascular networks show nonlinear values corresponding to the complexity of a diffusion limited aggregation (DLA) model, while in several acquired or genetic diseases they are approaching the ones of an invasion percolation model. PMID:23193796

  1. The P-Mesh: A Commodity-based Scalable Network Architecture for Clusters

    NASA Technical Reports Server (NTRS)

    Nitzberg, Bill; Kuszmaul, Chris; Stockdale, Ian; Becker, Jeff; Jiang, John; Wong, Parkson; Tweten, David (Technical Monitor)

    1998-01-01

    We designed a new network architecture, the P-Mesh which combines the scalability and fault resilience of a torus with the performance of a switch. We compare the scalability, performance, and cost of the hub, switch, torus, tree, and P-Mesh architectures. The latter three are capable of scaling to thousands of nodes, however, the torus has severe performance limitations with that many processors. The tree and P-Mesh have similar latency, bandwidth, and bisection bandwidth, but the P-Mesh outperforms the switch architecture (a lower bound for tree performance) on 16-node NAB Parallel Benchmark tests by up to 23%, and costs 40% less. Further, the P-Mesh has better fault resilience characteristics. The P-Mesh architecture trades increased management overhead for lower cost, and is a good bridging technology while the price of tree uplinks is expensive.

  2. Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data

    PubMed Central

    Faria, José P.; Overbeek, Ross; Taylor, Ronald C.; Conrad, Neal; Vonstein, Veronika; Goelzer, Anne; Fromion, Vincent; Rocha, Miguel; Rocha, Isabel; Henry, Christopher S.

    2016-01-01

    We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs, and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches, and small regulatory RNAs. Overall, regulatory information is included in the model for ∼2500 of the ∼4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how ARs for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how ARs can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental

  3. Reconstruction of the Regulatory Network for Bacillus subtilis and Reconciliation with Gene Expression Data.

    PubMed

    Faria, José P; Overbeek, Ross; Taylor, Ronald C; Conrad, Neal; Vonstein, Veronika; Goelzer, Anne; Fromion, Vincent; Rocha, Miguel; Rocha, Isabel; Henry, Christopher S

    2016-01-01

    We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs, and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches, and small regulatory RNAs. Overall, regulatory information is included in the model for ∼2500 of the ∼4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same "ON" and "OFF" gene expression profiles across multiple samples of experimental data. We show how ARs for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how ARs can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions

  4. Evolution of regulatory networks towards adaptability and stability in a changing environment

    NASA Astrophysics Data System (ADS)

    Lee, Deok-Sun

    2014-11-01

    Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

  5. Reverse Engineering of Genome-wide Gene Regulatory Networks from Gene Expression Data

    PubMed Central

    Liu, Zhi-Ping

    2015-01-01

    Transcriptional regulation plays vital roles in many fundamental biological processes. Reverse engineering of genome-wide regulatory networks from high-throughput transcriptomic data provides a promising way to characterize the global scenario of regulatory relationships between regulators and their targets. In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from microarray gene expression profiling data. We overview each of strategies and introduce representative methods respectively. Their assumptions, advantages, shortcomings, and possible improvements and extensions are also clarified and commented. PMID:25937810

  6. An Architecture for Performance Optimization in a Collaborative Knowledge-Based Approach for Wireless Sensor Networks

    PubMed Central

    Gadeo-Martos, Manuel Angel; Fernandez-Prieto, Jose Angel; Canada-Bago, Joaquin; Velasco, Juan Ramon

    2011-01-01

    Over the past few years, Intelligent Spaces (ISs) have received the attention of many Wireless Sensor Network researchers. Recently, several studies have been devoted to identify their common capacities and to set up ISs over these networks. However, little attention has been paid to integrating Fuzzy Rule-Based Systems into collaborative Wireless Sensor Networks for the purpose of implementing ISs. This work presents a distributed architecture proposal for collaborative Fuzzy Rule-Based Systems embedded in Wireless Sensor Networks, which has been designed to optimize the implementation of ISs. This architecture includes the following: (a) an optimized design for the inference engine; (b) a visual interface; (c) a module to reduce the redundancy and complexity of the knowledge bases; (d) a module to evaluate the accuracy of the new knowledge base; (e) a module to adapt the format of the rules to the structure used by the inference engine; and (f) a communications protocol. As a real-world application of this architecture and the proposed methodologies, we show an application to the problem of modeling two plagues of the olive tree: prays (olive moth, Prays oleae Bern.) and repilo (caused by the fungus Spilocaea oleagina). The results show that the architecture presented in this paper significantly decreases the consumption of resources (memory, CPU and battery) without a substantial decrease in the accuracy of the inferred values. PMID:22163687

  7. Signatures of arithmetic simplicity in metabolic network architecture.

    PubMed

    Riehl, William J; Krapivsky, Paul L; Redner, Sidney; Segrè, Daniel

    2010-04-01

    Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity. PMID:20369010

  8. Signatures of Arithmetic Simplicity in Metabolic Network Architecture

    PubMed Central

    Riehl, William J.; Krapivsky, Paul L.; Redner, Sidney; Segrè, Daniel

    2010-01-01

    Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity. PMID:20369010

  9. Shaping Networked Theatre: Experience Architectures, Behaviours and Creative Pedagogies

    ERIC Educational Resources Information Center

    Sutton, Paul

    2012-01-01

    Since 2006 the UK based applied theatre company C&T has been using its experience and expertise in mixing drama, learning and digital media to create a new online utility for shaping collaborative educational drama experiences. C&T describes this practice as "Networked Theatre". This article describes both the motivations for C&T's development of…

  10. Knowledge Network Architecture in Support of International Science

    NASA Astrophysics Data System (ADS)

    Hugo, Wim

    2015-04-01

    ICSU (The International Council for Science) created the World Data System (WDS) as an interdisciplinary body at its General Assembly in Maputo in 2008, and since then the membership of the WDS has grown to include 86 members, of whom 56 are institutions or data centres focused on providing quality-assured data and services to the scientific community. In addition to its objective of providing universal and equitable access to such data and services, WDS is also active in promoting stewardship, standards and conventions, and improved access to products derived from data and services. Whereas WDS is in process of aggregating and harmonizing the meta-data collections of its membership, it is clear that additional benefits can be obtained by supplementing such traditional meta-data sources with information about members, authors, and the coverages of the data, as well as metrics such as citation indices, quality indicators, and usability. Moreover, the relationships between the actors and systems that populate this meta-data landscape can be seen as a knowledge network that describes a sub-set of global scientific endeavor. Such a knowledge network is useful in many ways, supporting both machine-based and human requests for contextual information related to a specific data set, institution, author, topic, or other entities in the network. Specific use cases that can be realised include decision and policy support for funding agencies, identification of collaborators, ranking of data sources, availability of data for specific coverages, and many more. The paper defines the scope of and conceptual background to such a knowledge network, discusses some initial work done by WDS to establish the network, and proposes an implementation model for rapid operationalisation. In this model, established interests such as DataCITE, ORCID, and CrossRef have well-defined roles, and the standards, services, and registries required to build a community-maintained, scalable knowledge

  11. Special Issue on a Fault Tolerant Network on Chip Architecture

    NASA Astrophysics Data System (ADS)

    Janidarmian, Majid; Tinati, Melika; Khademzadeh, Ahmad; Ghavibazou, Maryam; Fekr, Atena Roshan

    2010-06-01

    In this paper a fast and efficient spare switch selection algorithm is presented in a reliable NoC architecture based on specific application mapped onto mesh topology called FERNA. Based on ring concept used in FERNA, this algorithm achieves best results equivalent to exhaustive algorithm with much less run time improving two parameters. Inputs of FERNA algorithm for response time of the system and extra communication cost minimization are derived from simulation of high transaction level using SystemC TLM and mathematical formulation, respectively. The results demonstrate that improvement of above mentioned parameters lead to advance whole system reliability that is analytically calculated. Mapping algorithm has been also investigated as an effective issue on extra bandwidth requirement and system reliability.

  12. The Zebrafish as Model for Deciphering the Regulatory Architecture of Vertebrate Genomes.

    PubMed

    Rastegar, S; Strähle, U

    2016-01-01

    Despite enormous progress to map cis-regulatory modules (CRMs), like enhancers and promoters in genomes, elucidation of the regulatory landscape of the developing embryo remains a challenge. The zebrafish embryo with its experimental virtues has a great potential to contribute to this endeavor. However, so far progress remained behind expectation. We discuss here available methods and their limitations and how the zebrafish embryo could contribute in the future to unravel the wiring of the vertebrate genome. PMID:27503358

  13. The role of genome and gene regulatory network canalization in the evolution of multi-trait polymorphisms and sympatric speciation

    PubMed Central

    2009-01-01

    Background Sexual reproduction has classically been considered as a barrier to the buildup of discrete phenotypic differentiation. This notion has been confirmed by models of sympatric speciation in which a fixed genetic architecture and a linear genotype phenotype mapping were assumed. In this paper we study the influence of a flexible genetic architecture and non-linear genotype phenotype map on differentiation under sexual reproduction. We use an individual based model in which organisms have a genome containing genes and transcription factor binding sites. Mutations involve single genes or binding sites or stretches of genome. The genome codes for a regulatory network that determines the gene expression pattern and hence the phenotype of the organism, resulting in a non-linear genotype phenotype map. The organisms compete in a multi-niche environment, imposing selection for phenotypic differentiation. Results We find as a generic outcome the evolution of discrete clusters of organisms adapted to different niches, despite random mating. Organisms from different clusters are distinct on the genotypic, the network and the phenotypic level. However, the genome and network differences are constrained to a subset of the genome locations, a process we call genotypic canalization. We demonstrate how this canalization leads to an increased robustness to recombination and increasing hybrid fitness. Finally, in case of assortative mating, we explain how this canalization increases the effectiveness of assortativeness. Conclusion We conclude that in case of a flexible genetic architecture and a non-linear genotype phenotype mapping, sexual reproduction does not constrain phenotypic differentiation, but instead constrains the genotypic differences underlying it. We hypothesize that, as genotypic canalization enables differentiation despite random mating and increases the effectiveness of assortative mating, sympatric speciation is more likely than is commonly suggested

  14. Transcription factor-microRNA synergistic regulatory network revealing the mechanism of polycystic ovary syndrome

    PubMed Central

    LIU, HAI-YING; HUANG, YU-LING; LIU, JIAN-QIAO; HUANG, QING

    2016-01-01

    Polycystic ovary syndrome (PCOS) is the most common type of endocrine disorder, affecting 5–11% of women of reproductive age worldwide. Transcription factors (TFs) and microRNAs are considered to have crucial roles in the developmental process of several diseases and have synergistic regulatory actions. However, the effects of TFs and microRNAs, and the patterns of their cooperation in the synergistic regulatory network of PCOS, remain to be elucidated. The present study aimed to determine the possible mechanism of PCOS, based on a TF-microRNA synergistic regulatory network. Initially, the differentially expressed genes (DEGs) in PCOS were identified using microarray data of the GSE34526 dataset. Subsequently, the TFs and microRNAs which regulated the DEGs of PCOS were identified, and a PCOS-associated TF-microRNA synergistic regulatory network was constructed. This network included 195 DEGs, 136 TFs and 283 microRNAs, and the DEGs were regulated by TFs and microRNAs. Based on topological and functional enrichment analyses, SP1, mir-355-5p and JUN were identified as potentially crucial regulators in the development of PCOS and in characterizing the regulatory mechanism. In conclusion, the TF-microRNA synergistic regulatory network constructed in the present study provides novel insight on the molecular mechanism of PCOS in the form of synergistic regulated model. PMID:27035648

  15. Transcription factor‑microRNA synergistic regulatory network revealing the mechanism of polycystic ovary syndrome.

    PubMed

    Liu, Hai-Ying; Huang, Yu-Ling; Liu, Jian-Qiao; Huang, Qing

    2016-05-01

    Polycystic ovary syndrome (PCOS) is the most common type of endocrine disorder, affecting 5‑11% of women of reproductive age worldwide. Transcription factors (TFs) and microRNAs are considered to have crucial roles in the developmental process of several diseases and have synergistic regulatory actions. However, the effects of TFs and microRNAs, and the patterns of their cooperation in the synergistic regulatory network of PCOS, remain to be elucidated. The present study aimed to determine the possible mechanism of PCOS, based on a TF‑microRNA synergistic regulatory network. Initially, the differentially expressed genes (DEGs) in PCOS were identified using microarray data of the GSE34526 dataset. Subsequently, the TFs and microRNAs which regulated the DEGs of PCOS were identified, and a PCOS‑associated TF‑microRNA synergistic regulatory network was constructed. This network included 195 DEGs, 136 TFs and 283 microRNAs, and the DEGs were regulated by TFs and microRNAs. Based on topological and functional enrichment analyses, SP1, mir‑355‑5p and JUN were identified as potentially crucial regulators in the development of PCOS and in characterizing the regulatory mechanism. In conclusion, the TF‑microRNA synergistic regulatory network constructed in the present study provides novel insight on the molecular mechanism of PCOS in the form of synergistic regulated model. PMID:27035648

