WorldWideScience

Sample records for interaction network yeast

  1. A Global Protein Kinase and Phosphatase Interaction Network in Yeast

    Science.gov (United States)

    Breitkreutz, Ashton; Choi, Hyungwon; Sharom, Jeffrey R.; Boucher, Lorrie; Neduva, Victor; Larsen, Brett; Lin, Zhen-Yuan; Breitkreutz, Bobby-Joe; Stark, Chris; Liu, Guomin; Ahn, Jessica; Dewar-Darch, Danielle; Reguly, Teresa; Tang, Xiaojing; Almeida, Ricardo; Qin, Zhaohui Steve; Pawson, Tony; Gingras, Anne-Claude; Nesvizhskii, Alexey I.; Tyers, Mike

    2011-01-01

    The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions. Notably, the cell cycle phosphatase Cdc14 associated with multiple kinases that revealed roles for Cdc14 in mitogen-activated protein kinase signaling, the DNA damage response, and metabolism, whereas interactions of the target of rapamycin complex 1 (TORC1) uncovered new effector kinases in nitrogen and carbon metabolism. An extensive backbone of kinase-kinase interactions cross-connects the proteome and may serve to coordinate diverse cellular responses. PMID:20489023

  2. Dynamical analysis of yeast protein interaction network during the sake brewing process.

    Science.gov (United States)

    Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

    2011-12-01

    Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

  3. An insight into the complex prion-prion interaction network in the budding yeast Saccharomyces cerevisiae.

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    Du, Zhiqiang; Valtierra, Stephanie; Li, Liming

    2014-01-01

    The budding yeast Saccharomyces cerevisiae is a valuable model system for studying prion-prion interactions as it contains multiple prion proteins. A recent study from our laboratory showed that the existence of Swi1 prion ([SWI(+)]) and overproduction of Swi1 can have strong impacts on the formation of 2 other extensively studied yeast prions, [PSI(+)] and [PIN(+)] ([RNQ(+)]) (Genetics, Vol. 197, 685-700). We showed that a single yeast cell is capable of harboring at least 3 heterologous prion elements and these prions can influence each other's appearance positively and/or negatively. We also showed that during the de novo [PSI(+)] formation process upon Sup35 overproduction, the aggregation patterns of a preexisting inducer ([RNQ(+)] or [SWI(+)]) can undergo significant remodeling from stably transmitted dot-shaped aggregates to aggregates that co-localize with the newly formed Sup35 aggregates that are ring/ribbon/rod- shaped. Such co-localization disappears once the newly formed [PSI(+)] prion stabilizes. Our finding provides strong evidence supporting the "cross-seeding" model for prion-prion interactions and confirms earlier reports that the interactions among different prions and their prion proteins mostly occur at the initiation stages of prionogenesis. Our results also highlight a complex prion interaction network in yeast. We believe that elucidating the mechanism underlying the yeast prion-prion interaction network will not only provide insight into the process of prion de novo generation and propagation in yeast but also shed light on the mechanisms that govern protein misfolding, aggregation, and amyloidogenesis in higher eukaryotes.

  4. Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

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    Zhao Yi

    2010-12-01

    Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

  5. Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

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    Tommi Aho

    2010-05-01

    Full Text Available Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our

  6. Construction and application of a protein and genetic interaction network (yeast interactome).

    Science.gov (United States)

    Stuart, Gregory R; Copeland, William C; Strand, Micheline K

    2009-04-01

    Cytoscape is a bioinformatic data analysis and visualization platform that is well-suited to the analysis of gene expression data. To facilitate the analysis of yeast microarray data using Cytoscape, we constructed an interaction network (interactome) using the curated interaction data available from the Saccharomyces Genome Database (www.yeastgenome.org) and the database of yeast transcription factors at YEASTRACT (www.yeastract.com). These data were formatted and imported into Cytoscape using semi-automated methods, including Linux-based scripts, that simplified the process while minimizing the introduction of processing errors. The methods described for the construction of this yeast interactome are generally applicable to the construction of any interactome. Using Cytoscape, we illustrate the use of this interactome through the analysis of expression data from a recent yeast diauxic shift experiment. We also report and briefly describe the complex associations among transcription factors that result in the regulation of thousands of genes through coordinated changes in expression of dozens of transcription factors. These cells are thus able to sensitively regulate cellular metabolism in response to changes in genetic or environmental conditions through relatively small changes in the expression of large numbers of genes, affecting the entire yeast metabolome.

  7. In silico modeling of the yeast protein and protein family interaction network

    Science.gov (United States)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2004-03-01

    Understanding of how protein interaction networks of living organisms have evolved or are organized can be the first stepping stone in unveiling how life works on a fundamental ground. Here we introduce an in silico ``coevolutionary'' model for the protein interaction network and the protein family network. The essential ingredient of the model includes the protein family identity and its robustness under evolution, as well as the three previously proposed: gene duplication, divergence, and mutation. This model produces a prototypical feature of complex networks in a wide range of parameter space, following the generalized Pareto distribution in connectivity. Moreover, we investigate other structural properties of our model in detail with some specific values of parameters relevant to the yeast Saccharomyces cerevisiae, showing excellent agreement with the empirical data. Our model indicates that the physical constraints encoded via the domain structure of proteins play a crucial role in protein interactions.

  8. Positive Selection and Centrality in the Yeast and Fly Protein-Protein Interaction Networks

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    Sandip Chakraborty

    2016-01-01

    Full Text Available Proteins within a molecular network are expected to be subject to different selective pressures depending on their relative hierarchical positions. However, it is not obvious what genes within a network should be more likely to evolve under positive selection. On one hand, only mutations at genes with a relatively high degree of control over adaptive phenotypes (such as those encoding highly connected proteins are expected to be “seen” by natural selection. On the other hand, a high degree of pleiotropy at these genes is expected to hinder adaptation. Previous analyses of the human protein-protein interaction network have shown that genes under long-term, recurrent positive selection (as inferred from interspecific comparisons tend to act at the periphery of the network. It is unknown, however, whether these trends apply to other organisms. Here, we show that long-term positive selection has preferentially targeted the periphery of the yeast interactome. Conversely, in flies, genes under positive selection encode significantly more connected and central proteins. These observations are not due to covariation of genes’ adaptability and centrality with confounding factors. Therefore, the distribution of proteins encoded by genes under recurrent positive selection across protein-protein interaction networks varies from one species to another.

  9. TheCellMap.org: A Web-Accessible Database for Visualizing and Mining the Global Yeast Genetic Interaction Network.

    Science.gov (United States)

    Usaj, Matej; Tan, Yizhao; Wang, Wen; VanderSluis, Benjamin; Zou, Albert; Myers, Chad L; Costanzo, Michael; Andrews, Brenda; Boone, Charles

    2017-05-05

    Providing access to quantitative genomic data is key to ensure large-scale data validation and promote new discoveries. TheCellMap.org serves as a central repository for storing and analyzing quantitative genetic interaction data produced by genome-scale Synthetic Genetic Array (SGA) experiments with the budding yeast Saccharomyces cerevisiae In particular, TheCellMap.org allows users to easily access, visualize, explore, and functionally annotate genetic interactions, or to extract and reorganize subnetworks, using data-driven network layouts in an intuitive and interactive manner. Copyright © 2017 Usaj et al.

  10. Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

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    Canard Bruno

    2011-10-01

    Full Text Available Abstract Background The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4. Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. Results We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. Conclusions We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.

  11. Predicting the binding patterns of hub proteins: a study using yeast protein interaction networks.

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    Carson M Andorf

    Full Text Available Protein-protein interactions are critical to elucidating the role played by individual proteins in important biological pathways. Of particular interest are hub proteins that can interact with large numbers of partners and often play essential roles in cellular control. Depending on the number of binding sites, protein hubs can be classified at a structural level as singlish-interface hubs (SIH with one or two binding sites, or multiple-interface hubs (MIH with three or more binding sites. In terms of kinetics, hub proteins can be classified as date hubs (i.e., interact with different partners at different times or locations or party hubs (i.e., simultaneously interact with multiple partners.Our approach works in 3 phases: Phase I classifies if a protein is likely to bind with another protein. Phase II determines if a protein-binding (PB protein is a hub. Phase III classifies PB proteins as singlish-interface versus multiple-interface hubs and date versus party hubs. At each stage, we use sequence-based predictors trained using several standard machine learning techniques.Our method is able to predict whether a protein is a protein-binding protein with an accuracy of 94% and a correlation coefficient of 0.87; identify hubs from non-hubs with 100% accuracy for 30% of the data; distinguish date hubs/party hubs with 69% accuracy and area under ROC curve of 0.68; and SIH/MIH with 89% accuracy and area under ROC curve of 0.84. Because our method is based on sequence information alone, it can be used even in settings where reliable protein-protein interaction data or structures of protein-protein complexes are unavailable to obtain useful insights into the functional and evolutionary characteristics of proteins and their interactions.We provide a web server for our three-phase approach: http://hybsvm.gdcb.iastate.edu.

  12. Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

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    Holland, David O; Johnson, Margaret E

    2018-03-01

    Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

  13. Reconstruction of the yeast protein-protein interaction network involved in nutrient sensing and global metabolic regulation

    DEFF Research Database (Denmark)

    Nandy, Subir Kumar; Jouhten, Paula; Nielsen, Jens

    2010-01-01

    proteins. Despite the value of BioGRID for studying protein-protein interactions, there is a need for manual curation of these interactions in order to remove false positives. RESULTS: Here we describe an annotated reconstruction of the protein-protein interactions around four key nutrient......) and for all the interactions between them (edges). The annotated information is readily available utilizing the functionalities of network modelling tools such as Cytoscape and CellDesigner. CONCLUSIONS: The reported fully annotated interaction model serves as a platform for integrated systems biology studies...

  14. Divergent Evolution of the Transcriptional Network Controlled by Snf1-Interacting Protein Sip4 in Budding Yeasts.

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    Constance Mehlgarten

    Full Text Available Cellular responses to starvation are of ancient origin since nutrient limitation has always been a common challenge to the stability of living systems. Hence, signaling molecules involved in sensing or transducing information about limiting metabolites are highly conserved, whereas transcription factors and the genes they regulate have diverged. In eukaryotes the AMP-activated protein kinase (AMPK functions as a central regulator of cellular energy homeostasis. The yeast AMPK ortholog SNF1 controls the transcriptional network that counteracts carbon starvation conditions by regulating a set of transcription factors. Among those Cat8 and Sip4 have overlapping DNA-binding specificity for so-called carbon source responsive elements and induce target genes upon SNF1 activation. To analyze the evolution of the Cat8-Sip4 controlled transcriptional network we have compared the response to carbon limitation of Saccharomyces cerevisiae to that of Kluyveromyces lactis. In high glucose, S. cerevisiae displays tumor cell-like aerobic fermentation and repression of respiration (Crabtree-positive while K. lactis has a respiratory-fermentative life-style, respiration being regulated by oxygen availability (Crabtree-negative, which is typical for many yeasts and for differentiated higher cells. We demonstrate divergent evolution of the Cat8-Sip4 network and present evidence that a role of Sip4 in controlling anabolic metabolism has been lost in the Saccharomyces lineage. We find that in K. lactis, but not in S. cerevisiae, the Sip4 protein plays an essential role in C2 carbon assimilation including induction of the glyoxylate cycle and the carnitine shuttle genes. Induction of KlSIP4 gene expression by KlCat8 is essential under these growth conditions and a primary function of KlCat8. Both KlCat8 and KlSip4 are involved in the regulation of lactose metabolism in K. lactis. In chromatin-immunoprecipitation experiments we demonstrate binding of both, KlSip4 and

  15. Interaction Between Yeasts and Zinc

    Science.gov (United States)

    Nicola, Raffaele De; Walker, Graeme

    Zinc is an essential trace element in biological systems. For example, it acts as a cellular membrane stabiliser, plays a critical role in gene expression and genome modification and activates nearly 300 enzymes, including alcohol dehydrogenase. The present chapter will be focused on the influence of zinc on cell physiology of industrial yeast strains of Saccharomyces cerevisiae, with special regard to the uptake and subsequent utilisation of this metal. Zinc uptake by yeast is metabolism-dependent, with most of the available zinc translocated very quickly into the vacuole. At cell division, zinc is distributed from mother to daughter cells and this effectively lowers the individual cellular zinc concentration, which may become zinc depleted at the onset of the fermentation. Zinc influences yeast fermentative performance and examples will be provided relating to brewing and wine fermentations. Industrial yeasts are subjected to several stresses that may impair fermentation performance. Such stresses may also impact on yeast cell zinc homeostasis. This chapter will discuss the practical implications for the correct management of zinc bioavailability for yeast-based biotechnologies aimed at improving yeast growth, viability, fermentation performance and resistance to environmental stresses

  16. MPact: the MIPS protein interaction resource on yeast.

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    Güldener, Ulrich; Münsterkötter, Martin; Oesterheld, Matthias; Pagel, Philipp; Ruepp, Andreas; Mewes, Hans-Werner; Stümpflen, Volker

    2006-01-01

    In recent years, the Munich Information Center for Protein Sequences (MIPS) yeast protein-protein interaction (PPI) dataset has been used in numerous analyses of protein networks and has been called a gold standard because of its quality and comprehensiveness [H. Yu, N. M. Luscombe, H. X. Lu, X. Zhu, Y. Xia, J. D. Han, N. Bertin, S. Chung, M. Vidal and M. Gerstein (2004) Genome Res., 14, 1107-1118]. MPact and the yeast protein localization catalog provide information related to the proximity of proteins in yeast. Beside the integration of high-throughput data, information about experimental evidence for PPIs in the literature was compiled by experts adding up to 4300 distinct PPIs connecting 1500 proteins in yeast. As the interaction data is a complementary part of CYGD, interactive mapping of data on other integrated data types such as the functional classification catalog [A. Ruepp, A. Zollner, D. Maier, K. Albermann, J. Hani, M. Mokrejs, I. Tetko, U. Güldener, G. Mannhaupt, M. Münsterkötter and H. W. Mewes (2004) Nucleic Acids Res., 32, 5539-5545] is possible. A survey of signaling proteins and comparison with pathway data from KEGG demonstrates that based on these manually annotated data only an extensive overview of the complexity of this functional network can be obtained in yeast. The implementation of a web-based PPI-analysis tool allows analysis and visualization of protein interaction networks and facilitates integration of our curated data with high-throughput datasets. The complete dataset as well as user-defined sub-networks can be retrieved easily in the standardized PSI-MI format. The resource can be accessed through http://mips.gsf.de/genre/proj/mpact.

  17. Environmental influences on organotin-yeast interactions

    OpenAIRE

    White, Jane S.

    2002-01-01

    As a consequence of the widespread industrial and agricultural applications of organotin compounds, contamination of various ecosystems has occurred in recent decades. Understanding how these compounds interact with cellular membranes is essential in assessing the risks of organotin pollution. The organotins, tributyltin (TBT) and trimethyltin (TMT) and inorganic tin, Sn(IV), were investigated for their physical interactions with non-metabolising cells and protoplasts of the yeast, Candida ma...

  18. Full Data of Yeast Interacting Proteins Database (Original Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Yeast Interacting Proteins Database Full Data of Yeast Interacting Proteins Database (Origin...al Version) Data detail Data name Full Data of Yeast Interacting Proteins Database (Original Version) DOI 10....18908/lsdba.nbdc00742-004 Description of data contents The entire data in the Yeast Interacting Proteins Database...eir interactions are required. Several sources including YPD (Yeast Proteome Database, Costanzo, M. C., Hoga...ematic name in the SGD (Saccharomyces Genome Database; http://www.yeastgenome.org /). Bait gene name The gen

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

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    Gonzalo A Ruz

    2014-01-01

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

  20. An improved, bias-reduced probabilistic functional gene network of baker's yeast, Saccharomyces cerevisiae.

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    Insuk Lee

    2007-10-01

    Full Text Available Probabilistic functional gene networks are powerful theoretical frameworks for integrating heterogeneous functional genomics and proteomics data into objective models of cellular systems. Such networks provide syntheses of millions of discrete experimental observations, spanning DNA microarray experiments, physical protein interactions, genetic interactions, and comparative genomics; the resulting networks can then be easily applied to generate testable hypotheses regarding specific gene functions and associations.We report a significantly improved version (v. 2 of a probabilistic functional gene network of the baker's yeast, Saccharomyces cerevisiae. We describe our optimization methods and illustrate their effects in three major areas: the reduction of functional bias in network training reference sets, the application of a probabilistic model for calculating confidences in pair-wise protein physical or genetic interactions, and the introduction of simple thresholds that eliminate many false positive mRNA co-expression relationships. Using the network, we predict and experimentally verify the function of the yeast RNA binding protein Puf6 in 60S ribosomal subunit biogenesis.YeastNet v. 2, constructed using these optimizations together with additional data, shows significant reduction in bias and improvements in precision and recall, in total covering 102,803 linkages among 5,483 yeast proteins (95% of the validated proteome. YeastNet is available from http://www.yeastnet.org.

  1. Interactions between yeasts, fungicides and apple fruit russeting

    NARCIS (Netherlands)

    Gildemacher, P.R.; Heijne, B.; Silvestri, M.; Houbraken, J.; Hoekstra, E.; Theelen, B.; Boekhout, T.

    2006-01-01

    The effect of inoculations with yeasts occurring on apple surfaces and fungicide treatments on the russeting of Elstar apples was studied. Captan, dithianon and a water treatment were implemented to study the interaction between the fungicides, the inoculated yeast species and Aureobasidium

  2. Core Data of Yeast Interacting Proteins Database (Original Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available y are in the reverse direction. *1 A comprehensive two-hybrid analysis to explore the yeast protein interact...s. 2000 Jan 1;28(1):73-6. *2 The yeast proteome database (YPD) and Caenorhabditis elegans proteome database (WormPD): comprehensive...000 Jan 1;28(1):73-6. *3 A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisia

  3. Sirtuins as regulators of the yeast metabolic network

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    Markus eRalser

    2012-03-01

    Full Text Available There is growing evidence that the metabolic network is an integral regulator of cellularphysiology. Dynamic changes in metabolite concentrations, metabolic flux, or networktopology act as reporters of biological or environmental signals, and are required for the cellto trigger an appropriate biological reaction. Changes in the metabolic network are recognizedby specific sensory macromolecules and translated into a transcriptional or translationalresponse. The protein family of sirtuins, discovered more than 30 years ago as regulators ofsilent chromatin, seems to fulfill the role of a metabolic sensor during aging and conditions ofcaloric restriction. NAD+/NADH interconverting metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase and alcohol dehydrogenase, as well as enzymes involved inNAD(H, synthesis provide or deprive NAD+ in close proximity to Sir2. This influence sirtuinactivity, and facilitates a dynamic response of the metabolic network to changes inmetabolism with effects on physiology and aging. The molecular network downstream Sir2,however, is complex. In just two orders, Sir2’s metabolism-related interactions span half ofthe yeast proteome, and are connected with virtually every physiological process. Thus,although it is fundamental to analyze single molecular mechanisms, it is at the same timecrucial to consider this genome-scale complexity when correlating single molecular eventswith phenotypes such as aging, cell growth, or stress resistance.

  4. Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

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    Heavner Benjamin D

    2012-06-01

    Full Text Available Abstract Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Additional file 1 Function testYeastModel.m.m. Click here for file Additional file 2 Function model

  5. Characterization of the interaction of yeast enolase with polynucleotides.

    Science.gov (United States)

    al-Giery, A G; Brewer, J M

    1992-09-23

    Yeast enolase is inhibited under certain conditions by DNA. The enzyme binds to single-stranded DNA-cellulose. Inhibition was used for routine characterization of the interaction. The presence of the substrate 2-phospho-D-glycerate reduces inhibition and binding. Both yeast enolase isozymes behave similarly. Impure yeast enolase was purified by adsorption onto a single-stranded DNA-cellulose column followed by elution with substrate. Interaction with RNA, double-stranded DNA, or degraded DNA results in less inhibition, suggesting that yeast enolase preferentially binds single-stranded DNA. However, yeast enolase is not a DNA-unwinding protein. The enzyme is inhibited by the short synthetic oligodeoxynucleotides G6, G8 and G10 but not T8 or T6, suggesting some base specificity in the interaction. The interaction is stronger at more acid pH values, with an apparent pK of 5.6. The interaction is prevented by 0.3 M KCl, suggesting that electrostatic factors are important. Histidine or lysine reverse the inhibition at lower concentrations, while phosphate is still more effective. Binding of single-stranded DNA to enolase reduces the reaction of protein histidyl residues with diethylpyrocarbonate. The inhibition of yeast enolase by single-stranded DNA is not total, and suggests the active site is not directly involved in the interaction. Binding of substrate may induce a conformational change in the enzyme that interferes with DNA binding and vice versa.

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

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    Christopher E Hart

    2006-12-01

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

  7. Catalytic site interactions in yeast OMP synthase

    DEFF Research Database (Denmark)

    Hansen, Michael Riis; Barr, Eric W.; Jensen, Kaj Frank

    2014-01-01

    45 (2006) 5330-5342]. This behavior was investigated in the yeast enzyme by mutations in the conserved catalytic loop and 5-phosphoribosyl-1-diphosphate (PRPP) binding motif. Although the reaction is mechanistically sequential, the wild-type (WT) enzyme shows parallel lines in double reciprocal...

  8. Yeast Interacting Proteins Database: YFR015C, YFR015C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available yeast homolog; expression induced by glucose limitation, nitrogen starvation, environmental stress, and entr...ression induced by glucose limitation, nitrogen starvation, environmental stress, and entry into stationary ...tion, nitrogen starvation, environmental stress, and entry into stationary phase Rows with this bait as bait..., the more highly expressed yeast homolog; expression induced by glucose limitation, nitrogen starvation, environmental

  9. Yeast Interacting Proteins Database: YFR015C, YJL137C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available yeast homolog; expression induced by glucose limitation, nitrogen starvation, environmental stress, and entr...pression induced by glucose limitation, nitrogen starvation, environmental stress, and entry into stationary

  10. Statistical indicators of collective behavior and functional clusters in gene networks of yeast

    Science.gov (United States)

    Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

    2006-03-01

    We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

  11. Binding properties of SUMO-interacting motifs (SIMs) in yeast.

    Science.gov (United States)

    Jardin, Christophe; Horn, Anselm H C; Sticht, Heinrich

    2015-03-01

    Small ubiquitin-like modifier (SUMO) conjugation and interaction play an essential role in many cellular processes. A large number of yeast proteins is known to interact non-covalently with SUMO via short SUMO-interacting motifs (SIMs), but the structural details of this interaction are yet poorly characterized. In the present work, sequence analysis of a large dataset of 148 yeast SIMs revealed the existence of a hydrophobic core binding motif and a preference for acidic residues either within or adjacent to the core motif. Thus the sequence properties of yeast SIMs are highly similar to those described for human. Molecular dynamics simulations were performed to investigate the binding preferences for four representative SIM peptides differing in the number and distribution of acidic residues. Furthermore, the relative stability of two previously observed alternative binding orientations (parallel, antiparallel) was assessed. For all SIMs investigated, the antiparallel binding mode remained stable in the simulations and the SIMs were tightly bound via their hydrophobic core residues supplemented by polar interactions of the acidic residues. In contrary, the stability of the parallel binding mode is more dependent on the sequence features of the SIM motif like the number and position of acidic residues or the presence of additional adjacent interaction motifs. This information should be helpful to enhance the prediction of SIMs and their binding properties in different organisms to facilitate the reconstruction of the SUMO interactome.

  12. Update History of This Database - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Yeast Interacting Proteins Database Update History of This Database Date Update contents 201...0/03/29 Yeast Interacting Proteins Database English archive site is opened. 2000/12/4 Yeast Interacting Proteins Database...( http://itolab.cb.k.u-tokyo.ac.jp/Y2H/ ) is released. About This Database Database Description... Download License Update History of This Database Site Policy | Contact Us Update History of This Database... - Yeast Interacting Proteins Database | LSDB Archive ...

  13. Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling

    Directory of Open Access Journals (Sweden)

    Wang Woei-Fuh

    2008-03-01

    Full Text Available Abstract Background With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality. Results Motivated by inferring transcriptional compensation (TC interactions in yeast, a stepwise structural equation modeling algorithm (SSEM is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC SSEM works best. SSEM with Bayesian information criterion (BIC results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1 small groups of genes that are synthetic sick or lethal (SSL to SGS1, and (2 a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1, SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2 are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted. Conclusion SSEM is a useful tool for inferring genetic networks, and the

  14. Yeast Interacting Proteins Database: YFR015C, YLR258W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available yeast homolog; expression induced by glucose limitation, nitrogen starvation, environmental stress, and entr...n synthase, similar to Gsy1p; expression induced by glucose limitation, nitrogen ...; expression induced by glucose limitation, nitrogen starvation, environmental stress, and entry into statio...ogen synthase, similar to Gsy1p; expression induced by glucose limitation, nitrogen starvation, heat shock,

  15. Yeast systems biology to unravel the network of life

    DEFF Research Database (Denmark)

    Mustacchi, Roberta; Hohmann, S; Nielsen, Jens

    2006-01-01

    Systems biology focuses on obtaining a quantitative description of complete biological systems, even complete cellular function. In this way, it will be possible to perform computer-guided design of novel drugs, advanced therapies for treatment of complex diseases, and to perform in silico design....... Furthermore, it serves as an industrial workhorse for production of a wide range of chemicals and pharmaceuticals. Systems biology involves the combination of novel experimental techniques from different disciplines as well as functional genomics, bioinformatics and mathematical modelling, and hence no single...... laboratory has access to all the necessary competences. For this reason the Yeast Systems Biology Network (YSBN) has been established. YSBN will coordinate research efforts, in yeast systems biology and, through the recently obtained EU funding for a Coordination Action, it will be possible to set...

  16. Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

    DEFF Research Database (Denmark)

    Usaite, Renata; Jewett, Michael Christopher; Soberano de Oliveira, Ana Paula

    2009-01-01

    Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite...

  17. Transcriptional robustness and protein interactions are associated in yeast

    Directory of Open Access Journals (Sweden)

    Conant Gavin C

    2011-05-01

    Full Text Available Abstract Background Robustness to insults, both external and internal, is a characteristic feature of life. One level of biological organization for which noise and robustness have been extensively studied is gene expression. Cells have a variety of mechanisms for buffering noise in gene expression, but it is not completely clear what rules govern whether or not a given gene uses such tools to maintain appropriate expression. Results Here, we show a general association between the degree to which yeast cells have evolved mechanisms to buffer changes in gene expression and whether they possess protein-protein interactions. We argue that this effect bears an affinity to epistasis, because yeast appears to have evolved regulatory mechanisms such that distant changes in gene copy number for a protein-protein interaction partner gene can alter a gene's expression. This association is not unexpected given recent work linking epistasis and the deleterious effects of changes in gene dosage (i.e., the dosage balance hypothesis. Using gene expression data from artificial aneuploid strains of bakers' yeast, we found that genes coding for proteins that physically interact with other proteins show less expression variation in response to aneuploidy than do other genes. This effect is even more pronounced for genes whose products interact with proteins encoded on aneuploid chromosomes. We further found that genes targeted by transcription factors encoded on aneuploid chromosomes were more likely to change in expression after aneuploidy. Conclusions We suggest that these observations can be best understood as resulting from the higher fitness cost of misexpression in epistatic genes and a commensurate greater regulatory control of them.

  18. Interacting neural networks

    Science.gov (United States)

    Metzler, R.; Kinzel, W.; Kanter, I.

    2000-08-01

    Several scenarios of interacting neural networks which are trained either in an identical or in a competitive way are solved analytically. In the case of identical training each perceptron receives the output of its neighbor. The symmetry of the stationary state as well as the sensitivity to the used training algorithm are investigated. Two competitive perceptrons trained on mutually exclusive learning aims and a perceptron which is trained on the opposite of its own output are examined analytically. An ensemble of competitive perceptrons is used as decision-making algorithms in a model of a closed market (El Farol Bar problem or the Minority Game. In this game, a set of agents who have to make a binary decision is considered.); each network is trained on the history of minority decisions. This ensemble of perceptrons relaxes to a stationary state whose performance can be better than random.

  19. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

    DEFF Research Database (Denmark)

    Liu, Guodong; Marras, Antonio; Nielsen, Jens

    2014-01-01

    regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional....... While many large-scale TRN reconstructions have been reported for yeast, these reconstructions still need to be improved regarding the functionality and dynamic property of the regulatory interactions. In addition, mathematical modeling approaches need to be further developed to efficiently integrate...

  20. Yeast Interacting Proteins Database: YPR103W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available tein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors...gulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf

  1. Yeast Interacting Proteins Database: YLR347C, YLR377C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available gy-mediated degradation depending on growth conditions; interacts with Vid30p Rows with this prey as prey (4...r autophagy-mediated degradation depending on growth conditions; interacts with V

  2. Yeast Interacting Proteins Database: YNL189W, YLR377C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available phagy-mediated degradation depending on growth conditions; interacts with Vid30p Rows with this prey as prey...ated or autophagy-mediated degradation depending on growth conditions; interacts

  3. Yeast Interacting Proteins Database: YML064C, YLR377C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available d or autophagy-mediated degradation depending on growth conditions; interacts with Vid30p Rows with this pre...er proteasome-mediated or autophagy-mediated degradation depending on growth conditions; interacts with Vid3

  4. Yeast Interacting Proteins Database: YGL237C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote... expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein

  5. Yeast Interacting Proteins Database: YLR447C, YDR277C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available uction pathway, required for repression of transcription by Rgt1p; interacts with Rgt1p and the Snf3p and Rgt2p glucose sensors...transduction pathway, required for repression of transcription by Rgt1p; interacts with Rgt1p and the Snf3p and Rgt2p glucose sensors

  6. Yeast Interacting Proteins Database: YKL002W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding prote...xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp

  7. Yeast Interacting Proteins Database: YLR447C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available xpression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Sp...; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act

  8. Yeast Interacting Proteins Database: YMR280C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available olved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensor... glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, an

  9. Yeast Interacting Proteins Database: YMR125W, YPL178W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available so contains Sto1p, component of the spliceosomal commitment complex; interacts with Npl3p, possibly to packa...lso contains Sto1p, component of the spliceosomal commitment complex; interacts with Npl3p, possibly to pack

  10. Yeast Interacting Proteins Database: YGR013W, YKL012W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available tion U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the formation of the second commitm... PRP40 U1 snRNP protein involved in splicing, interacts with the branchpoint-binding protein during the form...ation of the second commitment complex Rows with this prey as prey (1) Rows with

  11. Yeast Interacting Proteins Database: YDL239C, YGR268C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...sembly of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spi

  12. Yeast Interacting Proteins Database: YDL239C, YPL255W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...ediate assembly of a Don1p-containing structure at the leading edge of the prospore membrane via interaction

  13. Yeast Interacting Proteins Database: YDR176W, YDL239C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle pole...ining structure at the leading edge of the prospore membrane via interaction with spindle pole body componen...DY3 Prey description Protein required for spore wall formation, thought to mediate assembly of a Don1p-conta

  14. Yeast Interacting Proteins Database: YDL239C, YOR324C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p... a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle pole

  15. Yeast Interacting Proteins Database: YDL239C, YDR148C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...mbly of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spind

  16. Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Sloep, Peter

    2009-01-01

    The original publication is available from www.springerlink.com. Sloep, P. (2009). Social Interaction in Learning Networks. In R. Koper (Ed.), Learning Network Services for Professional Development (pp 13-15). Berlin, Germany: Springer Verlag.

  17. Yeast Interacting Proteins Database: YGL145W, YNL258C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ripheral membrane protein required for Golgi-to-ER retrograde traffic; component ... membrane protein required for Golgi-to-ER retrograde traffic; component of the ER target site that interact

  18. Yeast Interacting Proteins Database: YNR051C, YER151C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available that coregulates anterograde and retrograde transport between the endoplasmic reticulum and Golgi compartme...C UBP3 Ubiquitin-specific protease that interacts with Bre5p to co-regulate anterograde and retrograde...t coregulates anterograde and retrograde transport between the endoplasmic reticulum and Golgi compartments;...3 Prey description Ubiquitin-specific protease that interacts with Bre5p to co-regulate anterograde and retrograde

  19. Yeast Interacting Proteins Database: YLR377C, YLR377C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available sis pathway, required for glucose metabolism; undergoes either proteasome-mediated or autophagy-mediated degradation depending...utophagy-mediated degradation depending on growth conditions; interacts with Vid30p Rows with this prey as p...d or autophagy-mediated degradation depending on growth conditions; interacts wit...me-mediated or autophagy-mediated degradation depending on growth conditions; int

  20. Improving functional modules discovery by enriching interaction networks with gene profiles

    KAUST Repository

    Salem, Saeed; Alroobi, Rami; Banitaan, Shadi; Seridi, Loqmane; Aljarah, Ibrahim; Brewer, James

    2013-01-01

    networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional

  1. Network Compression as a Quality Measure for Protein Interaction Networks

    Science.gov (United States)

    Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

    2012-01-01

    With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

  2. Yeast Interacting Proteins Database: YOR302W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available rol of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt...tein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt1

  3. Yeast Interacting Proteins Database: YOR358W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ; interacts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; act...rotein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator o

  4. Yeast Interacting Proteins Database: YGL127C, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available ith protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regula...rotein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sensors

  5. Yeast Interacting Proteins Database: YNL258C, YKR022C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available YNL258C DSL1 Peripheral membrane protein required for Golgi-to-ER retrograde traffi...equired for Golgi-to-ER retrograde traffic; component of the ER target site that interacts with coatomer, th...it ORF YNL258C Bait gene name DSL1 Bait description Peripheral membrane protein r

  6. Yeast Interacting Proteins Database: YDL239C, YLR423C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...cription Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

  7. Yeast Interacting Proteins Database: YDL239C, YHR184W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...e wall formation, thought to mediate assembly of a Don1p-containing structure at the leading edge of the pro

  8. Yeast Interacting Proteins Database: YDL239C, YPL124W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...ore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading edge of the p

  9. Yeast Interacting Proteins Database: YDL239C, YPL070W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...cription Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

  10. Yeast Interacting Proteins Database: YDL239C, YAL028W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p... to mediate assembly of a Don1p-containing structure at the leading edge of the prospore membrane via intera

  11. Yeast Interacting Proteins Database: YDL239C, YML042W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...iption Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

  12. Yeast Interacting Proteins Database: YDL239C, YLR072W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p... wall formation, thought to mediate assembly of a Don1p-containing structure at the leading edge of the pros

  13. Yeast Interacting Proteins Database: YDL239C, YBR072W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...ht to mediate assembly of a Don1p-containing structure at the leading edge of the prospore membrane via inte

  14. Yeast Interacting Proteins Database: YDL239C, YKL103C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...ait description Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading

  15. Yeast Interacting Proteins Database: YOR047C, YKL038W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available racts with protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a...Bait description Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose senso...rs Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator of the tra

  16. Yeast Interacting Proteins Database: YFR049W, YOR047C [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available protein kinase Snf1p, glucose sensors Snf3p and Rgt2p, and TATA-binding protein Spt15p; acts as a regulator... (0) YOR047C STD1 Protein involved in control of glucose-regulated gene expression; interacts with protein kinase Snf1p, glucose sens...ors Snf3p and Rgt2p, and TATA-binding protein Spt15p; ac

  17. Yeast Interacting Proteins Database: YDL239C, YDR273W [Yeast Interacting Proteins Database

    Lifescience Database Archive (English)

    Full Text Available of a Don1p-containing structure at the leading edge of the prospore membrane via interaction with spindle p...it as prey (1) YDR273W DON1 Meiosis-specific component of the spindle pole body, part of the leading... edge protein (LEP) coat, forms a ring-like structure at the leading edge of the prospore...ption Protein required for spore wall formation, thought to mediate assembly of a Don1p-containing structure at the leading...description Meiosis-specific component of the spindle pole body, part of the leading edge protein (LEP) coat

  18. Yeast Augmented Network Analysis (YANA: a new systems approach to identify therapeutic targets for human genetic diseases [v1; ref status: indexed, http://f1000r.es/3gk

    Directory of Open Access Journals (Sweden)

    David J. Wiley

    2014-06-01

    Full Text Available Genetic interaction networks that underlie most human diseases are highly complex and poorly defined. Better-defined networks will allow identification of a greater number of therapeutic targets. Here we introduce our Yeast Augmented Network Analysis (YANA approach and test it with the X-linked spinal muscular atrophy (SMA disease gene UBA1. First, we express UBA1 and a mutant variant in fission yeast and use high-throughput methods to identify fission yeast genetic modifiers of UBA1. Second, we analyze available protein-protein interaction network databases in both fission yeast and human to construct UBA1 genetic networks. Third, from these networks we identified potential therapeutic targets for SMA. Finally, we validate one of these targets in a vertebrate (zebrafish SMA model. This study demonstrates the power of combining synthetic and chemical genetics with a simple model system to identify human disease gene networks that can be exploited for treating human diseases.

  19. Information processing in the transcriptional regulatory network of yeast: Functional robustness

    Directory of Open Access Journals (Sweden)

    Dehmer Matthias

    2009-03-01

    Full Text Available Abstract Background Gene networks are considered to represent various aspects of molecular biological systems meaningfully because they naturally provide a systems perspective of molecular interactions. In this respect, the functional understanding of the transcriptional regulatory network is considered as key to elucidate the functional organization of an organism. Results In this paper we study the functional robustness of the transcriptional regulatory network of S. cerevisiae. We model the information processing in the network as a first order Markov chain and study the influence of single gene perturbations on the global, asymptotic communication among genes. Modification in the communication is measured by an information theoretic measure allowing to predict genes that are 'fragile' with respect to single gene knockouts. Our results demonstrate that the predicted set of fragile genes contains a statistically significant enrichment of so called essential genes that are experimentally found to be necessary to ensure vital yeast. Further, a structural analysis of the transcriptional regulatory network reveals that there are significant differences between fragile genes, hub genes and genes with a high betweenness centrality value. Conclusion Our study does not only demonstrate that a combination of graph theoretical, information theoretical and statistical methods leads to meaningful biological results but also that such methods allow to study information processing in gene networks instead of just their structural properties.

  20. Networks and Interactivity

    DEFF Research Database (Denmark)

    Considine, Mark; Lewis, Jenny

    2012-01-01

    of `street-level' employment services staff for the impacts of this. Contrary to expectations, networking has generally declined over the last decade. There are signs of path dependence in networking patterns within each country, but also a convergence of patterns for the UK and Australia......The systemic reform of employment services in OECD countries was driven by New Public Management (NPM) and then post-NPM reforms, when first-phase changes such as privatization were amended with `joined up' processes to help manage fragmentation. This article examines the networking strategies......, but not The Netherlands. Networking appears to be mediated by policy and regulatory imperatives....

  1. Physicochemical and biochemical interactions in yeast immobilization by adhesion to a cellulose based support

    OpenAIRE

    Kurec, M.; Brányik, Tomáš; Mota, André; Domingues, Lucília; Teixeira, J. A.

    2008-01-01

    An important quality of yeast cell wall is the ability to adhere to other cell walls or solid surfaces. This feature of yeast is responsible for technologically important phenomena such as flocculation at the end of beer fermentation and cell adhesion to immobilization supports e.g. spent grains, DEAE-cellulose etc. Physicochemical properties of yeast surfaces, e.g. hydrophobicity and surface charge, have a substantial impact on cell adhesion and flocculation. The interaction e...

  2. Online Social Network Interactions:

    Directory of Open Access Journals (Sweden)

    Hui-Jung Chang

    2018-01-01

    Full Text Available A cross-cultural comparison of social networking structure on McDonald’s Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald’s Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald’s Facebook fan network has more fans, while Taiwan’s McDonald’s Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

  3. Interactions of Condensed Tannins with Saccharomyces cerevisiae Yeast Cells and Cell Walls: Tannin Location by Microscopy.

    Science.gov (United States)

    Mekoue Nguela, Julie; Vernhet, Aude; Sieczkowski, Nathalie; Brillouet, Jean-Marc

    2015-09-02

    Interactions between grape tannins/red wine polyphenols and yeast cells/cell walls was previously studied within the framework of red wine aging and the use of yeast-derived products as an alternative to aging on lees. Results evidenced a quite different behavior between whole cells (biomass grown to elaborate yeast-derived products, inactivated yeast, and yeast inactivated after autolysis) and yeast cell walls (obtained from mechanical disruption of the biomass). Briefly, whole cells exhibited a high capacity to irreversibly adsorb grape and wine tannins, whereas only weak interactions were observed for cell walls. This last point was quite unexpected considering the literature and called into question the real role of cell walls in yeasts' ability to fix tannins. In the present work, tannin location after interactions between grape and wine tannins and yeast cells and cell walls was studied by means of transmission electron microscopy, light epifluorescence, and confocal microscopy. Microscopy observations evidenced that if tannins interact with cell walls, and especially cell wall mannoproteins, they also diffuse freely through the walls of dead cells to interact with their plasma membrane and cytoplasmic components.

  4. Topology of molecular interaction networks

    NARCIS (Netherlands)

    Winterbach, W.; Van Mieghem, P.; Reinders, M.; Wang, H.; De Ridder, D.

    2013-01-01

    Molecular interactions are often represented as network models which have become the common language of many areas of biology. Graphs serve as convenient mathematical representations of network models and have themselves become objects of study. Their topology has been intensively researched over

  5. Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

    Science.gov (United States)

    Usaite, Renata; Jewett, Michael C; Oliveira, Ana Paula; Yates, John R; Olsson, Lisbeth; Nielsen, Jens

    2009-01-01

    Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite levels in wild type, Δsnf1, Δsnf4, and Δsnf1Δsnf4 knockout strains. Using four newly developed computational tools, including novel DOGMA sub-network analysis, we showed the benefits of three-level ome-data integration to uncover the global Snf1 kinase role in yeast. We for the first time identified Snf1's global regulation on gene and protein expression levels, and showed that yeast Snf1 has a far more extensive function in controlling energy metabolism than reported earlier. Additionally, we identified complementary roles of Snf1 and Snf4. Similar to the function of AMPK in humans, our findings showed that Snf1 is a low-energy checkpoint and that yeast can be used more extensively as a model system for studying the molecular mechanisms underlying the global regulation of AMPK in mammals, failure of which leads to metabolic diseases. PMID:19888214

  6. Interactive Network Exploration with Orange

    Directory of Open Access Journals (Sweden)

    Miha Štajdohar

    2013-04-01

    Full Text Available Network analysis is one of the most widely used techniques in many areas of modern science. Most existing tools for that purpose are limited to drawing networks and computing their basic general characteristics. The user is not able to interactively and graphically manipulate the networks, select and explore subgraphs using other statistical and data mining techniques, add and plot various other data within the graph, and so on. In this paper we present a tool that addresses these challenges, an add-on for exploration of networks within the general component-based environment Orange.

  7. Influence of degree correlations on network structure and stability in protein-protein interaction networks

    Directory of Open Access Journals (Sweden)

    Zimmer Ralf

    2007-08-01

    Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

  8. Interactions between Drosophila and its natural yeast symbionts-Is Saccharomyces cerevisiae a good model for studying the fly-yeast relationship?

    Science.gov (United States)

    Hoang, Don; Kopp, Artyom; Chandler, James Angus

    2015-01-01

    Yeasts play an important role in the biology of the fruit fly, Drosophila melanogaster. In addition to being a valuable source of nutrition, yeasts affect D. melanogaster behavior and interact with the host immune system. Most experiments investigating the role of yeasts in D. melanogaster biology use the baker's yeast, Saccharomyces cerevisiae. However, S. cerevisiae is rarely found with natural populations of D. melanogaster or other Drosophila species. Moreover, the strain of S. cerevisiae used most often in D. melanogaster experiments is a commercially and industrially important strain that, to the best of our knowledge, was not isolated from flies. Since disrupting natural host-microbe interactions can have profound effects on host biology, the results from D. melanogaster-S. cerevisiae laboratory experiments may not be fully representative of host-microbe interactions in nature. In this study, we explore the D. melanogaster-yeast relationship using five different strains of yeast that were isolated from wild Drosophila populations. Ingested live yeasts have variable persistence in the D. melanogaster gastrointestinal tract. For example, Hanseniaspora occidentalis persists relative to S. cerevisiae, while Brettanomyces naardenensis is removed. Despite these differences in persistence relative to S. cerevisiae, we find that all yeasts decrease in total abundance over time. Reactive oxygen species (ROS) are an important component of the D. melanogaster anti-microbial response and can inhibit S. cerevisiae growth in the intestine. To determine if sensitivity to ROS explains the differences in yeast persistence, we measured yeast growth in the presence and absence of hydrogen peroxide. We find that B. naardenesis is completely inhibited by hydrogen peroxide, while H. occidentalis is not, which is consistent with yeast sensitivity to ROS affecting persistence within the D. melanogaster gastrointestinal tract. We also compared the feeding preference of D

  9. Yeast-yeast interactions revealed by aromatic profile analysis of Sauvignon Blanc wine fermented by single or co-culture of non-Saccharomyces and Saccharomyces yeasts.

    Science.gov (United States)

    Sadoudi, Mohand; Tourdot-Maréchal, Raphaëlle; Rousseaux, Sandrine; Steyer, Damien; Gallardo-Chacón, Joan-Josep; Ballester, Jordi; Vichi, Stefania; Guérin-Schneider, Rémi; Caixach, Josep; Alexandre, Hervé

    2012-12-01

    There has been increasing interest in the use of selected non-Saccharomyces yeasts in co-culture with Saccharomyces cerevisiae. The main reason is that the multistarter fermentation process is thought to simulate indigenous fermentation, thus increasing wine aroma complexity while avoiding the risks linked to natural fermentation. However, multistarter fermentation is characterised by complex and largely unknown interactions between yeasts. Consequently the resulting wine quality is rather unpredictable. In order to better understand the interactions that take place between non-Saccharomyces and Saccharomyces yeasts during alcoholic fermentation, we analysed the volatile profiles of several mono-culture and co-cultures. Candida zemplinina, Torulaspora delbrueckii and Metschnikowia pulcherrima were used to conduct fermentations either in mono-culture or in co-culture with S. cerevisiae. Up to 48 volatile compounds belonging to different chemical families were quantified. For the first time, we show that C. zemplinina is a strong producer of terpenes and lactones. We demonstrate by means of multivariate analysis that different interactions exist between the co-cultures studied. We observed a synergistic effect on aromatic compound production when M. pulcherrima was in co-culture with S. cerevisiae. However a negative interaction was observed between C. zemplinina and S. cerevisiae, which resulted in a decrease in terpene and lactone content. These interactions are independent of biomass production. The aromatic profiles of T. delbrueckii and S. cerevisiae in mono-culture and in co-culture are very close, and are biomass-dependent, reflecting a neutral interaction. This study reveals that a whole family of compounds could be altered by such interactions. These results suggest that the entire metabolic pathway is affected by these interactions. Copyright © 2012 Elsevier Ltd. All rights reserved.

  10. Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

    Science.gov (United States)

    Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.

    2014-01-01

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891

  11. p53 inhibits autophagy by interacting with the human ortholog of yeast Atg17, RB1CC1/FIP200.

    Science.gov (United States)

    Morselli, Eugenia; Shen, Shensi; Ruckenstuhl, Christoph; Bauer, Maria Anna; Mariño, Guillermo; Galluzzi, Lorenzo; Criollo, Alfredo; Michaud, Mickael; Maiuri, Maria Chiara; Chano, Tokuhiro; Madeo, Frank; Kroemer, Guido

    2011-08-15

    The tumor suppressor protein p53 tonically suppresses autophagy when it is present in the cytoplasm. This effect is phylogenetically conserved from mammals to nematodes, and human p53 can inhibit autophagy in yeast, as we show here. Bioinformatic investigations of the p53 interactome in relationship to the autophagy-relevant protein network underscored the possible relevance of a direct molecular interaction between p53 and the mammalian ortholog of the essential yeast autophagy protein Atg17, namely RB1-inducible coiled-coil protein 1 (RB1CC1), also called FAK family kinase-interacting protein of 200 KDa (FIP200). Mutational analyses revealed that a single point mutation in p53 (K382R) abolished its capacity to inhibit autophagy upon transfection into p53-deficient human colon cancer or yeast cells. In conditions in which wild-type p53 co-immunoprecipitated with RB1CC1/FIP200, p53 (K382R) failed to do so, underscoring the importance of the physical interaction between these proteins for the control of autophagy. In conclusion, p53 regulates autophagy through a direct molecular interaction with RB1CC1/FIP200, a protein that is essential for the very apical step of autophagy initiation.

  12. Dynamic and interacting complex networks

    Science.gov (United States)

    Dickison, Mark E.

    This thesis employs methods of statistical mechanics and numerical simulations to study some aspects of dynamic and interacting complex networks. The mapping of various social and physical phenomena to complex networks has been a rich field in the past few decades. Subjects as broad as petroleum engineering, scientific collaborations, and the structure of the internet have all been analyzed in a network physics context, with useful and universal results. In the first chapter we introduce basic concepts in networks, including the two types of network configurations that are studied and the statistical physics and epidemiological models that form the framework of the network research, as well as covering various previously-derived results in network theory that are used in the work in the following chapters. In the second chapter we introduce a model for dynamic networks, where the links or the strengths of the links change over time. We solve the model by mapping dynamic networks to the problem of directed percolation, where the direction corresponds to the time evolution of the network. We show that the dynamic network undergoes a percolation phase transition at a critical concentration pc, that decreases with the rate r at which the network links are changed. The behavior near criticality is universal and independent of r. We find that for dynamic random networks fundamental laws are changed: i) The size of the giant component at criticality scales with the network size N for all values of r, rather than as N2/3 in static network, ii) In the presence of a broad distribution of disorder, the optimal path length between two nodes in a dynamic network scales as N1/2, compared to N1/3 in a static network. The third chapter consists of a study of the effect of quarantine on the propagation of epidemics on an adaptive network of social contacts. For this purpose, we analyze the susceptible-infected-recovered model in the presence of quarantine, where susceptible

  13. Detection of Protein Interactions in T3S Systems Using Yeast Two-Hybrid Analysis.

    Science.gov (United States)

    Nilles, Matthew L

    2017-01-01

    Two-hybrid systems, sometimes termed interaction traps, are genetic systems designed to find and analyze interactions between proteins. The most common systems are yeast based (commonly Saccharomyces cerevisae) and rely on the functional reconstitution of the GAL4 transcriptional activator. Reporter genes, such as the lacZ gene of Escherichia coli (encodes β-galactosidase), are placed under GAL4-dependent transcriptional control to provide quick and reliable detection of protein interactions. In this method the use of a yeast-based two-hybrid system is described to study protein interactions between components of type III secretion systems.

  14. Unveiling protein functions through the dynamics of the interaction network.

    Directory of Open Access Journals (Sweden)

    Irene Sendiña-Nadal

    Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

  15. Systematic Analysis of the DNA Damage Response Network in Telomere Defective Budding Yeast

    Directory of Open Access Journals (Sweden)

    Eva-Maria Holstein

    2017-07-01

    Full Text Available Functional telomeres are critically important to eukaryotic genetic stability. Scores of proteins and pathways are known to affect telomere function. Here, we report a series of related genome-wide genetic interaction screens performed on budding yeast cells with acute or chronic telomere defects. Genetic interactions were examined in cells defective in Cdc13 and Stn1, affecting two components of CST, a single stranded DNA (ssDNA binding complex that binds telomeric DNA. For comparison, genetic interactions were also examined in cells with defects in Rfa3, affecting the major ssDNA binding protein, RPA, which has overlapping functions with CST at telomeres. In more complex experiments, genetic interactions were measured in cells lacking EXO1 or RAD9, affecting different aspects of the DNA damage response, and containing a cdc13-1 induced telomere defect. Comparing fitness profiles across these data sets helps build a picture of the specific responses to different types of dysfunctional telomeres. The experiments show that each context reveals different genetic interactions, consistent with the idea that each genetic defect causes distinct molecular defects. To help others engage with the large volumes of data, the data are made available via two interactive web-based tools: Profilyzer and DIXY. One particularly striking genetic interaction observed was that the chk1∆ mutation improved fitness of cdc13-1 exo1∆ cells more than other checkpoint mutations (ddc1∆, rad9∆, rad17∆, and rad24∆, whereas, in cdc13-1 cells, the effects of all checkpoint mutations were similar. We show that this can be explained by Chk1 stimulating resection—a new function for Chk1 in the eukaryotic DNA damage response network.

  16. Dictyostelium discoideum as a novel host system to study the interaction between phagocytes and yeasts

    Directory of Open Access Journals (Sweden)

    Barbara Koller

    2016-10-01

    Full Text Available The social amoeba Dictyostelium discoideum is a well-established model organism to study the interaction between bacteria and phagocytes. In contrast, research using D. discoideum as a host model for fungi is rare. We describe a comprehensive study, which uses D. discoideum as a host model system to investigate the interaction with apathogenic (Saccharomyces cerevisiae and pathogenic (Candida sp. yeast. We show that Dictyostelium can be co-cultivated with yeasts on solid media, offering a convenient test to study the interaction between fungi and phagocytes. We demonstrate that a number of D. discoideum mutants increase (atg1-, kil1-, kil2- or decrease (atg6- the ability of the amoebae to predate yeast cells. On the yeast side, growth characteristics, reduced phagocytosis rate, as well as known virulence factors of C. albicans (EFG1, CPH1, HGC1, ICL1 contribute to the resistance of yeast cells against predation by the amoebae. Investigating haploid C. albicans strains, we suggest using the amoebae plate test for screening purposes after random mutagenesis. Finally, we discuss the potential of our adapted amoebae plate test to use D. discoideum for risk assessment of yeast strains.

  17. Database Description - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Yeast Interacting Proteins Database Database Description General information of database Database... name Yeast Interacting Proteins Database Alternative name - DOI 10.18908/lsdba.nbdc00742-000 Creator C...-ken 277-8561 Tel: +81-4-7136-3989 FAX: +81-4-7136-3979 E-mail : Database classif...s cerevisiae Taxonomy ID: 4932 Database description Information on interactions and related information obta...l Acad Sci U S A. 2001 Apr 10;98(8):4569-74. Epub 2001 Mar 13. External Links: Original website information Database

  18. Delineating functional principles of the bow tie structure of a kinase-phosphatase network in the budding yeast.

    Science.gov (United States)

    Abd-Rabbo, Diala; Michnick, Stephen W

    2017-03-16

    Kinases and phosphatases (KP) form complex self-regulating networks essential for cellular signal processing. In spite of having a wealth of data about interactions among KPs and their substrates, we have very limited models of the structures of the directed networks they form and consequently our ability to formulate hypotheses about how their structure determines the flow of information in these networks is restricted. We assembled and studied the largest bona fide kinase-phosphatase network (KP-Net) known to date for the yeast Saccharomyces cerevisiae. Application of the vertex sort (VS) algorithm on the KP-Net allowed us to elucidate its hierarchical structure in which nodes are sorted into top, core and bottom layers, forming a bow tie structure with a strongly connected core layer. Surprisingly, phosphatases tend to sort into the top layer, implying they are less regulated by phosphorylation than kinases. Superposition of the widest range of KP biological properties over the KP-Net hierarchy shows that core layer KPs: (i), receive the largest number of inputs; (ii), form bottlenecks implicated in multiple pathways and in decision-making; (iii), and are among the most regulated KPs both temporally and spatially. Moreover, top layer KPs are more abundant and less noisy than those in the bottom layer. Finally, we showed that the VS algorithm depends on node degrees without biasing the biological results of the sorted network. The VS algorithm is available as an R package ( https://cran.r-project.org/web/packages/VertexSort/index.html ). The KP-Net model we propose possesses a bow tie hierarchical structure in which the top layer appears to ensure highest fidelity and the core layer appears to mediate signal integration and cell state-dependent signal interpretation. Our model of the yeast KP-Net provides both functional insight into its organization as we understand today and a framework for future investigation of information processing in yeast and eukaryotes

  19. Graph theoretic analysis of protein interaction networks of eukaryotes

    Science.gov (United States)

    Goh, K.-I.; Kahng, B.; Kim, D.

    2005-11-01

    Owing to the recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, have been assayed. The datasets are obtained mainly by using the yeast hybrid method, which contains false-positive and false-negative simultaneously. Accordingly, while it is desirable to test such datasets through further wet experiments, here we invoke recent developed network theory to test such high-throughput datasets in a simple way. Based on the fact that the key biological processes indispensable to maintaining life are conserved across eukaryotic species, and the comparison of structural properties of the protein interaction networks (PINs) of the two species with those of the yeast PIN, we find that while the worm and yeast PIN datasets exhibit similar structural properties, the current fly dataset, though most comprehensively screened ever, does not reflect generic structural properties correctly as it is. The modularity is suppressed and the connectivity correlation is lacking. Addition of interologs to the current fly dataset increases the modularity and enhances the occurrence of triangular motifs as well. The connectivity correlation function of the fly, however, remains distinct under such interolog additions, for which we present a possible scenario through an in silico modeling.

  20. Nucleo-mitochondrial interaction of yeast in response to cadmium sulfide quantum dot exposure

    International Nuclear Information System (INIS)

    Pasquali, Francesco; Agrimonti, Caterina; Pagano, Luca; Zappettini, Andrea; Villani, Marco; Marmiroli, Marta; White, Jason C.; Marmiroli, Nelson

    2017-01-01

    Highlights: • CdS QDs induce oxidative stress in yeast. • CdS QDs disrupt mitochondrial membrane potentials and morphology. • CdS QDs do not affect mtDNA content. • CdS QDs modify the expression of genes involved in mitochondrial organization and function. • Deletion of some of these genes induces either tolerant or sensitive phenotypes to CdS QDs. - Abstract: Cell sensitivity to quantum dots (QDs) has been attributed to a cascade triggered by oxidative stress leading to apoptosis. The role and function of mitochondria in animal cells are well understood but little information is available on the complex genetic networks that regulate nucleo-mitochondrial interaction. The effect of CdS QD exposure in yeast Saccharomyces cerevisiae was assessed under conditions of limited lethality (<10%), using cell physiological and morphological endpoints. Whole-genomic array analysis and the screening of a deletion mutant library were also carried out. The results showed that QDs: increased the level of reactive oxygen species (ROS) and decreased the level of reduced vs oxidized glutathione (GSH/GSSG); reduced oxygen consumption and the abundance of respiratory cytochromes; disrupted mitochondrial membrane potentials and affected mitochondrial morphology. Exposure affected the capacity of cells to grow on galactose, which requires nucleo-mitochondrial involvement. However, QDs exposure did not materially induce respiratory deficient (RD) mutants but only RD phenocopies. All of these cellular changes were correlated with several key nuclear genes, including TOM5 and FKS1, involved in the maintenance of mitochondrial organization and function. The consequences of these cellular effects are discussed in terms of dysregulation of cell function in response to these “pathological mitochondria”.

  1. Nucleo-mitochondrial interaction of yeast in response to cadmium sulfide quantum dot exposure

    Energy Technology Data Exchange (ETDEWEB)

    Pasquali, Francesco; Agrimonti, Caterina [Department of Life Sciences, University of Parma, Parma (Italy); Pagano, Luca [Department of Life Sciences, University of Parma, Parma (Italy); Stockbridge school of Agriculture, University of Massachusetts, Amherst, MA (United States); The Connecticut Agricultural Experiment Station, New Haven, CT (United States); Zappettini, Andrea; Villani, Marco [IMEM-CNR - Istituto dei Materiali per l' Elettronica ed il Magnetismo, Parma (Italy); Marmiroli, Marta [Department of Life Sciences, University of Parma, Parma (Italy); White, Jason C. [The Connecticut Agricultural Experiment Station, New Haven, CT (United States); Marmiroli, Nelson, E-mail: nelson.marmiroli@unipr.it [Department of Life Sciences, University of Parma, Parma (Italy); CINSA - Consorzio Interuniversitario Nazionale per le Scienze Ambientali, University of Parma, Parma (Italy)

    2017-02-15

    Highlights: • CdS QDs induce oxidative stress in yeast. • CdS QDs disrupt mitochondrial membrane potentials and morphology. • CdS QDs do not affect mtDNA content. • CdS QDs modify the expression of genes involved in mitochondrial organization and function. • Deletion of some of these genes induces either tolerant or sensitive phenotypes to CdS QDs. - Abstract: Cell sensitivity to quantum dots (QDs) has been attributed to a cascade triggered by oxidative stress leading to apoptosis. The role and function of mitochondria in animal cells are well understood but little information is available on the complex genetic networks that regulate nucleo-mitochondrial interaction. The effect of CdS QD exposure in yeast Saccharomyces cerevisiae was assessed under conditions of limited lethality (<10%), using cell physiological and morphological endpoints. Whole-genomic array analysis and the screening of a deletion mutant library were also carried out. The results showed that QDs: increased the level of reactive oxygen species (ROS) and decreased the level of reduced vs oxidized glutathione (GSH/GSSG); reduced oxygen consumption and the abundance of respiratory cytochromes; disrupted mitochondrial membrane potentials and affected mitochondrial morphology. Exposure affected the capacity of cells to grow on galactose, which requires nucleo-mitochondrial involvement. However, QDs exposure did not materially induce respiratory deficient (RD) mutants but only RD phenocopies. All of these cellular changes were correlated with several key nuclear genes, including TOM5 and FKS1, involved in the maintenance of mitochondrial organization and function. The consequences of these cellular effects are discussed in terms of dysregulation of cell function in response to these “pathological mitochondria”.

  2. Statistical Mechanics of Temporal and Interacting Networks

    Science.gov (United States)

    Zhao, Kun

    In the last ten years important breakthroughs in the understanding of the topology of complexity have been made in the framework of network science. Indeed it has been found that many networks belong to the universality classes called small-world networks or scale-free networks. Moreover it was found that the complex architecture of real world networks strongly affects the critical phenomena defined on these structures. Nevertheless the main focus of the research has been the characterization of single and static networks. Recently, temporal networks and interacting networks have attracted large interest. Indeed many networks are interacting or formed by a multilayer structure. Example of these networks are found in social networks where an individual might be at the same time part of different social networks, in economic and financial networks, in physiology or in infrastructure systems. Moreover, many networks are temporal, i.e. the links appear and disappear on the fast time scale. Examples of these networks are social networks of contacts such as face-to-face interactions or mobile-phone communication, the time-dependent correlations in the brain activity and etc. Understanding the evolution of temporal and multilayer networks and characterizing critical phenomena in these systems is crucial if we want to describe, predict and control the dynamics of complex system. In this thesis, we investigate several statistical mechanics models of temporal and interacting networks, to shed light on the dynamics of this new generation of complex networks. First, we investigate a model of temporal social networks aimed at characterizing human social interactions such as face-to-face interactions and phone-call communication. Indeed thanks to the availability of data on these interactions, we are now in the position to compare the proposed model to the real data finding good agreement. Second, we investigate the entropy of temporal networks and growing networks , to provide

  3. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  4. Yeast ribonuclease III uses a network of multiple hydrogen bonds for RNA binding and cleavage.

    Science.gov (United States)

    Lavoie, Mathieu; Abou Elela, Sherif

    2008-08-19

    Members of the bacterial RNase III family recognize a variety of short structured RNAs with few common features. It is not clear how this group of enzymes supports high cleavage fidelity while maintaining a broad base of substrates. Here we show that the yeast orthologue of RNase III (Rnt1p) uses a network of 2'-OH-dependent interactions to recognize substrates with different structures. We designed a series of bipartite substrates permitting the distinction between binding and cleavage defects. Each substrate was engineered to carry a single or multiple 2'- O-methyl or 2'-fluoro ribonucleotide substitutions to prevent the formation of hydrogen bonds with a specific nucleotide or group of nucleotides. Interestingly, introduction of 2'- O-methyl ribonucleotides near the cleavage site increased the rate of catalysis, indicating that 2'-OH are not required for cleavage. Substitution of nucleotides in known Rnt1p binding site with 2'- O-methyl ribonucleotides inhibited cleavage while single 2'-fluoro ribonucleotide substitutions did not. This indicates that while no single 2'-OH is essential for Rnt1p cleavage, small changes in the substrate structure are not tolerated. Strikingly, several nucleotide substitutions greatly increased the substrate dissociation constant with little or no effect on the Michaelis-Menten constant or rate of catalysis. Together, the results indicate that Rnt1p uses a network of nucleotide interactions to identify its substrate and support two distinct modes of binding. One mode is primarily mediated by the dsRNA binding domain and leads to the formation of stable RNA/protein complex, while the other requires the presence of the nuclease and N-terminal domains and leads to RNA cleavage.

  5. Interactions between yeasts and bacteria in the smear surface-ripened cheeses.

    Science.gov (United States)

    Corsetti, A; Rossi, J; Gobbetti, M

    2001-09-19

    In the initial phase of ripening, the microflora of bacterial smear surface-ripened cheeses such as Limburger, Taleggio, Brick, Münster and Saint-Paulin and that of surface mould-ripened cheeses such as Camembert and Brie may be similar, but at the end of the ripening, bacteria such as Brevibacterium spp., Arthrobacter spp., Micrococcus spp., Corynebacterium spp. and moulds such as Penicillium camemberti are, respectively, the dominant microorganisms. Yeasts such as Candida spp., Cryptococcus spp., Debaryomyces spp., Geotrichum candidum, Pichia spp., Rhodotorula spp., Saccharomyces spp. and Yarrowia lipolytica are often and variably isolated from the smear surface-ripened cheeses. Although not dominant within the microorganisms of the smear surface-ripened cheeses, yeasts establish significant interactions with moulds and especially bacteria, including surface bacteria and lactic acid bacteria. Some aspects of the interactions between yeasts and bacteria in such type of cheeses are considered in this paper.

  6. Physical Interactions between Yeast Pichia guilliermondii and Post-Harvest Fruit Pathogen Penicillium expansum

    Directory of Open Access Journals (Sweden)

    SRI WIDYASTUTI

    2008-03-01

    Full Text Available Attachment of yeast cells or bacteria on fungal hyphae have been observed in various antagonisms between microorganisms. Physical interactions between yeast Pichia guilliermondii and postharvest fruit pathogen Penicillium expansum in culture were studied in detail using light and transmission electron microscope to give better understanding on their mode of antagonism. Both organisms were co-cultured for 24-hr on potato dextrose agar. Light microscopy observations on the co-culture showed that the yeast cells attached firmly on the fungal hyphae. This attachment was inhibited by several substances such as enzymes degrading protein (protease or trypsin, a respiration inhibitor (sodium azide, an acid (hydrochloric acid or an alkali (sodium hydroxide. Although autoclaved hyphae did not affect the attachment, but boiled enzymes and autoclaved yeast cells totally abolished the attachment. These evidences suggested that the attachment might be an active process mediated by certain protein from live yeast cells. Transmission electron micrographs on the ultrastructure of the co-culture revealed that the hyphae showed abnormalities in their structure and organelles, and a degree of obvious damage. Physical interactions observed in this study could be contributed to the mechanism of antagonism between P. guilliermondii and P. expansum.

  7. Prediction of quantitative phenotypes based on genetic networks: a case study in yeast sporulation

    Directory of Open Access Journals (Sweden)

    Shen Li

    2010-09-01

    Full Text Available Abstract Background An exciting application of genetic network is to predict phenotypic consequences for environmental cues or genetic perturbations. However, de novo prediction for quantitative phenotypes based on network topology is always a challenging task. Results Using yeast sporulation as a model system, we have assembled a genetic network from literature and exploited Boolean network to predict sporulation efficiency change upon deleting individual genes. We observe that predictions based on the curated network correlate well with the experimentally measured values. In addition, computational analysis reveals the robustness and hysteresis of the yeast sporulation network and uncovers several patterns of sporulation efficiency change caused by double gene deletion. These discoveries may guide future investigation of underlying mechanisms. We have also shown that a hybridized genetic network reconstructed from both temporal microarray data and literature is able to achieve a satisfactory prediction accuracy of the same quantitative phenotypes. Conclusions This case study illustrates the value of predicting quantitative phenotypes based on genetic network and provides a generic approach.

  8. Interactive optical trapping shows that confinement is a determinant of growth in a mixed yeast culture

    DEFF Research Database (Denmark)

    Arneborg, N.; Siegumfeldt, H.; Andersen, G.H.

    2005-01-01

    Applying a newly developed user-interactive optical trapping system, we controllably surrounded individual cells of one yeast species, Hanseniaspora uvarum, with viable cells of another yeast species, Saccharomyces cerevisiae, thus creating a confinement of the former. Growth of surrounded and non......-surrounded H. uvarum cells was followed under a microscope by determining their generation time. The average generation time of surrounded H. uvarum cells was 15% higher than that of non-surrounded cells thereby showing that the confinement imposed by viable S. cerevisiae cells on H. uvarum inhibits growth...

  9. Interaction between lactic acid bacteria and yeasts in airag, an alcoholic fermented milk.

    Science.gov (United States)

    Sudun; Wulijideligen; Arakawa, Kensuke; Miyamoto, Mari; Miyamoto, Taku

    2013-01-01

    The interaction between nine lactic acid bacteria (LAB) and five yeast strains isolated from airag of Inner Mongolia Autonomic Region, China was investigated. Three representative LAB and two yeasts showed symbioses were selected and incubated in 10% (w/v) reconstituted skim milk as single and mixed cultures to measure viable count, titratable acidity, ethanol and sugar content every 24 h for 1 week. LAB and yeasts showed high viable counts in the mixed cultures compared to the single cultures. Titratable acidity of the mixed cultures was obviously enhanced compared with that of the single cultures, except for the combinations of Lactobacillus reuteri 940B3 with Saccharomyces cerevisiae 4C and Lactobacillus helveticus 130B4 with Candida kefyr 2Y305. C. kefyr 2Y305 produced large amounts of ethanol (maximum 1.35 g/L), whereas non-lactose-fermenting S. cerevisiae 4C produced large amounts of ethanol only in the mixed cultures. Total glucose and galactose content increased while lactose content decreased in the single cultures of Leuconostoc mesenteroides 6B2081 and Lb. helveticus 130B4. However, both glucose and galactose were completely consumed and lactose was markedly reduced in the mixed cultures with yeasts. The result suggests that yeasts utilize glucose and galactose produced by LAB lactase to promote cell growth. © 2012 The Authors. Animal Science Journal © 2012 Japanese Society of Animal Science.

  10. Network Physiology: How Organ Systems Dynamically Interact.

    Science.gov (United States)

    Bartsch, Ronny P; Liu, Kang K L; Bashan, Amir; Ivanov, Plamen Ch

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems.

  11. Network Physiology: How Organ Systems Dynamically Interact

    Science.gov (United States)

    Bartsch, Ronny P.; Liu, Kang K. L.; Bashan, Amir; Ivanov, Plamen Ch.