  16. An experimentally supported model of the Bacillus subtilis global transcriptional regulatory network.

    PubMed

    Arrieta-Ortiz, Mario L; Hafemeister, Christoph; Bate, Ashley Rose; Chu, Timothy; Greenfield, Alex; Shuster, Bentley; Barry, Samantha N; Gallitto, Matthew; Liu, Brian; Kacmarczyk, Thadeous; Santoriello, Francis; Chen, Jie; Rodrigues, Christopher D A; Sato, Tsutomu; Rudner, David Z; Driks, Adam; Bonneau, Richard; Eichenberger, Patrick

    2015-11-01

    Organisms from all domains of life use gene regulation networks to control cell growth, identity, function, and responses to environmental challenges. Although accurate global regulatory models would provide critical evolutionary and functional insights, they remain incomplete, even for the best studied organisms. Efforts to build comprehensive networks are confounded by challenges including network scale, degree of connectivity, complexity of organism-environment interactions, and difficulty of estimating the activity of regulatory factors. Taking advantage of the large number of known regulatory interactions in Bacillus subtilis and two transcriptomics datasets (including one with 38 separate experiments collected specifically for this study), we use a new combination of network component analysis and model selection to simultaneously estimate transcription factor activities and learn a substantially expanded transcriptional regulatory network for this bacterium. In total, we predict 2,258 novel regulatory interactions and recall 74% of the previously known interactions. We obtained experimental support for 391 (out of 635 evaluated) novel regulatory edges (62% accuracy), thus significantly increasing our understanding of various cell processes, such as spore formation. PMID:26577401

  17. Gene regulatory network inference using fused LASSO on multiple data sets

    PubMed Central

    Omranian, Nooshin; Eloundou-Mbebi, Jeanne M. O.; Mueller-Roeber, Bernd; Nikoloski, Zoran

    2016-01-01

    Devising computational methods to accurately reconstruct gene regulatory networks given gene expression data is key to systems biology applications. Here we propose a method for reconstructing gene regulatory networks by simultaneous consideration of data sets from different perturbation experiments and corresponding controls. The method imposes three biologically meaningful constraints: (1) expression levels of each gene should be explained by the expression levels of a small number of transcription factor coding genes, (2) networks inferred from different data sets should be similar with respect to the type and number of regulatory interactions, and (3) relationships between genes which exhibit similar differential behavior over the considered perturbations should be favored. We demonstrate that these constraints can be transformed in a fused LASSO formulation for the proposed method. The comparative analysis on transcriptomics time-series data from prokaryotic species, Escherichia coli and Mycobacterium tuberculosis, as well as a eukaryotic species, mouse, demonstrated that the proposed method has the advantages of the most recent approaches for regulatory network inference, while obtaining better performance and assigning higher scores to the true regulatory links. The study indicates that the combination of sparse regression techniques with other biologically meaningful constraints is a promising framework for gene regulatory network reconstructions. PMID:26864687

  18. Regulatory Aspects of Smart Water Networks in the U.S.

    EPA Science Inventory

    The presentation addresses regulatory aspects of smart water networks in the U.S. It will be presented at the Smart Water Networks Forum (SWAN) annual conference in London, England from April 29-30, 2015. The conference will bring together key voices in the smart water space f...

  19. Intelligent Middle-Ware Architecture for Mobile Networks

    NASA Astrophysics Data System (ADS)

    Rayana, Rayene Ben; Bonnin, Jean-Marie

    Recent advances in electronic and automotive industries as well as in wireless telecommunication technologies have drawn a new picture where each vehicle became “fully networked”. Multiple stake-holders (network operators, drivers, car manufacturers, service providers, etc.) will participate in this emerging market, which could grow following various models. To free the market from technical constraints, it is important to return to the basics of the Internet, i.e., providing embarked devices with a fully operational Internet connectivity (IPv6).

  20. Heritability of the network architecture of intrinsic brain functional connectivity.

    PubMed

    Sinclair, Benjamin; Hansell, Narelle K; Blokland, Gabriëlla A M; Martin, Nicholas G; Thompson, Paul M; Breakspear, Michael; de Zubicaray, Greig I; Wright, Margaret J; McMahon, Katie L

    2015-11-01

    The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23 ± 2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h(2) (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤ 15%), and when global signal regression was implemented, heritability estimates decreased substantially h(2) (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices. PMID:26226088

  1. Inferring gene regulatory networks via nonlinear state-space models and exploiting sparsity.

    PubMed

    Noor, Amina; Serpedin, Erchin; Nounou, Mohamed; Nounou, Hazem N

    2012-01-01

    This paper considers the problem of learning the structure of gene regulatory networks from gene expression time series data. A more realistic scenario when the state space model representing a gene network evolves nonlinearly is considered while a linear model is assumed for the microarray data. To capture the nonlinearity, a particle filter-based state estimation algorithm is considered instead of the contemporary linear approximation-based approaches. The parameters characterizing the regulatory relations among various genes are estimated online using a Kalman filter. Since a particular gene interacts with a few other genes only, the parameter vector is expected to be sparse. The state estimates delivered by the particle filter and the observed microarray data are then subjected to a LASSO-based least squares regression operation which yields a parsimonious and efficient description of the regulatory network by setting the irrelevant coefficients to zero. The performance of the aforementioned algorithm is compared with the extended Kalman filter (EKF) and Unscented Kalman Filter (UKF) employing the Mean Square Error (MSE) as the fidelity criterion in recovering the parameters of gene regulatory networks from synthetic data and real biological data. Extensive computer simulations illustrate that the proposed particle filter-based network inference algorithm outperforms EKF and UKF, and therefore, it can serve as a natural framework for modeling gene regulatory networks with nonlinear and sparse structure. PMID:22350207

  2. Synchronization in heterogeneous FitzHugh-Nagumo networks with hierarchical architecture

    NASA Astrophysics Data System (ADS)

    Plotnikov, S. A.; Lehnert, J.; Fradkov, A. L.; Schöll, E.

    2016-07-01

    We study synchronization in heterogeneous FitzHugh-Nagumo networks. It is well known that heterogeneities in the nodes hinder synchronization when becoming too large. Here we develop a controller to counteract the impact of these heterogeneities. We first analyze the stability of the equilibrium point in a ring network of heterogeneous nodes. We then derive a sufficient condition for synchronization in the absence of control. Based on these results we derive the controller providing synchronization for parameter values where synchronization without control is absent. We demonstrate our results in networks with different topologies. Particular attention is given to hierarchical (fractal) topologies, which are relevant for the architecture of the brain.

  3. Synchronization in heterogeneous FitzHugh-Nagumo networks with hierarchical architecture.

    PubMed

    Plotnikov, S A; Lehnert, J; Fradkov, A L; Schöll, E

    2016-07-01

    We study synchronization in heterogeneous FitzHugh-Nagumo networks. It is well known that heterogeneities in the nodes hinder synchronization when becoming too large. Here we develop a controller to counteract the impact of these heterogeneities. We first analyze the stability of the equilibrium point in a ring network of heterogeneous nodes. We then derive a sufficient condition for synchronization in the absence of control. Based on these results we derive the controller providing synchronization for parameter values where synchronization without control is absent. We demonstrate our results in networks with different topologies. Particular attention is given to hierarchical (fractal) topologies, which are relevant for the architecture of the brain. PMID:27575119

  4. Architectural impact of FDDI network on scheduling hard real-time traffic

    NASA Technical Reports Server (NTRS)

    Agrawal, Gopal; Chen, Baio; Zhao, Wei; Davari, Sadegh

    1991-01-01

    The architectural impact on guaranteeing synchronous message deadlines in FDDI (Fiber Distributed Data Interface) token ring networks is examined. The FDDI network does not have facility to support (global) priority arbitration which is a useful facility for scheduling hard real time activities. As a result, it was found that the worst case utilization of synchronous traffic in an FDDI network can be far less than that in a centralized single processor system. Nevertheless, it is proposed and analyzed that a scheduling method can guarantee deadlines of synchronous messages having traffic utilization up to 33 pct., the highest to date.

  5. Planning assistance for the NASA 30/20 GHz program. Network control architecture study.

    NASA Technical Reports Server (NTRS)

    Inukai, T.; Bonnelycke, B.; Strickland, S.

    1982-01-01

    Network Control Architecture for a 30/20 GHz flight experiment system operating in the Time Division Multiple Access (TDMA) was studied. Architecture development, identification of processing functions, and performance requirements for the Master Control Station (MCS), diversity trunking stations, and Customer Premises Service (CPS) stations are covered. Preliminary hardware and software processing requirements as well as budgetary cost estimates for the network control system are given. For the trunking system control, areas covered include on board SS-TDMA switch organization, frame structure, acquisition and synchronization, channel assignment, fade detection and adaptive power control, on board oscillator control, and terrestrial network timing. For the CPS control, they include on board processing and adaptive forward error correction control.

  6. Architecture-dependent signal conduction in model networks of endothelial cells

    NASA Astrophysics Data System (ADS)

    Deymier, Pierre A.; Eray, Mete; Deymier, Martin J.; Runge, Keith; Hoying, James B.; Vasseur, Jérome O.

    2010-04-01

    Signal conduction between endothelial cells along the walls of vessels appears to play an important role in circulatory function. A recently developed approach to calculate analytically the spectrum of propagating compositional waves in models of multicellular architectures is extended to study putative signal conduction dynamics across networks of endothelial cells. Here, compositional waves originate from negative feedback loops, such as between Ca2+ and inositol triphosphate (IP3) in endothelial cells, and are shaped by their connection topologies. We consider models of networks constituted of a main chain of endothelial cells and multiple side chains. The resulting transmission spectra encode information concerning the position and size of the side branches in the form of gaps. This observation suggests that endothelial cell networks may be able to “communicate” information regarding long-range order in their architecture.

  7. Design and architecture of the Mars relay network planning and analysis framework

    NASA Technical Reports Server (NTRS)

    Cheung, K. M.; Lee, C. H.

    2002-01-01

    In this paper we describe the design and architecture of the Mars Network planning and analysis framework that supports generation and validation of efficient planning and scheduling strategy. The goals are to minimize the transmitting time, minimize the delaying time, and/or maximize the network throughputs. The proposed framework would require (1) a client-server architecture to support interactive, batch, WEB, and distributed analysis and planning applications for the relay network analysis scheme, (2) a high-fidelity modeling and simulation environment that expresses link capabilities between spacecraft to spacecraft and spacecraft to Earth stations as time-varying resources, and spacecraft activities, link priority, Solar System dynamic events, the laws of orbital mechanics, and other limiting factors as spacecraft power and thermal constraints, (3) an optimization methodology that casts the resource and constraint models into a standard linear and nonlinear constrained optimization problem that lends itself to commercial off-the-shelf (COTS)planning and scheduling algorithms.

  8. An Object-Oriented Network-Centric Software Architecture for Physical Computing

    NASA Astrophysics Data System (ADS)

    Palmer, Richard

    1997-08-01

    Recent developments in object-oriented computer languages and infrastructure such as the Internet, Web browsers, and the like provide an opportunity to define a more productive computational environment for scientific programming that is based more closely on the underlying mathematics describing physics than traditional programming languages such as FORTRAN or C++. In this talk I describe an object-oriented software architecture for representing physical problems that includes classes for such common mathematical objects as geometry, boundary conditions, partial differential and integral equations, discretization and numerical solution methods, etc. In practice, a scientific program written using this architecture looks remarkably like the mathematics used to understand the problem, is typically an order of magnitude smaller than traditional FORTRAN or C++ codes, and hence easier to understand, debug, describe, etc. All objects in this architecture are ``network-enabled,'' which means that components of a software solution to a physical problem can be transparently loaded from anywhere on the Internet or other global network. The architecture is expressed as an ``API,'' or application programmers interface specification, with reference embeddings in Java, Python, and C++. A C++ class library for an early version of this API has been implemented for machines ranging from PC's to the IBM SP2, meaning that phidentical codes run on all architectures.

  9. Genetic networks specifying the functional architecture of orientation domains in V1

    NASA Astrophysics Data System (ADS)

    Liedtke, Joscha; Wolf, Fred

    2015-03-01

    Although genetic information is critically important for brain development and structure, it is widely believed that neocortical functional architecture is largely shaped by activity dependent mechanisms. Here we show theoretically that mathematical models of genetic networks of principal neurons interacting by long range axonal morphogen transport can generate morphogen patterns that exactly prescribe the functional architecture of the primary visual cortex (V1) as experimentally observed. We analyze in detail an example genetic network that encodes the functional architecture of V1 by a dynamically generated morphogen pattern. We use analytical methods from weakly non-linear analysis [Cross & Hohenberg 1993] complemented by numerical simulations to obtain solutions of the model. In particular we find that the pinwheel statistics are in quantitative agreement with high precision experimental measurements [Kaschube et al. 2010]. This theory opens a novel perspective on the experimentally observed robustness of V1's architecture against radically abnormal developmental conditions such a dark rearing [White et al. 2001]. Furthermore, it provides for the first time a scheme how the pattern of a complex cortical architecture can be specified using only a small genetic bandwidth.

  10. Anticipated Ethics and Regulatory Challenges in PCORnet: The National Patient-Centered Clinical Research Network.

    PubMed

    Ali, Joseph; Califf, Robert; Sugarman, Jeremy

    2016-01-01

    PCORnet, the National Patient-Centered Clinical Research Network, seeks to establish a robust national health data network for patient-centered comparative effectiveness research. This article reports the results of a PCORnet survey designed to identify the ethics and regulatory challenges anticipated in network implementation. A 12-item online survey was developed by leadership of the PCORnet Ethics and Regulatory Task Force; responses were collected from the 29 PCORnet networks. The most pressing ethics issues identified related to informed consent, patient engagement, privacy and confidentiality, and data sharing. High priority regulatory issues included IRB coordination, privacy and confidentiality, informed consent, and data sharing. Over 150 IRBs and five different approaches to managing multisite IRB review were identified within PCORnet. Further empirical and scholarly work, as well as practical and policy guidance, is essential if important initiatives that rely on comparative effectiveness research are to move forward. PMID:26192996

  11. Modelling and analysis of gene regulatory network using feedback control theory

    NASA Astrophysics Data System (ADS)

    El-Samad, H.; Khammash, M.

    2010-01-01

    Molecular pathways are a part of a remarkable hierarchy of regulatory networks that operate at all levels of organisation. These regulatory networks are responsible for much of the biological complexity within the cell. The dynamic character of these pathways and the prevalence of feedback regulation strategies in their operation make them amenable to systematic mathematical analysis using the same tools that have been used with success in analysing and designing engineering control systems. In this article, we aim at establishing this strong connection through various examples where the behaviour exhibited by gene networks is explained in terms of their underlying control strategies. We complement our analysis by a survey of mathematical techniques commonly used to model gene regulatory networks and analyse their dynamic behaviour.

  12. Community Structure Reveals Biologically Functional Modules in MEF2C Transcriptional Regulatory Network

    PubMed Central

    Alcalá-Corona, Sergio A.; Velázquez-Caldelas, Tadeo E.; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

    2016-01-01

    Gene regulatory networks are useful to understand the activity behind the complex mechanisms in transcriptional regulation. A main goal in contemporary biology is using such networks to understand the systemic regulation of gene expression. In this work, we carried out a systematic study of a transcriptional regulatory network derived from a comprehensive selection of all potential transcription factor interactions downstream from MEF2C, a human transcription factor master regulator. By analyzing the connectivity structure of such network, we were able to find different biologically functional processes and specific biochemical pathways statistically enriched in communities of genes into the network, such processes are related to cell signaling, cell cycle and metabolism. In this way we further support the hypothesis that structural properties of biological networks encode an important part of their functional behavior in eukaryotic cells. PMID:27252657

  13. An ancient yet flexible cis-regulatory architecture allows localized Hedgehog tuning by patched/Ptch1

    PubMed Central

    Lorberbaum, David S; Ramos, Andrea I; Peterson, Kevin A; Carpenter, Brandon S; Parker, David S; De, Sandip; Hillers, Lauren E; Blake, Victoria M; Nishi, Yuichi; McFarlane, Matthew R; Chiang, Ason CY; Kassis, Judith A; Allen, Benjamin L; McMahon, Andrew P; Barolo, Scott

    2016-01-01

    The Hedgehog signaling pathway is part of the ancient developmental-evolutionary animal toolkit. Frequently co-opted to pattern new structures, the pathway is conserved among eumetazoans yet flexible and pleiotropic in its effects. The Hedgehog receptor, Patched, is transcriptionally activated by Hedgehog, providing essential negative feedback in all tissues. Our locus-wide dissections of the cis-regulatory landscapes of fly patched and mouse Ptch1 reveal abundant, diverse enhancers with stage- and tissue-specific expression patterns. The seemingly simple, constitutive Hedgehog response of patched/Ptch1 is driven by a complex regulatory architecture, with batteries of context-specific enhancers engaged in promoter-specific interactions to tune signaling individually in each tissue, without disturbing patterning elsewhere. This structure—one of the oldest cis-regulatory features discovered in animal genomes—explains how patched/Ptch1 can drive dramatic adaptations in animal morphology while maintaining its essential core function. It may also suggest a general model for the evolutionary flexibility of conserved regulators and pathways. DOI: http://dx.doi.org/10.7554/eLife.13550.001 PMID:27146892

  14. Selection Shapes Transcriptional Logic and Regulatory Specialization in Genetic Networks

    PubMed Central

    Fogelmark, Karl; Peterson, Carsten; Troein, Carl

    2016-01-01

    Background Living organisms need to regulate their gene expression in response to environmental signals and internal cues. This is a computational task where genes act as logic gates that connect to form transcriptional networks, which are shaped at all scales by evolution. Large-scale mutations such as gene duplications and deletions add and remove network components, whereas smaller mutations alter the connections between them. Selection determines what mutations are accepted, but its importance for shaping the resulting networks has been debated. Methodology To investigate the effects of selection in the shaping of transcriptional networks, we derive transcriptional logic from a combinatorially powerful yet tractable model of the binding between DNA and transcription factors. By evolving the resulting networks based on their ability to function as either a simple decision system or a circadian clock, we obtain information on the regulation and logic rules encoded in functional transcriptional networks. Comparisons are made between networks evolved for different functions, as well as with structurally equivalent but non-functional (neutrally evolved) networks, and predictions are validated against the transcriptional network of E. coli. Principal Findings We find that the logic rules governing gene expression depend on the function performed by the network. Unlike the decision systems, the circadian clocks show strong cooperative binding and negative regulation, which achieves tight temporal control of gene expression. Furthermore, we find that transcription factors act preferentially as either activators or repressors, both when binding multiple sites for a single target gene and globally in the transcriptional networks. This separation into positive and negative regulators requires gene duplications, which highlights the interplay between mutation and selection in shaping the transcriptional networks. PMID:26927540

  15. Research on mixed network architecture collaborative application model

    NASA Astrophysics Data System (ADS)

    Jing, Changfeng; Zhao, Xi'an; Liang, Song

    2009-10-01

    When facing complex requirements of city development, ever-growing spatial data, rapid development of geographical business and increasing business complexity, collaboration between multiple users and departments is needed urgently, however conventional GIS software (such as Client/Server model or Browser/Server model) are not support this well. Collaborative application is one of the good resolutions. Collaborative application has four main problems to resolve: consistency and co-edit conflict, real-time responsiveness, unconstrained operation, spatial data recoverability. In paper, application model called AMCM is put forward based on agent and multi-level cache. AMCM can be used in mixed network structure and supports distributed collaborative. Agent is an autonomous, interactive, initiative and reactive computing entity in a distributed environment. Agent has been used in many fields such as compute science and automation. Agent brings new methods for cooperation and the access for spatial data. Multi-level cache is a part of full data. It reduces the network load and improves the access and handle of spatial data, especially, in editing the spatial data. With agent technology, we make full use of its characteristics of intelligent for managing the cache and cooperative editing that brings a new method for distributed cooperation and improves the efficiency.

  16. A novel layer 1 virtual private network provisioning architecture in multi-domain optical networks

    NASA Astrophysics Data System (ADS)

    Sun, Ting; Zhang, Jie; Chen, Xiuzhong; Zhao, Yongli; Han, Dahai; Gu, Wanyi; Ji, Yuefeng

    2009-11-01

    A novel multi-domain L1VPN provisioning architecture is proposed based on service plane of the adaptive multiservices provisioning platform. It can provide the inter-domain L1VPN services flexibly, and can establish different L1VPNs by analyzing different service characteristics and constraints. Moreover, the architecture we proposed was experimentally demonstrated in our AMSON testbed.

  17. Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

    PubMed Central

    Zhu, Shijia; Wang, Yadong

    2015-01-01

    Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings. PMID:26680653

  18. Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks

    NASA Astrophysics Data System (ADS)

    Zhu, Shijia; Wang, Yadong

    2015-12-01

    Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is ‘stationarity’, and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings.

  19. Hidden Markov induced Dynamic Bayesian Network for recovering time evolving gene regulatory networks.

    PubMed

    Zhu, Shijia; Wang, Yadong

    2015-01-01

    Dynamic Bayesian Networks (DBN) have been widely used to recover gene regulatory relationships from time-series data in computational systems biology. Its standard assumption is 'stationarity', and therefore, several research efforts have been recently proposed to relax this restriction. However, those methods suffer from three challenges: long running time, low accuracy and reliance on parameter settings. To address these problems, we propose a novel non-stationary DBN model by extending each hidden node of Hidden Markov Model into a DBN (called HMDBN), which properly handles the underlying time-evolving networks. Correspondingly, an improved structural EM algorithm is proposed to learn the HMDBN. It dramatically reduces searching space, thereby substantially improving computational efficiency. Additionally, we derived a novel generalized Bayesian Information Criterion under the non-stationary assumption (called BWBIC), which can help significantly improve the reconstruction accuracy and largely reduce over-fitting. Moreover, the re-estimation formulas for all parameters of our model are derived, enabling us to avoid reliance on parameter settings. Compared to the state-of-the-art methods, the experimental evaluation of our proposed method on both synthetic and real biological data demonstrates more stably high prediction accuracy and significantly improved computation efficiency, even with no prior knowledge and parameter settings. PMID:26680653

  20. Expanding antigen-specific regulatory networks to treat autoimmunity.

    PubMed

    Clemente-Casares, Xavier; Blanco, Jesus; Ambalavanan, Poornima; Yamanouchi, Jun; Singha, Santiswarup; Fandos, Cesar; Tsai, Sue; Wang, Jinguo; Garabatos, Nahir; Izquierdo, Cristina; Agrawal, Smriti; Keough, Michael B; Yong, V Wee; James, Eddie; Moore, Anna; Yang, Yang; Stratmann, Thomas; Serra, Pau; Santamaria, Pere

    2016-02-25

    Regulatory T cells hold promise as targets for therapeutic intervention in autoimmunity, but approaches capable of expanding antigen-specific regulatory T cells in vivo are currently not available. Here we show that systemic delivery of nanoparticles coated with autoimmune-disease-relevant peptides bound to major histocompatibility complex class II (pMHCII) molecules triggers the generation and expansion of antigen-specific regulatory CD4(+) T cell type 1 (TR1)-like cells in different mouse models, including mice humanized with lymphocytes from patients, leading to resolution of established autoimmune phenomena. Ten pMHCII-based nanomedicines show similar biological effects, regardless of genetic background, prevalence of the cognate T-cell population or MHC restriction. These nanomedicines promote the differentiation of disease-primed autoreactive T cells into TR1-like cells, which in turn suppress autoantigen-loaded antigen-presenting cells and drive the differentiation of cognate B cells into disease-suppressing regulatory B cells, without compromising systemic immunity. pMHCII-based nanomedicines thus represent a new class of drugs, potentially useful for treating a broad spectrum of autoimmune conditions in a disease-specific manner. PMID:26886799