    2015-01-01

    We systematically study how diverse physiologic systems in the human organism dynamically interact and collectively behave to produce distinct physiologic states and functions. This is a fundamental question in the new interdisciplinary field of Network Physiology, and has not been previously explored. Introducing the novel concept of Time Delay Stability (TDS), we develop a computational approach to identify and quantify networks of physiologic interactions from long-term continuous, multi-channel physiological recordings. We also develop a physiologically-motivated visualization framework to map networks of dynamical organ interactions to graphical objects encoded with information about the coupling strength of network links quantified using the TDS measure. Applying a system-wide integrative approach, we identify distinct patterns in the network structure of organ interactions, as well as the frequency bands through which these interactions are mediated. We establish first maps representing physiologic organ network interactions and discover basic rules underlying the complex hierarchical reorganization in physiologic networks with transitions across physiologic states. Our findings demonstrate a direct association between network topology and physiologic function, and provide new insights into understanding how health and distinct physiologic states emerge from networked interactions among nonlinear multi-component complex systems. The presented here investigations are initial steps in building a first atlas of dynamic interactions among organ systems. PMID:26555073

  12. Strong FANCA/FANCG but weak FANCA/FANCC interaction in the yeast 2-hybrid system.

    Science.gov (United States)

    Reuter, T; Herterich, S; Bernhard, O; Hoehn, H; Gross, H J

    2000-01-15

    Three of at least 8 Fanconi anemia (FA) genes have been cloned (FANCA, FANCC, FANCG), but their functions remain unknown. Using the yeast 2-hybrid system and full-length cDNA, the authors found a strong interaction between FANCA and FANCG proteins. They also obtained evidence for a weak interaction between FANCA and FANCC. Neither FANCA nor FANCC was found to interact with itself. These results support the notion of a functional association between the FA gene products. (Blood. 2000;95:719-720)

  13. Investigation of Fanconi anemia protein interactions by yeast two-hybrid analysis.

    Science.gov (United States)

    Huber, P A; Medhurst, A L; Youssoufian, H; Mathew, C G

    2000-02-05

    Fanconi anemia is a chromosomal breakage disorder with eight complementation groups (A-H), and three genes (FANCA, FANCC, and FANCG) have been identified. Initial investigations of the interaction between FANCA and FANCC, principally by co-immunoprecipitation, have proved controversial. We used the yeast two-hybrid assay to test for interactions of the FANCA, FANCC, and FANCG proteins. No activation of the reporter gene was observed in yeast co-expressing FANCA and FANCC as hybrid proteins, suggesting that FANCA does not directly interact with FANCC. However, a high level of activation was found when FANCA was co-expressed with FANCG, indicating strong, direct interaction between these proteins. Both FANCA and FANCG show weak but consistent interaction with themselves, suggesting that their function may involve dimerisation. The site of interaction of FANCG with FANCA was investigated by analysis of 12 mutant fragments of FANCG. Although both N- and C-terminal fragments did interact, binding to FANCA was drastically reduced, suggesting that more than one region of the FANCG protein is required for proper interaction with FANCA. Copyright 2000 Academic Press.

  14. Construction and evaluation of yeast expression networks by database-guided predictions

    Directory of Open Access Journals (Sweden)

    Katharina Papsdorf

    2016-05-01

    Full Text Available DNA-Microarrays are powerful tools to obtain expression data on the genome-wide scale. We performed microarray experiments to elucidate the transcriptional networks, which are up- or down-regulated in response to the expression of toxic polyglutamine proteins in yeast. Such experiments initially generate hit lists containing differentially expressed genes. To look into transcriptional responses, we constructed networks from these genes. We therefore developed an algorithm, which is capable of dealing with very small numbers of microarrays by clustering the hits based on co-regulatory relationships obtained from the SPELL database. Here, we evaluate this algorithm according to several criteria and further develop its statistical capabilities. Initially, we define how the number of SPELL-derived co-regulated genes and the number of input hits influences the quality of the networks. We then show the ability of our networks to accurately predict further differentially expressed genes. Including these predicted genes into the networks improves the network quality and allows quantifying the predictive strength of the networks based on a newly implemented scoring method. We find that this approach is useful for our own experimental data sets and also for many other data sets which we tested from the SPELL microarray database. Furthermore, the clusters obtained by the described algorithm greatly improve the assignment to biological processes and transcription factors for the individual clusters. Thus, the described clustering approach, which will be available through the ClusterEx web interface, and the evaluation parameters derived from it represent valuable tools for the fast and informative analysis of yeast microarray data.

  15. Vulnerability of networks of interacting Markov chains.

    Science.gov (United States)

    Kocarev, L; Zlatanov, N; Trajanov, D

    2010-05-13

    The concept of vulnerability is introduced for a model of random, dynamical interactions on networks. In this model, known as the influence model, the nodes are arranged in an arbitrary network, while the evolution of the status at a node is according to an internal Markov chain, but with transition probabilities that depend not only on the current status of that node but also on the statuses of the neighbouring nodes. Vulnerability is treated analytically and numerically for several networks with different topological structures, as well as for two real networks--the network of infrastructures and the EU power grid--identifying the most vulnerable nodes of these networks.

  16. Interactions of grape tannins and wine polyphenols with a yeast protein extract, mannoproteins and β-glucan

    OpenAIRE

    Mekoue Nguela, Julie; Poncet-Legrand, Celine; Sieczkowski, N.; Vernhet, Aude

    2016-01-01

    At present, there is a great interest in enology for yeast derived products to replace aging on lees in winemaking or as an alternative for wine fining. These are yeast protein extracts (YPE), cell walls and mannoproteins. Our aim was to further understand the mechanisms that drive interactions between these components and red wine polyphenols. To this end, interactions between grape skin tannins or wine polyphenols or tannins and a YPE, a mannoprotein fraction and a β-glucan were monitored b...

  17. Hsp12p and PAU genes are involved in ecological interactions between natural yeast strains.

    Science.gov (United States)

    Rivero, Damaríz; Berná, Luisa; Stefanini, Irene; Baruffini, Enrico; Bergerat, Agnes; Csikász-Nagy, Attila; De Filippo, Carlotta; Cavalieri, Duccio

    2015-08-01

    The coexistence of different yeasts in a single vineyard raises the question on how they communicate and why slow growers are not competed out. Genetically modified laboratory strains of Saccharomyces cerevisiae are extensively used to investigate ecological interactions, but little is known about the genes regulating cooperation and competition in ecologically relevant settings. Here, we present evidences of Hsp12p-dependent altruistic and contact-dependent competitive interactions between two natural yeast isolates. Hsp12p is released during cell death for public benefit by a fast-growing strain that also produces a killer toxin to inhibit growth of a slow grower that can enjoy the benefits of released Hsp12p. We also show that the protein Pau5p is essential in the defense against the killer effect. Our results demonstrate that the combined action of Hsp12p, Pau5p and a killer toxin is sufficient to steer a yeast community. © 2015 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.

  18. A human protein interaction network shows conservation of aging processes between human and invertebrate species.

    Directory of Open Access Journals (Sweden)

    Russell Bell

    2009-03-01

    Full Text Available We have mapped a protein interaction network of human homologs of proteins that modify longevity in invertebrate species. This network is derived from a proteome-scale human protein interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity network is composed of 175 human homologs of proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human proteins that interact with these homologs. Overall, the network consists of 3,271 binary interactions among 2,338 unique proteins. A comparison of the average node degree of the human longevity homologs with random sets of proteins in the Core Network indicates that human homologs of longevity proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that proteins in this network are significantly more connected than would be expected by chance. To examine the relationship of this network to human aging phenotypes, we compared the genes encoding longevity network proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity protein homologs and their interactors, we observed enrichments for differentially expressed genes in the network. To determine whether homologs of human longevity interacting proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity protein interaction network presented here is enriched for novel conserved longevity proteins.

  19. Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

    DEFF Research Database (Denmark)

    Di Roberto, Raphaël B; Chang, Belinda; Trusina, Ala

    2016-01-01

    All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae......, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While...... demonstrate that a new receptor-ligand pair can evolve through network-altering mutations independently of receptor-ligand binding, and suggest a potential role for such mutations in disease....

  20. Statistical physics of interacting neural networks

    Science.gov (United States)

    Kinzel, Wolfgang; Metzler, Richard; Kanter, Ido

    2001-12-01

    Recent results on the statistical physics of time series generation and prediction are presented. A neural network is trained on quasi-periodic and chaotic sequences and overlaps to the sequence generator as well as the prediction errors are calculated numerically. For each network there exists a sequence for which it completely fails to make predictions. Two interacting networks show a transition to perfect synchronization. A pool of interacting networks shows good coordination in the minority game-a model of competition in a closed market. Finally, as a demonstration, a perceptron predicts bit sequences produced by human beings.

  1. Dissecting Fission Yeast Shelterin Interactions via MICro-MS Links Disruption of Shelterin Bridge to Tumorigenesis

    Directory of Open Access Journals (Sweden)

    Jinqiang Liu

    2015-09-01

    Full Text Available Shelterin, a six-member complex, protects telomeres from nucleolytic attack and regulates their elongation by telomerase. Here, we have developed a strategy, called MICro-MS (Mapping Interfaces via Crosslinking-Mass Spectrometry, that combines crosslinking-mass spectrometry and phylogenetic analysis to identify contact sites within the complex. This strategy allowed identification of separation-of-function mutants of fission yeast Ccq1, Poz1, and Pot1 that selectively disrupt their respective interactions with Tpz1. The various telomere dysregulation phenotypes observed in these mutants further emphasize the critical regulatory roles of Tpz1-centered shelterin interactions in telomere homeostasis. Furthermore, the conservation between fission yeast Tpz1-Pot1 and human TPP1-POT1 interactions led us to map a human melanoma-associated POT1 mutation (A532P to the TPP1-POT1 interface. Diminished TPP1-POT1 interaction caused by hPOT1-A532P may enable unregulated telomere extension, which, in turn, helps cancer cells to achieve replicative immortality. Therefore, our study reveals a connection between shelterin connectivity and tumorigenicity.

  2. Tombusvirus-yeast interactions identify conserved cell-intrinsic viral restriction factors

    Directory of Open Access Journals (Sweden)

    Zsuzsanna eSasvari

    2014-08-01

    Full Text Available To combat viral infections, plants possess innate and adaptive immune pathways, such as RNA silencing, R gene and recessive gene-mediated resistance mechanisms. However, it is likely that additional cell-intrinsic restriction factors (CIRF are also involved in limiting plant virus replication. This review discusses novel CIRFs with antiviral functions, many of them RNA-binding proteins or affecting the RNA binding activities of viral replication proteins. The CIRFs against tombusviruses have been identified in yeast (Saccharomyces cerevisiae, which is developed as an advanced model organism. Grouping of the identified CIRFs based on their known cellular functions and subcellular localization in yeast reveals that TBSV replication is limited by a wide variety of host gene functions. Yeast proteins with the highest connectivity in the network map include the well-characterized Xrn1p 5’-3’ exoribonuclease, Act1p actin protein and Cse4p centromere protein. The protein network map also reveals an important interplay between the pro-viral Hsp70 cellular chaperone and the antiviral co-chaperones, and possibly key roles for the ribosomal or ribosome-associated factors. We discuss the antiviral functions of selected CIRFs, such as the RNA binding nucleolin, ribonucleases, WW-domain proteins, single- and multi-domain cyclophilins, TPR-domain co-chaperones and cellular ion pumps. These restriction factors frequently target the RNA-binding region in the viral replication proteins, thus interfering with the recruitment of the viral RNA for replication and the assembly of the membrane-bound viral replicase. Although many of the characterized CIRFs act directly against TBSV, we propose that the TPR-domain co-chaperones function as guardians of the cellular Hsp70 chaperone system, which is subverted efficiently by TBSV for viral replicase assembly in the absence of the TPR-domain co-chaperones.

  3. Interactions Between Industrial Yeasts and Chemical Contaminants in Grape Juice Affect Wine Composition Profile

    Directory of Open Access Journals (Sweden)

    Etjen Bizaj

    2014-01-01

    Full Text Available The interaction between four industrial wine yeast strains and grape juice chemical contaminants during alcoholic fermentation was studied. Industrial strains of Saccharomyces cerevisiae (AWRI 0838, S. cerevisiae mutant with low H2S production phenotype (AWRI 1640, interspecies hybrid of S. cerevisiae and S. kudriavzevii (AWRI 1539 and a hybrid of AWRI 1640 and AWRI 1539 (AWRI 1810 were exposed separately to fungicides pyrimethanil (Pyr, 10 mg/L and fenhexamid (Fhx, 10 mg/L, as well as to the most common toxin produced by moulds on grapes, ochratoxin A (OTA, 5 μg/L, during alcoholic fermentation of Vitis vinifera L. cv. Sauvignon blanc juice. Contaminants were found to strongly impair fermentation performance and metabolic activity of all yeast strains studied. The chemical profile of wine was analyzed by HPLC (volatile acidity, concentrations of ethanol, fructose, glucose, glycerol and organic acids and the aromatic profile was analyzed using a stable isotope dilution technique using GC/MS (ethyl esters, acetates and aromatic alcohols and Kitagawa tubes (H2S. The chemical composition of wine with added contaminants was in all cases significantly different from the control. Of particular note is that the quantity of aromatic compounds produced by yeast was significantly lower. Yeast’s capacity to remove contaminants from wine at the end of the alcoholic fermentation, and after extended contact (7 days was determined. All the strains were able to remove contaminants from the media, moreover, after extended contact, the concentration of contaminants was in most cases lower.

  4. Evolution of a protein domain interaction network

    International Nuclear Information System (INIS)

    Li-Feng, Gao; Jian-Jun, Shi; Shan, Guan

    2010-01-01

    In this paper, we attempt to understand complex network evolution from the underlying evolutionary relationship between biological organisms. Firstly, we construct a Pfam domain interaction network for each of the 470 completely sequenced organisms, and therefore each organism is correlated with a specific Pfam domain interaction network; secondly, we infer the evolutionary relationship of these organisms with the nearest neighbour joining method; thirdly, we use the evolutionary relationship between organisms constructed in the second step as the evolutionary course of the Pfam domain interaction network constructed in the first step. This analysis of the evolutionary course shows: (i) there is a conserved sub-network structure in network evolution; in this sub-network, nodes with lower degree prefer to maintain their connectivity invariant, and hubs tend to maintain their role as a hub is attached preferentially to new added nodes; (ii) few nodes are conserved as hubs; most of the other nodes are conserved as one with very low degree; (iii) in the course of network evolution, new nodes are added to the network either individually in most cases or as clusters with relative high clustering coefficients in a very few cases. (general)

  5. License - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available List Contact us Yeast Interacting Proteins Database License to Use This Database Last updated : 2010/02/15 You may use this database...nal License described below. The Standard License specifies the license terms regarding the use of this database... and the requirements you must follow in using this database. The Additional ...the Standard License. Standard License The Standard License for this database is the license specified in th...e Creative Commons Attribution-Share Alike 2.1 Japan . If you use data from this database

  6. Scaling laws and universality for the strength of genetic interactions in yeast

    Science.gov (United States)

    Velenich, Andrea; Dai, Mingjie; Gore, Jeff

    2012-02-01

    Genetic interactions provide a window to the organization of the thousands of biochemical reactions in living cells. If two mutations affect unrelated cellular functions, the fitness effects of their combination can be easily predicted from the two separate fitness effects. However, because of interactions, for some pairs of mutations their combined fitness effect deviates from the naive prediction. We study genetic interactions in yeast cells by analyzing a publicly available database containing experimental growth rates of 5 million double mutants. We show that the characteristic strength of genetic interactions has a simple power law dependence on the fitness effects of the two interacting mutations and that the probability distribution of genetic interactions is a universal function. We further argue that the strength of genetic interactions depends only on the fitness effects of the interacting mutations and not on their biological origin in terms of single point mutations, entire gene knockouts or even more complicated physiological perturbations. Finally, we discuss the implications of the power law scaling of genetic interactions on the ruggedness of fitness landscapes and the consequent evolutionary dynamics.

  7. STATE NETWORK INTERNATIONAL POLITICAL INTERACTION

    Directory of Open Access Journals (Sweden)

    D. M. Feldman

    2011-01-01

    Full Text Available Abstract: The processes of fragmentation (regionalization and localization and globalization turn the state as the basic system forming element of the state-centric world political system into the component of the world political network. The political relations between actors of the world political network are ruled by the effectiveness and not by legitimacy (“victory rules”, what is different from the participatory principles of interstate relations (“participation rules” accepted by the Westphalian state system. The article argues that the post-Westphalian world political system will witness the clashes between victory rules and participation rules and their eventual coexistence since the very nature of the victory rules hinders its institutionalization, consolidation and legitimation. The article suggests that the new system of state relations regardless of the name will be not less Westphalian than the preceding one thus new participation rules will have to be formulated and codified.

  8. Unraveling spurious properties of interaction networks with tailored random networks.

    Directory of Open Access Journals (Sweden)

    Stephan Bialonski

    Full Text Available We investigate interaction networks that we derive from multivariate time series with methods frequently employed in diverse scientific fields such as biology, quantitative finance, physics, earth and climate sciences, and the neurosciences. Mimicking experimental situations, we generate time series with finite length and varying frequency content but from independent stochastic processes. Using the correlation coefficient and the maximum cross-correlation, we estimate interdependencies between these time series. With clustering coefficient and average shortest path length, we observe unweighted interaction networks, derived via thresholding the values of interdependence, to possess non-trivial topologies as compared to Erdös-Rényi networks, which would indicate small-world characteristics. These topologies reflect the mostly unavoidable finiteness of the data, which limits the reliability of typically used estimators of signal interdependence. We propose random networks that are tailored to the way interaction networks are derived from empirical data. Through an exemplary investigation of multichannel electroencephalographic recordings of epileptic seizures--known for their complex spatial and temporal dynamics--we show that such random networks help to distinguish network properties of interdependence structures related to seizure dynamics from those spuriously induced by the applied methods of analysis.

  9. Mapping DNA damage-dependent genetic interactions in yeast via party mating and barcode fusion genetics.

    Science.gov (United States)

    Díaz-Mejía, J Javier; Celaj, Albi; Mellor, Joseph C; Coté, Atina; Balint, Attila; Ho, Brandon; Bansal, Pritpal; Shaeri, Fatemeh; Gebbia, Marinella; Weile, Jochen; Verby, Marta; Karkhanina, Anna; Zhang, YiFan; Wong, Cassandra; Rich, Justin; Prendergast, D'Arcy; Gupta, Gaurav; Öztürk, Sedide; Durocher, Daniel; Brown, Grant W; Roth, Frederick P

    2018-05-28

    Condition-dependent genetic interactions can reveal functional relationships between genes that are not evident under standard culture conditions. State-of-the-art yeast genetic interaction mapping, which relies on robotic manipulation of arrays of double-mutant strains, does not scale readily to multi-condition studies. Here, we describe barcode fusion genetics to map genetic interactions (BFG-GI), by which double-mutant strains generated via en masse "party" mating can also be monitored en masse for growth to detect genetic interactions. By using site-specific recombination to fuse two DNA barcodes, each representing a specific gene deletion, BFG-GI enables multiplexed quantitative tracking of double mutants via next-generation sequencing. We applied BFG-GI to a matrix of DNA repair genes under nine different conditions, including methyl methanesulfonate (MMS), 4-nitroquinoline 1-oxide (4NQO), bleomycin, zeocin, and three other DNA-damaging environments. BFG-GI recapitulated known genetic interactions and yielded new condition-dependent genetic interactions. We validated and further explored a subnetwork of condition-dependent genetic interactions involving MAG1 , SLX4, and genes encoding the Shu complex, and inferred that loss of the Shu complex leads to an increase in the activation of the checkpoint protein kinase Rad53. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

  10. Defining the protein interaction network of human malaria parasite Plasmodium falciparum

    KAUST Repository

    Ramaprasad, Abhinay

    2012-02-01

    Malaria, caused by the protozoan parasite Plasmodium falciparum, affects around 225. million people yearly and a huge international effort is directed towards combating this grave threat to world health and economic development. Considerable advances have been made in malaria research triggered by the sequencing of its genome in 2002, followed by several high-throughput studies defining the malaria transcriptome and proteome. A protein-protein interaction (PPI) network seeks to trace the dynamic interactions between proteins, thereby elucidating their local and global functional relationships. Experimentally derived PPI network from high-throughput methods such as yeast two hybrid (Y2H) screens are inherently noisy, but combining these independent datasets by computational methods tends to give a greater accuracy and coverage. This review aims to discuss the computational approaches used till date to construct a malaria protein interaction network and to catalog the functional predictions and biological inferences made from analysis of the PPI network. © 2011 Elsevier Inc.

  11. A conserved mammalian protein interaction network.

    Directory of Open Access Journals (Sweden)

    Åsa Pérez-Bercoff

    Full Text Available Physical interactions between proteins mediate a variety of biological functions, including signal transduction, physical structuring of the cell and regulation. While extensive catalogs of such interactions are known from model organisms, their evolutionary histories are difficult to study given the lack of interaction data from phylogenetic outgroups. Using phylogenomic approaches, we infer a upper bound on the time of origin for a large set of human protein-protein interactions, showing that most such interactions appear relatively ancient, dating no later than the radiation of placental mammals. By analyzing paired alignments of orthologous and putatively interacting protein-coding genes from eight mammals, we find evidence for weak but significant co-evolution, as measured by relative selective constraint, between pairs of genes with interacting proteins. However, we find no strong evidence for shared instances of directional selection within an interacting pair. Finally, we use a network approach to show that the distribution of selective constraint across the protein interaction network is non-random, with a clear tendency for interacting proteins to share similar selective constraints. Collectively, the results suggest that, on the whole, protein interactions in mammals are under selective constraint, presumably due to their functional roles.

  12. [Identification of C(2)M interacting proteins by yeast two-hybrid screening].

    Science.gov (United States)

    Yue, Shan-shan; Xia, Lai-xin

    2015-11-01

    The synaptonemal complex (SC) is a huge structure which assembles between the homologous chromosomes during meiotic prophase I. Drosophila germ cell-specific nucleoprotein C(2)M clustering at chromosomes can induce SC formation. To further study the molecular function and mechanism of C(2)M in meiosis, we constructed a bait vector for C(2)M and used the yeast two-hybrid system to identify C(2)M interacting proteins. Forty interacting proteins were obtained, including many DNA and histone binding proteins, ATP synthases and transcription factors. Gene silencing assays in Drosophila showed that two genes, wech and Psf1, may delay the disappearance of SC. These results indicate that Wech and Psf1 may form a complex with C(2)M to participate in the formation or stabilization of the SC complex.

  13. Tombusviruses upregulate phospholipid biosynthesis via interaction between p33 replication protein and yeast lipid sensor proteins during virus replication in yeast

    International Nuclear Information System (INIS)

    Barajas, Daniel; Xu, Kai; Sharma, Monika; Wu, Cheng-Yu; Nagy, Peter D.

    2014-01-01

    Positive-stranded RNA viruses induce new membranous structures and promote membrane proliferation in infected cells to facilitate viral replication. In this paper, the authors show that a plant-infecting tombusvirus upregulates transcription of phospholipid biosynthesis genes, such as INO1, OPI3 and CHO1, and increases phospholipid levels in yeast model host. This is accomplished by the viral p33 replication protein, which interacts with Opi1p FFAT domain protein and Scs2p VAP protein. Opi1p and Scs2p are phospholipid sensor proteins and they repress the expression of phospholipid genes. Accordingly, deletion of OPI1 transcription repressor in yeast has a stimulatory effect on TBSV RNA accumulation and enhanced tombusvirus replicase activity in an in vitro assay. Altogether, the presented data convincingly demonstrate that de novo lipid biosynthesis is required for optimal TBSV replication. Overall, this work reveals that a (+)RNA virus reprograms the phospholipid biosynthesis pathway in a unique way to facilitate its replication in yeast cells. - Highlights: • Tombusvirus p33 replication protein interacts with FFAT-domain host protein. • Tombusvirus replication leads to upregulation of phospholipids. • Tombusvirus replication depends on de novo lipid synthesis. • Deletion of FFAT-domain host protein enhances TBSV replication. • TBSV rewires host phospholipid synthesis

  14. Control activity of yeast geranylgeranyl diphosphate synthase from dimer interface through H-bonds and hydrophobic interaction.

    Science.gov (United States)

    Chang, Chih-Kang; Teng, Kuo-Hsun; Lin, Sheng-Wei; Chang, Tao-Hsin; Liang, Po-Huang

    2013-04-23

    Previously we showed that yeast geranylgeranyl diphosphate synthase (GGPPS) becomes an inactive monomer when the first N-terminal helix involved in dimerization is deleted. This raises questions regarding why dimerization is required for GGPPS activity and which amino acids in the dimer interface are essential for dimerization-mediated activity. According to the GGPPS crystal structure, three amino acids (N101, N104, and Y105) located in the helix F of one subunit are near the active site of the other subunit. As presented here, when these residues were replaced individually with Ala caused insignificant activity changes, N101A/Y105A and N101A/N104A but not N104A/Y105A showed remarkably decreased k(cat) values (200-250-fold). The triple mutant N101A/N104A/Y105A displayed no detectable activity, although dimer was retained in these mutants. Because N101 and Y105 form H-bonds with H139 and R140 in the other subunit, respectively, we generated H139A/R140A double mutant and found it was inactive and became monomeric. Therefore, the multiple mutations apparently influence the integrity of the catalytic site due to the missing H-bonding network. Moreover, Met111, also on the highly conserved helix F, was necessary for dimer formation and enzyme activity. When Met111 was replaced with Glu, the negative-charged repulsion converted half of the dimer into a monomer. In conclusion, the H-bonds mainly through N101 for maintaining substrate binding stability and the hydrophobic interaction of M111 in dimer interface are essential for activity of yeast GGPPS.

  15. Improving functional modules discovery by enriching interaction networks with gene profiles

    KAUST Repository

    Salem, Saeed

    2013-05-01

    Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub-networks (modules). These discovered modules help to unravel the underlying mechanisms of the observed biological processes. While most of the existing module discovery methods use only the interaction data, in this work we propose, CLARM, which discovers biological modules by incorporating gene profiles data with protein-protein interaction networks. We demonstrate the effectiveness of CLARM on Yeast and Human interaction datasets, and gene expression and molecular function profiles. Experiments on these real datasets show that the CLARM approach is competitive to well established functional module discovery methods.

  16. A Physical Interaction Network of Dengue Virus and Human Proteins*

    Science.gov (United States)

    Khadka, Sudip; Vangeloff, Abbey D.; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S.; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J.; Perera, Rushika; LaCount, Douglas J.

    2011-01-01

    Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection. PMID:21911577

  17. A physical interaction network of dengue virus and human proteins.

    Science.gov (United States)

    Khadka, Sudip; Vangeloff, Abbey D; Zhang, Chaoying; Siddavatam, Prasad; Heaton, Nicholas S; Wang, Ling; Sengupta, Ranjan; Sahasrabudhe, Sudhir; Randall, Glenn; Gribskov, Michael; Kuhn, Richard J; Perera, Rushika; LaCount, Douglas J

    2011-12-01

    Dengue virus (DENV), an emerging mosquito-transmitted pathogen capable of causing severe disease in humans, interacts with host cell factors to create a more favorable environment for replication. However, few interactions between DENV and human proteins have been reported to date. To identify DENV-human protein interactions, we used high-throughput yeast two-hybrid assays to screen the 10 DENV proteins against a human liver activation domain library. From 45 DNA-binding domain clones containing either full-length viral genes or partially overlapping gene fragments, we identified 139 interactions between DENV and human proteins, the vast majority of which are novel. These interactions involved 105 human proteins, including six previously implicated in DENV infection and 45 linked to the replication of other viruses. Human proteins with functions related to the complement and coagulation cascade, the centrosome, and the cytoskeleton were enriched among the DENV interaction partners. To determine if the cellular proteins were required for DENV infection, we used small interfering RNAs to inhibit their expression. Six of 12 proteins targeted (CALR, DDX3X, ERC1, GOLGA2, TRIP11, and UBE2I) caused a significant decrease in the replication of a DENV replicon. We further showed that calreticulin colocalized with viral dsRNA and with the viral NS3 and NS5 proteins in DENV-infected cells, consistent with a direct role for calreticulin in DENV replication. Human proteins that interacted with DENV had significantly higher average degree and betweenness than expected by chance, which provides additional support for the hypothesis that viruses preferentially target cellular proteins that occupy central position in the human protein interaction network. This study provides a valuable starting point for additional investigations into the roles of human proteins in DENV infection.

  18. Reconstruction and in silico analysis of metabolic network for an oleaginous yeast, Yarrowia lipolytica.

    Directory of Open Access Journals (Sweden)

    Pengcheng Pan

    Full Text Available With the emergence of energy scarcity, the use of renewable energy sources such as biodiesel is becoming increasingly necessary. Recently, many researchers have focused their minds on Yarrowia lipolytica, a model oleaginous yeast, which can be employed to accumulate large amounts of lipids that could be further converted to biodiesel. In order to understand the metabolic characteristics of Y. lipolytica at a systems level and to examine the potential for enhanced lipid production, a genome-scale compartmentalized metabolic network was reconstructed based on a combination of genome annotation and the detailed biochemical knowledge from multiple databases such as KEGG, ENZYME and BIGG. The information about protein and reaction associations of all the organisms in KEGG and Expasy-ENZYME database was arranged into an EXCEL file that can then be regarded as a new useful database to generate other reconstructions. The generated model iYL619_PCP accounts for 619 genes, 843 metabolites and 1,142 reactions including 236 transport reactions, 125 exchange reactions and 13 spontaneous reactions. The in silico model successfully predicted the minimal media and the growing abilities on different substrates. With flux balance analysis, single gene knockouts were also simulated to predict the essential genes and partially essential genes. In addition, flux variability analysis was applied to design new mutant strains that will redirect fluxes through the network and may enhance the production of lipid. This genome-scale metabolic model of Y. lipolytica can facilitate system-level metabolic analysis as well as strain development for improving the production of biodiesels and other valuable products by Y. lipolytica and other closely related oleaginous yeasts.

  19. Protein complex prediction in large ontology attributed protein-protein interaction networks.

    Science.gov (United States)

    Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

    2013-01-01

    Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

  20. Topology and weights in a protein domain interaction network--a novel way to predict protein interactions.

    Science.gov (United States)

    Wuchty, Stefan

    2006-05-23

    While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. We consider a web of interactions between protein domains of the Protein Family database (PFAM), which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we show a simple way to predict potential protein interactions

  1. Topology and weights in a protein domain interaction network – a novel way to predict protein interactions

    Directory of Open Access Journals (Sweden)

    Wuchty Stefan

    2006-05-01

    Full Text Available Abstract Background While the analysis of unweighted biological webs as diverse as genetic, protein and metabolic networks allowed spectacular insights in the inner workings of a cell, biological networks are not only determined by their static grid of links. In fact, we expect that the heterogeneity in the utilization of connections has a major impact on the organization of cellular activities as well. Results We consider a web of interactions between protein domains of the Protein Family database (PFAM, which are weighted by a probability score. We apply metrics that combine the static layout and the weights of the underlying interactions. We observe that unweighted measures as well as their weighted counterparts largely share the same trends in the underlying domain interaction network. However, we only find weak signals that weights and the static grid of interactions are connected entities. Therefore assuming that a protein interaction is governed by a single domain interaction, we observe strong and significant correlations of the highest scoring domain interaction and the confidence of protein interactions in the underlying interactions of yeast and fly. Modeling an interaction between proteins if we find a high scoring protein domain interaction we obtain 1, 428 protein interactions among 361 proteins in the human malaria parasite Plasmodium falciparum. Assessing their quality by a logistic regression method we observe that increasing confidence of predicted interactions is accompanied by high scoring domain interactions and elevated levels of functional similarity and evolutionary conservation. Conclusion Our results indicate that probability scores are randomly distributed, allowing to treat static grid and weights of domain interactions as separate entities. In particular, these finding confirms earlier observations that a protein interaction is a matter of a single interaction event on domain level. As an immediate application, we

  2. Protein interaction networks by proteome peptide scanning.

    Directory of Open Access Journals (Sweden)

    Christiane Landgraf

    2004-01-01

    Full Text Available A substantial proportion of protein interactions relies on small domains binding to short peptides in the partner proteins. Many of these interactions are relatively low affinity and transient, and they impact on signal transduction. However, neither the number of potential interactions mediated by each domain nor the degree of promiscuity at a whole proteome level has been investigated. We have used a combination of phage display and SPOT synthesis to discover all the peptides in the yeast proteome that have the potential to bind to eight SH3 domains. We first identified the peptides that match a relaxed consensus, as deduced from peptides selected by phage display experiments. Next, we synthesized all the matching peptides at high density on a cellulose membrane, and we probed them directly with the SH3 domains. The domains that we have studied were grouped by this approach into five classes with partially overlapping specificity. Within the classes, however, the domains display a high promiscuity and bind to a large number of common targets with comparable affinity. We estimate that the yeast proteome contains as few as six peptides that bind to the Abp1 SH3 domain with a dissociation constant lower than 100 microM, while it contains as many as 50-80 peptides with corresponding affinity for the SH3 domain of Yfr024c. All the targets of the Abp1 SH3 domain, identified by this approach, bind to the native protein in vivo, as shown by coimmunoprecipitation experiments. Finally, we demonstrate that this strategy can be extended to the analysis of the entire human proteome. We have developed an approach, named WISE (whole interactome scanning experiment, that permits rapid and reliable identification of the partners of any peptide recognition module by peptide scanning of a proteome. Since the SPOT synthesis approach is semiquantitative and provides an approximation of the dissociation constants of the several thousands of interactions that are

  3. Evaluating the interactions of vertebrate receptors with persistent pollutants and antifouling pesticides using recombinant yeast assays

    Energy Technology Data Exchange (ETDEWEB)

    Noguerol, Tania-Noelia; Boronat, Susanna; Casado, Marta; Pina, Benjamin [Institut de Biologia Molecular de Barcelona, CSIC, Department of Molecular Biology, Barcelona (Spain); Raldua, Demetrio [Laboratory of Environmental Toxicology, INTEXTER -UP, Terrassa (Spain); Barcelo, Damia [IIQAB-CSIC, Department of Environmental Chemistry, Barcelona (Spain)

    2006-07-15

    The development of in vitro methods for screening potentially harmful biological activities of new compounds is an extremely important way to increase not only their intrinsic environmental safety, but also the public perception of the safety standards associated with them. In this work we use two yeast systems to test the ability of different chemicals to bind and activate two vertebrate receptors which are intimately related to adverse biological effects of pollution in exposed fauna: the estrogen receptor (ER) and the aryl hydrocarbon receptor (AhR). The panel of compounds analysed here includes well-known pollutants, like PCBs, pp'-DDT and hexachlorobenzene, together with the less-known, emerging putative pollutants, such as Sea-Nine, Irgarol and diuron. Results show the ability of some of these compounds to interact with one or both receptors, provide hints about the relationship between structure and activity, and suggest mechanistic explanations for the biological activities already described in whole-animal experiments. In addition, we show that AhR may have an intrinsic ligand promiscuity comparable to that of ER, a feature not fully appreciated in the past due to the technical difficulties involved with testing highly lipophilic substances in yeast-based assays. (orig.)

  4. Adding biological meaning to human protein-protein interactions identified by yeast two-hybrid screenings: A guide through bioinformatics tools.