  1. Regulatory Enhancements, Infrastructure Modernization, and Connecticut's Interactive, Distance Learning Network.

    ERIC Educational Resources Information Center

    Pietras, Jesse John

    This paper presents an overview of the regulatory, technological, and economic status of interactive distance learning in Connecticut as it relates to the current and future provisioning of services by the telecommunications and cable television industries. The review is predicated upon the following questions: (1) What obligations should the…

  2. Bayesian non-negative factor analysis for reconstructing transcription factor mediated regulatory networks

    PubMed Central

    2011-01-01

    Background Transcriptional regulation by transcription factor (TF) controls the time and abundance of mRNA transcription. Due to the limitation of current proteomics technologies, large scale measurements of protein level activities of TFs is usually infeasible, making computational reconstruction of transcriptional regulatory network a difficult task. Results We proposed here a novel Bayesian non-negative factor model for TF mediated regulatory networks. Particularly, the non-negative TF activities and sample clustering effect are modeled as the factors from a Dirichlet process mixture of rectified Gaussian distributions, and the sparse regulatory coefficients are modeled as the loadings from a sparse distribution that constrains its sparsity using knowledge from database; meantime, a Gibbs sampling solution was developed to infer the underlying network structure and the unknown TF activities simultaneously. The developed approach has been applied to simulated system and breast cancer gene expression data. Result shows that, the proposed method was able to systematically uncover TF mediated transcriptional regulatory network structure, the regulatory coefficients, the TF protein level activities and the sample clustering effect. The regulation target prediction result is highly coordinated with the prior knowledge, and sample clustering result shows superior performance over previous molecular based clustering method. Conclusions The results demonstrated the validity and effectiveness of the proposed approach in reconstructing transcriptional networks mediated by TFs through simulated systems and real data. PMID:22166063

  3. Coupling root architecture and pore network modeling - an attempt towards better understanding root-soil interactions

    NASA Astrophysics Data System (ADS)

    Leitner, Daniel; Bodner, Gernot; Raoof, Amir

    2013-04-01

    Understanding root-soil interactions is of high importance for environmental and agricultural management. Root uptake is an essential component in water and solute transport modeling. The amount of groundwater recharge and solute leaching significantly depends on the demand based plant extraction via its root system. Plant uptake however not only responds to the potential demand, but in most situations is limited by supply form the soil. The ability of the plant to access water and solutes in the soil is governed mainly by root distribution. Particularly under conditions of heterogeneous distribution of water and solutes in the soil, it is essential to capture the interaction between soil and roots. Root architecture models allow studying plant uptake from soil by describing growth and branching of root axes in the soil. Currently root architecture models are able to respond dynamically to water and nutrient distribution in the soil by directed growth (tropism), modified branching and enhanced exudation. The porous soil medium as rooting environment in these models is generally described by classical macroscopic water retention and sorption models, average over the pore scale. In our opinion this simplified description of the root growth medium implies several shortcomings for better understanding root-soil interactions: (i) It is well known that roots grow preferentially in preexisting pores, particularly in more rigid/dry soil. Thus the pore network contributes to the architectural form of the root system; (ii) roots themselves can influence the pore network by creating preferential flow paths (biopores) which are an essential element of structural porosity with strong impact on transport processes; (iii) plant uptake depend on both the spatial location of water/solutes in the pore network as well as the spatial distribution of roots. We therefore consider that for advancing our understanding in root-soil interactions, we need not only to extend our root models

  4. PNNI routing support for ad hoc mobile networking: A flat architecture

    SciTech Connect

    Martinez, L.; Sholander, P.; Tolendino, L.

    1997-12-01

    This contribution extends the Outside Nodal Hierarchy List (ONHL) procedures described in ATM Form Contribution 97-0766. These extensions allow multiple mobile networks to form either an ad hoc network or an extension of a fixed PNNI infrastructure. This contribution covers the simplest case where the top-most Logical Group Nodes (LGNs), in those mobile networks, all reside at the same level in a PNNI hierarchy. Future contributions will cover the general case where those top-most LGNs reside at different hierarchy levels. This contribution considers a flat ad hoc network architecture--in the sense that each mobile network always participates in the PNNI hierarchy at the preconfigured level of its top-most LGN.

  5. Value proposition for amplets as banded amplification solutions in evolving WDM metro network architectures

    NASA Astrophysics Data System (ADS)

    Antoniades, N.; Menon, N.; Chbouki, N.; Ellinas, G.

    2005-03-01

    The benefits of amplets as banded amplification solutions in metro networks are quantified. In current networks that employ WDM as point-to-point fiber relief among pairs of super-hubs in synchronous optical network (SONET) rings, banded solutions based on erbium-doped waveguide amplifiers (EDWAs) provide a strong techno-economic value proposition. As WDM penetrates into the metro core with the introduction of WDM ring/mesh connectivity and eventually into the edge, this specific value proposition weakens. We present a physical transport performance model as well as simplified economic analysis on specific network simulation scenarios that represent the above actual metro network architecture evolution to support the value proposition.

  6. Survivable architectures for time and wavelength division multiplexed passive optical networks

    NASA Astrophysics Data System (ADS)

    Wong, Elaine

    2014-08-01

    The increased network reach and customer base of next-generation time and wavelength division multiplexed PON (TWDM-PONs) have necessitated rapid fault detection and subsequent restoration of services to its users. However, direct application of existing solutions for conventional PONs to TWDM-PONs is unsuitable as these schemes rely on the loss of signal (LOS) of upstream transmissions to trigger protection switching. As TWDM-PONs are required to potentially use sleep/doze mode optical network units (ONU), the loss of upstream transmission from a sleeping or dozing ONU could erroneously trigger protection switching. Further, TWDM-PONs require its monitoring modules for fiber/device fault detection to be more sensitive than those typically deployed in conventional PONs. To address the above issues, three survivable architectures that are compliant with TWDM-PON specifications are presented in this work. These architectures combine rapid detection and protection switching against multipoint failure, and most importantly do not rely on upstream transmissions for LOS activation. Survivability analyses as well as evaluations of the additional costs incurred to achieve survivability are performed and compared to the unprotected TWDM-PON. Network parameters that impact the maximum achievable network reach, maximum split ratio, connection availability, fault impact, and the incremental reliability costs for each proposed survivable architecture are highlighted.

  7. A TDMA Broadcast Satellite/Ground Architecture for the Aeronautical Telecommunications Network

    NASA Technical Reports Server (NTRS)

    Shamma, Mohammed A.; Raghavan, Rajesh S.

    2003-01-01

    An initial evaluation of a TDMA satellite broadcast architecture with an integrated ground network is proposed in this study as one option for the Aeronautical Telecommunications Network (ATN). The architecture proposed consists of a ground based network that is dedicated to the reception and transmissions of Automatic Dependent Surveillance Broadcast (ADS-B) messages from Mode-S or UAT type systems, along with tracks from primary and secondary surveillance radars. Additionally, the ground network could contain VHF Digital Link Mode 2, 3 or 4 transceivers for the reception and transmissions of Controller-Pilot Data Link Communications (CPDLC) messages and for voice. The second part of the ATN network consists of a broadcast satellite based system that is mainly dedicated for the transmission of surveillance data as well as En-route Flight Information Service Broadcast (FIS-B) to all aircraft. The system proposed integrates those two network to provide a nation wide comprehensive service utilizing near term or existing technologies and hence keeping the economic factor in prospective. The next few sections include a background introduction, the ground subnetwork, the satellite subnetwork, modeling and simulations, and conclusion and recommendations.

  8. A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe.

    PubMed

    Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

    2016-01-01

    Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies. PMID:27014338

  9. A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe

    PubMed Central

    Berto, Stefano; Perdomo-Sabogal, Alvaro; Gerighausen, Daniel; Qin, Jing; Nowick, Katja

    2016-01-01

    Cognitive abilities, such as memory, learning, language, problem solving, and planning, involve the frontal lobe and other brain areas. Not much is known yet about the molecular basis of cognitive abilities, but it seems clear that cognitive abilities are determined by the interplay of many genes. One approach for analyzing the genetic networks involved in cognitive functions is to study the coexpression networks of genes with known importance for proper cognitive functions, such as genes that have been associated with cognitive disorders like intellectual disability (ID) or autism spectrum disorders (ASD). Because many of these genes are gene regulatory factors (GRFs) we aimed to provide insights into the gene regulatory networks active in the human frontal lobe. Using genome wide human frontal lobe expression data from 10 independent data sets, we first derived 10 individual coexpression networks for all GRFs including their potential target genes. We observed a high level of variability among these 10 independently derived networks, pointing out that relying on results from a single study can only provide limited biological insights. To instead focus on the most confident information from these 10 networks we developed a method for integrating such independently derived networks into a consensus network. This consensus network revealed robust GRF interactions that are conserved across the frontal lobes of different healthy human individuals. Within this network, we detected a strong central module that is enriched for 166 GRFs known to be involved in brain development and/or cognitive disorders. Interestingly, several hubs of the consensus network encode for GRFs that have not yet been associated with brain functions. Their central role in the network suggests them as excellent new candidates for playing an essential role in the regulatory network of the human frontal lobe, which should be investigated in future studies. PMID:27014338

  10. A common network architecture efficiently implements a variety of sparsity-based inference problems.

    PubMed

    Charles, Adam S; Garrigues, Pierre; Rozell, Christopher J

    2012-12-01

    The sparse coding hypothesis has generated significant interest in the computational and theoretical neuroscience communities, but there remain open questions about the exact quantitative form of the sparsity penalty and the implementation of such a coding rule in neurally plausible architectures. The main contribution of this work is to show that a wide variety of sparsity-based probabilistic inference problems proposed in the signal processing and statistics literatures can be implemented exactly in the common network architecture known as the locally competitive algorithm (LCA). Among the cost functions we examine are approximate l(p) norms (0 ≤ p ≤ 2), modified l(p)-norms, block-l1 norms, and reweighted algorithms. Of particular interest is that we show significantly increased performance in reweighted l1 algorithms by inferring all parameters jointly in a dynamical system rather than using an iterative approach native to digital computational architectures. PMID:22970876

  11. Teledesic Global Wireless Broadband Network: Space Infrastructure Architecture, Design Features and Technologies

    NASA Technical Reports Server (NTRS)

    Stuart, James R.

    1995-01-01

    The Teledesic satellites are a new class of small satellites which demonstrate the important commercial benefits of using technologies developed for other purposes by U.S. National Laboratories. The Teledesic satellite architecture, subsystem design features, and new technologies are described. The new Teledesic satellite manufacturing, integration, and test approaches which use modern high volume production techniques and result in surprisingly low space segment costs are discussed. The constellation control and management features and attendant software architecture features are addressed. After briefly discussing the economic and technological impact on the USA commercial space industries of the space communications revolution and such large constellation projects, the paper concludes with observations on the trend toward future system architectures using networked groups of much smaller satellites.

  12. Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis.

    PubMed

    Chauhan, Rinki; Ravi, Janani; Datta, Pratik; Chen, Tianlong; Schnappinger, Dirk; Bassler, Kevin E; Balázsi, Gábor; Gennaro, Maria Laura

    2016-01-01

    Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics. PMID:27029515

  13. Reconstruction and topological characterization of the sigma factor regulatory network of Mycobacterium tuberculosis

    PubMed Central

    Chauhan, Rinki; Ravi, Janani; Datta, Pratik; Chen, Tianlong; Schnappinger, Dirk; Bassler, Kevin E.; Balázsi, Gábor; Gennaro, Maria Laura

    2016-01-01

    Accessory sigma factors, which reprogram RNA polymerase to transcribe specific gene sets, activate bacterial adaptive responses to noxious environments. Here we reconstruct the complete sigma factor regulatory network of the human pathogen Mycobacterium tuberculosis by an integrated approach. The approach combines identification of direct regulatory interactions between M. tuberculosis sigma factors in an E. coli model system, validation of selected links in M. tuberculosis, and extensive literature review. The resulting network comprises 41 direct interactions among all 13 sigma factors. Analysis of network topology reveals (i) a three-tiered hierarchy initiating at master regulators, (ii) high connectivity and (iii) distinct communities containing multiple sigma factors. These topological features are likely associated with multi-layer signal processing and specialized stress responses involving multiple sigma factors. Moreover, the identification of overrepresented network motifs, such as autoregulation and coregulation of sigma and anti-sigma factor pairs, provides structural information that is relevant for studies of network dynamics. PMID:27029515

  14. Heterogeneous sensor networks: a bio-inspired overlay architecture

    NASA Astrophysics Data System (ADS)

    Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Klein, Daniel; Isaacs, Jason; Venkateswaran, Sriram; Pham, Tien

    2010-04-01

    Teledyne Scientific Company, the University of California at Santa Barbara (UCSB) and the Army Research Lab are developing technologies for automated data exfiltration from heterogeneous sensor networks through the Institute for Collaborative Biotechnologies (ICB). Unmanned air vehicles (UAV) provide an effective means to autonomously collect data from unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous data-driven collection routes. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data across heterogeneous sensors. A fast and accurate method has been developed for routing UAVs and localizing an event by fusing data from a sparse number of UGSs; it leverages a bio-inspired technique based on chemotaxis or the motion of bacteria seeking nutrients in their environment. The system was implemented and successfully tested using a high level simulation environment using a flight simulator to emulate a UAV. A field test was also conducted in November 2009 at Camp Roberts, CA using a UAV provided by AeroMech Engineering. The field test results showed that the system can detect and locate the source of an acoustic event with an accuracy of about 3 meters average circular error.