    Science.gov (United States)

    Felgueiras, Juliana; Silva, Joana Vieira; Fardilha, Margarida

    2018-01-16

    "A man is known by the company he keeps" is a popular expression that perfectly fits proteins. A common approach to characterize the function of a target protein is to identify its interacting partners and thus infer its roles based on the known functions of the interactors. Protein-protein interaction networks (PPINs) have been created for several organisms, including humans, primarily as results of high-throughput screenings, such as yeast two-hybrid (Y2H). Their unequivocal use to understand events underlying human pathophysiology is promising in identifying genes and proteins associated with diseases. Therefore, numerous opportunities have emerged for PPINs as tools for clinical management of diseases: network-based disease classification systems, discovery of biomarkers and identification of therapeutic targets. Despite the great advantages of PPINs, their use is still unrecognised by several researchers who generate high-throughput data to generally characterize interactions in a certain model or to select an interaction to study in detail. We strongly believe that both approaches are not exclusive and that we can use PPINs as a complementary methodology and rich-source of information to the initial study proposal. Here, we suggest a pipeline to deal with Y2H results using bioinformatics tools freely available for academics. Yeast two-hybrid is widely-used to identify protein-protein interactions. Conventionally, the positive clones that result from a yeast two-hybrid screening are sequenced to identify the interactors of the protein of interest (also known as bait protein), and few interactions, thought as potentially relevant for the model in study, are selected for further validation using biochemical methods (e.g. co-immunoprecipitation and co-localization). The huge amount of data that is potentially lost during this conservative approach motivated us to write this tutorial-like review, so that researchers feel encouraged to take advantage of

  5. Dynamic Metabolic Footprinting Reveals the Key Components of Metabolic Network in Yeast Saccharomyces cerevisiae

    DEFF Research Database (Denmark)

    Chumnanpuen, Pramote; Hansen, Michael Adsetts Edberg; Smedsgaard, Jørn

    2014-01-01

    relies on analysis at a single time point. Using direct infusion-mass spectrometry (DI-MS), we could observe the dynamic metabolic footprinting in yeast S. cerevisiae BY4709 (wild type) cultured on 3 different C-sources (glucose, glycerol, and ethanol) and sampled along 10 time points with 5 biological...... replicates. In order to analyze the dynamic mass spectrometry data, we developed the novel analysis methods that allow us to perform correlation analysis to identify metabolites that significantly correlate over time during growth on the different carbon sources. Both positive and negative electrospray...... reconstructed an interaction map that provides information of how different metabolic pathways have correlated patterns during growth on the different carbon sources....

  6. Synchronization in networks with multiple interaction layers

    Science.gov (United States)

    del Genio, Charo I.; Gómez-Gardeñes, Jesús; Bonamassa, Ivan; Boccaletti, Stefano

    2016-01-01

    The structure of many real-world systems is best captured by networks consisting of several interaction layers. Understanding how a multilayered structure of connections affects the synchronization properties of dynamical systems evolving on top of it is a highly relevant endeavor in mathematics and physics and has potential applications in several socially relevant topics, such as power grid engineering and neural dynamics. We propose a general framework to assess the stability of the synchronized state in networks with multiple interaction layers, deriving a necessary condition that generalizes the master stability function approach. We validate our method by applying it to a network of Rössler oscillators with a double layer of interactions and show that highly rich phenomenology emerges from this. This includes cases where the stability of synchronization can be induced even if both layers would have individually induced unstable synchrony, an effect genuinely arising from the true multilayer structure of the interactions among the units in the network. PMID:28138540

  7. Structure of the human chromosome interaction network.

    Directory of Open Access Journals (Sweden)

    Sergio Sarnataro

    Full Text Available New Hi-C technologies have revealed that chromosomes have a complex network of spatial contacts in the cell nucleus of higher organisms, whose organisation is only partially understood. Here, we investigate the structure of such a network in human GM12878 cells, to derive a large scale picture of nuclear architecture. We find that the intensity of intra-chromosomal interactions is power-law distributed. Inter-chromosomal interactions are two orders of magnitude weaker and exponentially distributed, yet they are not randomly arranged along the genomic sequence. Intra-chromosomal contacts broadly occur between epigenomically homologous regions, whereas inter-chromosomal contacts are especially associated with regions rich in highly expressed genes. Overall, genomic contacts in the nucleus appear to be structured as a network of networks where a set of strongly individual chromosomal units, as envisaged in the 'chromosomal territory' scenario derived from microscopy, interact with each other via on average weaker, yet far from random and functionally important interactions.

  8. Designing Networked Adaptive Interactive Hybrid Systems

    NARCIS (Netherlands)

    Kester, L.J.H.M.

    2008-01-01

    Advances in network technologies enable distributed systems, operating in complex physical environments, to coordinate their activities over larger areas within shorter time intervals. In these systems humans and intelligent machines will, in close interaction, be able to reach their goals under

  9. The interaction of uranyl ions with inorganic pyrophosphatase from baker's yeast

    International Nuclear Information System (INIS)

    Bienwald, B.; Heitmann, P.

    1978-01-01

    The interaction of uranyl ions with inorganic pyrophosphatase from baker's yeast was investigated by measurement of their effect on the protein fluorescence. Fluorescence titrations of the native enzyme with uranyl nitrate show that there is a specific binding of uranyl ions to the enzyme. It was deduced that each subunit of the enzyme binds one uranyl ion. The binding constant was estimated to be in the order of 10 7 M -1 . The enzyme which contains a small number of chemically modified carboxyl groups was not able to bind uranyl ions specifically. The modification of carboxyl groups was carried out by use of a water soluble carbodiimide and the nucleophilic reagent N-(2,4-dinitro-phenyl)-hexamethylenediamine. The substrate analogue calcium pyrophosphate displaced the uranyl ions from their binding sites at the enzyme From the results it is concluded that carboxyl groups of the active site are the ligands for the binding of uranyl ions. (author)

  10. The yeast Sks1p kinase signaling network regulates pseudohyphal growth and glucose response.

    Directory of Open Access Journals (Sweden)

    Cole Johnson

    2014-03-01

    Full Text Available The yeast Saccharomyces cerevisiae undergoes a dramatic growth transition from its unicellular form to a filamentous state, marked by the formation of pseudohyphal filaments of elongated and connected cells. Yeast pseudohyphal growth is regulated by signaling pathways responsive to reductions in the availability of nitrogen and glucose, but the molecular link between pseudohyphal filamentation and glucose signaling is not fully understood. Here, we identify the glucose-responsive Sks1p kinase as a signaling protein required for pseudohyphal growth induced by nitrogen limitation and coupled nitrogen/glucose limitation. To identify the Sks1p signaling network, we applied mass spectrometry-based quantitative phosphoproteomics, profiling over 900 phosphosites for phosphorylation changes dependent upon Sks1p kinase activity. From this analysis, we report a set of novel phosphorylation sites and highlight Sks1p-dependent phosphorylation in Bud6p, Itr1p, Lrg1p, Npr3p, and Pda1p. In particular, we analyzed the Y309 and S313 phosphosites in the pyruvate dehydrogenase subunit Pda1p; these residues are required for pseudohyphal growth, and Y309A mutants exhibit phenotypes indicative of impaired aerobic respiration and decreased mitochondrial number. Epistasis studies place SKS1 downstream of the G-protein coupled receptor GPR1 and the G-protein RAS2 but upstream of or at the level of cAMP-dependent PKA. The pseudohyphal growth and glucose signaling transcription factors Flo8p, Mss11p, and Rgt1p are required to achieve wild-type SKS1 transcript levels. SKS1 is conserved, and deletion of the SKS1 ortholog SHA3 in the pathogenic fungus Candida albicans results in abnormal colony morphology. Collectively, these results identify Sks1p as an important regulator of filamentation and glucose signaling, with additional relevance towards understanding stress-responsive signaling in C. albicans.

  11. Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

    Science.gov (United States)

    Reguly, Teresa; Breitkreutz, Ashton; Boucher, Lorrie; Breitkreutz, Bobby-Joe; Hon, Gary C; Myers, Chad L; Parsons, Ainslie; Friesen, Helena; Oughtred, Rose; Tong, Amy; Stark, Chris; Ho, Yuen; Botstein, David; Andrews, Brenda; Boone, Charles; Troyanskya, Olga G; Ideker, Trey; Dolinski, Kara; Batada, Nizar N; Tyers, Mike

    2006-01-01

    Background The study of complex biological networks and prediction of gene function has been enabled by high-throughput (HTP) methods for detection of genetic and protein interactions. Sparse coverage in HTP datasets may, however, distort network properties and confound predictions. Although a vast number of well substantiated interactions are recorded in the scientific literature, these data have not yet been distilled into networks that enable system-level inference. Results We describe here a comprehensive database of genetic and protein interactions, and associated experimental evidence, for the budding yeast Saccharomyces cerevisiae, as manually curated from over 31,793 abstracts and online publications. This literature-curated (LC) dataset contains 33,311 interactions, on the order of all extant HTP datasets combined. Surprisingly, HTP protein-interaction datasets currently achieve only around 14% coverage of the interactions in the literature. The LC network nevertheless shares attributes with HTP networks, including scale-free connectivity and correlations between interactions, abundance, localization, and expression. We find that essential genes or proteins are enriched for interactions with other essential genes or proteins, suggesting that the global network may be functionally unified. This interconnectivity is supported by a substantial overlap of protein and genetic interactions in the LC dataset. We show that the LC dataset considerably improves the predictive power of network-analysis approaches. The full LC dataset is available at the BioGRID () and SGD () databases. Conclusion Comprehensive datasets of biological interactions derived from the primary literature provide critical benchmarks for HTP methods, augment functional prediction, and reveal system-level attributes of biological networks. PMID:16762047

  12. Network Interactions in the Great Altai Region

    Directory of Open Access Journals (Sweden)

    Lev Aleksandrovich Korshunov

    2017-12-01

    Full Text Available To improve the efficiency and competitiveness of the regional economy, an effective interaction between educational institutions in the Great Altai region is needed. The innovation growth can enhancing this interaction. The article explores the state of network structures in the economy and higher education in the border territories of the countries of Great Altai. The authors propose an updated approach to the three-level classification of network interaction. We analyze growing influence of the countries with emerging economies. We define the factors that impede the more stable and multifaceted regional development of these countries. Further, the authors determine indicators of the higher education systems and cooperation systems at the university level between the Shanghai Cooperation Organization countries (SCO and BRICS countries, showing the international rankings of the universities in these countries. The teaching language is important to overcome the obstacles in the interregional cooperation. The authors specify the problems of the development of the universities of the SCO and BRICS countries as global educational networks. The research applies basic scientific logical methods of analysis and synthesis, induction and deduction, as well as the SWOT analysis method. We have indentified and analyzed the existing economic and educational relations. To promote the economic innovation development of the border territories of the Great Altai, we propose a model of regional network university. Modern universities function in a new economic environment. Thus, in a great extent, they form the technological and social aspects of this environment. Innovative network structures contribute to the formation of a new network institutional environment of the regional economy, which impacts the macro- and microeconomic performance of the region as a whole. The results of the research can help to optimize the regional economies of the border

  13. Using network component analysis to dissect regulatory networks mediated by transcription factors in yeast.

    Directory of Open Access Journals (Sweden)

    Chun Ye

    2009-03-01

    Full Text Available Understanding the relationship between genetic variation and gene expression is a central question in genetics. With the availability of data from high-throughput technologies such as ChIP-Chip, expression, and genotyping arrays, we can begin to not only identify associations but to understand how genetic variations perturb the underlying transcription regulatory networks to induce differential gene expression. In this study, we describe a simple model of transcription regulation where the expression of a gene is completely characterized by two properties: the concentrations and promoter affinities of active transcription factors. We devise a method that extends Network Component Analysis (NCA to determine how genetic variations in the form of single nucleotide polymorphisms (SNPs perturb these two properties. Applying our method to a segregating population of Saccharomyces cerevisiae, we found statistically significant examples of trans-acting SNPs located in regulatory hotspots that perturb transcription factor concentrations and affinities for target promoters to cause global differential expression and cis-acting genetic variations that perturb the promoter affinities of transcription factors on a single gene to cause local differential expression. Although many genetic variations linked to gene expressions have been identified, it is not clear how they perturb the underlying regulatory networks that govern gene expression. Our work begins to fill this void by showing that many genetic variations affect the concentrations of active transcription factors in a cell and their affinities for target promoters. Understanding the effects of these perturbations can help us to paint a more complete picture of the complex landscape of transcription regulation. The software package implementing the algorithms discussed in this work is available as a MATLAB package upon request.

  14. Prioritization of gene regulatory interactions from large-scale modules in yeast

    Directory of Open Access Journals (Sweden)

    Bringas Ricardo

    2008-01-01

    Full Text Available Abstract Background The identification of groups of co-regulated genes and their transcription factors, called transcriptional modules, has been a focus of many studies about biological systems. While methods have been developed to derive numerous modules from genome-wide data, individual links between regulatory proteins and target genes still need experimental verification. In this work, we aim to prioritize regulator-target links within transcriptional modules based on three types of large-scale data sources. Results Starting with putative transcriptional modules from ChIP-chip data, we first derive modules in which target genes show both expression and function coherence. The most reliable regulatory links between transcription factors and target genes are established by identifying intersection of target genes in coherent modules for each enriched functional category. Using a combination of genome-wide yeast data in normal growth conditions and two different reference datasets, we show that our method predicts regulatory interactions with significantly higher predictive power than ChIP-chip binding data alone. A comparison with results from other studies highlights that our approach provides a reliable and complementary set of regulatory interactions. Based on our results, we can also identify functionally interacting target genes, for instance, a group of co-regulated proteins related to cell wall synthesis. Furthermore, we report novel conserved binding sites of a glycoprotein-encoding gene, CIS3, regulated by Swi6-Swi4 and Ndd1-Fkh2-Mcm1 complexes. Conclusion We provide a simple method to prioritize individual TF-gene interactions from large-scale transcriptional modules. In comparison with other published works, we predict a complementary set of regulatory interactions which yields a similar or higher prediction accuracy at the expense of sensitivity. Therefore, our method can serve as an alternative approach to prioritization for

  15. Screening for proteins interacting with MCM7 in human lung cancer library using yeast two hybrid system

    Directory of Open Access Journals (Sweden)

    Yuchen HAN

    2008-08-01

    Full Text Available Background and objective MCM7 is a subunit of the MCM complex that plays a key role in DNA replication initiation. But little is known about its interaction proteins. In this study yeast two hybrid screening was used to identify the MCM7 interacting proteins. Methods Yeast expression vector containing human full length MCM7-pGBKT7 plasmid was constructed, and with a library of cDNAs from human lung cancer-pACT2 plasmid was transformed into yeast strain AH109, and was electively grew in X-a-gal auxotrophy medium SD/-Trp-Leu-His-Ade, and the blue colonies were picked up, the plasmid of the yeast colonies was extracted , and transformed into E. Coli to extract DNA and performed sequence analysis. Results Eleven proteins were identified which could specifically interact with MCM7 proteins, among these five were cytoskeleton proteins, six were enzymes, kinases and related receptors. Conclusion The investigation provides functional clues for further exploration of MCM7 gene.

  16. Inferring the effective TOR-dependent network: a computational study in yeast.

    Science.gov (United States)

    Mohammadi, Shahin; Subramaniam, Shankar; Grama, Ananth

    2013-08-30

    Calorie restriction (CR) is one of the most conserved non-genetic interventions that extends healthspan in evolutionarily distant species, ranging from yeast to mammals. The target of rapamycin (TOR) has been shown to play a key role in mediating healthspan extension in response to CR by integrating different signals that monitor nutrient-availability and orchestrating various components of cellular machinery in response. Both genetic and pharmacological interventions that inhibit the TOR pathway exhibit a similar phenotype, which is not further amplified by CR. In this paper, we present the first comprehensive, computationally derived map of TOR downstream effectors, with the objective of discovering key lifespan mediators, their crosstalk, and high-level organization. We adopt a systematic approach for tracing information flow from the TOR complex and use it to identify relevant signaling elements. By constructing a high-level functional map of TOR downstream effectors, we show that our approach is not only capable of recapturing previously known pathways, but also suggests potential targets for future studies.Information flow scores provide an aggregate ranking of relevance of proteins with respect to the TOR signaling pathway. These rankings must be normalized for degree bias, appropriately interpreted, and mapped to associated roles in pathways. We propose a novel statistical framework for integrating information flow scores, the set of differentially expressed genes in response to rapamycin treatment, and the transcriptional regulatory network. We use this framework to identify the most relevant transcription factors in mediating the observed transcriptional response, and to construct the effective response network of the TOR pathway. This network is hypothesized to mediate life-span extension in response to TOR inhibition. Our approach, unlike experimental methods, is not limited to specific aspects of cellular response. Rather, it predicts transcriptional

  17. The growth, properties and interactions of yeasts and bacteria associated with the maturation of Camembert and blue-veined cheeses.

    Science.gov (United States)

    Addis, E; Fleet, G H; Cox, J M; Kolak, D; Leung, T

    2001-09-19

    The growth of yeasts and bacteria were monitored during the maturation of Camembert and blue-veined cheese produced in Australia. Yeasts were prominent throughout maturation, growing to 10(5)-10(9)/g, depending on the manufacturer. Debaryomyces hansenii predominated, but there were lesser, inconsistent contributions from Yarrowia lipolytica. Of the non-lactic acid bacteria, Acinetobacter species were significant during the maturation of Camembert but not blue-veined cheeses, and grew to 10(6)-10(8) cfu/g. Staphylococcus and Micrococcus species were consistently isolated from the cheeses with Staphylococcus xylosus growing to 10(5)-10(9) cfu/g, depending on the product. Lactic acid bacteria (10(7)-10(9) cfu/g) were present throughout maturation but were not identified. Interactions between the various yeasts and bacterial isolates were examined. Several strains of D. hansenii exhibited killer activity but not against Y. lipolytica. None of the yeasts were antagonistic towards the bacteria but some strains of D. hansenii enhanced the growth of Y. lipolytica and S. xylosus. The yeast and bacterial isolates exhibited various degrees of extracellular proteolytic and lipolytic activities.

  18. The Global Alzheimer's Association Interactive Network.

    Science.gov (United States)

    Toga, Arthur W; Neu, Scott C; Bhatt, Priya; Crawford, Karen L; Ashish, Naveen

    2016-01-01

    The Global Alzheimer's Association Interactive Network (GAAIN) is consolidating the efforts of independent Alzheimer's disease data repositories around the world with the goals of revealing more insights into the causes of Alzheimer's disease, improving treatments, and designing preventative measures that delay the onset of physical symptoms. We developed a system for federating these repositories that is reliant on the tenets that (1) its participants require incentives to join, (2) joining the network is not disruptive to existing repository systems, and (3) the data ownership rights of its members are protected. We are currently in various phases of recruitment with over 55 data repositories in North America, Europe, Asia, and Australia and can presently query >250,000 subjects using GAAIN's search interfaces. GAAIN's data sharing philosophy, which guided our architectural choices, is conducive to motivating membership in a voluntary data sharing network. Copyright © 2016 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  19. Data management of protein interaction networks

    CERN Document Server

    Cannataro, Mario

    2012-01-01

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

  20. [Yeast urinary tract infections. Multicentre study in 14 hospitals belonging to the Buenos Aires City Mycology Network].

    Science.gov (United States)

    Maldonado, Ivana; Arechavala, Alicia; Guelfand, Liliana; Relloso, Silvia; Garbasz, Claudia

    2016-01-01

    Urinary tract infections are a frequent ailment in patients in intensive care units. Candida and other yeasts cause 5-12% of these infections. The value of the finding of any yeast is controversial, and there is no consensus about which parameters are adequate for differentiating urinary infections from colonization or contamination. To analyse the epidemiological characteristics of patients with funguria, to determine potential cut-off points in cultures (to distinguish an infection from other conditions), to identify the prevalent yeast species, and to determine the value of a second urine sample. A multicentre study was conducted in intensive care units of 14 hospitals in the Buenos Aires City Mycology Network. The first and second samples of urine from every patient were cultured. The presence of white cells and yeasts in direct examination, colony counts, and the identification of the isolated species, were evaluated. Yeasts grew in 12.2% of the samples. There was no statistical correlation between the number of white cells and the fungal colony-forming units. Eighty five percent of the patients had indwelling catheters. Funguria was not prevalent in women or in patients over the age of 65. Candida albicans, followed by Candida tropicalis, were the most frequently isolated yeasts. Candida parapsilosis and Candida glabrata appeared less frequently. The same species were isolated in 70% of second samples, and in 23% of the cases the second culture was negative. It was not possible to determine a useful cut-off point for colony counts to help in the diagnosis of urinary infections. As in other publications, C. albicans, followed by C. tropicalis, were the most prevalent species. Copyright © 2015 Asociación Española de Micología. Published by Elsevier Espana. All rights reserved.

  1. Temporal stability in human interaction networks

    Science.gov (United States)

    Fabbri, Renato; Fabbri, Ricardo; Antunes, Deborah Christina; Pisani, Marilia Mello; de Oliveira, Osvaldo Novais

    2017-11-01

    This paper reports on stable (or invariant) properties of human interaction networks, with benchmarks derived from public email lists. Activity, recognized through messages sent, along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free trace, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, 45% are peripheral vertices. Similar results for the distribution of participants in the three sectors and for the relative importance of the topological metrics were obtained for 12 additional networks from Facebook, Twitter and ParticipaBR. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria.

  2. Yeast-2-Hybrid data file showing progranulin interactions in human fetal brain and bone marrow libraries

    Directory of Open Access Journals (Sweden)

    Irmgard Tegeder

    2016-12-01

    Full Text Available Progranulin deficiency in humans is associated with neurodegeneration. Its mechanisms are not yet fully understood. We performed a Yeast-2-Hybrid screen using human full-length progranulin as bait to assess the interactions of progranulin. Progranulin was screened against human fetal brain and human bone marrow libraries using the standard Matchmaker technology (Clontech. This article contains the full Y2H data table, including blast results and sequences, a sorted table according to selection criteria for likely positive, putatively positive, likely false and false preys, and tables showing the gene ontology terms associated with the likely and putative preys of the brain and bone marrow libraries. The interactions with autophagy proteins were confirmed and functionally analyzed in "Progranulin overexpression in sensory neurons attenuates neuropathic pain in mice: Role of autophagy" (C. Altmann, S. Hardt, C. Fischer, J. Heidler, H.Y. Lim, A. Haussler, B. Albuquerque, B. Zimmer, C. Moser, C. Behrends, F. Koentgen, I. Wittig, M.H. Schmidt, A.M. Clement, T. Deller, I. Tegeder, 2016 [1].

  3. Yeast-2-Hybrid data file showing progranulin interactions in human fetal brain and bone marrow libraries.

    Science.gov (United States)

    Tegeder, Irmgard

    2016-12-01

    Progranulin deficiency in humans is associated with neurodegeneration. Its mechanisms are not yet fully understood. We performed a Yeast-2-Hybrid screen using human full-length progranulin as bait to assess the interactions of progranulin. Progranulin was screened against human fetal brain and human bone marrow libraries using the standard Matchmaker technology (Clontech). This article contains the full Y2H data table, including blast results and sequences, a sorted table according to selection criteria for likely positive, putatively positive, likely false and false preys, and tables showing the gene ontology terms associated with the likely and putative preys of the brain and bone marrow libraries. The interactions with autophagy proteins were confirmed and functionally analyzed in "Progranulin overexpression in sensory neurons attenuates neuropathic pain in mice: Role of autophagy" (C. Altmann, S. Hardt, C. Fischer, J. Heidler, H.Y. Lim, A. Haussler, B. Albuquerque, B. Zimmer, C. Moser, C. Behrends, F. Koentgen, I. Wittig, M.H. Schmidt, A.M. Clement, T. Deller, I. Tegeder, 2016) [1].

  4. Sensitive voltammetric detection of yeast RNA based on its interaction with Victoria Blue B

    Directory of Open Access Journals (Sweden)

    WEI SUN

    2009-12-01

    Full Text Available Voltammetric studies of the interaction of yeast RNA (y-RNA with Victoria Blue B (VBB are described in this paper. Furthermore, a linear sweep voltammetric method for the detection of y-RNA was established. The reaction conditions, such as acidity and amount of buffer solution, the concentration of VBB, the reaction time and temperature, etc., were carefully investigated by second order derivative linear sweep voltammetry. Under the optimal conditions, the reduction peak current of VBB at –0.75 V decreased greatly after the addition of y-RNA to the solution without any shift of the reduction peak potential. Based on the decrease of the peak current, a new quantitative method for the determination of y-RNA was developed. The effects of co-existing substances on the determination were carefully investigated and three synthetic samples were determined with satisfactory results. The stoichiometry of the VBB–y-RNA complex was calculated by linear sweep voltammetry and the interaction mechanism is discussed.

  5. A conserved signaling network monitors delivery of sphingolipids to the plasma membrane in budding yeast.

    Science.gov (United States)

    Clarke, Jesse; Dephoure, Noah; Horecka, Ira; Gygi, Steven; Kellogg, Douglas

    2017-10-01

    In budding yeast, cell cycle progression and ribosome biogenesis are dependent on plasma membrane growth, which ensures that events of cell growth are coordinated with each other and with the cell cycle. However, the signals that link the cell cycle and ribosome biogenesis to membrane growth are poorly understood. Here we used proteome-wide mass spectrometry to systematically discover signals associated with membrane growth. The results suggest that membrane trafficking events required for membrane growth generate sphingolipid-dependent signals. A conserved signaling network appears to play an essential role in signaling by responding to delivery of sphingolipids to the plasma membrane. In addition, sphingolipid-dependent signals control phosphorylation of protein kinase C (Pkc1), which plays an essential role in the pathways that link the cell cycle and ribosome biogenesis to membrane growth. Together these discoveries provide new clues as to how growth--dependent signals control cell growth and the cell cycle. © 2017 Clarke et al. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  6. The Protein Interaction Network of Bacteriophage Lambda with Its Host, Escherichia coli

    Science.gov (United States)

    Blasche, Sonja; Wuchty, Stefan; Rajagopala, Seesandra V.

    2013-01-01

    Although most of the 73 open reading frames (ORFs) in bacteriophage λ have been investigated intensively, the function of many genes in host-phage interactions remains poorly understood. Using yeast two-hybrid screens of all lambda ORFs for interactions with its host Escherichia coli, we determined a raw data set of 631 host-phage interactions resulting in a set of 62 high-confidence interactions after multiple rounds of retesting. These links suggest novel regulatory interactions between the E. coli transcriptional network and lambda proteins. Targeted host proteins and genes required for lambda infection are enriched among highly connected proteins, suggesting that bacteriophages resemble interaction patterns of human viruses. Lambda tail proteins interact with both bacterial fimbrial proteins and E. coli proteins homologous to other phage proteins. Lambda appears to dramatically differ from other phages, such as T7, because of its unusually large number of modified and processed proteins, which reduces the number of host-virus interactions detectable by yeast two-hybrid screens. PMID:24049175

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

    Directory of Open Access Journals (Sweden)

    van Helden Jacques

    2006-11-01

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

  8. The function of communities in protein interaction networks at multiple scales

    Directory of Open Access Journals (Sweden)

    Jones Nick S

    2010-07-01

    Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

  9. Effect of dataset selection on the topological interpretation of protein interaction networks

    Directory of Open Access Journals (Sweden)

    Robertson David L

    2005-09-01

    Full Text Available Abstract Background Studies of the yeast protein interaction network have revealed distinct correlations between the connectivity of individual proteins within the network and the average connectivity of their neighbours. Although a number of biological mechanisms have been proposed to account for these findings, the significance and influence of the specific datasets included in these studies has not been appreciated adequately. Results We show how the use of different interaction data sets, such as those resulting from high-throughput or small-scale studies, and different modelling methodologies for the derivation pair-wise protein interactions, can dramatically change the topology of these networks. Furthermore, we show that some of the previously reported features identified in these networks may simply be the result of experimental or methodological errors and biases. Conclusion When performing network-based studies, it is essential to define what is meant by the term "interaction" and this must be taken into account when interpreting the topologies of the networks generated. Consideration must be given to the type of data included and appropriate controls that take into account the idiosyncrasies of the data must be selected

  10. Interactions between yeast lees and wine polyphenols during simulation of wine aging: I. Analysis of remnant polyphenolic compounds in the resulting wines.

    Science.gov (United States)

    Mazauric, Jean-Paul; Salmon, Jean-Michel

    2005-07-13

    Wine aging on yeast lees is a traditional enological practice used during the manufacture of wines. This technique has increased in popularity in recent years for the aging of red wines. Although wine polyphenols interact with yeast lees to a limited extent, such interactions have a large effect on the reactivity toward oxygen of wine polyphenolic compounds and yeast lees. Various domains of the yeast cell wall are protected by wine polyphenols from the action of extracellular hydrolytic enzymatic activities. Polysaccharides released during autolysis are thought to exert a significant effect on the sensory qualities of wine. We studied the chemical composition of polyphenolic compounds remaining in solution or adsorbed on yeast lees after various contact times during the simulation of wine aging. The analysis of the remnant polyphenols in the wine indicated that wine polyphenols adsorption on yeast lees follows biphasic kinetics. An initial and rapid fixation is followed by a slow, constant, and saturating fixation that reaches its maximum after about 1 week. Only very few monomeric phenolic compounds remained adsorbed on yeast lees, and no preferential adsorption of low or high polymeric size tannins occurred. The remnant condensed tannins in the wine contained fewer epigallocatechin units than the initial tannins, indicating that polar condensed tannins were preferentially adsorbed on yeast lees. Conversely, the efficiency of anthocyanin adsorption on yeast lees was unrelated to its polarity.

  11. Solution NMR study of the yeast cytochrome c peroxidase: cytochrome c interaction

    Energy Technology Data Exchange (ETDEWEB)

    Volkov, Alexander N., E-mail: ovolkov@vub.ac.be; Nuland, Nico A. J. van [Vrije Universiteit Brussel, Jean Jeener NMR Centre, Structural Biology Brussels (Belgium)

    2013-07-15

    Here we present a solution NMR study of the complex between yeast cytochrome c (Cc) and cytochrome c peroxidase (CcP), a paradigm for understanding the biological electron transfer. Performed for the first time, the CcP-observed heteronuclear NMR experiments were used to probe the Cc binding in solution. Combining the Cc- and CcP-detected experiments, the binding interface on both proteins was mapped out, confirming that the X-ray structure of the complex is maintained in solution. Using NMR titrations and chemical shift perturbation analysis, we show that the interaction is independent of the CcP spin-state and is only weakly affected by the Cc redox state. Based on these findings, we argue that the complex of the ferrous Cc and the cyanide-bound CcP is a good mimic of the catalytically-active Cc-CcP compound I species. Finally, no chemical shift perturbations due to the Cc binding at the low-affinity CcP site were observed at low ionic strength. We discuss possible reasons for the absence of the effects and outline future research directions.

  12. The human-bacterial pathogen protein interaction networks of Bacillus anthracis, Francisella tularensis, and Yersinia pestis.

    Directory of Open Access Journals (Sweden)

    Matthew D Dyer

    2010-08-01

    Full Text Available Bacillus anthracis, Francisella tularensis, and Yersinia pestis are bacterial pathogens that can cause anthrax, lethal acute pneumonic disease, and bubonic plague, respectively, and are listed as NIAID Category A priority pathogens for possible use as biological weapons. However, the interactions between human proteins and proteins in these bacteria remain poorly characterized leading to an incomplete understanding of their pathogenesis and mechanisms of immune evasion.In this study, we used a high-throughput yeast two-hybrid assay to identify physical interactions between human proteins and proteins from each of these three pathogens. From more than 250,000 screens performed, we identified 3,073 human-B. anthracis, 1,383 human-F. tularensis, and 4,059 human-Y. pestis protein-protein interactions including interactions involving 304 B. anthracis, 52 F. tularensis, and 330 Y. pestis proteins that are uncharacterized. Computational analysis revealed that pathogen proteins preferentially interact with human proteins that are hubs and bottlenecks in the human PPI network. In addition, we computed modules of human-pathogen PPIs that are conserved amongst the three networks. Functionally, such conserved modules reveal commonalities between how the different pathogens interact with crucial host pathways involved in inflammation and immunity.These data constitute the first extensive protein interaction networks constructed for bacterial pathogens and their human hosts. This study provides novel insights into host-pathogen interactions.

  13. The role of the Parkinson's disease gene PARK9 in essential cellular pathways and the manganese homeostasis network in yeast.

    Directory of Open Access Journals (Sweden)

    Alessandra Chesi

    Full Text Available YPK9 (Yeast PARK9; also known as YOR291W is a non-essential yeast gene predicted by sequence to encode a transmembrane P-type transport ATPase. However, its substrate specificity is unknown. Mutations in the human homolog of YPK9, ATP13A2/PARK9, have been linked to genetic forms of early onset parkinsonism. We previously described a strong genetic interaction between Ypk9 and another Parkinson's disease (PD protein α-synuclein in multiple model systems, and a role for Ypk9 in manganese detoxification in yeast. In humans, environmental exposure to toxic levels of manganese causes a syndrome similar to PD and is thus an environmental risk factor for the disease. How manganese contributes to neurodegeneration is poorly understood. Here we describe multiple genome-wide screens in yeast aimed at defining the cellular function of Ypk9 and the mechanisms by which it protects cells from manganese toxicity. In physiological conditions, we found that Ypk9 genetically interacts with essential genes involved in cellular trafficking and the cell cycle. Deletion of Ypk9 sensitizes yeast cells to exposure to excess manganese. Using a library of non-essential gene deletions, we screened for additional genes involved in tolerance to excess manganese exposure, discovering several novel pathways involved in manganese homeostasis. We defined the dependence of the deletion strain phenotypes in the presence of manganese on Ypk9, and found that Ypk9 deletion modifies the manganese tolerance of only a subset of strains. These results confirm a role for Ypk9 in manganese homeostasis and illuminates cellular pathways and biological processes in which Ypk9 likely functions.

  14. Interactions of grape tannins and wine polyphenols with a yeast protein extract, mannoproteins and β-glucan.

    Science.gov (United States)

    Mekoue Nguela, J; Poncet-Legrand, C; Sieczkowski, N; Vernhet, A

    2016-11-01

    At present, there is a great interest in enology for yeast derived products to replace aging on lees in winemaking or as an alternative for wine fining. These are yeast protein extracts (YPE), cell walls and mannoproteins. Our aim was to further understand the mechanisms that drive interactions between these components and red wine polyphenols. To this end, interactions between grape skin tannins or wine polyphenols or tannins and a YPE, a mannoprotein fraction and a β-glucan were monitored by binding experiments, ITC and DLS. Depending on the tannin structure, a different affinity between the polyphenols and the YPE was observed, as well as differences in the stability of the aggregates. This was attributed to the mean degree of polymerization of tannins in the polyphenol fractions and to chemical changes that occur during winemaking. Much lower affinities were found between polyphenols and polysaccharides, with different behaviors between mannoproteins and β-glucans. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Repulsive interactions between two polyelectrolyte networks

    Science.gov (United States)

    Erbas, Aykut; Olvera de La Cruz, Monica; Olvera Group Collaboration

    Surfaces formed by charged polymeric species are highly_abundant in both synthetic and biological systems, for which maintaining_an optimum contact distance and a pressure balance is paramount. We investigate interactions between surfaces of two same-charged and_highly swollen polyelectrolyte gels, using extensive molecular dynamic_simulations and minimal analytical methods. The external-pressure_responses of the gels and the polymer-free ionic solvent layer separating_two surfaces are considered. Simulations confirmed that the surfaces are_held apart by osmotic pressure resulting from excess charges diffusing out_of the network. Both the solvent layer and pressure dependence are well_described by an analytical model based on the Poisson -Boltzmann solution for low and moderate electrostatic strengths. Our results can be of great importance for systems where charged gels or gel-like structures interact in various solvents, including systems encapsulated by gels and microgels in confinement.

  16. Topology-function conservation in protein-protein interaction networks.

    Science.gov (United States)

    Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

    2015-05-15

    Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

  17. Pathway Detection from Protein Interaction Networks and Gene Expression Data Using Color-Coding Methods and A* Search Algorithms

    Directory of Open Access Journals (Sweden)

    Cheng-Yu Yeh

    2012-01-01

    Full Text Available With the large availability of protein interaction networks and microarray data supported, to identify the linear paths that have biological significance in search of a potential pathway is a challenge issue. We proposed a color-coding method based on the characteristics of biological network topology and applied heuristic search to speed up color-coding method. In the experiments, we tested our methods by applying to two datasets: yeast and human prostate cancer networks and gene expression data set. The comparisons of our method with other existing methods on known yeast MAPK pathways in terms of precision and recall show that we can find maximum number of the proteins and perform comparably well. On the other hand, our method is more efficient than previous ones and detects the paths of length 10 within 40 seconds using CPU Intel 1.73GHz and 1GB main memory running under windows operating system.

  18. Yeast two-hybrid screening of proteins interacting with plasmin receptor subunit: C-terminal fragment of annexin A2.

    Science.gov (United States)

    Li, Qun; Laumonnier, Yves; Syrovets, Tatiana; Simmet, Thomas

    2011-11-01

    To identify proteins that interact with the C-terminal fragment of annexin A2 (A2IC), generated by plasmin cleavage of the plasmin receptor, a heterotetramer (AA2t) containing annexin A2. The gene that encodes the A2IC fragment was obtained from PCR-amplified cDNA isolated from human monocytes, and was ligated into the pBTM116 vector using a DNA ligation kit. The resultant plasmid (pBTM116-A2IC) was sequenced with an ABI PRISM 310 Genetic Analyzer. The expression of an A2IC bait protein fused with a LexA-DNA binding domain (BD) was determined using Western blot analysis. The identification of proteins that interact with A2IC and are encoded in a human monocyte cDNA library was performed using yeast two-hybrid screening. The DNA sequences of the relevant cDNAs were determined using an ABI PRISM BigDye terminator cycle sequencing ready reaction kit. Nucleotide sequence databases were searched for homologous sequences using BLAST search analysis (http://www.ncbi.nlm.nih.gov). Confirmation of the interaction between the protein LexA-A2IC and each of cathepsin S and SNX17 was conducted using a small-scale yeast transformation and X-gal assay. The yeast transformed with plasmids encoding the bait proteins were screened with a human monocyte cDNA library by reconstituting full-length transcription factors containing the GAL4-active domain (GAL4-AD) as the prey in a yeast two-hybrid approach. After screening 1×10(7) clones, 23 independent β-Gal-positive clones were identified. Sequence analysis and a database search revealed that 15 of these positive clones matched eight different proteins (SNX17, ProCathepsin S, RPS2, ZBTB4, OGDH, CCDC32, PAPD4, and actin which was already known to interact with annexin A2). A2IC A2IC interacts with various proteins to form protein complexes, which may contribute to the molecular mechanism of monocyte activation induced by plasmin. The yeast two-hybrid system is an efficient approach for investigating protein interactions.

  19. Genes2Networks: connecting lists of gene symbols using mammalian protein interactions databases

    Directory of Open Access Journals (Sweden)

    Ma'ayan Avi

    2007-10-01

    Full Text Available Abstract Background In recent years, mammalian protein-protein interaction network databases have been developed. The interactions in these databases are either extracted manually from low-throughput experimental biomedical research literature, extracted automatically from literature using techniques such as natural language processing (NLP, generated experimentally using high-throughput methods such as yeast-2-hybrid screens, or interactions are predicted using an assortment of computational approaches. Genes or proteins identified as significantly changing in proteomic experiments, or identified as susceptibility disease genes in genomic studies, can be placed in the context of protein interaction networks in order to assign these genes and proteins to pathways and protein complexes. Results Genes2Networks is a software system that integrates the content of ten mammalian interaction network datasets. Filtering techniques to prune low-confidence interactions were implemented. Genes2Networks is delivered as a web-based service using AJAX. The system can be used to extract relevant subnetworks created from "seed" lists of human Entrez gene symbols. The output includes a dynamic linkable three color web-based network map, with a statistical analysis report that identifies significant intermediate nodes used to connect the seed list. Conclusion Genes2Networks is powerful web-based software that can help experimental biologists to interpret lists of genes and proteins such as those commonly produced through genomic and proteomic experiments, as well as lists of genes and proteins associated with disease processes. This system can be used to find relationships between genes and proteins from seed lists, and predict additional genes or proteins that may play key roles in common pathways or protein complexes.

  20. A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

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    Teeraphan Laomettachit

    Full Text Available To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.

  1. Brewing and volatiles analysis of three tea beers indicate a potential interaction between tea components and lager yeast.

    Science.gov (United States)

    Rong, Lei; Peng, Li-Juan; Ho, Chi-Tang; Yan, Shou-He; Meurens, Marc; Zhang, Zheng-Zhu; Li, Da-Xiang; Wan, Xiao-Chun; Bao, Guan-Hu; Gao, Xue-Ling; Ling, Tie-Jun

    2016-04-15

    Green tea, oolong tea and black tea were separately introduced to brew three kinds of tea beers. A model was designed to investigate the tea beer flavour character. Comparison of the volatiles between the sample of tea beer plus water mixture (TBW) and the sample of combination of tea infusion and normal beer (CTB) was accomplished by triangular sensory test and HS-SPME GC-MS analysis. The PCA of GC-MS data not only showed a significant difference between volatile features of each TBW and CTB group, but also suggested some key compounds to distinguish TBW from CTB. The results of GC-MS showed that the relative concentrations of many typical tea volatiles were significantly changed after the brewing process. More interestingly, the behaviour of yeast fermentation was influenced by tea components. A potential interaction between tea components and lager yeast could be suggested. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Exploring Protein Interactions on a Minimal Type II Polyketide Synthase Using a Yeast Two-Hybrid System

    Directory of Open Access Journals (Sweden)

    Gaetano Castaldo

    2005-01-01

    Full Text Available Interactions between proteins that form the ’minimal’ type II polyketide synthase in the doxorubicin producing biosynthetic pathway from Streptomyces peucetius were investigated using a yeast two-hybrid system (Y2H. Proteins that function as the so called ’chain length factor’ (DpsB and putative transacylase (DpsD were found to interact with the ketosynthase subunit (DpsA, which can also interact with itself. On the basis of these results we propose a head-to-tail homodimeric structure, which is consistent with previously published in vivo mutagenesis studies. No interactions were found between the acyl-carrier protein (DpsG and any of the other constituents of the complex, however, transient interactions, not detectable using the Y2H system, cannot be discounted and warrant further investigation.

  3. Detection of Locally Over-Represented GO Terms in Protein-Protein Interaction Networks

    Science.gov (United States)

    LAVALLÉE-ADAM, MATHIEU; COULOMBE, BENOIT; BLANCHETTE, MATHIEU

    2015-01-01

    High-throughput methods for identifying protein-protein interactions produce increasingly complex and intricate interaction networks. These networks are extremely rich in information, but extracting biologically meaningful hypotheses from them and representing them in a human-readable manner is challenging. We propose a method to identify Gene Ontology terms that are locally over-represented in a subnetwork of a given biological network. Specifically, we propose several methods to evaluate the degree of clustering of proteins associated to a particular GO term in both weighted and unweighted PPI networks, and describe efficient methods to estimate the statistical significance of the observed clustering. We show, using Monte Carlo simulations, that our best approximation methods accurately estimate the true p-value, for random scale-free graphs as well as for actual yeast and human networks. When applied to these two biological networks, our approach recovers many known complexes and pathways, but also suggests potential functions for many subnetworks. Online Supplementary Material is available at www.liebertonline.com. PMID:20377456

  4. Game theory in communication networks cooperative resolution of interactive networking scenarios

    CERN Document Server

    Antoniou, Josephina

    2012-01-01

    A mathematical tool for scientists and researchers who work with computer and communication networks, Game Theory in Communication Networks: Cooperative Resolution of Interactive Networking Scenarios addresses the question of how to promote cooperative behavior in interactive situations between heterogeneous entities in communication networking scenarios. It explores network design and management from a theoretical perspective, using game theory and graph theory to analyze strategic situations and demonstrate profitable behaviors of the cooperative entities. The book promotes the use of Game T

  5. Binding interactions between yeast tRNA ligase and a precursor transfer ribonucleic acid containing two photoreactive uridine analogues

    International Nuclear Information System (INIS)

    Tanner, N.K.; Hanna, M.M.; Abelson, J.

    1988-01-01

    Yeast tRNA ligase, from Saccharomyces cerevisiae, is one of the protein components that is involved in the splicing reaction of intron-containing yeast precursor tRNAs. It is an unusual protein because it has three distinct catalytic activities. It functions as a polynucleotide kinase, as a cyclic phosphodiesterase, and as an RNA ligase. We have studied the binding interactions between ligase and precursor tRNAs containing two photoreactive uridine analogues, 4-thiouridine and 5-bromouridine. When irradiated with long ultraviolet light, RNA containing these analogues can form specific covalent bonds with associated proteins. In this paper, we show that 4-thiouridine triphosphate and 5-bromouridine triphosphate were readily incorporated into a precursor tRNA(Phe) that was synthesized, in vitro, with bacteriophage T7 RNA polymerase. The analogue-containing precursor tRNAs were authentic substrates for the two splicing enzymes that were tested (endonuclease and ligase), and they formed specific covalent bonds with ligase when they were irradiated with long-wavelength ultraviolet light. We have determined the position of three major cross-links and one minor cross-link on precursor tRNA(Phe) that were located within the intron and near the 3' splice site. On the basis of these data, we present a model for the in vivo splicing reaction of yeast precursor tRNAs

  6. Mouse homologue of yeast Prp19 interacts with mouse SUG1, the regulatory subunit of 26S proteasome

    International Nuclear Information System (INIS)

    Sihn, Choong-Ryoul; Cho, Si Young; Lee, Jeong Ho; Lee, Tae Ryong; Kim, Sang Hoon

    2007-01-01

    Yeast Prp19 has been shown to involve in pre-mRNA splicing and DNA repair as well as being an ubiquitin ligase. Mammalian homologue of yeast Prp19 also plays on similar functional activities in cells. In the present study, we isolated mouse SUG1 (mSUG1) as binding partner of mouse Prp19 (mPrp19) by the yeast two-hybrid system. We confirmed the interaction of mPrp9 with mSUG1 by GST pull-down assay and co-immunoprecipitation assay. The N-terminus of mPrp19 including U-box domain was associated with the C-terminus of mSUG1. Although, mSUG1 is a regulatory subunit of 26S proteasome, mPrp19 was not degraded in the proteasome-dependent pathway. Interestingly, GFP-mPrp19 fusion protein was co-localized with mSUG1 protein in cytoplasm as the formation of the speckle-like structures in the presence of a proteasome inhibitor MG132. In addition, the activity of proteasome was increased in cells transfected with mPrp19. Taken together, these results suggest that mPrp19 involves the regulation of protein turnover and may transport its substrates to 26S proteasome through mSUG1 protein

  7. The tumor suppressor homolog in fission yeast, myh1+, displays a strong interaction with the checkpoint gene rad1+

    International Nuclear Information System (INIS)

    Jansson, Kristina; Warringer, Jonas; Farewell, Anne; Park, Han-Oh; Hoe, Kwang-Lae; Kim, Dong-Uk; Hayles, Jacqueline; Sunnerhagen, Per

    2008-01-01

    The DNA glycosylase MutY is strongly conserved in evolution, and homologs are found in most eukaryotes and prokaryotes examined. This protein is implicated in repair of oxidative DNA damage, in particular adenine mispaired opposite 7,8-dihydro-8-oxoguanine. Previous investigations in Escherichia coli, fission yeast, and mammalian cells show an association of mutations in MutY homologs with a mutator phenotype and carcinogenesis. Eukaryotic MutY homologs physically associate with several proteins with a role in replication, DNA repair, and checkpoint signaling, specifically the trimeric 9-1-1 complex. In a genetic investigation of the fission yeast MutY homolog, myh1 + , we show that the myh1 mutation confers a moderately increased UV sensitivity alone and in combination with mutations in several DNA repair genes. The myh1 rad1, and to a lesser degree myh1 rad9, double mutants display a synthetic interaction resulting in enhanced sensitivity to DNA damaging agents and hydroxyurea. UV irradiation of myh1 rad1 double mutants results in severe chromosome segregation defects and visible DNA fragmentation, and a failure to activate the checkpoint. Additionally, myh1 rad1 double mutants exhibit morphological defects in the absence of DNA damaging agents. We also found a moderate suppression of the slow growth and UV sensitivity of rhp51 mutants by the myh1 mutation. Our results implicate fission yeast Myh1 in repair of a wider range of DNA damage than previously thought, and functionally link it to the checkpoint pathway

  8. Enhancing the Functional Content of Eukaryotic Protein Interaction Networks

    Science.gov (United States)

    Pandey, Gaurav; Arora, Sonali; Manocha, Sahil; Whalen, Sean

    2014-01-01

    Protein interaction networks are a promising type of data for studying complex biological systems. However, despite the rich information embedded in these networks, these networks face important data quality challenges of noise and incompleteness that adversely affect the results obtained from their analysis. Here, we apply a robust measure of local network structure called common neighborhood similarity (CNS) to address these challenges. Although several CNS measures have been proposed in the literature, an understanding of their relative efficacies for the analysis of interaction networks has been lacking. We follow the framework of graph transformation to convert the given interaction network into a transformed network corresponding to a variety of CNS measures evaluated. The effectiveness of each measure is then estimated by comparing the quality of protein function predictions obtained from its corresponding transformed network with those from the original network. Using a large set of human and fly protein interactions, and a set of over GO terms for both, we find that several of the transformed networks produce more accurate predictions than those obtained from the original network. In particular, the measure and other continuous CNS measures perform well this task, especially for large networks. Further investigation reveals that the two major factors contributing to this improvement are the abilities of CNS measures to prune out noisy edges and enhance functional coherence in the transformed networks. PMID:25275489

  9. Interactions between yeast lees and wine polyphenols during simulation of wine aging. II. Analysis of desorbed polyphenol compounds from yeast lees.

    Science.gov (United States)

    Mazauric, Jean-Paul; Salmon, Jean-Michel

    2006-05-31

    In the first part of this work, the analysis of the polyphenolic compounds remaining in the wine after different contact times with yeast lees during simulation of red wine aging was undertaken. To achieve a more precise view of the wine polyphenols adsorbed on lees during red wine aging and to establish a clear balance between adsorbed and remnant polyphenol compounds, the specific analysis of the chemical composition of the adsorbed polyphenolic compounds (condensed tannins and anthocyanins) after their partial desorbtion from yeast lees by denaturation treatments was realized in the second part of the study. The total recovery of polyphenol compounds from yeast lees was not complete, since a rather important part of the initial wine colored polyphenols, especially those with a dominant blue color component, remained strongly adsorbed on yeast lees, as monitored by color tristimulus and reflectance spectra measurements. All anthocyanins were recovered at a rather high percentage (about 62%), and it was demonstrated that they were not adsorbed in relation with their sole polarity. Very few monomeric phenolic compounds were extracted from yeast lees. With the use of drastic denaturing treatments, the total recovery of condensed tannins reached 83%. Such tannins extracted from yeast lees exhibited very high polymeric size and a rather high percentage of galloylated residues by comparison with initial wine tannins, indicating that nonpolar tannins were preferentially desorbed from yeast lees by the extraction treatments.

  10. Online networks, social interaction and segregation: An evolutionary approach

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio

    2018-01-01

    There is growing evidence that face-to-face interaction is declining in many countries, exacerbating the phenomenon of social isolation. On the other hand, social interaction through online networking sites is steeply rising. To analyze these societal dynamics, we have built an evolutionary game model in which agents can choose between three strategies of social participation: 1) interaction via both online social networks and face-to-face encounters; 2) interaction by exclusive means of face...

  11. Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools.

    Science.gov (United States)

    Miryala, Sravan Kumar; Anbarasu, Anand; Ramaiah, Sudha

    2018-02-05

    Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks. Copyright © 2017 Elsevier B.V. All rights reserved.

  12. Genetic interaction network of the Saccharomyces cerevisiae type 1 phosphatase Glc7

    Directory of Open Access Journals (Sweden)

    Neszt Michael

    2008-07-01

    Full Text Available Abstract Background Protein kinases and phosphatases regulate protein phosphorylation, a critical means of modulating protein function, stability and localization. The identification of functional networks for protein phosphatases has been slow due to their redundant nature and the lack of large-scale analyses. We hypothesized that a genome-scale analysis of genetic interactions using the Synthetic Genetic Array could reveal protein phosphatase functional networks. We apply this approach to the conserved type 1 protein phosphatase Glc7, which regulates numerous cellular processes in budding yeast. Results We created a novel glc7 catalytic mutant (glc7-E101Q. Phenotypic analysis indicates that this novel allele exhibits slow growth and defects in glucose metabolism but normal cell cycle progression and chromosome segregation. This suggests that glc7-E101Q is a hypomorphic glc7 mutant. Synthetic Genetic Array analysis of glc7-E101Q revealed a broad network of 245 synthetic sick/lethal interactions reflecting that many processes are required when Glc7 function is compromised such as histone modification, chromosome segregation and cytokinesis, nutrient sensing and DNA damage. In addition, mitochondrial activity and inheritance and lipid metabolism were identified as new processes involved in buffering Glc7 function. An interaction network among 95 genes genetically interacting with GLC7 was constructed by integration of genetic and physical interaction data. The obtained network has a modular architecture, and the interconnection among the modules reflects the cooperation of the processes buffering Glc7 function. Conclusion We found 245 genes required for the normal growth of the glc7-E101Q mutant. Functional grouping of these genes and analysis of their physical and genetic interaction patterns bring new information on Glc7-regulated processes.

  13. Photolabeling identifies an interaction between phosphatidylcholine and glycerol-3-phosphate dehydrogenase (Gut2p) in yeast mitochondria

    DEFF Research Database (Denmark)

    Janssen, Marjolein J F W; van Voorst, Frank; Ploeger, Ginette E J

    2002-01-01

    In search of mitochondrial proteins interacting with phosphatidylcholine (PC), a photolabeling approach was applied, in which photoactivatable probes were incorporated into isolated yeast mitochondria. Only a limited number of proteins were labeled upon photoactivation, using either the PC analogue......-dependent mitochondrial glycerol-3-phosphate dehydrogenase. This was confirmed by the lack of specific labeling in mitochondria from a gut2 deletion strain. Only under conditions where the inner membrane was accessible to the probe, Gut2p was labeled by [125I]TID-PC, in parallel with increased labeling of the phosphate...

  14. Core Data of Yeast Interacting Proteins Database (Annotation Updated Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available hod As the indicator of reliability of the interactions obtained by the experiment, the literature informati...ic Acids Res. 28, 73-76.) are used for literature collection. Number of data entries 841 interactions Data i...d from the YPD. Literature sharing score The score concerning co-occurrence of Prey and Bait in the litera...ture, calculated by the calculation formula. Calculation formula for the score: Cur

  15. Yeast for virus research

    Science.gov (United States)

    Zhao, Richard Yuqi

    2017-01-01

    Budding yeast (Saccharomyces cerevisiae) and fission yeast (Schizosaccharomyces pombe) are two popular model organisms for virus research. They are natural hosts for viruses as they carry their own indigenous viruses. Both yeasts have been used for studies of plant, animal and human viruses. Many positive sense (+) RNA viruses and some DNA viruses replicate with various levels in yeasts, thus allowing study of those viral activities during viral life cycle. Yeasts are single cell eukaryotic organisms. Hence, many of the fundamental cellular functions such as cell cycle regulation or programed cell death are highly conserved from yeasts to higher eukaryotes. Therefore, they are particularly suited to study the impact of those viral activities on related cellular activities during virus-host interactions. Yeasts present many unique advantages in virus research over high eukaryotes. Yeast cells are easy to maintain in the laboratory with relative short doubling time. They are non-biohazardous, genetically amendable with small genomes that permit genome-wide analysis of virologic and cellular functions. In this review, similarities and differences of these two yeasts are described. Studies of virologic activities such as viral translation, viral replication and genome-wide study of virus-cell interactions in yeasts are highlighted. Impacts of viral proteins on basic cellular functions such as cell cycle regulation and programed cell death are discussed. Potential applications of using yeasts as hosts to carry out functional analysis of small viral genome and to develop high throughput drug screening platform for the discovery of antiviral drugs are presented. PMID:29082230

  16. Analysis of the Yeast Kinome Reveals a Network of Regulated Protein Localization during Filamentous Growth

    OpenAIRE

    Bharucha, Nikë; Ma, Jun; Dobry, Craig J.; Lawson, Sarah K.; Yang, Zhifen; Kumar, Anuj

    2008-01-01

    The subcellular distribution of kinases and other signaling proteins is regulated in response to cellular cues; however, the extent of this regulation has not been investigated for any gene set in any organism. Here, we present a systematic analysis of protein kinases in the budding yeast, screening for differential localization during filamentous growth. Filamentous growth is an important stress response involving mitogen-activated protein kinase and cAMP-dependent protein kinase signaling m...

  17. Cluster Approach to Network Interaction in Pedagogical University

    Science.gov (United States)

    Chekaleva, Nadezhda V.; Makarova, Natalia S.; Drobotenko, Yulia B.

    2016-01-01

    The study presented in the article is devoted to the analysis of theory and practice of network interaction within the framework of education clusters. Education clusters are considered to be a novel form of network interaction in pedagogical education in Russia. The aim of the article is to show the advantages and disadvantages of the cluster…

  18. Cellular localization of Sun4p and its interaction with proteins in the yeast birth scar

    Czech Academy of Sciences Publication Activity Database

    Kuznetsov, E.; Váchová, Libuše; Palková, Z.

    2016-01-01

    Roč. 15, č. 14 (2016), s. 1898-1907 ISSN 1538-4101 R&D Projects: GA ČR GA13-08605S; GA MŠk(CZ) ED1.1.00/02.0109 Institutional support: RVO:61388971 Keywords : cell wall * glucanases * SUN family of proteins * yeast birth scar Subject RIV: EE - Microbiology, Virology Impact factor: 3.530, year: 2016

  19. Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

    Directory of Open Access Journals (Sweden)

    Arthur Brady

    Full Text Available As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all. We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

  20. Fault tolerance in protein interaction networks: stable bipartite subgraphs and redundant pathways.

    Science.gov (United States)

    Brady, Arthur; Maxwell, Kyle; Daniels, Noah; Cowen, Lenore J

    2009-01-01

    As increasing amounts of high-throughput data for the yeast interactome become available, more system-wide properties are uncovered. One interesting question concerns the fault tolerance of protein interaction networks: whether there exist alternative pathways that can perform some required function if a gene essential to the main mechanism is defective, absent or suppressed. A signature pattern for redundant pathways is the BPM (between-pathway model) motif, introduced by Kelley and Ideker. Past methods proposed to search the yeast interactome for BPM motifs have had several important limitations. First, they have been driven heuristically by local greedy searches, which can lead to the inclusion of extra genes that may not belong in the motif; second, they have been validated solely by functional coherence of the putative pathways using GO enrichment, making it difficult to evaluate putative BPMs in the absence of already known biological annotation. We introduce stable bipartite subgraphs, and show they form a clean and efficient way of generating meaningful BPMs which naturally discard extra genes included by local greedy methods. We show by GO enrichment measures that our BPM set outperforms previous work, covering more known complexes and functional pathways. Perhaps most importantly, since our BPMs are initially generated by examining the genetic-interaction network only, the location of edges in the protein-protein physical interaction network can then be used to statistically validate each candidate BPM, even with sparse GO annotation (or none at all). We uncover some interesting biological examples of previously unknown putative redundant pathways in such areas as vesicle-mediated transport and DNA repair.

  1. Full Data of Yeast Interacting Proteins Database (Annotation Updated Version) - Yeast Interacting Proteins Database | LSDB Archive [Life Science Database Archive metadata

    Lifescience Database Archive (English)

    Full Text Available As the indicator of reliability of the interactions obtained by the experiment, the literature...cids Res. 28, 73-76.) are used for literature collection. Number of data entries ...ber of articles obtained from the YPD. Literature sharing score The score concerning co-occurrence of Prey and Bait in the literature

  2. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Directory of Open Access Journals (Sweden)

    Recep Colak

    2010-10-01

    Full Text Available Computational prediction of functionally related groups of genes (functional modules from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented.We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB, by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples.We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely

  3. Module discovery by exhaustive search for densely connected, co-expressed regions in biomolecular interaction networks.

    Science.gov (United States)

    Colak, Recep; Moser, Flavia; Chu, Jeffrey Shih-Chieh; Schönhuth, Alexander; Chen, Nansheng; Ester, Martin

    2010-10-25

    Computational prediction of functionally related groups of genes (functional modules) from large-scale data is an important issue in computational biology. Gene expression experiments and interaction networks are well studied large-scale data sources, available for many not yet exhaustively annotated organisms. It has been well established, when analyzing these two data sources jointly, modules are often reflected by highly interconnected (dense) regions in the interaction networks whose participating genes are co-expressed. However, the tractability of the problem had remained unclear and methods by which to exhaustively search for such constellations had not been presented. We provide an algorithmic framework, referred to as Densely Connected Biclustering (DECOB), by which the aforementioned search problem becomes tractable. To benchmark the predictive power inherent to the approach, we computed all co-expressed, dense regions in physical protein and genetic interaction networks from human and yeast. An automatized filtering procedure reduces our output which results in smaller collections of modules, comparable to state-of-the-art approaches. Our results performed favorably in a fair benchmarking competition which adheres to standard criteria. We demonstrate the usefulness of an exhaustive module search, by using the unreduced output to more quickly perform GO term related function prediction tasks. We point out the advantages of our exhaustive output by predicting functional relationships using two examples. We demonstrate that the computation of all densely connected and co-expressed regions in interaction networks is an approach to module discovery of considerable value. Beyond confirming the well settled hypothesis that such co-expressed, densely connected interaction network regions reflect functional modules, we open up novel computational ways to comprehensively analyze the modular organization of an organism based on prevalent and largely available large

  4. Utilizing Biotinylated Proteins Expressed in Yeast to Visualize DNA–Protein Interactions at the Single-Molecule Level

    Directory of Open Access Journals (Sweden)

    Huijun Xue

    2017-10-01

    Full Text Available Much of our knowledge in conventional biochemistry has derived from bulk assays. However, many stochastic processes and transient intermediates are hidden when averaged over the ensemble. The powerful technique of single-molecule fluorescence microscopy has made great contributions to the understanding of life processes that are inaccessible when using traditional approaches. In single-molecule studies, quantum dots (Qdots have several unique advantages over other fluorescent probes, such as high brightness, extremely high photostability, and large Stokes shift, thus allowing long-time observation and improved signal-to-noise ratios. So far, however, there is no convenient way to label proteins purified from budding yeast with Qdots. Based on BirA–Avi and biotin–streptavidin systems, we have established a simple method to acquire a Qdot-labeled protein and visualize its interaction with DNA using total internal reflection fluorescence microscopy. For proof-of-concept, we chose replication protein A (RPA and origin recognition complex (ORC as the proteins of interest. Proteins were purified from budding yeast with high biotinylation efficiency and rapidly labeled with streptavidin-coated Qdots. Interactions between proteins and DNA were observed successfully at the single-molecule level.

  5. Interactions of checkpoint-genes RAD9, RAD17, RAD24 and RAD53 determining radioresistance of Yeast Saccharomyces Cerevisiae

    International Nuclear Information System (INIS)

    Koltovaya, N.A.; Nikulushkina, Yu.V.; Roshchina, M.P.; Devin, A.B.

    2007-01-01

    The mechanisms of genetic control of progress through the division cell cycle (checkpoint-control) in yeast Saccharomyces cerevisiae have been studied intensively. To investigate the role of checkpoint-genes RAD9, RAD17, RAD24, RAD53 in cell radioresistance we have investigated cell sensitivity of double mutants to γ-ray. Double mutants involving various combinations with rad9Δ show epistatic interactions, i.e. the sensitivity of the double mutants to γ-ray was no greater than that of more sensitive of the two single mutants. This suggests that all these genes govern the same pathway. This group of genes was named RAD9-epistasis group. It is interesting to note that the genes RAD9 and RAD53 have positive effect but RAD17 and RAD24 have negative effect on radiosensitivity of yeast cells. Interactions between mutations may differ depending on the agent γ-ray or UV-light, for example mutations rad9Δ and rad24Δ show additive effect for γ-ray and epistatic effect for UV-light

  6. Interaction of CSFV E2 protein with swine host factors as detected by yeast two-hybrid system.

    Directory of Open Access Journals (Sweden)

    Douglas P Gladue

    Full Text Available E2 is one of the envelope glycoproteins of pestiviruses, including classical swine fever virus (CSFV and bovine viral diarrhea virus (BVDV. E2 is involved in several critical functions, including virus entry into target cells, induction of a protective immune response and virulence in swine. However, there is no information regarding any host binding partners for the E2 proteins. Here, we utilized the yeast two-hybrid system and identified fifty-seven host proteins as positive binding partners which bound E2 from both CSFV and BVDV with the exception of two proteins that were found to be positive for binding only to CSFV E2. Alanine scanning of CSFV E2 demonstrated that the binding sites for these cellular proteins on E2 are likely non-linear binding sites. The possible roles of the identified host proteins are discussed as the results presented here will be important for future studies to elucidate mechanisms of host protein-virus interactions during pestivirus infection. However, due to the limitations of the yeast two hybrid system, the proteins identified is not exhaustive and each interaction identified needs to be confirmed by independent experimental approaches in the context of virus-infected cells before any definitive conclusion can be drawn on relevance for the virus life cycle.

  7. Spatial organization of the budding yeast genome in the cell nucleus and identification of specific chromatin interactions from multi-chromosome constrained chromatin model.

    Science.gov (United States)

    Gürsoy, Gamze; Xu, Yun; Liang, Jie

    2017-07-01

    Nuclear landmarks and biochemical factors play important roles in the organization of the yeast genome. The interaction pattern of budding yeast as measured from genome-wide 3C studies are largely recapitulated by model polymer genomes subject to landmark constraints. However, the origin of inter-chromosomal interactions, specific roles of individual landmarks, and the roles of biochemical factors in yeast genome organization remain unclear. Here we describe a multi-chromosome constrained self-avoiding chromatin model (mC-SAC) to gain understanding of the budding yeast genome organization. With significantly improved sampling of genome structures, both intra- and inter-chromosomal interaction patterns from genome-wide 3C studies are accurately captured in our model at higher resolution than previous studies. We show that nuclear confinement is a key determinant of the intra-chromosomal interactions, and centromere tethering is responsible for the inter-chromosomal interactions. In addition, important genomic elements such as fragile sites and tRNA genes are found to be clustered spatially, largely due to centromere tethering. We uncovered previously unknown interactions that were not captured by genome-wide 3C studies, which are found to be enriched with tRNA genes, RNAPIII and TFIIS binding. Moreover, we identified specific high-frequency genome-wide 3C interactions that are unaccounted for by polymer effects under landmark constraints. These interactions are enriched with important genes and likely play biological roles.

  8. Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach

    Directory of Open Access Journals (Sweden)

    Luan Yihui

    2009-09-01

    Full Text Available Abstract Background Many aspects of biological functions can be modeled by biological networks, such as protein interaction networks, metabolic networks, and gene coexpression networks. Studying the statistical properties of these networks in turn allows us to infer biological function. Complex statistical network models can potentially more accurately describe the networks, but it is not clear whether such complex models are better suited to find biologically meaningful subnetworks. Results Recent studies have shown that the degree distribution of the nodes is not an adequate statistic in many molecular networks. We sought to extend this statistic with 2nd and 3rd order degree correlations and developed a pseudo-likelihood approach to estimate the parameters. The approach was used to analyze the MIPS and BIOGRID yeast protein interaction networks, and two yeast coexpression networks. We showed that 2nd order degree correlation information gave better predictions of gene interactions in both protein interaction and gene coexpression networks. However, in the biologically important task of predicting functionally homogeneous modules, degree correlation information performs marginally better in the case of the MIPS and BIOGRID protein interaction networks, but worse in the case of gene coexpression networks. Conclusion Our use of dK models showed that incorporation of degree correlations could increase predictive power in some contexts, albeit sometimes marginally, but, in all contexts, the use of third-order degree correlations decreased accuracy. However, it is possible that other parameter estimation methods, such as maximum likelihood, will show the usefulness of incorporating 2nd and 3rd degree correlations in predicting functionally homogeneous modules.

  9. Usefulness and limitations of dK random graph models to predict interactions and functional homogeneity in biological networks under a pseudo-likelihood parameter estimation approach.

    Science.gov (United States)

    Wang, Wenhui; Nunez-Iglesias, Juan; Luan, Yihui; Sun, Fengzhu

    2009-09-03

    Many aspects of biological functions can be modeled by biological networks, such as protein interaction networks, metabolic networks, and gene coexpression networks. Studying the statistical properties of these networks in turn allows us to infer biological function. Complex statistical network models can potentially more accurately describe the networks, but it is not clear whether such complex models are better suited to find biologically meaningful subnetworks. Recent studies have shown that the degree distribution of the nodes is not an adequate statistic in many molecular networks. We sought to extend this statistic with 2nd and 3rd order degree correlations and developed a pseudo-likelihood approach to estimate the parameters. The approach was used to analyze the MIPS and BIOGRID yeast protein interaction networks, and two yeast coexpression networks. We showed that 2nd order degree correlation information gave better predictions of gene interactions in both protein interaction and gene coexpression networks. However, in the biologically important task of predicting functionally homogeneous modules, degree correlation information performs marginally better in the case of the MIPS and BIOGRID protein interaction networks, but worse in the case of gene coexpression networks. Our use of dK models showed that incorporation of degree correlations could increase predictive power in some contexts, albeit sometimes marginally, but, in all contexts, the use of third-order degree correlations decreased accuracy. However, it is possible that other parameter estimation methods, such as maximum likelihood, will show the usefulness of incorporating 2nd and 3rd degree correlations in predicting functionally homogeneous modules.

  10. The interactive effect of fungicide residues and yeast assimilable nitrogen on fermentation kinetics and hydrogen sulfide production during cider fermentation.

    Science.gov (United States)

    Boudreau, Thomas F; Peck, Gregory M; O'Keefe, Sean F; Stewart, Amanda C

    2017-01-01

    Fungicide residues on fruit may adversely affect yeast during cider fermentation, leading to sluggish or stuck fermentation or the production of hydrogen sulfide (H 2 S), which is an undesirable aroma compound. This phenomenon has been studied in grape fermentation but not in apple fermentation. Low nitrogen availability, which is characteristic of apples, may further exacerbate the effects of fungicides on yeast during fermentation. The present study explored the effects of three fungicides: elemental sulfur (S 0 ) (known to result in increased H 2 S in wine); fenbuconazole (used in orchards but not vineyards); and fludioxonil (used in post-harvest storage of apples). Only S 0 led to increased H 2 S production. Fenbuconazole (≥0.2 mg L -1 ) resulted in a decreased fermentation rate and increased residual sugar. An interactive effect of yeast assimilable nitrogen (YAN) concentration and fenbuconazole was observed such that increasing the YAN concentration alleviated the negative effects of fenbuconazole on fermentation kinetics. Cidermakers should be aware that residual fenbuconazole (as low as 0.2 mg L -1 ) in apple juice may lead to stuck fermentation, especially when the YAN concentration is below 250 mg L -1 . These results indicate that fermentation problems attributed to low YAN may be caused or exacerbated by additional factors such as fungicide residues, which have a greater impact on fermentation performance under low YAN conditions. © 2016 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. © 2016 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

  11. Investigating physics learning with layered student interaction networks

    DEFF Research Database (Denmark)

    Bruun, Jesper; Traxler, Adrienne

    Centrality in student interaction networks (SINs) can be linked to variables like grades [1], persistence [2], and participation [3]. Recent efforts in the field of network science have been done to investigate layered - or multiplex - networks as mathematical objects [4]. These networks can be e......, this study investigates how target entropy [5,1] and pagerank [6,7] are affected when we take time and modes of interaction into account. We present our preliminary models and results and outline our future work in this area....

  12. Global patterns of interaction specialization in bird-flower networks

    DEFF Research Database (Denmark)

    Zanata, Thais B.; Dalsgaard, Bo; Passos, Fernando C.

    2017-01-01

    , such as plant species richness, asymmetry, latitude, insularity, topography, sampling methods and intensity. Results: Hummingbird–flower networks were more specialized than honeyeater–flower networks. Specifically, hummingbird–flower networks had a lower proportion of realized interactions (lower C), decreased...... in the interaction patterns with their floral resources. Location: Americas, Africa, Asia and Oceania/Australia. Methods: We compiled interaction networks between birds and floral resources for 79 hummingbird, nine sunbird and 33 honeyeater communities. Interaction specialization was quantified through connectance...... (C), complementary specialization (H2′), binary (QB) and weighted modularity (Q), with both observed and null-model corrected values. We compared interaction specialization among the three types of bird–flower communities, both independently and while controlling for potential confounding variables...