  15. A comprehensive gene regulatory network for the diauxic shift in Saccharomyces cerevisiae.

    PubMed

    Geistlinger, Ludwig; Csaba, Gergely; Dirmeier, Simon; Küffner, Robert; Zimmer, Ralf

    2013-10-01

    Existing machine-readable resources for large-scale gene regulatory networks usually do not provide context information characterizing the activating conditions for a regulation and how targeted genes are affected. Although this information is essentially required for data interpretation, available networks are often restricted to not condition-dependent, non-quantitative, plain binary interactions as derived from high-throughput screens. In this article, we present a comprehensive Petri net based regulatory network that controls the diauxic shift in Saccharomyces cerevisiae. For 100 specific enzymatic genes, we collected regulations from public databases as well as identified and manually curated >400 relevant scientific articles. The resulting network consists of >300 multi-input regulatory interactions providing (i) activating conditions for the regulators; (ii) semi-quantitative effects on their targets; and (iii) classification of the experimental evidence. The diauxic shift network compiles widespread distributed regulatory information and is available in an easy-to-use machine-readable form. Additionally, we developed a browsable system organizing the network into pathway maps, which allows to inspect and trace the evidence for each annotated regulation in the model. PMID:23873954

  16. A comprehensive gene regulatory network for the diauxic shift in Saccharomyces cerevisiae

    PubMed Central

    Geistlinger, Ludwig; Csaba, Gergely; Dirmeier, Simon; Küffner, Robert; Zimmer, Ralf

    2013-01-01

    Existing machine-readable resources for large-scale gene regulatory networks usually do not provide context information characterizing the activating conditions for a regulation and how targeted genes are affected. Although this information is essentially required for data interpretation, available networks are often restricted to not condition-dependent, non-quantitative, plain binary interactions as derived from high-throughput screens. In this article, we present a comprehensive Petri net based regulatory network that controls the diauxic shift in Saccharomyces cerevisiae. For 100 specific enzymatic genes, we collected regulations from public databases as well as identified and manually curated >400 relevant scientific articles. The resulting network consists of >300 multi-input regulatory interactions providing (i) activating conditions for the regulators; (ii) semi-quantitative effects on their targets; and (iii) classification of the experimental evidence. The diauxic shift network compiles widespread distributed regulatory information and is available in an easy-to-use machine-readable form. Additionally, we developed a browsable system organizing the network into pathway maps, which allows to inspect and trace the evidence for each annotated regulation in the model. PMID:23873954

  17. Integrated inference and analysis of regulatory networks from multi-level measurements.

    PubMed

    Poultney, Christopher S; Greenfield, Alex; Bonneau, Richard

    2012-01-01

    Regulatory and signaling networks coordinate the enormously complex interactions and processes that control cellular processes (such as metabolism and cell division), coordinate response to the environment, and carry out multiple cell decisions (such as development and quorum sensing). Regulatory network inference is the process of inferring these networks, traditionally from microarray data but increasingly incorporating other measurement types such as proteomics, ChIP-seq, metabolomics, and mass cytometry. We discuss existing techniques for network inference. We review in detail our pipeline, which consists of an initial biclustering step, designed to estimate co-regulated groups; a network inference step, designed to select and parameterize likely regulatory models for the control of the co-regulated groups from the biclustering step; and a visualization and analysis step, designed to find and communicate key features of the network. Learning biological networks from even the most complete data sets is challenging; we argue that integrating new data types into the inference pipeline produces networks of increased accuracy, validity, and biological relevance. PMID:22482944

  18. Principles of dynamical modularity in biological regulatory networks

    PubMed Central

    Deritei, Dávid; Aird, William C.; Ercsey-Ravasz, Mária; Regan, Erzsébet Ravasz

    2016-01-01

    Intractable diseases such as cancer are associated with breakdown in multiple individual functions, which conspire to create unhealthy phenotype-combinations. An important challenge is to decipher how these functions are coordinated in health and disease. We approach this by drawing on dynamical systems theory. We posit that distinct phenotype-combinations are generated by interactions among robust regulatory switches, each in control of a discrete set of phenotypic outcomes. First, we demonstrate the advantage of characterizing multi-switch regulatory systems in terms of their constituent switches by building a multiswitch cell cycle model which points to novel, testable interactions critical for early G2/M commitment to division. Second, we define quantitative measures of dynamical modularity, namely that global cell states are discrete combinations of switch-level phenotypes. Finally, we formulate three general principles that govern the way coupled switches coordinate their function. PMID:26979940

  19. Fungal Genes in Context: Genome Architecture Reflects Regulatory Complexity and Function

    PubMed Central

    Noble, Luke M.; Andrianopoulos, Alex

    2013-01-01

    Gene context determines gene expression, with local chromosomal environment most influential. Comparative genomic analysis is often limited in scope to conserved or divergent gene and protein families, and fungi are well suited to this approach with low functional redundancy and relatively streamlined genomes. We show here that one aspect of gene context, the amount of potential upstream regulatory sequence maintained through evolution, is highly predictive of both molecular function and biological process in diverse fungi. Orthologs with large upstream intergenic regions (UIRs) are strongly enriched in information processing functions, such as signal transduction and sequence-specific DNA binding, and, in the genus Aspergillus, include the majority of experimentally studied, high-level developmental and metabolic transcriptional regulators. Many uncharacterized genes are also present in this class and, by implication, may be of similar importance. Large intergenic regions also share two novel sequence characteristics, currently of unknown significance: they are enriched for plus-strand polypyrimidine tracts and an information-rich, putative regulatory motif that was present in the last common ancestor of the Pezizomycotina. Systematic consideration of gene UIR in comparative genomics, particularly for poorly characterized species, could help reveal organisms’ regulatory priorities. PMID:23699226

  20. Novel players in the AP2-miR172 regulatory network for common bean nodulation

    PubMed Central

    Íñiguez, Luis P; Nova-Franco, Bárbara; Hernández, Georgina

    2015-01-01

    The intricate regulatory network for floral organogenesis in plants that includes AP2/ERF, SPL and AGL transcription factors, miR172 and miR156 along with other components is well documented, though its complexity and size keep increasing. The miR172/AP2 node was recently proposed as essential regulator in the legume-rhizobia nitrogen-fixing symbiosis. Research from our group contributed to demonstrate the control of common bean (Phaseolus vulgaris) nodulation by miR172c/AP2-1, however no other components of such regulatory network have been reported. Here we propose AGLs as new protagonists in the regulation of common bean nodulation and discuss the relevance of future deeper analysis of the complex AP2 regulatory network for nodule organogenesis in legumes. PMID:26211831

  1. Using gene expression programming to infer gene regulatory networks from time-series data.

    PubMed

    Zhang, Yongqing; Pu, Yifei; Zhang, Haisen; Su, Yabo; Zhang, Lifang; Zhou, Jiliu

    2013-12-01

    Gene regulatory networks inference is currently a topic under heavy research in the systems biology field. In this paper, gene regulatory networks are inferred via evolutionary model based on time-series microarray data. A non-linear differential equation model is adopted. Gene expression programming (GEP) is applied to identify the structure of the model and least mean square (LMS) is used to optimize the parameters in ordinary differential equations (ODEs). The proposed work has been first verified by synthetic data with noise-free and noisy time-series data, respectively, and then its effectiveness is confirmed by three real time-series expression datasets. Finally, a gene regulatory network was constructed with 12 Yeast genes. Experimental results demonstrate that our model can improve the prediction accuracy of microarray time-series data effectively. PMID:24140883

  2. LncReg: a reference resource for lncRNA-associated regulatory networks

    PubMed Central

    Zhou, Zhong; Shen, Yi; Khan, Muhammad Riaz; Li, Ao

    2015-01-01

    Long non-coding RNAs (lncRNAs) are critical in the regulation of various biological processes. In recent years, plethora of lncRNAs have been identified in mammalian genomes through different approaches, and the researchers are constantly reporting the regulatory roles of these lncRNAs, which leads to complexity of literature about particular lncRNAs. Therefore, for the convenience of the researchers, we collected regulatory relationships of the lncRNAs and built a database called ‘LncReg’. This database is developed by collecting 1081 validated lncRNA-associated regulatory entries, including 258 non-redundant lncRNAs and 571 non-redundant genes. With regulatory relationships information, LncReg can provide overall perspectives of regulatory networks of lncRNAs and comprehensive data for bioinformatics research, which is useful for understanding the functional roles of lncRNAs. Database URL: http://bioinformatics.ustc.edu.cn/lncreg/ PMID:26363021

  3. Novel Insights into the Regulatory Architecture of CD4+ T Cells in Rheumatoid Arthritis

    PubMed Central

    Aterido, Adrià; Palacio, Carlos; Marsal, Sara; Ávila, Gabriela; Julià, Antonio

    2014-01-01

    Rheumatoid arthritis (RA) is the most frequent autoimmune chronic inflammatory disease of the joints and it is characterized by the inflammation of the synovial membrane and the subsequent destruction of the joints. In RA, CD4+ T cells are the main drivers of disease initiation and the perpetuation of the damaging inflammatory process. To date, however, the genetic regulatory mechanisms of CD4+ T cells associated with RA etiology are poorly understood. The genome-wide analysis of expression quantitative trait loci (eQTL) in disease-relevant cell types is a recent genomic integration approach that is providing significant insights into the genetic regulatory mechanisms of many human pathologies. The objective of the present study was to analyze, for the first time, the genome-wide genetic regulatory mechanisms associated with the gene expression of CD4+ T cells in RA. Whole genome gene expression profiling of CD4+ T cells and the genome-wide genotyping (598,258 SNPs) of 29 RA patients with an active disease were performed. In order to avoid the excessive burden of multiple testing associated with genome-wide trans-eQTL analysis, we developed and implemented a novel systems genetics approach. Finally, we compared the genomic regulation pattern of CD4+ T cells in RA with the genomic regulation observed in reference lymphoblastoid cell lines (LCLs). We identified a genome-wide significant cis-eQTL associated with the expression of FAM66C gene (P = 6.51e−9). Using our new systems genetics approach we identified six statistically significant trans-eQTLs associated with the expression of KIAA0101 (P<7.4e−8) and BIRC5 (P = 5.35e−8) genes. Finally, comparing the genomic regulation profiles between RA CD4+ T cells and control LCLs we found 20 genes showing differential regulatory patterns between both cell types. The present genome-wide eQTL analysis has identified new genetic regulatory elements that are key to the activity of CD4+ T cells in RA. PMID:24959711

  4. Low-Power Direct-Sequence Spread-Spectrum Modem Architecture for Distributed Wireless Sensor Networks

    SciTech Connect

    Chien, C; Elgorriaga, I; McConaghy, C

    2001-07-03

    Emerging CMOS and MEMS technologies enable the implementation of a large number of wireless distributed microsensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors should operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. This paper presents a direct-sequence spread-spectrum modem architecture that provides robust communications for wireless sensor networks while dissipating very low power. The modem architecture has been verified in an FPGA implementation that dissipates only 33 mW for both transmission and reception. The implementation can be easily mapped to an ASIC technology, with an estimated power performance of less than 1 mW.

  5. Neural Network Classifier Architectures for Phoneme Recognition. CRC Technical Note No. CRC-TN-92-001.

    ERIC Educational Resources Information Center

    Treurniet, William

    A study applied artificial neural networks, trained with the back-propagation learning algorithm, to modelling phonemes extracted from the DARPA TIMIT multi-speaker, continuous speech data base. A number of proposed network architectures were applied to the phoneme classification task, ranging from the simple feedforward multilayer network to more…

  6. Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii.

    PubMed

    Gargouri, Mahmoud; Park, Jeong-Jin; Holguin, F Omar; Kim, Min-Jeong; Wang, Hongxia; Deshpande, Rahul R; Shachar-Hill, Yair; Hicks, Leslie M; Gang, David R

    2015-08-01

    Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combined omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. Evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism. PMID:26022256

  7. Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii

    PubMed Central

    Gargouri, Mahmoud; Park, Jeong-Jin; Holguin, F. Omar; Kim, Min-Jeong; Wang, Hongxia; Deshpande, Rahul R.; Shachar-Hill, Yair; Hicks, Leslie M.; Gang, David R.

    2015-01-01

    Microalgae-based biofuels are promising sources of alternative energy, but improvements throughout the production process are required to establish them as economically feasible. One of the most influential improvements would be a significant increase in lipid yields, which could be achieved by altering the regulation of lipid biosynthesis and accumulation. Chlamydomonas reinhardtii accumulates oil (triacylglycerols, TAG) in response to nitrogen (N) deprivation. Although a few important regulatory genes have been identified that are involved in controlling this process, a global understanding of the larger regulatory network has not been developed. In order to uncover this network in this species, a combined omics (transcriptomic, proteomic and metabolomic) analysis was applied to cells grown in a time course experiment after a shift from N-replete to N-depleted conditions. Changes in transcript and protein levels of 414 predicted transcription factors (TFs) and transcriptional regulators (TRs) were monitored relative to other genes. The TF and TR genes were thus classified by two separate measures: up-regulated versus down-regulated and early response versus late response relative to two phases of polar lipid synthesis (before and after TAG biosynthesis initiation). Lipidomic and primary metabolite profiling generated compound accumulation levels that were integrated with the transcript dataset and TF profiling to produce a transcriptional regulatory network. Evaluation of this proposed regulatory network led to the identification of several regulatory hubs that control many aspects of cellular metabolism, from N assimilation and metabolism, to central metabolism, photosynthesis and lipid metabolism. PMID:26022256

  8. An integrated architecture for deploying a virtual private medical network over the web.

    PubMed

    Gritzalis, S; Gritzalis, D; Moulinos, C; Iliadis, J

    2001-01-01

    In this paper we describe a pilot architecture aiming at protecting Web-based medical applications through the development of a virtual private medical network. The basic technology, which is utilized by this integrated architecture, is the Trusted Third Party (TTP). In specific, a TTP is used to generate, distribute, and revoke digital certificates to/from medical practitioners and healthcare organizations wishing to communicate in a secure way. Digital certificates and digital signatures are, in particular, used to provide peer and data origin authentication and access control functionalities. We also propose a logical Public Key Infrastructure (PKI) architecture, which is robust, scalable, and based on standards. This architecture aims at supporting large-scale healthcare applications. It supports openness, scalability, flexibility and extensibility, and can be integrated with existing TTP schemes and infrastructures offering transparency and adequate security. Finally, it is demonstrated that the proposed architecture enjoys all desirable usability characteristics, and meets the set of criteria, which constitutes an applicable framework for the development of trusted medical services over the Web. PMID:11583408

  9. The Architecture of Information Fusion System Ingreenhouse Wireless Sensor Network Based on Multi-Agent

    NASA Astrophysics Data System (ADS)

    Zhu, Wenting; Chen, Ming

    In view of current unprogressive situation of factory breeding in aquaculture, this article designed a standardized, informationized and intelligentized aquaculture system, proposed a information fusion architecture based on multi-agent in greenhouse wireless sensor network (GWSN), and researched mainly the structural characteristic of the four-classed information fusion based on distributed multi-agent and the method to construct the structure inside of every agent.

  10. STOMP: A Software Architecture for the Design and Simulation UAV-Based Sensor Networks

    SciTech Connect

    Jones, E D; Roberts, R S; Hsia, T C S

    2002-10-28

    This paper presents the Simulation, Tactical Operations and Mission Planning (STOMP) software architecture and framework for simulating, controlling and communicating with unmanned air vehicles (UAVs) servicing large distributed sensor networks. STOMP provides hardware-in-the-loop capability enabling real UAVs and sensors to feedback state information, route data and receive command and control requests while interacting with other real or virtual objects thereby enhancing support for simulation of dynamic and complex events.

  11. Toward a Genome-Wide Reconstruction of Cis-Regulatory Networks in the Human Genome

    PubMed Central

    Cecchini, Katharine R.; Banerjee, A. Raja; Kim, Tae Hoon

    2009-01-01

    The vast amount of recent progress made on the sequence of the human genome has allowed an unprecedented examination of cis-regulatory networks. These networks consist of functional elements such as promoters, enhancers, silencers, and insulators, and their coordinated activity is responsible for regulation of gene expression. Recent studies surveyed the entire genome, identifying novel elements and evaluating functional differences in respect to development. These investigations present the first steps towards a global regulatory map for expression in the human genome. PMID:19560550

  12. Dual control system - A novel scaffolding architecture of an inducible regulatory device for the precise regulation of gene expression.

    PubMed

    Horbal, L; Luzhetskyy, A

    2016-09-01

    Here, we present a novel scaffolding architecture of an inducible regulatory device. This dual control system is completely silent in the off stage and is coupled to the regulation of gene expression at both the transcriptional and translational levels. This system also functions as an AND gate. We demonstrated the effectiveness of the cumate-riboswitch dual control system for the control of pamamycin production in Streptomyces albus. Placing the cre recombinase gene under the control of this system permitted the construction of synthetic devices with non-volatile memory that sense the signal and respond by altering DNA at the chromosomal level, thereby producing changes that are heritable. In addition, we present a library of synthetic inducible promoters based on the previously described cumate switch. With only one inducer and different promoters, we demonstrate that simultaneous modulation of the expression of several genes to different levels in various operons is possible. Because all modules of the AND gates are functional in bacteria other than Streptomyces, we anticipate that these regulatory devices can be used to control gene expression in other Actinobacteria. The features described in this study make these systems promising tools for metabolic engineering and biotechnology in Actinobacteria. PMID:27040671

  13. Predicting electrocardiogram and arterial blood pressure waveforms with different Echo State Network architectures.

    PubMed

    Fong, Allan; Mittu, Ranjeev; Ratwani, Raj; Reggia, James

    2014-01-01

    Alarm fatigue caused by false alarms and alerts is an extremely important issue for the medical staff in Intensive Care Units. The ability to predict electrocardiogram and arterial blood pressure waveforms can potentially help the staff and hospital systems better classify a patient's waveforms and subsequent alarms. This paper explores the use of Echo State Networks, a specific type of neural network for mining, understanding, and predicting electrocardiogram and arterial blood pressure waveforms. Several network architectures are designed and evaluated. The results show the utility of these echo state networks, particularly ones with larger integrated reservoirs, for predicting electrocardiogram waveforms and the adaptability of such models across individuals. The work presented here offers a unique approach for understanding and predicting a patient's waveforms in order to potentially improve alarm generation. We conclude with a brief discussion of future extensions of this research. PMID:25954359

  14. Standard Spacecraft Interfaces and IP Network Architectures: Prototyping Activities at the GSFC

    NASA Technical Reports Server (NTRS)

    Schnurr, Richard; Marquart, Jane; Lin, Michael

    2003-01-01

    Advancements in fright semiconductor technology have opened the door for IP-based networking in spacecraft architectures. The GSFC believes the same signlJicant cost savings gained using MIL-STD-1553/1773 as a standard low rate interface for spacecraft busses cun be realized for highspeed network interfaces. To that end, GSFC is developing hardware and software to support a seamless, space mission IP network based on Ethernet and MIL-STD-1553. The Ethernet network shall connect all fright computers and communications systems using interface standards defined by the CCSDS Standard Onboard InterFace (SOIF) Panel. This paper shall discuss the prototyping effort underway at GSFC and expected results.

  15. Modeling workplace contact networks: The effects of organizational structure, architecture, and reporting errors on epidemic predictions

    PubMed Central

    Potter, Gail E.; Smieszek, Timo; Sailer, Kerstin

    2015-01-01

    Face-to-face social contacts are potentially important transmission routes for acute respiratory infections, and understanding the contact network can improve our ability to predict, contain, and control epidemics. Although workplaces are important settings for infectious disease transmission, few studies have collected workplace contact data and estimated workplace contact networks. We use contact diaries, architectural distance measures, and institutional structures to estimate social contact networks within a Swiss research institute. Some contact reports were inconsistent, indicating reporting errors. We adjust for this with a latent variable model, jointly estimating the true (unobserved) network of contacts and duration-specific reporting probabilities. We find that contact probability decreases with distance, and that research group membership, role, and shared projects are strongly predictive of contact patterns. Estimated reporting probabilities were low only for 0–5 min contacts. Adjusting for reporting error changed the estimate of the duration distribution, but did not change the estimates of covariate effects and had little effect on epidemic predictions. Our epidemic simulation study indicates that inclusion of network structure based on architectural and organizational structure data can improve the accuracy of epidemic forecasting models. PMID:26634122

  16. An Area-Based Overlay Architecture for Scalable Integration of Sensor Networks

    NASA Astrophysics Data System (ADS)

    Pappas, Lampros; Lalis, Spyros

    With many different sensor networks being deployed, there will be an increased need to facilitate their uniform and efficient access at a large, perhaps even global, scale. To this end, we present an overlay-based architecture for organizing and querying multiple sensor networks based on their geographical area. The nodes of the system, representing query processors and individual sensor network gateways, are organized in a hierarchy which is used for query forwarding and result delivery. The key features of our system are: (i) support for the dynamic addition and removal of query processors and sensor network gateways; (ii) automatic hierarchy construction and awareness of sensing capabilities based on explicit metadata information; and (iii) efficient query multiplexing and result de-multiplexing within the overlay. We present a first evaluation of the proposed architecture. Results indicate that our design considerably reduces the communication between the nodes of the overlay as well as the actual sensing load at the edges (sensor networks) of the system.

  17. Characterizing the interplay betwen mulitple levels of organization within bacterial sigma factor regulatory networks

    SciTech Connect

    Yu, Qiu; Nagarajan, Harish; Embree, Mallory; Shieu, Wendy; Abate, Elisa; Juarez, Katy; Cho, Byung-Kwan; Elkins, James G; Nevin, Kelly P.; Barrett, Christian; Lovley, Derek; Palsson, Bernhard O.; Zengler, Karsten

    2013-01-01

    Bacteria contain multiple sigma factors, each targeting diverse, but often overlapping sets of promoters, thereby forming a complex network. The layout and deployment of such a sigma factor network directly impacts global transcriptional regulation and ultimately dictates the phenotype. Here we integrate multi-omic data sets to determine the topology, the operational, and functional states of the sigma factor network in Geobacter sulfurreducens, revealing a unique network topology of interacting sigma factors. Analysis of the operational state of the sigma factor network shows a highly modular structure with sN being the major regulator of energy metabolism. Surprisingly, the functional state of the network during the two most divergent growth conditions is nearly static, with sigma factor binding profiles almost invariant to environmental stimuli. This first comprehensive elucidation of the interplay between different levels of the sigma factor network organization is fundamental to characterize transcriptional regulatory mechanisms in bacteria.