  13. Predicting and validating protein interactions using network structure.

    Directory of Open Access Journals (Sweden)

    Pao-Yang Chen

    2008-07-01

    Full Text Available Protein interactions play a vital part in the function of a cell. As experimental techniques for detection and validation of protein interactions are time consuming, there is a need for computational methods for this task. Protein interactions appear to form a network with a relatively high degree of local clustering. In this paper we exploit this clustering by suggesting a score based on triplets of observed protein interactions. The score utilises both protein characteristics and network properties. Our score based on triplets is shown to complement existing techniques for predicting protein interactions, outperforming them on data sets which display a high degree of clustering. The predicted interactions score highly against test measures for accuracy. Compared to a similar score derived from pairwise interactions only, the triplet score displays higher sensitivity and specificity. By looking at specific examples, we show how an experimental set of interactions can be enriched and validated. As part of this work we also examine the effect of different prior databases upon the accuracy of prediction and find that the interactions from the same kingdom give better results than from across kingdoms, suggesting that there may be fundamental differences between the networks. These results all emphasize that network structure is important and helps in the accurate prediction of protein interactions. The protein interaction data set and the program used in our analysis, and a list of predictions and validations, are available at http://www.stats.ox.ac.uk/bioinfo/resources/PredictingInteractions.

  14. Specific non-monotonous interactions increase persistence of ecological networks.

    Science.gov (United States)

    Yan, Chuan; Zhang, Zhibin

    2014-03-22

    The relationship between stability and biodiversity has long been debated in ecology due to opposing empirical observations and theoretical predictions. Species interaction strength is often assumed to be monotonically related to population density, but the effects on stability of ecological networks of non-monotonous interactions that change signs have not been investigated previously. We demonstrate that for four kinds of non-monotonous interactions, shifting signs to negative or neutral interactions at high population density increases persistence (a measure of stability) of ecological networks, while for the other two kinds of non-monotonous interactions shifting signs to positive interactions at high population density decreases persistence of networks. Our results reveal a novel mechanism of network stabilization caused by specific non-monotonous interaction types through either increasing stable equilibrium points or reducing unstable equilibrium points (or both). These specific non-monotonous interactions may be important in maintaining stable and complex ecological networks, as well as other networks such as genes, neurons, the internet and human societies.

  15. Do networks of social interactions reflect patterns of kinship?

    Directory of Open Access Journals (Sweden)

    Joah R. MADDEN, Johanna F. NIELSEN, Tim H. CLUTTON-BROCK

    2012-04-01

    Full Text Available The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal association between individuals, and is presumed to facilitate inclusive fitness benefits. Such structure may be evident at a finer, behavioural, scale with individuals preferentially interacting with kin. We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks: grooming, dominance or foraging competitions. Networks of dominance interactions were positively related to networks of kinship, with close relatives engaging in dominance interactions with each other. This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin, which are most likely to be able to discern kin through simple rules of thumb. Conversely, we found no relationship between kinship networks and either grooming networks or networks of foraging competitions. This is surprising because a positive association between kin in a grooming network, or a negative association between kin in a network of foraging competitions offers opportunities for inclusive fitness benefits. Indeed, the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members. We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fitness benefits, and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to individuals perhaps through mutualism or manipulation [Current Zoology 58 (2: 319-328, 2012].

  16. Do networks of social interactions reflect patterns of kinship?

    Institute of Scientific and Technical Information of China (English)

    Joah R. MADDEN; Johanna F. NIEL SEN; Tim H. CLUTTON-BROCK

    2012-01-01

    The underlying kin structure of groups of animals may be glimpsed from patterns of spatial position or temporal association between individuals,and is presumed to facilitate inclusive fitness benefits.Such structure may be evident at a finer,behavioural,scale with individuals preferentially interacting with kin.We tested whether kin structure within groups of meerkats Suricata suricatta matched three forms of social interaction networks:grooming,dominance or foraging competitions.Networks of dominance interactions were positively related to networks of kinship,with close relatives engaging in dominance interactions with each other.This relationship persisted even after excluding the breeding dominant pair and when we restricted the kinship network to only include links between first order kin,which are most likely to be able to discern kin through simple rules of thumb.Conversely,we found no relationship between kinship networks and either grooming networks or networks of foraging competitions.This is surprising because a positive association between kin in a grooming network,or a negative association between kin in a network of foraging competitions offers opportunities for inclusive fitness benefits.Indeed,the positive association between kin in a network of dominance interactions that we did detect does not offer clear inclusive fitness benefits to group members.We conclude that kin structure in behavioural interactions in meerkats may be driven by factors other than indirect fitness benefits,and that networks of cooperative behaviours such as grooming may be driven by direct benefits accruing to individuals perhaps through mutualism or manipulation [Current Zoology 58 (2):319-328,2012].

  17. A Type-2 fuzzy data fusion approach for building reliable weighted protein interaction networks with application in protein complex detection.

    Science.gov (United States)

    Mehranfar, Adele; Ghadiri, Nasser; Kouhsar, Morteza; Golshani, Ashkan

    2017-09-01

    Detecting the protein complexes is an important task in analyzing the protein interaction networks. Although many algorithms predict protein complexes in different ways, surveys on the interaction networks indicate that about 50% of detected interactions are false positives. Consequently, the accuracy of existing methods needs to be improved. In this paper we propose a novel algorithm to detect the protein complexes in 'noisy' protein interaction data. First, we integrate several biological data sources to determine the reliability of each interaction and determine more accurate weights for the interactions. A data fusion component is used for this step, based on the interval type-2 fuzzy voter that provides an efficient combination of the information sources. This fusion component detects the errors and diminishes their effect on the detection protein complexes. So in the first step, the reliability scores have been assigned for every interaction in the network. In the second step, we have proposed a general protein complex detection algorithm by exploiting and adopting the strong points of other algorithms and existing hypotheses regarding real complexes. Finally, the proposed method has been applied for the yeast interaction datasets for predicting the interactions. The results show that our framework has a better performance regarding precision and F-measure than the existing approaches. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Influences of brain development and ageing on cortical interactive networks.

    Science.gov (United States)

    Zhu, Chengyu; Guo, Xiaoli; Jin, Zheng; Sun, Junfeng; Qiu, Yihong; Zhu, Yisheng; Tong, Shanbao

    2011-02-01

    To study the effect of brain development and ageing on the pattern of cortical interactive networks. By causality analysis of multichannel electroencephalograph (EEG) with partial directed coherence (PDC), we investigated the different neural networks involved in the whole cortex as well as the anterior and posterior areas in three age groups, i.e., children (0-10 years), mid-aged adults (26-38 years) and the elderly (56-80 years). By comparing the cortical interactive networks in different age groups, the following findings were concluded: (1) the cortical interactive network in the right hemisphere develops earlier than its left counterpart in the development stage; (2) the cortical interactive network of anterior cortex, especially at C3 and F3, is demonstrated to undergo far more extensive changes, compared with the posterior area during brain development and ageing; (3) the asymmetry of the cortical interactive networks declines during ageing with more loss of connectivity in the left frontal and central areas. The age-related variation of cortical interactive networks from resting EEG provides new insights into brain development and ageing. Our findings demonstrated that the PDC analysis of EEG is a powerful approach for characterizing the cortical functional connectivity during brain development and ageing. Copyright © 2010 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

  19. Mean field interaction in biochemical reaction networks

    KAUST Repository

    Tembine, Hamidou; Tempone, Raul; Vilanova, Pedro

    2011-01-01

    In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits

  20. Insight into bacterial virulence mechanisms against host immune response via the Yersinia pestis-human protein-protein interaction network.

    Science.gov (United States)

    Yang, Huiying; Ke, Yuehua; Wang, Jian; Tan, Yafang; Myeni, Sebenzile K; Li, Dong; Shi, Qinghai; Yan, Yanfeng; Chen, Hui; Guo, Zhaobiao; Yuan, Yanzhi; Yang, Xiaoming; Yang, Ruifu; Du, Zongmin

    2011-11-01

    A Yersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66 Y. pestis bait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted by Y. pestis were significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted by Y. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted by Y. pestis are highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance of Y. pestis to phagocytosis. Interference with TLR and MAPK signaling pathways by Y. pestis reflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting with Y. pestis (16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibit in vitro actin assembly mediated by VASP.

  1. Empirical evaluation of neutral interactions in host-parasite networks.

    Science.gov (United States)

    Canard, E F; Mouquet, N; Mouillot, D; Stanko, M; Miklisova, D; Gravel, D

    2014-04-01

    While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization.

  2. A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

    NARCIS (Netherlands)

    Herrgård, Markus J.; Swainston, Neil; Dobson, Paul; Dunn, Warwick B.; Arga, K. Yalçin; Arvas, Mikko; Blüthgen, Nils; Borger, Simon; Costenoble, Roeland; Heinemann, Matthias; Hucka, Michael; Novère, Nicolas Le; Li, Peter; Liebermeister, Wolfram; Mo, Monica L.; Oliveira, Ana Paula; Petranovic, Dina; Pettifer, Stephen; Simeonidis, Evangelos; Smallbone, Kieran; Spasić, Irena; Weichart, Dieter; Brent, Roger; Broomhead, David S.; Westerhoff, Hans V.; Kırdar, Betül; Penttilä, Merja; Klipp, Edda; Palsson, Bernhard Ø.; Sauer, Uwe; Oliver, Stephen G.; Mendes, Pedro; Nielsen, Jens; Kell, Douglas B.

    2008-01-01

    Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and

  3. Yeasts in foods and beverages: impact on product quality and safety.

    Science.gov (United States)

    Fleet, Graham H

    2007-04-01

    The role of yeasts in food and beverage production extends beyond the well-known bread, beer and wine fermentations. Molecular analytical technologies have led to a major revision of yeast taxonomy, and have facilitated the ecological study of yeasts in many other products. The mechanisms by which yeasts grow in these ecosystems and impact on product quality can now be studied at the level of gene expression. Their growth and metabolic activities are moderated by a network of strain and species interactions, including interactions with bacteria and other fungi. Some yeasts have been developed as agents for the biocontrol of food spoilage fungi, and others are being considered as novel probiotic organisms. The association of yeasts with opportunistic infections and other adverse responses in humans raises new issues in the field of food safety.

  4. Interaction Networks: Generating High Level Hints Based on Network Community Clustering

    Science.gov (United States)

    Eagle, Michael; Johnson, Matthew; Barnes, Tiffany

    2012-01-01

    We introduce a novel data structure, the Interaction Network, for representing interaction-data from open problem solving environment tutors. We show how using network community detecting techniques are used to identify sub-goals in problems in a logic tutor. We then use those community structures to generate high level hints between sub-goals.…

  5. Default network modulation and large-scale network interactivity in healthy young and old adults.

    Science.gov (United States)

    Spreng, R Nathan; Schacter, Daniel L

    2012-11-01

    We investigated age-related changes in default, attention, and control network activity and their interactions in young and old adults. Brain activity during autobiographical and visuospatial planning was assessed using multivariate analysis and with intrinsic connectivity networks as regions of interest. In both groups, autobiographical planning engaged the default network while visuospatial planning engaged the attention network, consistent with a competition between the domains of internalized and externalized cognition. The control network was engaged for both planning tasks. In young subjects, the control network coupled with the default network during autobiographical planning and with the attention network during visuospatial planning. In old subjects, default-to-control network coupling was observed during both planning tasks, and old adults failed to deactivate the default network during visuospatial planning. This failure is not indicative of default network dysfunction per se, evidenced by default network engagement during autobiographical planning. Rather, a failure to modulate the default network in old adults is indicative of a lower degree of flexible network interactivity and reduced dynamic range of network modulation to changing task demands.

  6. Interacting Social Processes on Interconnected Networks.

    Directory of Open Access Journals (Sweden)

    Lucila G Alvarez-Zuzek

    Full Text Available We propose and study a model for the interplay between two different dynamical processes -one for opinion formation and the other for decision making- on two interconnected networks A and B. The opinion dynamics on network A corresponds to that of the M-model, where the state of each agent can take one of four possible values (S = -2,-1, 1, 2, describing its level of agreement on a given issue. The likelihood to become an extremist (S = ±2 or a moderate (S = ±1 is controlled by a reinforcement parameter r ≥ 0. The decision making dynamics on network B is akin to that of the Abrams-Strogatz model, where agents can be either in favor (S = +1 or against (S = -1 the issue. The probability that an agent changes its state is proportional to the fraction of neighbors that hold the opposite state raised to a power β. Starting from a polarized case scenario in which all agents of network A hold positive orientations while all agents of network B have a negative orientation, we explore the conditions under which one of the dynamics prevails over the other, imposing its initial orientation. We find that, for a given value of β, the two-network system reaches a consensus in the positive state (initial state of network A when the reinforcement overcomes a crossover value r*(β, while a negative consensus happens for r βc. We develop an analytical mean-field approach that gives an insight into these regimes and shows that both dynamics are equivalent along the crossover line (r*, β*.

  7. Personal Profiles: Enhancing Social Interaction in Learning Networks

    NARCIS (Netherlands)

    Berlanga, Adriana; Bitter-Rijpkema, Marlies; Brouns, Francis; Sloep, Peter; Fetter, Sibren

    2009-01-01

    Berlanga, A. J., Bitter-Rijpkema, M., Brouns, F., Sloep, P. B., & Fetter, S. (2011). Personal Profiles: Enhancing Social Interaction in Learning Networks. International Journal of Web Based Communities, 7(1), 66-82.

  8. An X-ray absorption spectroscopy study of the interactions of Ni2+ with yeast enolase.

    Science.gov (United States)

    Wang, S; Scott, R A; Lebioda, L; Zhou, Z H; Brewer, J M

    1995-05-15

    An x-ray absorption spectroscopy (XAS) study was carried out at pH 7.6 on solutions of Ni2+ and yeast enolase depleted of its physiological cofactor (Mg2+) in the presence or absence of substrate/product, the very strongly bound competitive inhibitor 2-phosphonoacetohydroxamate and Mg2+. Both "conformational" and "catalytic" Ni2+ are distorted octahedral in coordination, in agreement with several spectroscopic studies but in contrast to the coordination in the crystal at pH 6.0. The data are consistent with direct coordination of what must be the catalytic Ni2+ to the phosphate of the substrate, in agreement with some previous data but in disagreement with recent interpretations by other workers. The ligands around the metal ions obtained from the x-ray structure give simulated XAS spectra in good agreement with the observed spectra.

  9. Interactions within the yeast t-SNARE Sso1p that control SNARE complex assembly.

    Science.gov (United States)

    Munson, M; Chen, X; Cocina, A E; Schultz, S M; Hughson, F M

    2000-10-01

    In the eukaryotic secretory and endocytic pathways, transport vesicles shuttle cargo among intracellular organelles and to and from the plasma membrane. Cargo delivery entails fusion of the transport vesicle with its target, a process thought to be mediated by membrane bridging SNARE protein complexes. Temporal and spatial control of intracellular trafficking depends in part on regulating the assembly of these complexes. In vitro, SNARE assembly is inhibited by the closed conformation adopted by the syntaxin family of SNAREs. To visualize this closed conformation directly, the X-ray crystal structure of a yeast syntaxin, Sso1p, has been determined and refined to 2.1 A resolution. Mutants designed to destabilize the closed conformation exhibit accelerated rates of SNARE assembly. Our results provide insight into the mechanism of SNARE assembly and its intramolecular and intermolecular regulation.

  10. Defaunation leads to interaction deficits, not interaction compensation, in an island seed dispersal network.

    Science.gov (United States)

    Fricke, Evan C; Tewksbury, Joshua J; Rogers, Haldre S

    2018-01-01

    Following defaunation, the loss of interactions with mutualists such as pollinators or seed dispersers may be compensated through increased interactions with remaining mutualists, ameliorating the negative cascading impacts on biodiversity. Alternatively, remaining mutualists may respond to altered competition by reducing the breadth or intensity of their interactions, exacerbating negative impacts on biodiversity. Despite the importance of these responses for our understanding of the dynamics of mutualistic networks and their response to global change, the mechanism and magnitude of interaction compensation within real mutualistic networks remains largely unknown. We examined differences in mutualistic interactions between frugivores and fruiting plants in two island ecosystems possessing an intact or disrupted seed dispersal network. We determined how changes in the abundance and behavior of remaining seed dispersers either increased mutualistic interactions (contributing to "interaction compensation") or decreased interactions (causing an "interaction deficit") in the disrupted network. We found a "rich-get-richer" response in the disrupted network, where remaining frugivores favored the plant species with highest interaction frequency, a dynamic that worsened the interaction deficit among plant species with low interaction frequency. Only one of five plant species experienced compensation and the other four had significant interaction deficits, with interaction frequencies 56-95% lower in the disrupted network. These results do not provide support for the strong compensating mechanisms assumed in theoretical network models, suggesting that existing network models underestimate the prevalence of cascading mutualism disruption after defaunation. This work supports a mutualist biodiversity-ecosystem functioning relationship, highlighting the importance of mutualist diversity for sustaining diverse and resilient ecosystems. © 2017 John Wiley & Sons Ltd.

  11. Development of Attention Networks and Their Interactions in Childhood

    Science.gov (United States)

    Pozuelos, Joan P.; Paz-Alonso, Pedro M.; Castillo, Alejandro; Fuentes, Luis J.; Rueda, M. Rosario

    2014-01-01

    In the present study, we investigated developmental trajectories of alerting, orienting, and executive attention networks and their interactions over childhood. Two cross-sectional experiments were conducted with different samples of 6-to 12-year-old children using modified versions of the attention network task (ANT). In Experiment 1 (N = 106),…

  12. Global Diffusion of Interactive Networks. The Impact of Culture

    OpenAIRE

    Maitland, Carleen

    1998-01-01

    The Internet and other interactive networks are diffusing across the globe at rates that vary from country to country. Typically, economic and market structure variables are used to explain these differences. The addition of culture to these variables will provide a more robust understanding of the differences in Internet and interactive network diffusion. Existing analyses that identify culture as a predictor of diffusion do not adequately specificy the dimensions of culture and their imp...

  13. Functional Interaction Network Construction and Analysis for Disease Discovery.

    Science.gov (United States)

    Wu, Guanming; Haw, Robin

    2017-01-01

    Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

  14. Evidence for the additions of clustered interacting nodes during the evolution of protein interaction networks from network motifs

    Directory of Open Access Journals (Sweden)

    Guo Hao

    2011-05-01

    Full Text Available Abstract Background High-throughput screens have revealed large-scale protein interaction networks defining most cellular functions. How the proteins were added to the protein interaction network during its growth is a basic and important issue. Network motifs represent the simplest building blocks of cellular machines and are of biological significance. Results Here we study the evolution of protein interaction networks from the perspective of network motifs. We find that in current protein interaction networks, proteins of the same age class tend to form motifs and such co-origins of motif constituents are affected by their topologies and biological functions. Further, we find that the proteins within motifs whose constituents are of the same age class tend to be densely interconnected, co-evolve and share the same biological functions, and these motifs tend to be within protein complexes. Conclusions Our findings provide novel evidence for the hypothesis of the additions of clustered interacting nodes and point out network motifs, especially the motifs with the dense topology and specific function may play important roles during this process. Our results suggest functional constraints may be the underlying driving force for such additions of clustered interacting nodes.

  15. Functional modules by relating protein interaction networks and gene expression.

    Science.gov (United States)

    Tornow, Sabine; Mewes, H W

    2003-11-01

    Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

  16. Development of Novel Random Network Theory-Based Approaches to Identify Network Interactions among Nitrifying Bacteria

    Energy Technology Data Exchange (ETDEWEB)

    Shi, Cindy

    2015-07-17

    The interactions among different microbial populations in a community could play more important roles in determining ecosystem functioning than species numbers and their abundances, but very little is known about such network interactions at a community level. The goal of this project is to develop novel framework approaches and associated software tools to characterize the network interactions in microbial communities based on high throughput, large scale high-throughput metagenomics data and apply these approaches to understand the impacts of environmental changes (e.g., climate change, contamination) on network interactions among different nitrifying populations and associated microbial communities.

  17. Potyvirus helper component-proteinase self-interaction in the yeast two-hybrid system and delineation of the interaction domain involved.

    Science.gov (United States)

    Urcuqui-Inchima, S; Walter, J; Drugeon, G; German-Retana, S; Haenni, A L; Candresse, T; Bernardi, F; Le Gall, O

    1999-05-25

    Using the yeast two-hybrid system, a screen was performed for possible interactions between the proteins encoded by the 5' region of potyviral genomes [P1, helper component-proteinase (HC-Pro), and P3]. A positive self-interaction involving HC-Pro was detected with lettuce mosaic virus (LMV) and potato virus Y (PVY). The possibility of heterologous interaction between the HC-Pro of LMV and of PVY was also demonstrated. No interaction involving either the P1 or the P3 proteins was detected. A series of ordered deletions from either the N- or C-terminal end of the LMV HC-Pro was used to map the domain involved in interaction to the 72 N-terminal amino acids of the protein, a region known to be dispensable for virus viability but necessary for aphid transmission. A similar but less detailed analysis mapped the interacting domain to the N-terminal half of the PVY HC-Pro. Copyright 1999 Academic Press.

  18. Building a glaucoma interaction network using a text mining approach.

    Science.gov (United States)

    Soliman, Maha; Nasraoui, Olfa; Cooper, Nigel G F

    2016-01-01

    The volume of biomedical literature and its underlying knowledge base is rapidly expanding, making it beyond the ability of a single human being to read through all the literature. Several automated methods have been developed to help make sense of this dilemma. The present study reports on the results of a text mining approach to extract gene interactions from the data warehouse of published experimental results which are then used to benchmark an interaction network associated with glaucoma. To the best of our knowledge, there is, as yet, no glaucoma interaction network derived solely from text mining approaches. The presence of such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease. A glaucoma corpus was constructed from PubMed Central and a text mining approach was applied to extract genes and their relations from this corpus. The extracted relations between genes were checked using reference interaction databases and classified generally as known or new relations. The extracted genes and relations were then used to construct a glaucoma interaction network. Analysis of the resulting network indicated that it bears the characteristics of a small world interaction network. Our analysis showed the presence of seven glaucoma linked genes that defined the network modularity. A web-based system for browsing and visualizing the extracted glaucoma related interaction networks is made available at http://neurogene.spd.louisville.edu/GlaucomaINViewer/Form1.aspx. This study has reported the first version of a glaucoma interaction network using a text mining approach. The power of such an approach is in its ability to cover a wide range of glaucoma related studies published over many years. Hence, a bigger picture of the disease can be established. To the best of our knowledge, this is the first glaucoma interaction network to summarize the known literature. The major findings were a set of

  19. Unified Alignment of Protein-Protein Interaction Networks.

    Science.gov (United States)

    Malod-Dognin, Noël; Ban, Kristina; Pržulj, Nataša

    2017-04-19

    Paralleling the increasing availability of protein-protein interaction (PPI) network data, several network alignment methods have been proposed. Network alignments have been used to uncover functionally conserved network parts and to transfer annotations. However, due to the computational intractability of the network alignment problem, aligners are heuristics providing divergent solutions and no consensus exists on a gold standard, or which scoring scheme should be used to evaluate them. We comprehensively evaluate the alignment scoring schemes and global network aligners on large scale PPI data and observe that three methods, HUBALIGN, L-GRAAL and NATALIE, regularly produce the most topologically and biologically coherent alignments. We study the collective behaviour of network aligners and observe that PPI networks are almost entirely aligned with a handful of aligners that we unify into a new tool, Ulign. Ulign enables complete alignment of two networks, which traditional global and local aligners fail to do. Also, multiple mappings of Ulign define biologically relevant soft clusterings of proteins in PPI networks, which may be used for refining the transfer of annotations across networks. Hence, PPI networks are already well investigated by current aligners, so to gain additional biological insights, a paradigm shift is needed. We propose such a shift come from aligning all available data types collectively rather than any particular data type in isolation from others.

  20. Mean field interaction in biochemical reaction networks

    KAUST Repository

    Tembine, Hamidou

    2011-09-01

    In this paper we establish a relationship between chemical dynamics and mean field game dynamics. We show that chemical reaction networks can be studied using noisy mean field limits. We provide deterministic, noisy and switching mean field limits and illustrate them with numerical examples. © 2011 IEEE.

  1. Unravelling Protein-Protein Interaction Networks Linked to Aliphatic and Indole Glucosinolate Biosynthetic Pathways in Arabidopsis

    Directory of Open Access Journals (Sweden)

    Sebastian J. Nintemann

    2017-11-01

    Full Text Available Within the cell, biosynthetic pathways are embedded in protein-protein interaction networks. In Arabidopsis, the biosynthetic pathways of aliphatic and indole glucosinolate defense compounds are well-characterized. However, little is known about the spatial orchestration of these enzymes and their interplay with the cellular environment. To address these aspects, we applied two complementary, untargeted approaches—split-ubiquitin yeast 2-hybrid and co-immunoprecipitation screens—to identify proteins interacting with CYP83A1 and CYP83B1, two homologous enzymes specific for aliphatic and indole glucosinolate biosynthesis, respectively. Our analyses reveal distinct functional networks with substantial interconnection among the identified interactors for both pathway-specific markers, and add to our knowledge about how biochemical pathways are connected to cellular processes. Specifically, a group of protein interactors involved in cell death and the hypersensitive response provides a potential link between the glucosinolate defense compounds and defense against biotrophic pathogens, mediated by protein-protein interactions.

  2. Erv14 cargo receptor participates in yeast salt tolerance via its interaction with the plasma-membrane Nha1 cation/proton antiporter

    Czech Academy of Sciences Publication Activity Database

    Rosas-Santiago, P.; Zimmermannová, Olga; Vera-Estrella, R.; Sychrová, Hana; Pantoja, O.

    2016-01-01

    Roč. 1858, č. 1 (2016), s. 67-74 ISSN 0005-2736 Institutional support: RVO:67985823 Keywords : Erv14p * Nha1p * protein–protein interaction * mislocalization * salt-tolerance * yeast Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.498, year: 2016

  3. EVALUATING AUSTRALIAN FOOTBALL LEAGUE PLAYER CONTRIBUTIONS USING INTERACTIVE NETWORK SIMULATION

    Directory of Open Access Journals (Sweden)

    Jonathan Sargent

    2013-03-01

    Full Text Available This paper focuses on the contribution of Australian Football League (AFL players to their team's on-field network by simulating player interactions within a chosen team list and estimating the net effect on final score margin. A Visual Basic computer program was written, firstly, to isolate the effective interactions between players from a particular team in all 2011 season matches and, secondly, to generate a symmetric interaction matrix for each match. Negative binomial distributions were fitted to each player pairing in the Geelong Football Club for the 2011 season, enabling an interactive match simulation model given the 22 chosen players. Dynamic player ratings were calculated from the simulated network using eigenvector centrality, a method that recognises and rewards interactions with more prominent players in the team network. The centrality ratings were recorded after every network simulation and then applied in final score margin predictions so that each player's match contribution-and, hence, an optimal team-could be estimated. The paper ultimately demonstrates that the presence of highly rated players, such as Geelong's Jimmy Bartel, provides the most utility within a simulated team network. It is anticipated that these findings will facilitate optimal AFL team selection and player substitutions, which are key areas of interest to coaches. Network simulations are also attractive for use within betting markets, specifically to provide information on the likelihood of a chosen AFL team list "covering the line".

  4. Structural stability of interaction networks against negative external fields

    Science.gov (United States)

    Yoon, S.; Goltsev, A. V.; Mendes, J. F. F.

    2018-04-01

    We explore structural stability of weighted and unweighted networks of positively interacting agents against a negative external field. We study how the agents support the activity of each other to confront the negative field, which suppresses the activity of agents and can lead to collapse of the whole network. The competition between the interactions and the field shape the structure of stable states of the system. In unweighted networks (uniform interactions) the stable states have the structure of k -cores of the interaction network. The interplay between the topology and the distribution of weights (heterogeneous interactions) impacts strongly the structural stability against a negative field, especially in the case of fat-tailed distributions of weights. We show that apart from critical slowing down there is also a critical change in the system structure that precedes the network collapse. The change can serve as an early warning of the critical transition. To characterize changes of network structure we develop a method based on statistical analysis of the k -core organization and so-called "corona" clusters belonging to the k -cores.

  5. End of Interactive Emailing from the Technical Network

    CERN Multimedia

    2006-01-01

    According to the CNIC Security Policy for Control Systems (EDMS #584092), interactive emailing on PCs (and other devices) connected to the Technical Network is prohibited. Please note that from November 6th, neither reading emails nor sending emails interactively using e.g. Outlook or Pine mail clients on PCs connected to the Technical Network will be possible anymore. However, automatically generated emails will not be blocked and can still be sent off using CERNMX.CERN.CH as mail server. These restrictions DO NOT apply to PCs connected to any other network, like the General Purpose (or office) network. If you have questions, please do not hesitate to contact Uwe Epting, Pierre Charrue or Stefan Lueders (Technical-Network.Administrator@cern.ch). Your CNIC Working Group

  6. Bilingual Lexical Interactions in an Unsupervised Neural Network Model

    Science.gov (United States)

    Zhao, Xiaowei; Li, Ping

    2010-01-01

    In this paper we present an unsupervised neural network model of bilingual lexical development and interaction. We focus on how the representational structures of the bilingual lexicons can emerge, develop, and interact with each other as a function of the learning history. The results show that: (1) distinct representations for the two lexicons…

  7. Evidence of probabilistic behaviour in protein interaction networks

    Directory of Open Access Journals (Sweden)

    Reifman Jaques

    2008-01-01

    Full Text Available Abstract Background Data from high-throughput experiments of protein-protein interactions are commonly used to probe the nature of biological organization and extract functional relationships between sets of proteins. What has not been appreciated is that the underlying mechanisms involved in assembling these networks may exhibit considerable probabilistic behaviour. Results We find that the probability of an interaction between two proteins is generally proportional to the numerical product of their individual interacting partners, or degrees. The degree-weighted behaviour is manifested throughout the protein-protein interaction networks studied here, except for the high-degree, or hub, interaction areas. However, we find that the probabilities of interaction between the hubs are still high. Further evidence is provided by path length analyses, which show that these hubs are separated by very few links. Conclusion The results suggest that protein-protein interaction networks incorporate probabilistic elements that lead to scale-rich hierarchical architectures. These observations seem to be at odds with a biologically-guided organization. One interpretation of the findings is that we are witnessing the ability of proteins to indiscriminately bind rather than the protein-protein interactions that are actually utilized by the cell in biological processes. Therefore, the topological study of a degree-weighted network requires a more refined methodology to extract biological information about pathways, modules, or other inferred relationships among proteins.

  8. Interactive lethal and mutagenic effects of ultraviolet light and bleomycin in yeast: synergism or antagonism?

    Science.gov (United States)

    Lillo, O L; Severgnini, A A; Nunes, E M

    1997-11-01

    The mutagenic interactions of ultraviolet light and bleomycin in haploid populations of Saccharomyces cerevisiae were analyzed. Survival and mutation frequency as a function of different bleomycin concentrations after one conditioning dose of UV radiation were determined. Furthermore, corresponding interaction functions and sensitization factors were calculated. A synergistic interaction between UV light and bleomycin was shown for both lethal and mutagenic events when the cells were in nutrient broth during the treatments. Conversely, the interaction between UV light and bleomycin was antagonistic when the cells were in deionized water during the treatment. The magnitude of lethal and mutagenic interactions depends on dose, and thus presumably on the number of lesions. The observed interactions between UV light and bleomycin suggest that the mechanism that is most likely involved is the induction of repair systems with different error probabilities during the delay of cell division.

  9. Major component analysis of dynamic networks of physiologic organ interactions

    International Nuclear Information System (INIS)

    Liu, Kang K L; Ma, Qianli D Y; Ivanov, Plamen Ch; Bartsch, Ronny P

    2015-01-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function. (paper)

  10. Network traffic intelligence using a low interaction honeypot

    Science.gov (United States)

    Nyamugudza, Tendai; Rajasekar, Venkatesh; Sen, Prasad; Nirmala, M.; Madhu Viswanatham, V.

    2017-11-01

    Advancements in networking technology have seen more and more devices becoming connected day by day. This has given organizations capacity to extend their networks beyond their boundaries to remote offices and remote employees. However as the network grows security becomes a major challenge since the attack surface also increases. There is need to guard the network against different types of attacks like intrusion and malware through using different tools at different networking levels. This paper describes how network intelligence can be acquired through implementing a low-interaction honeypot which detects and track network intrusion. Honeypot allows an organization to interact and gather information about an attack earlier before it compromises the network. This process is important because it allows the organization to learn about future attacks of the same nature and allows them to develop counter measures. The paper further shows how honeypot-honey net based model for interruption detection system (IDS) can be used to get the best valuable information about the attacker and prevent unexpected harm to the network.

  11. Specificity and evolvability in eukaryotic protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Pedro Beltrao

    2007-02-01

    Full Text Available Progress in uncovering the protein interaction networks of several species has led to questions of what underlying principles might govern their organization. Few studies have tried to determine the impact of protein interaction network evolution on the observed physiological differences between species. Using comparative genomics and structural information, we show here that eukaryotic species have rewired their interactomes at a fast rate of approximately 10(-5 interactions changed per protein pair, per million years of divergence. For Homo sapiens this corresponds to 10(3 interactions changed per million years. Additionally we find that the specificity of binding strongly determines the interaction turnover and that different biological processes show significantly different link dynamics. In particular, human proteins involved in immune response, transport, and establishment of localization show signs of positive selection for change of interactions. Our analysis suggests that a small degree of molecular divergence can give rise to important changes at the network level. We propose that the power law distribution observed in protein interaction networks could be partly explained by the cell's requirement for different degrees of protein binding specificity.

  12. Interactively Evolving Compositional Sound Synthesis Networks

    DEFF Research Database (Denmark)

    Jónsson, Björn Þór; Hoover, Amy K.; Risi, Sebastian

    2015-01-01

    the space of potential sounds that can be generated through such compositional sound synthesis networks (CSSNs). To study the effect of evolution on subjective appreciation, participants in a listener study ranked evolved timbres by personal preference, resulting in preferences skewed toward the first......While the success of electronic music often relies on the uniqueness and quality of selected timbres, many musicians struggle with complicated and expensive equipment and techniques to create their desired sounds. Instead, this paper presents a technique for producing novel timbres that are evolved...