  18. A Functional and Regulatory Network Associated with PIP Expression in Human Breast Cancer

    PubMed Central

    Debily, Marie-Anne; Marhomy, Sandrine El; Boulanger, Virginie; Eveno, Eric; Mariage-Samson, Régine; Camarca, Alessandra; Auffray, Charles; Piatier-Tonneau, Dominique; Imbeaud, Sandrine

    2009-01-01

    Background The PIP (prolactin-inducible protein) gene has been shown to be expressed in breast cancers, with contradictory results concerning its implication. As both the physiological role and the molecular pathways in which PIP is involved are poorly understood, we conducted combined gene expression profiling and network analysis studies on selected breast cancer cell lines presenting distinct PIP expression levels and hormonal receptor status, to explore the functional and regulatory network of PIP co-modulated genes. Principal Findings Microarray analysis allowed identification of genes co-modulated with PIP independently of modulations resulting from hormonal treatment or cell line heterogeneity. Relevant clusters of genes that can discriminate between [PIP+] and [PIP−] cells were identified. Functional and regulatory network analyses based on a knowledge database revealed a master network of PIP co-modulated genes, including many interconnecting oncogenes and tumor suppressor genes, half of which were detected as differentially expressed through high-precision measurements. The network identified appears associated with an inhibition of proliferation coupled with an increase of apoptosis and an enhancement of cell adhesion in breast cancer cell lines, and contains many genes with a STAT5 regulatory motif in their promoters. Conclusions Our global exploratory approach identified biological pathways modulated along with PIP expression, providing further support for its good prognostic value of disease-free survival in breast cancer. Moreover, our data pointed to the importance of a regulatory subnetwork associated with PIP expression in which STAT5 appears as a potential transcriptional regulator. PMID:19262752

  19. Stochasticity, Bistability and the Wisdom of Crowds: A Model for Associative Learning in Genetic Regulatory Networks

    PubMed Central

    Sorek, Matan; Balaban, Nathalie Q.; Loewenstein, Yonatan

    2013-01-01

    It is generally believed that associative memory in the brain depends on multistable synaptic dynamics, which enable the synapses to maintain their value for extended periods of time. However, multistable dynamics are not restricted to synapses. In particular, the dynamics of some genetic regulatory networks are multistable, raising the possibility that even single cells, in the absence of a nervous system, are capable of learning associations. Here we study a standard genetic regulatory network model with bistable elements and stochastic dynamics. We demonstrate that such a genetic regulatory network model is capable of learning multiple, general, overlapping associations. The capacity of the network, defined as the number of associations that can be simultaneously stored and retrieved, is proportional to the square root of the number of bistable elements in the genetic regulatory network. Moreover, we compute the capacity of a clonal population of cells, such as in a colony of bacteria or a tissue, to store associations. We show that even if the cells do not interact, the capacity of the population to store associations substantially exceeds that of a single cell and is proportional to the number of bistable elements. Thus, we show that even single cells are endowed with the computational power to learn associations, a power that is substantially enhanced when these cells form a population. PMID:23990765

  20. Reconstruction of large-scale gene regulatory networks using Bayesian model averaging.

    PubMed

    Kim, Haseong; Gelenbe, Erol

    2012-09-01

    Gene regulatory networks provide the systematic view of molecular interactions in a complex living system. However, constructing large-scale gene regulatory networks is one of the most challenging problems in systems biology. Also large burst sets of biological data require a proper integration technique for reliable gene regulatory network construction. Here we present a new reverse engineering approach based on Bayesian model averaging which attempts to combine all the appropriate models describing interactions among genes. This Bayesian approach with a prior based on the Gibbs distribution provides an efficient means to integrate multiple sources of biological data. In a simulation study with maximum of 2000 genes, our method shows better sensitivity than previous elastic-net and Gaussian graphical models, with a fixed specificity of 0.99. The study also shows that the proposed method outperforms the other standard methods for a DREAM dataset generated by nonlinear stochastic models. In brain tumor data analysis, three large-scale networks consisting of 4422 genes were built using the gene expression of non-tumor, low and high grade tumor mRNA expression samples, along with DNA-protein binding affinity information. We found that genes having a large variation of degree distribution among the three tumor networks are the ones that see most involved in regulatory and developmental processes, which possibly gives a novel insight concerning conventional differentially expressed gene analysis. PMID:22987132

  1. Automated selection of synthetic biology parts for genetic regulatory networks.

    PubMed

    Yaman, Fusun; Bhatia, Swapnil; Adler, Aaron; Densmore, Douglas; Beal, Jacob

    2012-08-17

    Raising the level of abstraction for synthetic biology design requires solving several challenging problems, including mapping abstract designs to DNA sequences. In this paper we present the first formalism and algorithms to address this problem. The key steps of this transformation are feature matching, signal matching, and part matching. Feature matching ensures that the mapping satisfies the regulatory relationships in the abstract design. Signal matching ensures that the expression levels of functional units are compatible. Finally, part matching finds a DNA part sequence that can implement the design. Our software tool MatchMaker implements these three steps. PMID:23651287

  2. Service oriented network architecture for control and management of home appliances

    NASA Astrophysics Data System (ADS)

    Hayakawa, Hiroshi; Koita, Takahiro; Sato, Kenya

    2005-12-01

    Recent advances in multimedia network systems and mechatronics have led to the development of a new generation of applications that associate the use of various multimedia objects with the behavior of multiple robotic actors. The connection of audio and video devices through high speed multimedia networks is expected to make the system more convenient to use. For example, many home appliances, such as a video camera, a display monitor, a video recorder, an audio system and so on, are being equipped with a communication interface in the near future. Recently some platforms (i.e. UPnP1, HAVi2 and so on) are proposed for constructing home networks; however, there are some issues to be solved to realize various services by connecting different equipment via the pervasive peer-to-peer network. UPnP offers network connectivity of PCs of intelligent home appliances, practically, which means to require a PC in the network to control other devices. Meanwhile, HAVi has been developed for intelligent AV equipments with sophisticated functions using high CPU power and large memory. Considering the targets of home alliances are embedded systems, this situation raises issues of software and hardware complexity, cost, power consumption and so on. In this study, we have proposed and developed the service oriented network architecture for control and management of home appliances, named SONICA (Service Oriented Network Interoperability for Component Adaptation), to address these issues described before.

  3. Dissecting neural differentiation regulatory networks through epigenetic footprinting

    PubMed Central

    Yaffe, Yakey; Donaghey, Julie; Pop, Ramona; Mallard, William; Issner, Robbyn; Gifford, Casey A.; Goren, Alon; Xing, Jeff; Gu, Hongcang; Cachiarelli, Davide; Tsankov, Alexander; Epstein, Chuck; Rinn, John R.; Mikkelsen, Tarjei S.; Kohlbacher, Oliver; Gnirke, Andreas; Bernstein, Bradley E.

    2014-01-01

    Human pluripotent stem cell derived models that accurately recapitulate neural development in vitro and allow for the generation of specific neuronal subtypes are of major interest to the stem cell and biomedical community. Notch signaling, particularly through the Notch effector HES5, is a major pathway critical for the onset and maintenance of neural progenitor cells (NPCs) in the embryonic and adult nervous system1-3. This can be exploited to isolate distinct populations of human embryonic stem (ES) cell derived NPCs4. Here, we report the transcriptional and epigenomic analysis of six consecutive stages derived from a HES5-GFP reporter ES cell line5 differentiated along the neural trajectory aimed at modeling key cell fate decisions including specification, expansion and patterning during the ontogeny of cortical neural stem and progenitor cells. In order to dissect the regulatory mechanisms that orchestrate the stage-specific differentiation process, we developed a computational framework to infer key regulators of each cell state transition based on the progressive remodeling of the epigenetic landscape and then validated these through a pooled shRNA screen. We were also able to refine our previous observations on epigenetic priming at transcription factor binding sites and show here that they are mediated by combinations of core and stage- specific factors. Taken together, we demonstrate the utility of our system and outline a general framework, not limited to the context of the neural lineage, to dissect regulatory circuits of differentiation. PMID:25533951

  4. Design of artificial genetic regulatory networks with multiple delayed adaptive responses*

    NASA Astrophysics Data System (ADS)

    Kaluza, Pablo; Inoue, Masayo

    2016-06-01

    Genetic regulatory networks with adaptive responses are widely studied in biology. Usually, models consisting only of a few nodes have been considered. They present one input receptor for activation and one output node where the adaptive response is computed. In this work, we design genetic regulatory networks with many receptors and many output nodes able to produce delayed adaptive responses. This design is performed by using an evolutionary algorithm of mutations and selections that minimizes an error function defined by the adaptive response in signal shapes. We present several examples of network constructions with a predefined required set of adaptive delayed responses. We show that an output node can have different kinds of responses as a function of the activated receptor. Additionally, complex network structures are presented since processing nodes can be involved in several input-output pathways.

  5. Identifying Cancer Subtypes from miRNA-TF-mRNA Regulatory Networks and Expression Data

    PubMed Central

    Liu, Lin; Wang, Rujing; Sun, Bingyu; Li, Jiuyong

    2016-01-01

    Background Identifying cancer subtypes is an important component of the personalised medicine framework. An increasing number of computational methods have been developed to identify cancer subtypes. However, existing methods rarely use information from gene regulatory networks to facilitate the subtype identification. It is widely accepted that gene regulatory networks play crucial roles in understanding the mechanisms of diseases. Different cancer subtypes are likely caused by different regulatory mechanisms. Therefore, there are great opportunities for developing methods that can utilise network information in identifying cancer subtypes. Results In this paper, we propose a method, weighted similarity network fusion (WSNF), to utilise the information in the complex miRNA-TF-mRNA regulatory network in identifying cancer subtypes. We firstly build the regulatory network where the nodes represent the features, i.e. the microRNAs (miRNAs), transcription factors (TFs) and messenger RNAs (mRNAs) and the edges indicate the interactions between the features. The interactions are retrieved from various interatomic databases. We then use the network information and the expression data of the miRNAs, TFs and mRNAs to calculate the weight of the features, representing the level of importance of the features. The feature weight is then integrated into a network fusion approach to cluster the samples (patients) and thus to identify cancer subtypes. We applied our method to the TCGA breast invasive carcinoma (BRCA) and glioblastoma multiforme (GBM) datasets. The experimental results show that WSNF performs better than the other commonly used computational methods, and the information from miRNA-TF-mRNA regulatory network contributes to the performance improvement. The WSNF method successfully identified five breast cancer subtypes and three GBM subtypes which show significantly different survival patterns. We observed that the expression patterns of the features in some mi

  6. Development of Network-based Communications Architectures for Future NASA Missions

    NASA Technical Reports Server (NTRS)

    Slywczak, Richard A.

    2007-01-01

    Since the Vision for Space Exploration (VSE) announcement, NASA has been developing a communications infrastructure that combines existing terrestrial techniques with newer concepts and capabilities. The overall goal is to develop a flexible, modular, and extensible architecture that leverages and enhances terrestrial networking technologies that can either be directly applied or modified for the space regime. In addition, where existing technologies leaves gaps, new technologies must be developed. An example includes dynamic routing that accounts for constrained power and bandwidth environments. Using these enhanced technologies, NASA can develop nodes that provide characteristics, such as routing, store and forward, and access-on-demand capabilities. But with the development of the new infrastructure, challenges and obstacles will arise. The current communications infrastructure has been developed on a mission-by-mission basis rather than an end-to-end approach; this has led to a greater ground infrastructure, but has not encouraged communications between space-based assets. This alone provides one of the key challenges that NASA must encounter. With the development of the new Crew Exploration Vehicle (CEV), NASA has the opportunity to provide an integration path for the new vehicles and provide standards for their development. Some of the newer capabilities these vehicles could include are routing, security, and Software Defined Radios (SDRs). To meet these needs, the NASA/Glenn Research Center s (GRC) Network Emulation Laboratory (NEL) has been using both simulation and emulation to study and evaluate these architectures. These techniques provide options to NASA that directly impact architecture development. This paper identifies components of the infrastructure that play a pivotal role in the new NASA architecture, develops a scheme using simulation and emulation for testing these architectures and demonstrates how NASA can strengthen the new infrastructure by

  7. Reconstructing genome-wide regulatory network of E. coli using transcriptome data and predicted transcription factor activities

    PubMed Central

    2011-01-01

    Background Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Understanding the connections and the activity levels of regulators is important for the research of gene regulatory networks. While relevance score based algorithms that reconstruct gene regulatory networks from transcriptome data can infer genome-wide gene regulatory networks, they are unfortunately prone to false positive results. Transcription factor activities (TFAs) quantitatively reflect the ability of the transcription factor to regulate target genes. However, classic relevance score based gene regulatory network reconstruction algorithms use models do not include the TFA layer, thus missing a key regulatory element. Results This work integrates TFA prediction algorithms with relevance score based network reconstruction algorithms to reconstruct gene regulatory networks with improved accuracy over classic relevance score based algorithms. This method is called Gene expression and Transcription factor activity based Relevance Network (GTRNetwork). Different combinations of TFA prediction algorithms and relevance score functions have been applied to find the most efficient combination. When the integrated GTRNetwork method was applied to E. coli data, the reconstructed genome-wide gene regulatory network predicted 381 new regulatory links. This reconstructed gene regulatory network including the predicted new regulatory links show promising biological significances. Many of the new links are verified by known TF binding site information, and many other links can be verified from the literature and databases such as EcoCyc. The reconstructed gene regulatory network is applied to a recent transcriptome analysis of E. coli during isobutanol stress. In addition to the 16 significantly changed TFAs detected in the original paper, another 7 significantly changed TFAs have been detected by

  8. Architecture of the Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet)

    SciTech Connect

    Aiken, R.J.; Carlson, R.A.; Foster, I.T.

    1997-01-01

    The research and education (R&E) community requires persistent and scaleable network infrastructure to concurrently support production and research applications as well as network research. In the past, the R&E community has relied on supporting parallel network and end-node infrastructures, which can be very expensive and inefficient for network service managers and application programmers. The grand challenge in networking is to provide support for multiple, concurrent, multi-layer views of the network for the applications and the network researchers, and to satisfy the sometimes conflicting requirements of both while ensuring one type of traffic does not adversely affect the other. Internet and telecommunications service providers will also benefit from a multi-modal infrastructure, which can provide smoother transitions to new technologies and allow for testing of these technologies with real user traffic while they are still in the pre-production mode. The authors proposed approach requires the use of as much of the same network and end system infrastructure as possible to reduce the costs needed to support both classes of activities (i.e., production and research). Breaking the infrastructure into segments and objects (e.g., routers, switches, multiplexors, circuits, paths, etc.) gives the capability to dynamically construct and configure the virtual active networks to address these requirements. These capabilities must be supported at the campus, regional, and wide-area network levels to allow for collaboration by geographically dispersed groups. The Multi-Modal Organizational Research and Production Heterogeneous Network (MORPHnet) described in this report is an initial architecture and framework designed to identify and support the capabilities needed for the proposed combined infrastructure and to address related research issues.

  9. Ensuring Data Storage Security in Tree cast Routing Architecture for Sensor Networks

    NASA Astrophysics Data System (ADS)

    Kumar, K. E. Naresh; Sagar, U. Vidya; Waheed, Mohd. Abdul

    2010-10-01

    In this paper presents recent advances in technology have made low-cost, low-power wireless sensors with efficient energy consumption. A network of such nodes can coordinate among themselves for distributed sensing and processing of certain data. For which, we propose an architecture to provide a stateless solution in sensor networks for efficient routing in wireless sensor networks. This type of architecture is known as Tree Cast. We propose a unique method of address allocation, building up multiple disjoint trees which are geographically inter-twined and rooted at the data sink. Using these trees, routing messages to and from the sink node without maintaining any routing state in the sensor nodes is possible. In contrast to traditional solutions, where the IT services are under proper physical, logical and personnel controls, this routing architecture moves the application software and databases to the large data centers, where the management of the data and services may not be fully trustworthy. This unique attribute, however, poses many new security challenges which have not been well understood. In this paper, we focus on data storage security, which has always been an important aspect of quality of service. To ensure the correctness of users' data in this architecture, we propose an effective and flexible distributed scheme with two salient features, opposing to its predecessors. By utilizing the homomorphic token with distributed verification of erasure-coded data, our scheme achieves the integration of storage correctness insurance and data error localization, i.e., the identification of misbehaving server(s). Unlike most prior works, the new scheme further supports secure and efficient dynamic operations on data blocks, including: data update, delete and append. Extensive security and performance analysis shows that the proposed scheme is highly efficient and resilient against Byzantine failure, malicious data modification attack, and even server

  10. Regulatory Networks in Pollen Development under Cold Stress

    PubMed Central

    Sharma, Kamal D.; Nayyar, Harsh

    2016-01-01

    Cold stress modifies anthers’ metabolic pathways to induce pollen sterility. Cold-tolerant plants, unlike the susceptible ones, produce high proportion of viable pollen. Anthers in susceptible plants, when exposed to cold stress, increase abscisic acid (ABA) metabolism and reduce ABA catabolism. Increased ABA negatively regulates expression of tapetum cell wall bound invertase and monosaccharide transport genes resulting in distorted carbohydrate pool in anther. Cold-stress also reduces endogenous levels of the bioactive gibberellins (GAs), GA4 and GA7, in susceptible anthers by repression of the GA biosynthesis genes. Here, we discuss recent findings on mechanisms of cold susceptibility in anthers which determine pollen sterility. We also discuss differences in regulatory pathways between cold-stressed anthers of susceptible and tolerant plants that decide pollen sterility or viability. PMID:27066044

  11. Transcriptional Regulatory Network Analysis of MYB Transcription Factor Family Genes in Rice

    PubMed Central

    Smita, Shuchi; Katiyar, Amit; Chinnusamy, Viswanathan; Pandey, Dev M.; Bansal, Kailash C.

    2015-01-01

    MYB transcription factor (TF) is one of the largest TF families and regulates defense responses to various stresses, hormone signaling as well as many metabolic and developmental processes in plants. Understanding these regulatory hierarchies of gene expression networks in response to developmental and environmental cues is a major challenge due to the complex interactions between the genetic elements. Correlation analyses are useful to unravel co-regulated gene pairs governing biological process as well as identification of new candidate hub genes in response to these complex processes. High throughput expression profiling data are highly useful for construction of co-expression networks. In the present study, we utilized transcriptome data for comprehensive regulatory network studies of MYB TFs by “top-down” and “guide-gene” approaches. More than 50% of OsMYBs were strongly correlated under 50 experimental conditions with 51 hub genes via “top-down” approach. Further, clusters were identified using Markov Clustering (MCL). To maximize the clustering performance, parameter evaluation of the MCL inflation score (I) was performed in terms of enriched GO categories by measuring F-score. Comparison of co-expressed cluster and clads analyzed from phylogenetic analysis signifies their evolutionarily conserved co-regulatory role. We utilized compendium of known interaction and biological role with Gene Ontology enrichment analysis to hypothesize function of coexpressed OsMYBs. In the other part, the transcriptional regulatory network analysis by “guide-gene” approach revealed 40 putative targets of 26 OsMYB TF hubs with high correlation value utilizing 815 microarray data. The putative targets with MYB-binding cis-elements enrichment in their promoter region, functional co-occurrence as well as nuclear localization supports our finding. Specially, enrichment of MYB binding regions involved in drought-inducibility implying their regulatory role in drought

  12. GINsim: a software suite for the qualitative modelling, simulation and analysis of regulatory networks.

    PubMed

    Gonzalez, A Gonzalez; Naldi, A; Sánchez, L; Thieffry, D; Chaouiya, C

    2006-05-01

    This paper presents GINsim, a Java software suite devoted to the qualitative modelling, analysis and simulation of genetic regulatory networks. Formally, our approach leans on discrete mathematical and graph-theoretical concepts. GINsim encompasses an intuitive graph editor, enabling the definition and the parameterisation of a regulatory graph, as well as a simulation engine to compute the corresponding qualitative dynamical behaviour. Our computational approach is illustrated by a preliminary model analysis of the inter-cellular regulatory network activating Notch at the dorsal-ventral boundary in the wing imaginal disc of Drosophila. We focus on the cross-regulations between five genes (within and between two cells), which implements the dorsal-ventral border in the developing imaginal disc. Our simulations qualitatively reproduce the wild-type developmental pathway, as well as the outcome of various types of experimental perturbations, such as loss-of-function mutations or ectopically induced gene expression. PMID:16434137

  13. Toward a complete in silico, multi-layered embryonic stem cell regulatory network

    PubMed Central

    Xu, Huilei; Schaniel, Christoph; Lemischka, Ihor R.; Ma’ayan, Avi

    2010-01-01

    Recent efforts in systematically profiling embryonic stem (ES) cells have yielded a wealth of high-throughput data. Complementarily, emerging databases and computational tools facilitate ES cell studies and further pave the way toward the in silico reconstruction of regulatory networks encompassing multiple molecular layers. Here, we briefly survey databases, algorithms, and software tools used to organize and analyze high-throughput experimental data collected to study mammalian cellular systems with a focus on ES cells. The vision of using heterogeneous data to reconstruct a complete multilayered ES cell regulatory network is discussed. This review also provides an accompanying manually extracted dataset of different types of regulatory interactions from low-throughput experimental ES cell studies available at http://amp.pharm.mssm.edu/iscmid/literature. PMID:20890967

  14. Systems and evolutionary characterization of microRNAs and their underlying regulatory networks in soybean cotyledons

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soybean cotyledons have evolved as a sink organ to synthesize and deposit the storage protein and oil reserve over seed maturation. MicroRNAs represent a class of key components in gene regulatory networks underlying diverse biological processes. However, our understanding of the microRNAs in soybea...

  15. Multi-tissue omics analyses reveal molecular regulatory networks for puberty in composite beef cattle

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Puberty is a complex physiological event by which animals mature into an adult capable of sexual reproduction. In order to enhance our understanding of the genes and regulatory pathways and networks involved in puberty, we characterized the transcriptome of five reproductive tissues (i.e., hypothal...

  16. Statistical Inference and Reverse Engineering of Gene Regulatory Networks from Observational Expression Data

    PubMed Central

    Emmert-Streib, Frank; Glazko, Galina V.; Altay, Gökmen; de Matos Simoes, Ricardo

    2012-01-01

    In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms. PMID:22408642

  17. Development of Bioinformatic and Experimental Technologies for Identification of Prokaryotic Regulatory Networks

    SciTech Connect

    Lawrence, Charles E; McCue, Lee Ann

    2008-07-31

    The transcription regulatory network is arguably the most important foundation of cellular function, since it exerts the most fundamental control over the abundance of virtually all of a cell’s functional macromolecules. The two major components of a prokaryotic cell’s transcription regulation network are the transcription factors (TFs) and the transcription factor binding sites (TFBS); these components are connected by the binding of TFs to their cognate TFBS under appropriate environmental conditions. Comparative genomics has proven to be a powerful bioinformatics method with which to study transcription regulation on a genome-wide level. We have further extended comparative genomics technologies that we introduced over the last several years. Specifically, we developed and applied statistical approaches to analysis of correlated sequence data (i.e., sequences from closely related species). We also combined these technologies with functional genomic, proteomic and sequence data from multiple species, and developed computational technologies that provide inferences on the regulatory network connections, identifying the cognate transcription factor for predicted regulatory sites. Arguably the most important contribution of this work emerged in the course of the project. Specifically, the development of novel procedures of estimation and prediction in discrete high-D settings has broad implications for biology, genomics and well beyond. We showed that these procedures enjoy advantages over existing technologies in the identification of TBFS. These efforts are aimed toward identifying a cell’s complete transcription regulatory network and underlying molecular mechanisms.

  18. Architectural Organization of the Metabolic Regulatory Enzyme Ghrelin O-Acyltransferase*

    PubMed Central

    Taylor, Martin S.; Ruch, Travis R.; Hsiao, Po-Yuan; Hwang, Yousang; Zhang, Pingfeng; Dai, Lixin; Huang, Cheng Ran Lisa; Berndsen, Christopher E.; Kim, Min-Sik; Pandey, Akhilesh; Wolberger, Cynthia; Marmorstein, Ronen; Machamer, Carolyn; Boeke, Jef D.; Cole, Philip A.

    2013-01-01

    Ghrelin O-acyltransferase (GOAT) is a polytopic integral membrane protein required for activation of ghrelin, a secreted metabolism-regulating peptide hormone. Although GOAT is a potential therapeutic target for the treatment of obesity and diabetes and plays a key role in other physiologic processes, little is known about its structure or mechanism. GOAT is a member of the membrane-bound O-acyltransferase (MBOAT) family, a group of polytopic integral membrane proteins involved in lipid-biosynthetic and lipid-signaling reactions from prokaryotes to humans. Here we use phylogeny and a variety of bioinformatic tools to predict the topology of GOAT. Using selective permeabilization indirect immunofluorescence microscopy in combination with glycosylation shift immunoblotting, we demonstrate that GOAT contains 11 transmembrane helices and one reentrant loop. Development of the V5Glyc tag, a novel, small, and sensitive dual topology reporter, facilitated these experiments. The MBOAT family invariant residue His-338 is in the ER lumen, consistent with other family members, but conserved Asn-307 is cytosolic, making it unlikely that both are involved in catalysis. Photocross-linking of synthetic ghrelin analogs and inhibitors demonstrates binding to the C-terminal region of GOAT, consistent with a role of His-338 in the active site. This knowledge of GOAT architecture is important for a deeper understa