  13. Dynamic Interactions for Network Visualization and Simulation

    Science.gov (United States)

    2009-03-01

    projects.htm, Site accessed January 5, 2009. 12. John S. Weir, Major, USAF, Mediated User-Simulator Interactive Command with Visualization ( MUSIC -V). Master’s...Computing Sciences in Colleges, December 2005). 14. Enrique Campos -Nanez, “nscript user manual,” Department of System Engineer- ing University of

  14. Differential gene expression and Hog1 interaction with osmoresponsive genes in the extremely halotolerant black yeast Hortaea werneckii

    Directory of Open Access Journals (Sweden)

    Plemenitaš Ana

    2007-08-01

    Full Text Available Abstract Background Fluctuations in external salinity force eukaryotic cells to respond by changes in the gene expression of proteins acting in protective biochemical processes, thus counteracting the changing osmotic pressure. The high-osmolarity glycerol (HOG signaling pathway is essential for the efficient up-regulation of the osmoresponsive genes. In this study, the differential gene expression of the extremely halotolerant black yeast Hortaea werneckii was explored. Furthermore, the interaction of mitogen-activated protein kinase HwHog1 and RNA polymerase II with the chromatin in cells adapted to an extremely hypersaline environment was analyzed. Results A cDNA subtraction library was constructed for H. werneckii, adapted to moderate salinity or an extremely hypersaline environment of 4.5 M NaCl. An uncommon osmoresponsive set of 95 differentially expressed genes was identified. The majority of these had not previously been connected with the adaptation of salt-sensitive S. cerevisiae to hypersaline conditions. The transcriptional response in hypersaline-adapted and hypersaline-stressed cells showed that only a subset of the identified genes responded to acute salt-stress, whereas all were differentially expressed in adapted cells. Interaction with HwHog1 was shown for 36 of the 95 differentially expressed genes. The majority of the identified osmoresponsive and HwHog1-dependent genes in H. werneckii have not been previously reported as Hog1-dependent genes in the salt-sensitive S. cerevisiae. The study further demonstrated the co-occupancy of HwHog1 and RNA polymerase II on the chromatin of 17 up-regulated and 2 down-regulated genes in 4.5 M NaCl-adapted H. werneckii cells. Conclusion Extremely halotolerant H. werneckii represents a suitable and highly relevant organism to study cellular responses to environmental salinity. In comparison with the salt-sensitive S. cerevisiae, this yeast shows a different set of genes being expressed at

  15. Yeast screens identify the RNA polymerase II CTD and SPT5 as relevant targets of BRCA1 interaction.

    Directory of Open Access Journals (Sweden)

    Craig B Bennett

    2008-01-01

    Full Text Available BRCA1 has been implicated in numerous DNA repair pathways that maintain genome integrity, however the function responsible for its tumor suppressor activity in breast cancer remains obscure. To identify the most highly conserved of the many BRCA1 functions, we screened the evolutionarily distant eukaryote Saccharomyces cerevisiae for mutants that suppressed the G1 checkpoint arrest and lethality induced following heterologous BRCA1 expression. A genome-wide screen in the diploid deletion collection combined with a screen of ionizing radiation sensitive gene deletions identified mutants that permit growth in the presence of BRCA1. These genes delineate a metabolic mRNA pathway that temporally links transcription elongation (SPT4, SPT5, CTK1, DEF1 to nucleopore-mediated mRNA export (ASM4, MLP1, MLP2, NUP2, NUP53, NUP120, NUP133, NUP170, NUP188, POM34 and cytoplasmic mRNA decay at P-bodies (CCR4, DHH1. Strikingly, BRCA1 interacted with the phosphorylated RNA polymerase II (RNAPII carboxy terminal domain (P-CTD, phosphorylated in the pattern specified by the CTDK-I kinase, to induce DEF1-dependent cleavage and accumulation of a RNAPII fragment containing the P-CTD. Significantly, breast cancer associated BRCT domain defects in BRCA1 that suppressed P-CTD cleavage and lethality in yeast also suppressed the physical interaction of BRCA1 with human SPT5 in breast epithelial cells, thus confirming SPT5 as a relevant target of BRCA1 interaction. Furthermore, enhanced P-CTD cleavage was observed in both yeast and human breast cells following UV-irradiation indicating a conserved eukaryotic damage response. Moreover, P-CTD cleavage in breast epithelial cells was BRCA1-dependent since damage-induced P-CTD cleavage was only observed in the mutant BRCA1 cell line HCC1937 following ectopic expression of wild type BRCA1. Finally, BRCA1, SPT5 and hyperphosphorylated RPB1 form a complex that was rapidly degraded following MMS treatment in wild type but not BRCA1

  16. A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization

    Directory of Open Access Journals (Sweden)

    Tuikkala Johannes

    2012-03-01

    Full Text Available Abstract Background Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. Methods We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. Results The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. Conclusions By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

  17. A multilevel layout algorithm for visualizing physical and genetic interaction networks, with emphasis on their modular organization.

    Science.gov (United States)

    Tuikkala, Johannes; Vähämaa, Heidi; Salmela, Pekka; Nevalainen, Olli S; Aittokallio, Tero

    2012-03-26

    Graph drawing is an integral part of many systems biology studies, enabling visual exploration and mining of large-scale biological networks. While a number of layout algorithms are available in popular network analysis platforms, such as Cytoscape, it remains poorly understood how well their solutions reflect the underlying biological processes that give rise to the network connectivity structure. Moreover, visualizations obtained using conventional layout algorithms, such as those based on the force-directed drawing approach, may become uninformative when applied to larger networks with dense or clustered connectivity structure. We implemented a modified layout plug-in, named Multilevel Layout, which applies the conventional layout algorithms within a multilevel optimization framework to better capture the hierarchical modularity of many biological networks. Using a wide variety of real life biological networks, we carried out a systematic evaluation of the method in comparison with other layout algorithms in Cytoscape. The multilevel approach provided both biologically relevant and visually pleasant layout solutions in most network types, hence complementing the layout options available in Cytoscape. In particular, it could improve drawing of large-scale networks of yeast genetic interactions and human physical interactions. In more general terms, the biological evaluation framework developed here enables one to assess the layout solutions from any existing or future graph drawing algorithm as well as to optimize their performance for a given network type or structure. By making use of the multilevel modular organization when visualizing biological networks, together with the biological evaluation of the layout solutions, one can generate convenient visualizations for many network biology applications.

  18. Detecting Friendship Within Dynamic Online Interaction Networks

    OpenAIRE

    Merritt, Sears; Jacobs, Abigail Z.; Mason, Winter; Clauset, Aaron

    2013-01-01

    In many complex social systems, the timing and frequency of interactions between individuals are observable but friendship ties are hidden. Recovering these hidden ties, particularly for casual users who are relatively less active, would enable a wide variety of friendship-aware applications in domains where labeled data are often unavailable, including online advertising and national security. Here, we investigate the accuracy of multiple statistical features, based either purely on temporal...

  19. Human cancer protein-protein interaction network: a structural perspective.

    Directory of Open Access Journals (Sweden)

    Gozde Kar

    2009-12-01

    Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

  20. Interacting epidemics and coinfection on contact networks.

    Science.gov (United States)

    Newman, M E J; Ferrario, Carrie R

    2013-01-01

    The spread of certain diseases can be promoted, in some cases substantially, by prior infection with another disease. One example is that of HIV, whose immunosuppressant effects significantly increase the chances of infection with other pathogens. Such coinfection processes, when combined with nontrivial structure in the contact networks over which diseases spread, can lead to complex patterns of epidemiological behavior. Here we consider a mathematical model of two diseases spreading through a single population, where infection with one disease is dependent on prior infection with the other. We solve exactly for the sizes of the outbreaks of both diseases in the limit of large population size, along with the complete phase diagram of the system. Among other things, we use our model to demonstrate how diseases can be controlled not only by reducing the rate of their spread, but also by reducing the spread of other infections upon which they depend.

  1. Interacting epidemics and coinfection on contact networks.

    Directory of Open Access Journals (Sweden)

    M E J Newman

    Full Text Available The spread of certain diseases can be promoted, in some cases substantially, by prior infection with another disease. One example is that of HIV, whose immunosuppressant effects significantly increase the chances of infection with other pathogens. Such coinfection processes, when combined with nontrivial structure in the contact networks over which diseases spread, can lead to complex patterns of epidemiological behavior. Here we consider a mathematical model of two diseases spreading through a single population, where infection with one disease is dependent on prior infection with the other. We solve exactly for the sizes of the outbreaks of both diseases in the limit of large population size, along with the complete phase diagram of the system. Among other things, we use our model to demonstrate how diseases can be controlled not only by reducing the rate of their spread, but also by reducing the spread of other infections upon which they depend.

  2. Speech networks at rest and in action: interactions between functional brain networks controlling speech production

    Science.gov (United States)

    Fuertinger, Stefan

    2015-01-01

    Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. PMID:25673742

  3. Speech networks at rest and in action: interactions between functional brain networks controlling speech production.

    Science.gov (United States)

    Simonyan, Kristina; Fuertinger, Stefan

    2015-04-01

    Speech production is one of the most complex human behaviors. Although brain activation during speaking has been well investigated, our understanding of interactions between the brain regions and neural networks remains scarce. We combined seed-based interregional correlation analysis with graph theoretical analysis of functional MRI data during the resting state and sentence production in healthy subjects to investigate the interface and topology of functional networks originating from the key brain regions controlling speech, i.e., the laryngeal/orofacial motor cortex, inferior frontal and superior temporal gyri, supplementary motor area, cingulate cortex, putamen, and thalamus. During both resting and speaking, the interactions between these networks were bilaterally distributed and centered on the sensorimotor brain regions. However, speech production preferentially recruited the inferior parietal lobule (IPL) and cerebellum into the large-scale network, suggesting the importance of these regions in facilitation of the transition from the resting state to speaking. Furthermore, the cerebellum (lobule VI) was the most prominent region showing functional influences on speech-network integration and segregation. Although networks were bilaterally distributed, interregional connectivity during speaking was stronger in the left vs. right hemisphere, which may have underlined a more homogeneous overlap between the examined networks in the left hemisphere. Among these, the laryngeal motor cortex (LMC) established a core network that fully overlapped with all other speech-related networks, determining the extent of network interactions. Our data demonstrate complex interactions of large-scale brain networks controlling speech production and point to the critical role of the LMC, IPL, and cerebellum in the formation of speech production network. Copyright © 2015 the American Physiological Society.

  4. Integrated multimedia information system on interactive CATV network

    Science.gov (United States)

    Lee, Meng-Huang; Chang, Shin-Hung

    1998-10-01

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

  5. The yeast three-hybrid system as an experimental platform to identify proteins interacting with small signaling molecules in plant cells: Potential and limitations

    Directory of Open Access Journals (Sweden)

    Stéphanie eCottier

    2011-12-01

    Full Text Available Chemical genetics is a powerful scientific strategy that utilizes small bioactive molecules as experimental tools to unravel biological processes. Bioactive compounds occurring in nature represent an enormous diversity of structures that can be used to dissect functions of biological systems. Once the bioactivity of a natural or synthetic compound has been critically evaluated the challenge remains to identify its molecular target and mode of action, which usually is a time consuming and labor-intensive process. To facilitate this task, we decided to implement the yeast three-hybrid (Y3H technology as a general experimental platform to scan the whole Arabidopsis proteome for targets of small signaling molecules. The Y3H technology is based on the yeast two-hybrid system and allows direct cloning of proteins that interact in vivo with a synthetic hybrid ligand, which comprises the biologically active molecule of interest covalently linked to methotrexate (Mtx. In yeast nucleus the hybrid ligand connects two fusion proteins: the Mtx part binding to dihydrofolate reductase fused to a DNA binding domain (encoded in the yeast strain, and the bioactive molecule part binding to its potential protein target fused to a DNA activating domain (encoded on a cDNA expression vector. During cDNA library screening, the formation of this ternary, transcriptional activator complex leads to reporter gene activation in yeast cells, and thereby allows selection of the putative targets of small bioactive molecules of interest. Here we present the strategy and experimental details for construction and application of a Y3H platform, including chemical synthesis of different hybrid ligands, construction of suitable cDNA libraries, the choice of yeast strains, and appropriate screening conditions. Based on the results obtained and the current literature we discussed the perspectives and limitations of the Y3H approach for identifying targets of small bioactive molecules.

  6. Hazard interactions and interaction networks (cascades) within multi-hazard methodologies

    Science.gov (United States)

    Gill, Joel C.; Malamud, Bruce D.

    2016-08-01

    This paper combines research and commentary to reinforce the importance of integrating hazard interactions and interaction networks (cascades) into multi-hazard methodologies. We present a synthesis of the differences between multi-layer single-hazard approaches and multi-hazard approaches that integrate such interactions. This synthesis suggests that ignoring interactions between important environmental and anthropogenic processes could distort management priorities, increase vulnerability to other spatially relevant hazards or underestimate disaster risk. In this paper we proceed to present an enhanced multi-hazard framework through the following steps: (i) description and definition of three groups (natural hazards, anthropogenic processes and technological hazards/disasters) as relevant components of a multi-hazard environment, (ii) outlining of three types of interaction relationship (triggering, increased probability, and catalysis/impedance), and (iii) assessment of the importance of networks of interactions (cascades) through case study examples (based on the literature, field observations and semi-structured interviews). We further propose two visualisation frameworks to represent these networks of interactions: hazard interaction matrices and hazard/process flow diagrams. Our approach reinforces the importance of integrating interactions between different aspects of the Earth system, together with human activity, into enhanced multi-hazard methodologies. Multi-hazard approaches support the holistic assessment of hazard potential and consequently disaster risk. We conclude by describing three ways by which understanding networks of interactions contributes to the theoretical and practical understanding of hazards, disaster risk reduction and Earth system management. Understanding interactions and interaction networks helps us to better (i) model the observed reality of disaster events, (ii) constrain potential changes in physical and social vulnerability

  7. Modeling human dynamics of face-to-face interaction networks

    OpenAIRE

    Starnini, Michele; Baronchelli, Andrea; Pastor-Satorras, Romualdo

    2013-01-01

    Face-to-face interaction networks describe social interactions in human gatherings, and are the substrate for processes such as epidemic spreading and gossip propagation. The bursty nature of human behavior characterizes many aspects of empirical data, such as the distribution of conversation lengths, of conversations per person, or of inter-conversation times. Despite several recent attempts, a general theoretical understanding of the global picture emerging from data is still lacking. Here ...

  8. Generation and comprehensive analysis of an influenza virus polymerase cellular interaction network.

    Science.gov (United States)

    Tafforeau, Lionel; Chantier, Thibault; Pradezynski, Fabrine; Pellet, Johann; Mangeot, Philippe E; Vidalain, Pierre-Olivier; Andre, Patrice; Rabourdin-Combe, Chantal; Lotteau, Vincent

    2011-12-01

    The influenza virus transcribes and replicates its genome inside the nucleus of infected cells. Both activities are performed by the viral RNA-dependent RNA polymerase that is composed of the three subunits PA, PB1, and PB2, and recent studies have shown that it requires host cell factors to transcribe and replicate the viral genome. To identify these cellular partners, we generated a comprehensive physical interaction map between each polymerase subunit and the host cellular proteome. A total of 109 human interactors were identified by yeast two-hybrid screens, whereas 90 were retrieved by literature mining. We built the FluPol interactome network composed of the influenza virus polymerase (PA, PB1, and PB2) and the nucleoprotein NP and 234 human proteins that are connected through 279 viral-cellular protein interactions. Analysis of this interactome map revealed enriched cellular functions associated with the influenza virus polymerase, including host factors involved in RNA polymerase II-dependent transcription and mRNA processing. We confirmed that eight influenza virus polymerase-interacting proteins are required for virus replication and transcriptional activity of the viral polymerase. These are involved in cellular transcription (C14orf166, COPS5, MNAT1, NMI, and POLR2A), translation (EIF3S6IP), nuclear transport (NUP54), and DNA repair (FANCG). Conversely, we identified PRKRA, which acts as an inhibitor of the viral polymerase transcriptional activity and thus is required for the cellular antiviral response.

  9. Screening and identification of host proteins interacting with Theileria annulata cysteine proteinase (TaCP by yeast-two-hybrid system

    Directory of Open Access Journals (Sweden)

    Shuaiyang Zhao

    2017-10-01

    Full Text Available Abstract Background Theileria annulata can infect monocytes/macrophages and B lymphocytes and causes severe lymphoproliferative disease in ruminants. Meanwhile, infection by T. annulata leads to the permanent proliferation of cell population through regulating signaling pathways of host cells. Cysteine proteinases (CPs are one kind of protein hydrolase and usually play critical roles in parasite virulence, host invasion, nutrition and host immune response. However, the biological function of T. annulata CP (TaCP is still unclear. In this study, a yeast-two-hybrid assay was performed to screen host proteins interacting with TaCP, to provide information to help our understanding of the molecular mechanisms between T. annulata and host cells. Methods The cDNA from purified bovine B cells was inserted into pGADT7-SfiI vector (pGADT7-SfiI-BcDNA, Prey plasmid for constructing the yeast two-hybrid cDNA library. TaCP was cloned into the pGBKT7 vector (pGBKT7-TaCP and was considered as bait plasmid after evaluating the expression, auto-activation and toxicity tests in the yeast strain Y2HGold. The yeast two-hybrid screening was carried out via co-transforming bait and prey plasmids into yeast strain Y2HGold. Sequences of positive preys were analyzed using BLAST, Gene Ontology, UniProt and STRING. Results Two host proteins, CRBN (Bos taurus cereblon transcript variant X2 and Ppp4C (Bos indicus protein phosphatase 4 catalytic subunit were identified to interact with TaCP. The results of functional analysis showed that the two proteins were involved in many cellular processes, such as ubiquitylation regulation, microtubule organization, DNA repair, cell apoptosis and maturation of spliceosomal snRNPs. Conclusions This study is the first to screen the host proteins of bovine B cells interacting with TaCP, and 2 proteins, CRBN and Ppp4C, were identified using yeast two-hybrid technique. The results of functional analysis suggest that the two proteins are

  10. Epidemic spreading in networks with nonrandom long-range interactions

    Science.gov (United States)

    Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

    2011-09-01

    An “infection,” understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both “close” contacts and “casual” encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called “conductance” controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

  11. Epidemic spreading in networks with nonrandom long-range interactions.

    Science.gov (United States)

    Estrada, Ernesto; Kalala-Mutombo, Franck; Valverde-Colmeiro, Alba

    2011-09-01

    An "infection," understood here in a very broad sense, can be propagated through the network of social contacts among individuals. These social contacts include both "close" contacts and "casual" encounters among individuals in transport, leisure, shopping, etc. Knowing the first through the study of the social networks is not a difficult task, but having a clear picture of the network of casual contacts is a very hard problem in a society of increasing mobility. Here we assume, on the basis of several pieces of empirical evidence, that the casual contacts between two individuals are a function of their social distance in the network of close contacts. Then, we assume that we know the network of close contacts and infer the casual encounters by means of nonrandom long-range (LR) interactions determined by the social proximity of the two individuals. This approach is then implemented in a susceptible-infected-susceptible (SIS) model accounting for the spread of infections in complex networks. A parameter called "conductance" controls the feasibility of those casual encounters. In a zero conductance network only contagion through close contacts is allowed. As the conductance increases the probability of having casual encounters also increases. We show here that as the conductance parameter increases, the rate of propagation increases dramatically and the infection is less likely to die out. This increment is particularly marked in networks with scale-free degree distributions, where infections easily become epidemics. Our model provides a general framework for studying epidemic spreading in networks with arbitrary topology with and without casual contacts accounted for by means of LR interactions.

  12. Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

    Directory of Open Access Journals (Sweden)

    Peng Liu

    2015-01-01

    Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

  13. Application of random matrix theory to biological networks

    Energy Technology Data Exchange (ETDEWEB)

    Luo Feng [Department of Computer Science, Clemson University, 100 McAdams Hall, Clemson, SC 29634 (United States); Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States); Zhong Jianxin [Department of Physics, Xiangtan University, Hunan 411105 (China) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)]. E-mail: zhongjn@ornl.gov; Yang Yunfeng [Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States); Scheuermann, Richard H. [Department of Pathology, U.T. Southwestern Medical Center, 5323 Harry Hines Blvd. Dallas, TX 75390-9072 (United States); Zhou Jizhong [Department of Botany and Microbiology, University of Oklahoma, Norman, OK 73019 (United States) and Oak Ridge National Laboratory, Oak Ridge, TN 37831 (United States)]. E-mail: zhouj@ornl.gov

    2006-09-25

    We show that spectral fluctuation of interaction matrices of a yeast protein-protein interaction network and a yeast metabolic network follows the description of the Gaussian orthogonal ensemble (GOE) of random matrix theory (RMT). Furthermore, we demonstrate that while the global biological networks evaluated belong to GOE, removal of interactions between constituents transitions the networks to systems of isolated modules described by the Poisson distribution. Our results indicate that although biological networks are very different from other complex systems at the molecular level, they display the same statistical properties at network scale. The transition point provides a new objective approach for the identification of functional modules.

  14. Simulating market dynamics: interactions between consumer psychology and social networks.

    Science.gov (United States)

    Janssen, Marco A; Jager, Wander

    2003-01-01

    Markets can show different types of dynamics, from quiet markets dominated by one or a few products, to markets with continual penetration of new and reintroduced products. In a previous article we explored the dynamics of markets from a psychological perspective using a multi-agent simulation model. The main results indicated that the behavioral rules dominating the artificial consumer's decision making determine the resulting market dynamics, such as fashions, lock-in, and unstable renewal. Results also show the importance of psychological variables like social networks, preferences, and the need for identity to explain the dynamics of markets. In this article we extend this work in two directions. First, we will focus on a more systematic investigation of the effects of different network structures. The previous article was based on Watts and Strogatz's approach, which describes the small-world and clustering characteristics in networks. More recent research demonstrated that many large networks display a scale-free power-law distribution for node connectivity. In terms of market dynamics this may imply that a small proportion of consumers may have an exceptional influence on the consumptive behavior of others (hubs, or early adapters). We show that market dynamics is a self-organized property depending on the interaction between the agents' decision-making process (heuristics), the product characteristics (degree of satisfaction of unit of consumption, visibility), and the structure of interactions between agents (size of network and hubs in a social network).

  15. Drug-domain interaction networks in myocardial infarction.

    Science.gov (United States)

    Wang, Haiying; Zheng, Huiru; Azuaje, Francisco; Zhao, Xing-Ming

    2013-09-01

    It has been well recognized that the pace of the development of new drugs and therapeutic interventions lags far behind biological knowledge discovery. Network-based approaches have emerged as a promising alternative to accelerate the discovery of new safe and effective drugs. Based on the integration of several biological resources including two recently published datasets i.e., Drug-target interactions in myocardial infarction (My-DTome) and drug-domain interaction network, this paper reports the association between drugs and protein domains in the context of myocardial infarction (MI). A MI drug-domain interaction network, My-DDome, was firstly constructed, followed by topological analysis and functional characterization of the network. The results show that My-DDome has a very clear modular structure, where drugs interacting with the same domain(s) within each module tend to have similar therapeutic effects. Moreover it has been found that drugs acting on blood and blood forming organs (ATC code B) and sensory organs (ATC code S) are significantly enriched in My-DDome (p drugs, their known targets, and seemingly unrelated proteins can be revealed.

  16. Robust collaborative process interactions under system crash and network failures

    NARCIS (Netherlands)

    Wang, Lei; Wombacher, Andreas; Ferreira Pires, Luis; van Sinderen, Marten J.; Chi, Chihung

    2013-01-01

    With the possibility of system crashes and network failures, the design of robust client/server interactions for collaborative process execution is a challenge. If a business process changes its state, it sends messages to the relevant processes to inform about this change. However, server crashes

  17. Characterizing interactions in online social networks during exceptional events

    Science.gov (United States)

    Omodei, Elisa; De Domenico, Manlio; Arenas, Alex

    2015-08-01

    Nowadays, millions of people interact on a daily basis on online social media like Facebook and Twitter, where they share and discuss information about a wide variety of topics. In this paper, we focus on a specific online social network, Twitter, and we analyze multiple datasets each one consisting of individuals' online activity before, during and after an exceptional event in terms of volume of the communications registered. We consider important events that occurred in different arenas that range from policy to culture or science. For each dataset, the users' online activities are modeled by a multilayer network in which each layer conveys a different kind of interaction, specifically: retweeting, mentioning and replying. This representation allows us to unveil that these distinct types of interaction produce networks with different statistical properties, in particular concerning the degree distribution and the clustering structure. These results suggests that models of online activity cannot discard the information carried by this multilayer representation of the system, and should account for the different processes generated by the different kinds of interactions. Secondly, our analysis unveils the presence of statistical regularities among the different events, suggesting that the non-trivial topological patterns that we observe may represent universal features of the social dynamics on online social networks during exceptional events.

  18. Modulation of the genotoxicity of bleomycin by amines through noncovalent DNA interactions and alteration of physiological conditions in yeast

    International Nuclear Information System (INIS)

    Hoffmann, George R.; Gessner, Gabrielle S.; Hughes, Jennifer F.; Ronan, Matthew V.; Sylvia, Katelyn E.; Willett, Christine J.

    2007-01-01

    The effects of amines on the induction of mitotic gene conversion by bleomycin (BLM) were studied at the trp5 locus in Saccharomyces cerevisiae strain D7. BLM induces double-strand breaks in DNA and is a potent recombinagen in this assay. The polyamine spermidine causes concentration-dependent protection against the genotoxicity of BLM, reducing the convertant frequency by over 90% under the most protective conditions. Spermine, diethylenetriamine, ethylenediamine, putrescine, and ethylamine were also antigenotoxic in combined treatments with BLM. There was a general correspondence between the protective effect and the number of amino groups, suggesting that more strongly cationic amines tend to be stronger antirecombinagens. Electrostatic association of the amines with DNA probably hinders BLM access to the 4' position of deoxyribose where it generates a free radical. Other amines interact with BLM differently from these unbranched aliphatic amines. The aminothiol cysteamine inhibits the genotoxicity of BLM under hypoxic conditions but increases it under euoxic conditions. In contrast, pargyline potentiates the genotoxicity of BLM under hypoxic conditions but not under euoxic conditions. The antirecombinagenic effect of cysteamine apparently involves DNA binding and depletion of oxygen needed for BLM activity, whereas its potentiation of BLM entails its serving as an electron source for the activation of BLM. Pargyline may enhance BLM indirectly by preventing the depletion of oxygen by monoamine and polyamine oxidase. The planar 9-aminoacridine weakly induces gene conversion in strain D7, but it is strongly synergistic with BLM. Enhancement of BLM activity by this compound and by the related nitroacridine Entozon is apparently mediated by intercalation of the acridine ring system into DNA. Thus, the influence of amines on the genotoxicity of BLM in yeast encompasses antigenotoxic, potentiating, and synergistic interactions. The underlying mechanisms involve

  19. Modulation of the genotoxicity of bleomycin by amines through noncovalent DNA interactions and alteration of physiological conditions in yeast

    Energy Technology Data Exchange (ETDEWEB)

    Hoffmann, George R. [Department of Biology, College of the Holy Cross, One College Street, Worcester, MA 01610-2395 (United States)], E-mail: ghoffmann@holycross.edu; Gessner, Gabrielle S.; Hughes, Jennifer F.; Ronan, Matthew V.; Sylvia, Katelyn E.; Willett, Christine J. [Department of Biology, College of the Holy Cross, One College Street, Worcester, MA 01610-2395 (United States)

    2007-10-01

    The effects of amines on the induction of mitotic gene conversion by bleomycin (BLM) were studied at the trp5 locus in Saccharomyces cerevisiae strain D7. BLM induces double-strand breaks in DNA and is a potent recombinagen in this assay. The polyamine spermidine causes concentration-dependent protection against the genotoxicity of BLM, reducing the convertant frequency by over 90% under the most protective conditions. Spermine, diethylenetriamine, ethylenediamine, putrescine, and ethylamine were also antigenotoxic in combined treatments with BLM. There was a general correspondence between the protective effect and the number of amino groups, suggesting that more strongly cationic amines tend to be stronger antirecombinagens. Electrostatic association of the amines with DNA probably hinders BLM access to the 4' position of deoxyribose where it generates a free radical. Other amines interact with BLM differently from these unbranched aliphatic amines. The aminothiol cysteamine inhibits the genotoxicity of BLM under hypoxic conditions but increases it under euoxic conditions. In contrast, pargyline potentiates the genotoxicity of BLM under hypoxic conditions but not under euoxic conditions. The antirecombinagenic effect of cysteamine apparently involves DNA binding and depletion of oxygen needed for BLM activity, whereas its potentiation of BLM entails its serving as an electron source for the activation of BLM. Pargyline may enhance BLM indirectly by preventing the depletion of oxygen by monoamine and polyamine oxidase. The planar 9-aminoacridine weakly induces gene conversion in strain D7, but it is strongly synergistic with BLM. Enhancement of BLM activity by this compound and by the related nitroacridine Entozon is apparently mediated by intercalation of the acridine ring system into DNA. Thus, the influence of amines on the genotoxicity of BLM in yeast encompasses antigenotoxic, potentiating, and synergistic interactions. The underlying mechanisms involve

  20. Bayesian network model for identification of pathways by integrating protein interaction with genetic interaction data.

    Science.gov (United States)

    Fu, Changhe; Deng, Su; Jin, Guangxu; Wang, Xinxin; Yu, Zu-Guo

    2017-09-21

    Molecular interaction data at proteomic and genetic levels provide physical and functional insights into a molecular biosystem and are helpful for the construction of pathway structures complementarily. Despite advances in inferring biological pathways using genetic interaction data, there still exists weakness in developed models, such as, activity pathway networks (APN), when integrating the data from proteomic and genetic levels. It is necessary to develop new methods to infer pathway structure by both of interaction data. We utilized probabilistic graphical model to develop a new method that integrates genetic interaction and protein interaction data and infers exquisitely detailed pathway structure. We modeled the pathway network as Bayesian network and applied this model to infer pathways for the coherent subsets of the global genetic interaction profiles, and the available data set of endoplasmic reticulum genes. The protein interaction data were derived from the BioGRID database. Our method can accurately reconstruct known cellular pathway structures, including SWR complex, ER-Associated Degradation (ERAD) pathway, N-Glycan biosynthesis pathway, Elongator complex, Retromer complex, and Urmylation pathway. By comparing N-Glycan biosynthesis pathway and Urmylation pathway identified from our approach with that from APN, we found that our method is able to overcome its weakness (certain edges are inexplicable). According to underlying protein interaction network, we defined a simple scoring function that only adopts genetic interaction information to avoid the balance difficulty in the APN. Using the effective stochastic simulation algorithm, the performance of our proposed method is significantly high. We developed a new method based on Bayesian network to infer detailed pathway structures from interaction data at proteomic and genetic levels. The results indicate that the developed method performs better in predicting signaling pathways than previously

  1. Interaction of the RNP1 motif in PRT1 with HCR1 promotes 40S binding of eukaryotic initiation factor 3 in yeast

    DEFF Research Database (Denmark)

    Nielsen, Klaus H; Valásek, Leos; Sykes, Caroah

    2006-01-01

    We found that mutating the RNP1 motif in the predicted RRM domain in yeast eukaryotic initiation factor 3 (eIF3) subunit b/PRT1 (prt1-rnp1) impairs its direct interactions in vitro with both eIF3a/TIF32 and eIF3j/HCR1. The rnp1 mutation in PRT1 confers temperature-sensitive translation initiation...

  2. HDA2 and HDA3 are related proteins that interact with and are essential for the activity of the yeast histone deacetylase HDA1

    OpenAIRE

    Wu, Jiansheng; Carmen, Andrew A.; Kobayashi, Ryuji; Suka, Noriyuki; Grunstein, Michael

    2001-01-01

    Histone deacetylase HDA1, the prototype for the class II mammalian deacetylases, is likely the catalytic subunit of the HDA1-containing complex that is involved in TUP1-specific repression and global deacetylation in yeast. Although the class I RPD3-like enzymatic complexes have been well characterized, little is known about the identity and interactions of the factors that associate to form the HDA1 complex. In this paper, we identify related HDA2 and HDA3 proteins that ...

  3. Learning Predictive Interactions Using Information Gain and Bayesian Network Scoring.

    Directory of Open Access Journals (Sweden)

    Xia Jiang

    Full Text Available The problems of correlation and classification are long-standing in the fields of statistics and machine learning, and techniques have been developed to address these problems. We are now in the era of high-dimensional data, which is data that can concern billions of variables. These data present new challenges. In particular, it is difficult to discover predictive variables, when each variable has little marginal effect. An example concerns Genome-wide Association Studies (GWAS datasets, which involve millions of single nucleotide polymorphism (SNPs, where some of the SNPs interact epistatically to affect disease status. Towards determining these interacting SNPs, researchers developed techniques that addressed this specific problem. However, the problem is more general, and so these techniques are applicable to other problems concerning interactions. A difficulty with many of these techniques is that they do not distinguish whether a learned interaction is actually an interaction or whether it involves several variables with strong marginal effects.We address this problem using information gain and Bayesian network scoring. First, we identify candidate interactions by determining whether together variables provide more information than they do separately. Then we use Bayesian network scoring to see if a candidate interaction really is a likely model. Our strategy is called MBS-IGain. Using 100 simulated datasets and a real GWAS Alzheimer's dataset, we investigated the performance of MBS-IGain.When analyzing the simulated datasets, MBS-IGain substantially out-performed nine previous methods at locating interacting predictors, and at identifying interactions exactly. When analyzing the real Alzheimer's dataset, we obtained new results and results that substantiated previous findings. We conclude that MBS-IGain is highly effective at finding interactions in high-dimensional datasets. This result is significant because we have increasingly

  4. How People Interact in Evolving Online Affiliation Networks

    Science.gov (United States)

    Gallos, Lazaros K.; Rybski, Diego; Liljeros, Fredrik; Havlin, Shlomo; Makse, Hernán A.

    2012-07-01

    The study of human interactions is of central importance for understanding the behavior of individuals, groups, and societies. Here, we observe the formation and evolution of networks by monitoring the addition of all new links, and we analyze quantitatively the tendencies used to create ties in these evolving online affiliation networks. We show that an accurate estimation of these probabilistic tendencies can be achieved only by following the time evolution of the network. Inferences about the reason for the existence of links using statistical analysis of network snapshots must therefore be made with great caution. Here, we start by characterizing every single link when the tie was established in the network. This information allows us to describe the probabilistic tendencies of tie formation and extract meaningful sociological conclusions. We also find significant differences in behavioral traits in the social tendencies among individuals according to their degree of activity, gender, age, popularity, and other attributes. For instance, in the particular data sets analyzed here, we find that women reciprocate connections 3 times as much as men and that this difference increases with age. Men tend to connect with the most popular people more often than women do, across all ages. On the other hand, triangular tie tendencies are similar, independent of gender, and show an increase with age. These results require further validation in other social settings. Our findings can be useful to build models of realistic social network structures and to discover the underlying laws that govern establishment of ties in evolving social networks.

  5. Exact tensor network ansatz for strongly interacting systems

    Science.gov (United States)

    Zaletel, Michael P.

    It appears that the tensor network ansatz, while not quite complete, is an efficient coordinate system for the tiny subset of a many-body Hilbert space which can be realized as a low energy state of a local Hamiltonian. However, we don't fully understand precisely which phases are captured by the tensor network ansatz, how to compute their physical observables (even numerically), or how to compute a tensor network representation for a ground state given a microscopic Hamiltonian. These questions are algorithmic in nature, but their resolution is intimately related to understanding the nature of quantum entanglement in many-body systems. For this reason it is useful to compute the tensor network representation of various `model' wavefunctions representative of different phases of matter; this allows us to understand how the entanglement properties of each phase are expressed in the tensor network ansatz, and can serve as test cases for algorithm development. Condensed matter physics has many illuminating model wavefunctions, such as Laughlin's celebrated wave function for the fractional quantum Hall effect, the Bardeen-Cooper-Schrieffer wave function for superconductivity, and Anderson's resonating valence bond ansatz for spin liquids. This thesis presents some results on exact tensor network representations of these model wavefunctions. In addition, a tensor network representation is given for the time evolution operator of a long-range one-dimensional Hamiltonian, which allows one to numerically simulate the time evolution of power-law interacting spin chains as well as two-dimensional strips and cylinders.

  6. The TORC2-Dependent Signaling Network in the Yeast Saccharomyces cerevisiae.

    Science.gov (United States)

    Roelants, Françoise M; Leskoske, Kristin L; Martinez Marshall, Maria Nieves; Locke, Melissa N; Thorner, Jeremy

    2017-09-05

    To grow, eukaryotic cells must expand by inserting glycerolipids, sphingolipids, sterols, and proteins into their plasma membrane, and maintain the proper levels and bilayer distribution. A fungal cell must coordinate growth with enlargement of its cell wall. In Saccharomyces cerevisiae, a plasma membrane-localized protein kinase complex, Target of Rapamicin (TOR) complex-2 (TORC2) (mammalian ortholog is mTORC2), serves as a sensor and masterregulator of these plasma membrane- and cell wall-associated events by directly phosphorylating and thereby stimulating the activity of two types of effector protein kinases: Ypk1 (mammalian ortholog is SGK1), along with a paralog (Ypk2); and, Pkc1 (mammalian ortholog is PKN2/PRK2). Ypk1 is a central regulator of pathways and processes required for plasma membrane lipid and protein homeostasis, and requires phosphorylation on its T-loop by eisosome-associated protein kinase Pkh1 (mammalian ortholog is PDK1) and a paralog (Pkh2). For cell survival under various stresses, Ypk1 function requires TORC2-mediated phosphorylation at multiple sites near its C terminus. Pkc1 controls diverse processes, especially cell wall synthesis and integrity. Pkc1 is also regulated by Pkh1- and TORC2-dependent phosphorylation, but, in addition, by interaction with Rho1-GTP and lipids phosphatidylserine (PtdSer) and diacylglycerol (DAG). We also describe here what is currently known about the downstream substrates modulated by Ypk1-mediated and Pkc1-mediated phosphorylation.

  7. Digital Ecology: Coexistence and Domination among Interacting Networks

    Science.gov (United States)

    Kleineberg, Kaj-Kolja; Boguñá, Marián

    2015-05-01

    The overwhelming success of Web 2.0, within which online social networks are key actors, has induced a paradigm shift in the nature of human interactions. The user-driven character of Web 2.0 services has allowed researchers to quantify large-scale social patterns for the first time. However, the mechanisms that determine the fate of networks at the system level are still poorly understood. For instance, the simultaneous existence of multiple digital services naturally raises questions concerning which conditions these services can coexist under. Analogously to the case of population dynamics, the digital world forms a complex ecosystem of interacting networks. The fitness of each network depends on its capacity to attract and maintain users’ attention, which constitutes a limited resource. In this paper, we introduce an ecological theory of the digital world which exhibits stable coexistence of several networks as well as the dominance of an individual one, in contrast to the competitive exclusion principle. Interestingly, our theory also predicts that the most probable outcome is the coexistence of a moderate number of services, in agreement with empirical observations.

  8. Myths on Bi-direction Communication of Web 2.0 Based Social Networks: Is Social Network Truly Interactive?

    Science.gov (United States)

    2011-03-10

    more and more social interactions are happening on the on-line. Especially recent uptake of the social network sites (SNSs), such as Facebook (http...Smart phones • Live updates within social networks • Facebook & Twitters Solution: WebMon for Risk Management Need for New WebMon for Social Networks ...Title: Myths on bi-direction communication of Web 2.0 based social networks : Is social network truly interactive

  9. Self-organization of social hierarchy on interaction networks

    International Nuclear Information System (INIS)

    Fujie, Ryo; Odagaki, Takashi

    2011-01-01

    In order to examine the effects of interaction network structures on the self-organization of social hierarchy, we introduce the agent-based model: each individual as on a node of a network has its own power and its internal state changes by fighting with its neighbors and relaxation. We adopt three different networks: regular lattice, small-world network and scale-free network. For the regular lattice, we find the emergence of classes distinguished by the internal state. The transition points where each class emerges are determined analytically, and we show that each class is characterized by the local ranking relative to their neighbors. We also find that the antiferromagnetic-like configuration emerges just above the critical point. For the heterogeneous networks, individuals become winners (or losers) in descending order of the number of their links. By using mean-field analysis, we reveal that the transition point is determined by the maximum degree and the degree distribution in its neighbors

  10. Yeast Tdh3 (glyceraldehyde 3-phosphate dehydrogenase is a Sir2-interacting factor that regulates transcriptional silencing and rDNA recombination.

    Directory of Open Access Journals (Sweden)

    Alison E Ringel

    Full Text Available Sir2 is an NAD(+-dependent histone deacetylase required to mediate transcriptional silencing and suppress rDNA recombination in budding yeast. We previously identified Tdh3, a glyceraldehyde 3-phosphate dehydrogenase (GAPDH, as a high expression suppressor of the lethality caused by Sir2 overexpression in yeast cells. Here we show that Tdh3 interacts with Sir2, localizes to silent chromatin in a Sir2-dependent manner, and promotes normal silencing at the telomere and rDNA. Characterization of specific TDH3 alleles suggests that Tdh3's influence on silencing requires nuclear localization but does not correlate with its catalytic activity. Interestingly, a genetic assay suggests that Tdh3, an NAD(+-binding protein, influences nuclear NAD(+ levels; we speculate that Tdh3 links nuclear Sir2 with NAD(+ from the cytoplasm.

  11. Feed forward neural networks modeling for K-P interactions

    International Nuclear Information System (INIS)

    El-Bakry, M.Y.

    2003-01-01

    Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K-P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data

  12. Auditing Medical Records Accesses via Healthcare Interaction Networks

    Science.gov (United States)

    Chen, You; Nyemba, Steve; Malin, Bradley

    2012-01-01

    Healthcare organizations are deploying increasingly complex clinical information systems to support patient care. Traditional information security practices (e.g., role-based access control) are embedded in enterprise-level systems, but are insufficient to ensure patient privacy. This is due, in part, to the dynamic nature of healthcare, which makes it difficult to predict which care providers need access to what and when. In this paper, we show that modeling operations at a higher level of granularity (e.g., the departmental level) are stable in the context of a relational network, which may enable more effective auditing strategies. We study three months of access logs from a large academic medical center to illustrate that departmental interaction networks exhibit certain invariants, such as the number, strength, and reciprocity of relationships. We further show that the relations extracted from the network can be leveraged to assess the extent to which a patient’s care satisfies expected organizational behavior. PMID:23304277

  13. Overexpression of O‐methyltransferase leads to improved vanillin production in baker's yeast only when complemented with model‐guided network engineering

    DEFF Research Database (Denmark)

    Brochado, Ana Rita; Patil, Kiran R.

    2013-01-01

    limited in eukaryotic systems. In this study, we compared the effects of overexpressing a key gene in de novo vanillin biosynthesis (coding for O‐methyltransferase, hsOMT) in two yeast strains, with and without model‐guided global network modifications. Overexpression of hsOMT resulted in increased...... vanillin production only in the strain with model‐guided modifications, exemplifying advantage of using a global strategy prior to local pathway manipulation. Biotechnol. Bioeng. 2013; 110: 656–659. © 2012 Wiley Periodicals, Inc....

  14. Games as Actors - Interaction, Play, Design, and Actor Network Theory

    DEFF Research Database (Denmark)

    Jessen, Jari Due; Jessen, Carsten

    2014-01-01

    When interacting with computer games, users are forced to follow the rules of the game in return for the excitement, joy, fun, or other pursued experiences. In this paper, we investigate how games a chieve these experiences in the perspective of Actor Network Theory (ANT). Based on a qualitative......, and by doing so they create in humans what in modern play theory is known as a “state of play”...

  15. Protein Annotation from Protein Interaction Networks and Gene Ontology

    OpenAIRE

    Nguyen, Cao D.; Gardiner, Katheleen J.; Cios, Krzysztof J.

    2011-01-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precis...

  16. Modeling of intracerebral interictal epileptic discharges: Evidence for network interactions.

    Science.gov (United States)

    Meesters, Stephan; Ossenblok, Pauly; Colon, Albert; Wagner, Louis; Schijns, Olaf; Boon, Paul; Florack, Luc; Fuster, Andrea

    2018-06-01

    The interictal epileptic discharges (IEDs) occurring in stereotactic EEG (SEEG) recordings are in general abundant compared to ictal discharges, but difficult to interpret due to complex underlying network interactions. A framework is developed to model these network interactions. To identify the synchronized neuronal activity underlying the IEDs, the variation in correlation over time of the SEEG signals is related to the occurrence of IEDs using the general linear model. The interdependency is assessed of the brain areas that reflect highly synchronized neural activity by applying independent component analysis, followed by cluster analysis of the spatial distributions of the independent components. The spatiotemporal interactions of the spike clusters reveal the leading or lagging of brain areas. The analysis framework was evaluated for five successfully operated patients, showing that the spike cluster that was related to the MRI-visible brain lesions coincided with the seizure onset zone. The additional value of the framework was demonstrated for two more patients, who were MRI-negative and for whom surgery was not successful. A network approach is promising in case of complex epilepsies. Analysis of IEDs is considered a valuable addition to routine review of SEEG recordings, with the potential to increase the success rate of epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

  17. Network characteristics emerging from agent interactions in balanced distributed system.

    Science.gov (United States)

    Salman, Mahdi Abed; Bertelle, Cyrille; Sanlaville, Eric

    2015-01-01

    A distributed computing system behaves like a complex network, the interactions between nodes being essential information exchanges and migrations of jobs or services to execute. These actions are performed by software agents, which behave like the members of social networks, cooperating and competing to obtain knowledge and services. The load balancing consists in distributing the load evenly between system nodes. It aims at enhancing the resource usage. A load balancing strategy specifies scenarios for the cooperation. Its efficiency depends on quantity, accuracy, and distribution of available information. Nevertheless, the distribution of information on the nodes, together with the initial network structure, may create different logical network structures. In this paper, different load balancing strategies are tested on different network structures using a simulation. The four tested strategies are able to distribute evenly the load so that the system reaches a steady state (the mean response time of the jobs is constant), but it is shown that a given strategy indeed behaves differently according to structural parameters and information spreading. Such a study, devoted to distributed computing systems (DCSs), can be useful to understand and drive the behavior of other complex systems.

  18. KNOWNET: Exploring Interactive Knowledge Networking across Insurance Supply Chains

    Directory of Open Access Journals (Sweden)

    Susan Grant

    2014-01-01

    Full Text Available Social media has become an extremely powerful phenomenon with millions of users who post status updates, blog, links and pictures on social networking sites such as Facebook, LinkedIn, and Twitter. However, social networking has so far spread mainly among consumers. Businesses are only now beginning to acknowledge the benefits of using social media to enhance employee and supplier collaboration to support new ideas and innovation through knowledge sharing across functions and organizational boundaries. Many businesses are still trying to understand the various implications of integrating internal communication systems with social media tools and private collaboration and networking platforms. Indeed, a current issue in organizations today is to explore the value of social media mechanisms across a range of functions within their organizations and across their supply chains.The KNOWNET project (an EC funded Marie Curie IAPP seeks to assess the value of social networking for knowledge exchange across Insurance supply chains. A key objective of the project being to develop and build a web based interactive environment - a Supplier Social Network or SSN, to support and facilitate exchange of good ideas, insights, knowledge, innovations etc across a diverse group of suppliers within a multi level supply chain within the Insurance sector.

  19. Oligomeric protein structure networks: insights into protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Brinda KV

    2005-12-01

    Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

  20. Metabolic network analysis on Phaffia rhodozyma yeast using C-13-labeled glucose and gas chromatography-mass spectrometry

    DEFF Research Database (Denmark)

    Cannizzaro, C.; Christensen, B.; Nielsen, Jens

    2004-01-01

    Carotenoid production by micro organisms, as opposed to chemical synthesis, could fulfill an ever-increasing demand for 'all natural' products. The yeast Phaffia rhodozyma has received considerable attention because it produces the red pigment astaxanthin, commonly used as an animal feed suppleme...

  1. Peptide microarrays to probe for competition for binding sites in a protein interaction network

    NARCIS (Netherlands)

    Sinzinger, M.D.S.; Ruttekolk, I.R.R.; Gloerich, J.; Wessels, H.; Chung, Y.D.; Adjobo-Hermans, M.J.W.; Brock, R.E.

    2013-01-01

    Cellular protein interaction networks are a result of the binding preferences of a particular protein and the entirety of interactors that mutually compete for binding sites. Therefore, the reconstruction of interaction networks by the accumulation of interaction networks for individual proteins

  2. Exploring drug-target interaction networks of illicit drugs.

    Science.gov (United States)

    Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

    2013-01-01

    Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network

  3. Overexpression of O-methyltransferase leads to improved vanillin production in baker's yeast only when complemented with model-guided network engineering.

    Science.gov (United States)

    Brochado, Ana Rita; Patil, Kiran R

    2013-02-01

    Overproduction of a desired metabolite is often achieved via manipulation of the pathway directly leading to the product or through engineering of distant nodes within the metabolic network. Empirical examples illustrating the combined effect of these local and global strategies have been so far limited in eukaryotic systems. In this study, we compared the effects of overexpressing a key gene in de novo vanillin biosynthesis (coding for O-methyltransferase, hsOMT) in two yeast strains, with and without model-guided global network modifications. Overexpression of hsOMT resulted in increased vanillin production only in the strain with model-guided modifications, exemplifying advantage of using a global strategy prior to local pathway manipulation. Copyright © 2012 Wiley Periodicals, Inc.

  4. Exploration of the dynamic properties of protein complexes predicted from spatially constrained protein-protein interaction networks.

    Directory of Open Access Journals (Sweden)

    Eric A Yen

    2014-05-01

    Full Text Available Protein complexes are not static, but rather highly dynamic with subunits that undergo 1-dimensional diffusion with respect to each other. Interactions within protein complexes are modulated through regulatory inputs that alter interactions and introduce new components and deplete existing components through exchange. While it is clear that the structure and function of any given protein complex is coupled to its dynamical properties, it remains a challenge to predict the possible conformations that complexes can adopt. Protein-fragment Complementation Assays detect physical interactions between protein pairs constrained to ≤8 nm from each other in living cells. This method has been used to build networks composed of 1000s of pair-wise interactions. Significantly, these networks contain a wealth of dynamic information, as the assay is fully reversible and the proteins are expressed in their natural context. In this study, we describe a method that extracts this valuable information in the form of predicted conformations, allowing the user to explore the conformational landscape, to search for structures that correlate with an activity state, and estimate the abundance of conformations in the living cell. The generator is based on a Markov Chain Monte Carlo simulation that uses the interaction dataset as input and is constrained by the physical resolution of the assay. We applied this method to an 18-member protein complex composed of the seven core proteins of the budding yeast Arp2/3 complex and 11 associated regulators and effector proteins. We generated 20,480 output structures and identified conformational states using principle component analysis. We interrogated the conformation landscape and found evidence of symmetry breaking, a mixture of likely active and inactive conformational states and dynamic exchange of the core protein Arc15 between core and regulatory components. Our method provides a novel tool for prediction and

  5. Network of interactions between ciliates and phytoplankton during spring

    Directory of Open Access Journals (Sweden)

    Thomas ePosch

    2015-11-01

    Full Text Available The annually recurrent spring phytoplankton blooms in freshwater lakes initiate pronounced successions of planktonic ciliate species. Although there is considerable knowledge on the taxonomic diversity of these ciliates, their species-specific interactions with other microorganisms are still not well understood. Here we present the succession patterns of 20 morphotypes of ciliates during spring in Lake Zurich, Switzerland, and we relate their abundances to phytoplankton genera, flagellates, heterotrophic bacteria, and abiotic parameters. Interspecific relationships were analyzed by contemporaneous correlations and time-lagged co-occurrence and visualized as association networks. The contemporaneous network pointed to the pivotal role of distinct ciliate species (e.g., Balanion planctonicum, Rimostrombidium humile as primary consumers of cryptomonads, revealed a clear overclustering of mixotrophic / omnivorous species, and highlighted the role of Halteria / Pelagohalteria as important bacterivores. By contrast, time-lagged statistical approaches (like local similarity analyses, LSA proved to be inadequate for the evaluation of high-frequency sampling data. LSA led to a conspicuous inflation of significant associations, making it difficult to establish ecologically plausible interactions between ciliates and other microorganisms. Nevertheless, if adequate statistical procedures are selected, association networks can be powerful tools to formulate testable hypotheses about the autecology of only recently described ciliate species.

  6. Systems pharmacology - Towards the modeling of network interactions.

    Science.gov (United States)

    Danhof, Meindert

    2016-10-30

    Mechanism-based pharmacokinetic and pharmacodynamics (PKPD) and disease system (DS) models have been introduced in drug discovery and development research, to predict in a quantitative manner the effect of drug treatment in vivo in health and disease. This requires consideration of several fundamental properties of biological systems behavior including: hysteresis, non-linearity, variability, interdependency, convergence, resilience, and multi-stationarity. Classical physiology-based PKPD models consider linear transduction pathways, connecting processes on the causal path between drug administration and effect, as the basis of drug action. Depending on the drug and its biological target, such models may contain expressions to characterize i) the disposition and the target site distribution kinetics of the drug under investigation, ii) the kinetics of target binding and activation and iii) the kinetics of transduction. When connected to physiology-based DS models, PKPD models can characterize the effect on disease progression in a mechanistic manner. These models have been found useful to characterize hysteresis and non-linearity, yet they fail to explain the effects of the other fundamental properties of biological systems behavior. Recently systems pharmacology has been introduced as novel approach to predict in vivo drug effects, in which biological networks rather than single transduction pathways are considered as the basis of drug action and disease progression. These models contain expressions to characterize the functional interactions within a biological network. Such interactions are relevant when drugs act at multiple targets in the network or when homeostatic feedback mechanisms are operative. As a result systems pharmacology models are particularly useful to describe complex patterns of drug action (i.e. synergy, oscillatory behavior) and disease progression (i.e. episodic disorders). In this contribution it is shown how physiology-based PKPD and

  7. Higher-Order Synaptic Interactions Coordinate Dynamics in Recurrent Networks.

    Directory of Open Access Journals (Sweden)

    Brendan Chambers

    2016-08-01

    Full Text Available Linking synaptic connectivity to dynamics is key to understanding information processing in neocortex. Circuit dynamics emerge from complex interactions of interconnected neurons, necessitating that links between connectivity and dynamics be evaluated at the network level. Here we map propagating activity in large neuronal ensembles from mouse neocortex and compare it to a recurrent network model, where connectivity can be precisely measured and manipulated. We find that a dynamical feature dominates statistical descriptions of propagating activity for both neocortex and the model: convergent clusters comprised of fan-in triangle motifs, where two input neurons are themselves connected. Fan-in triangles coordinate the timing of presynaptic inputs during ongoing activity to effectively generate postsynaptic spiking. As a result, paradoxically, fan-in triangles dominate the statistics of spike propagation even in randomly connected recurrent networks. Interplay between higher-order synaptic connectivity and the integrative properties of neurons constrains the structure of network dynamics and shapes the routing of information in neocortex.

  8. Interactive social contagions and co-infections on complex networks

    Science.gov (United States)

    Liu, Quan-Hui; Zhong, Lin-Feng; Wang, Wei; Zhou, Tao; Eugene Stanley, H.

    2018-01-01

    What we are learning about the ubiquitous interactions among multiple social contagion processes on complex networks challenges existing theoretical methods. We propose an interactive social behavior spreading model, in which two behaviors sequentially spread on a complex network, one following the other. Adopting the first behavior has either a synergistic or an inhibiting effect on the spread of the second behavior. We find that the inhibiting effect of the first behavior can cause the continuous phase transition of the second behavior spreading to become discontinuous. This discontinuous phase transition of the second behavior can also become a continuous one when the effect of adopting the first behavior becomes synergistic. This synergy allows the second behavior to be more easily adopted and enlarges the co-existence region of both behaviors. We establish an edge-based compartmental method, and our theoretical predictions match well with the simulation results. Our findings provide helpful insights into better understanding the spread of interactive social behavior in human society.

  9. Supply Chain Management: from Linear Interactions to Networked Processes

    Directory of Open Access Journals (Sweden)

    Doina FOTACHE

    2006-01-01

    Full Text Available Supply Chain Management is a distinctive product, with a tremendous impact on the software applications market. SCM applications are back-end solutions intended to link suppliers, manufacturers, distributors and resellers in a production and distribution network, which allows the enterprise to track and consolidate the flows of materials and data trough the process of manufacturing and distribution of goods/services. The advent of the Web as a major means of conducting business transactions and business-tobusiness communications, coupled with evolving web-based supply chain management (SCM technology, has resulted in a transition period from “linear” supply chain models to "networked" supply chain models. The technologies to enable dynamic process changes and real time interactions between extended supply chain partners are emerging and being deployed at an accelerated pace.

  10. Visualization of protein interaction networks: problems and solutions

    Directory of Open Access Journals (Sweden)

    Agapito Giuseppe

    2013-01-01

    Full Text Available Abstract Background Visualization concerns the representation of data visually and is an important task in scientific research. Protein-protein interactions (PPI are discovered using either wet lab techniques, such mass spectrometry, or in silico predictions tools, resulting in large collections of interactions stored in specialized databases. The set of all interactions of an organism forms a protein-protein interaction network (PIN and is an important tool for studying the behaviour of the cell machinery. Since graphic representation of PINs may highlight important substructures, e.g. protein complexes, visualization is more and more used to study the underlying graph structure of PINs. Although graphs are well known data structures, there are different open problems regarding PINs visualization: the high number of nodes and connections, the heterogeneity of nodes (proteins and edges (interactions, the possibility to annotate proteins and interactions with biological information extracted by ontologies (e.g. Gene Ontology that enriches the PINs with semantic information, but complicates their visualization. Methods In these last years many software tools for the visualization of PINs have been developed. Initially thought for visualization only, some of them have been successively enriched with new functions for PPI data management and PIN analysis. The paper analyzes the main software tools for PINs visualization considering four main criteria: (i technology, i.e. availability/license of the software and supported OS (Operating System platforms; (ii interoperability, i.e. ability to import/export networks in various formats, ability to export data in a graphic format, extensibility of the system, e.g. through plug-ins; (iii visualization, i.e. supported layout and rendering algorithms and availability of parallel implementation; (iv analysis, i.e. availability of network analysis functions, such as clustering or mining of the graph, and the

  11. Interacting loop-current model of superconducting networks

    International Nuclear Information System (INIS)

    Chi, C.C.; Santhanam, P.; Bloechl, P.E.

    1992-01-01

    The authors review their recent approximation scheme to calculate the normal-superconducting phase boundary, T c (H), of a superconducting wire network in a magnetic field in terms of interacting loop currents. The theory is based on the London approximation of the linearized Ginzburg-Landau equation. An approximate general formula is derived for any two-dimensional space-filling lattice comprising tiles of two shapes. Many examples are provided illustrating the use of this method, with a particular emphasis on the fluxoid distribution. In addition to periodic lattices, quasiperiodic lattices and fractal Sierpinski gaskets are also discussed

  12. Protein annotation from protein interaction networks and Gene Ontology.

    Science.gov (United States)

    Nguyen, Cao D; Gardiner, Katheleen J; Cios, Krzysztof J

    2011-10-01

    We introduce a novel method for annotating protein function that combines Naïve Bayes and association rules, and takes advantage of the underlying topology in protein interaction networks and the structure of graphs in the Gene Ontology. We apply our method to proteins from the Human Protein Reference Database (HPRD) and show that, in comparison with other approaches, it predicts protein functions with significantly higher recall with no loss of precision. Specifically, it achieves 51% precision and 60% recall versus 45% and 26% for Majority and 24% and 61% for χ²-statistics, respectively. Copyright © 2011 Elsevier Inc. All rights reserved.

  13. Interaction of human laminin receptor with Sup35, the [PSI⁺] prion-forming protein from S. cerevisiae: a yeast model for studies of LamR interactions with amyloidogenic proteins.

    Directory of Open Access Journals (Sweden)

    Christine Pampeno

    Full Text Available The laminin receptor (LamR is a cell surface receptor for extracellular matrix laminin, whereas the same protein within the cell interacts with ribosomes, nuclear proteins and cytoskeletal fibers. LamR has been shown to be a receptor for several bacteria and viruses. Furthermore, LamR interacts with both cellular and infectious forms of the prion protein, PrP(C and PrP(Sc. Indeed, LamR is a receptor for PrP(C. Whether LamR interacts with PrP(Sc exclusively in a capacity of the PrP receptor, or LamR specifically recognizes prion determinants of PrP(Sc, is unclear. In order to explore whether LamR has a propensity to interact with prions and amyloids, we examined LamR interaction with the yeast prion-forming protein, Sup35. Sup35 is a translation termination factor with no homology or functional relationship to PrP. Plasmids expressing LamR or LamR fused with the green fluorescent protein (GFP were transformed into yeast strain variants differing by the presence or absence of the prion conformation of Sup35, respectively [PSI⁺] and [psi⁻]. Analyses by immunoprecipitation, centrifugal fractionation and fluorescent microscopy reveal interaction between LamR and Sup35 in [PSI⁺] strains. The presence of [PSI⁺] promotes LamR co-precipitation with Sup35 as well as LamR aggregation. In [PSI⁺] cells, LamR tagged with GFP or mCherry forms bright fluorescent aggregates that co-localize with visible [PSI⁺] foci. The yeast prion model will facilitate studying the interaction of LamR with amyloidogenic prions in a safe and easily manipulated system that may lead to a better understanding and treatment of amyloid diseases.

  14. Coevolution of Synchronization and Cooperation in Costly Networked Interactions

    Science.gov (United States)

    Antonioni, Alberto; Cardillo, Alessio

    2017-06-01

    Despite the large number of studies on synchronization, the hypothesis that interactions bear a cost for involved individuals has seldom been considered. The introduction of costly interactions leads, instead, to the formulation of a dichotomous scenario in which an individual may decide to cooperate and pay the cost in order to get synchronized with the rest of the population. Alternatively, the same individual can decide to free ride, without incurring any cost, waiting for others to get synchronized to his or her state. Thus, the emergence of synchronization may be seen as the byproduct of an evolutionary game in which individuals decide their behavior according to the benefit-to-cost ratio they accrued in the past. We study the onset of cooperation and synchronization in networked populations of Kuramoto oscillators and report how topology is essential in order for cooperation to thrive. We also display how different classes of topology foster synchronization differently both at microscopic and macroscopic levels.

  15. Messaging Performance of FIPA Interaction Protocols in Networked Embedded Controllers

    Directory of Open Access Journals (Sweden)

    García JoséAPérez

    2008-01-01

    Full Text Available Abstract Agent-based technologies in production control systems could facilitate seamless reconfiguration and integration of mechatronic devices/modules into systems. Advances in embedded controllers which are continuously improving computational capabilities allow for software modularization and distribution of decisions. Agent platforms running on embedded controllers could hide the complexity of bootstrap and communication. Therefore, it is important to investigate the messaging performance of the agents whose main motivation is the resource allocation in manufacturing systems (i.e., conveyor system. The tests were implemented using the FIPA-compliant JADE-LEAP agent platform. Agent containers were distributed through networked embedded controllers, and agents were communicating using request and contract-net FIPA interaction protocols. The test scenarios are organized in intercontainer and intracontainer communications. The work shows the messaging performance for the different test scenarios using both interaction protocols.

  16. Messaging Performance of FIPA Interaction Protocols in Networked Embedded Controllers

    Directory of Open Access Journals (Sweden)

    Omar Jehovani López Orozco

    2007-12-01

    Full Text Available Agent-based technologies in production control systems could facilitate seamless reconfiguration and integration of mechatronic devices/modules into systems. Advances in embedded controllers which are continuously improving computational capabilities allow for software modularization and distribution of decisions. Agent platforms running on embedded controllers could hide the complexity of bootstrap and communication. Therefore, it is important to investigate the messaging performance of the agents whose main motivation is the resource allocation in manufacturing systems (i.e., conveyor system. The tests were implemented using the FIPA-compliant JADE-LEAP agent platform. Agent containers were distributed through networked embedded controllers, and agents were communicating using request and contract-net FIPA interaction protocols. The test scenarios are organized in intercontainer and intracontainer communications. The work shows the messaging performance for the different test scenarios using both interaction protocols.

  17. Chaos in generically coupled phase oscillator networks with nonpairwise interactions

    Energy Technology Data Exchange (ETDEWEB)

    Bick, Christian; Ashwin, Peter; Rodrigues, Ana [Centre for Systems, Dynamics and Control and Department of Mathematics, University of Exeter, Exeter EX4 4QF (United Kingdom)

    2016-09-15

    The Kuramoto–Sakaguchi system of coupled phase oscillators, where interaction between oscillators is determined by a single harmonic of phase differences of pairs of oscillators, has very simple emergent dynamics in the case of identical oscillators that are globally coupled: there is a variational structure that means the only attractors are full synchrony (in-phase) or splay phase (rotating wave/full asynchrony) oscillations and the bifurcation between these states is highly degenerate. Here we show that nonpairwise coupling—including three and four-way interactions of the oscillator phases—that appears generically at the next order in normal-form based calculations can give rise to complex emergent dynamics in symmetric phase oscillator networks. In particular, we show that chaos can appear in the smallest possible dimension of four coupled phase oscillators for a range of parameter values.

  18. Chaos in generically coupled phase oscillator networks with nonpairwise interactions.

    Science.gov (United States)

    Bick, Christian; Ashwin, Peter; Rodrigues, Ana

    2016-09-01

    The Kuramoto-Sakaguchi system of coupled phase oscillators, where interaction between oscillators is determined by a single harmonic of phase differences of pairs of oscillators, has very simple emergent dynamics in the case of identical oscillators that are globally coupled: there is a variational structure that means the only attractors are full synchrony (in-phase) or splay phase (rotating wave/full asynchrony) oscillations and the bifurcation between these states is highly degenerate. Here we show that nonpairwise coupling-including three and four-way interactions of the oscillator phases-that appears generically at the next order in normal-form based calculations can give rise to complex emergent dynamics in symmetric phase oscillator networks. In particular, we show that chaos can appear in the smallest possible dimension of four coupled phase oscillators for a range of parameter values.

  19. Disease candidate gene identification and prioritization using protein interaction networks

    Directory of Open Access Journals (Sweden)

    Aronow Bruce J

    2009-02-01

    Full Text Available Abstract Background Although most of the current disease candidate gene identification and prioritization methods depend on functional annotations, the coverage of the gene functional annotations is a limiting factor. In the current study, we describe a candidate gene prioritization method that is entirely based on protein-protein interaction network (PPIN analyses. Results For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate genes in a training-test schema. Using a list of known disease-related genes from our earlier study as a training set ("seeds", and the rest of the known genes as a test list, we perform large-scale cross validation to rank the candidate genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Conclusion Even though network-based methods are generally not as effective as integrated functional annotation-based methods for disease candidate gene prioritization, in a one-to-one comparison, PPIN-based candidate gene prioritization performs better than all other gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate gene prioritization.

  20. Sequence memory based on coherent spin-interaction neural networks.

    Science.gov (United States)

    Xia, Min; Wong, W K; Wang, Zhijie

    2014-12-01

    Sequence information processing, for instance, the sequence memory, plays an important role on many functions of brain. In the workings of the human brain, the steady-state period is alterable. However, in the existing sequence memory models using heteroassociations, the steady-state period cannot be changed in the sequence recall. In this work, a novel neural network model for sequence memory with controllable steady-state period based on coherent spininteraction is proposed. In the proposed model, neurons fire collectively in a phase-coherent manner, which lets a neuron group respond differently to different patterns and also lets different neuron groups respond differently to one pattern. The simulation results demonstrating the performance of the sequence memory are presented. By introducing a new coherent spin-interaction sequence memory model, the steady-state period can be controlled by dimension parameters and the overlap between the input pattern and the stored patterns. The sequence storage capacity is enlarged by coherent spin interaction compared with the existing sequence memory models. Furthermore, the sequence storage capacity has an exponential relationship to the dimension of the neural network.

  1. The paradox of caffeine-zolpidem interaction: a network analysis.

    Science.gov (United States)

    Myslobodsky, Michael

    2009-10-01

    A widely prescribed and potent short-acting hypnotic, zolpidem has become the mainstay for the treatment of middle-of-the-night sleeplessness. It is expected to be antagonized by caffeine. Paradoxically, in some cases caffeine appears to slightly enhance zolpidem sedation. The pharmacokinetic and pharmacodynamic nature of this odd effect remains unexplored. The purpose of this study is to reproduce a hypothetical molecular network recruited by caffeine when co-administered with zolpidem using Ingenuity Pathway Analysis. Thus generated, network drew attention to several possible contributors to caffeine sedation, such as tachykinin precursor 1, cannabinoid, and GABA receptors. The present overview is centered on the possibility that caffeine potentiation of zolpidem sedation does not involve a centralized interaction of specific neurotransmitters, but rather is contributed by its antioxidant capacity. It is proposed that by modifying the cellular redox state, caffeine ultimately reduces the pool of reactive oxygen species, thereby increasing the bioavailability of endogenous melatonin for interaction with zolpidem. This side effect of caffeine encourages further studies of multiple antioxidants as an attractive way to potentially increasing somnolence.

  2. Accessing Wireless Sensor Networks Via Dynamically Reconfigurable Interaction Models

    Directory of Open Access Journals (Sweden)

    Maria Cecília Gomes

    2012-12-01

    Full Text Available The Wireless Sensor Networks (WSNs technology is already perceived as fundamental for science across many domains, since it provides a low cost solution for environment monitoring. WSNs representation via the service concept and its inclusion in Web environments, e.g. through Web services, supports particularly their open/standard access and integration. Although such Web enabled WSNs simplify data access, network parameterization and aggregation, the existing interaction models and run-time adaptation mechanisms available to clients are still scarce. Nevertheless, applications increasingly demand richer and more flexible accesses besides the traditional client/server. For instance, applications may require a streaming model in order to avoid sequential data requests, or the asynchronous notification of subscribed data through the publish/subscriber. Moreover, the possibility to automatically switch between such models at runtime allows applications to define flexible context-based data acquisition. To this extent, this paper discusses the relevance of the session and pattern abstractions on the design of a middleware prototype providing richer and dynamically reconfigurable interaction models to Web enabled WSNs.

  3. Protein-Protein Interaction Network and Gene Ontology

    Science.gov (United States)

    Choi, Yunkyu; Kim, Seok; Yi, Gwan-Su; Park, Jinah

    Evolution of computer technologies makes it possible to access a large amount and various kinds of biological data via internet such as DNA sequences, proteomics data and information discovered about them. It is expected that the combination of various data could help researchers find further knowledge about them. Roles of a visualization system are to invoke human abilities to integrate information and to recognize certain patterns in the data. Thus, when the various kinds of data are examined and analyzed manually, an effective visualization system is an essential part. One instance of these integrated visualizations can be combination of protein-protein interaction (PPI) data and Gene Ontology (GO) which could help enhance the analysis of PPI network. We introduce a simple but comprehensive visualization system that integrates GO and PPI data where GO and PPI graphs are visualized side-by-side and supports quick reference functions between them. Furthermore, the proposed system provides several interactive visualization methods for efficiently analyzing the PPI network and GO directedacyclic- graph such as context-based browsing and common ancestors finding.

  4. The yeast two hybrid system in a screen for proteins interacting with axolotl (Ambystoma mexicanum) Msx1 during early limb regeneration.

    Science.gov (United States)

    Abuqarn, Mehtap; Allmeling, Christina; Amshoff, Inga; Menger, Bjoern; Nasser, Inas; Vogt, Peter M; Reimers, Kerstin

    2011-07-01

    Urodele amphibians are exceptional in their ability to regenerate complex body structures such as limbs. Limb regeneration depends on a process called dedifferentiation. Under an inductive wound epidermis terminally differentiated cells transform to pluripotent progenitor cells that coordinately proliferate and eventually redifferentiate to form the new appendage. Recent studies have developed molecular models integrating a set of genes that might have important functions in the control of regenerative cellular plasticity. Among them is Msx1, which induced dedifferentiation in mammalian myotubes in vitro. Herein, we screened for interaction partners of axolotl Msx1 using a yeast two hybrid system. A two hybrid cDNA library of 5-day-old wound epidermis and underlying tissue containing more than 2×10⁶ cDNAs was constructed and used in the screen. 34 resulting cDNA clones were isolated and sequenced. We then compared sequences of the isolated clones to annotated EST contigs of the Salamander EST database (BLASTn) to identify presumptive orthologs. We subsequently searched all no-hit clone sequences against non redundant NCBI sequence databases using BLASTx. It is the first time, that the yeast two hybrid system was adapted to the axolotl animal model and successfully used in a screen for proteins interacting with Msx1 in the context of amphibian limb regeneration. 2011 Elsevier B.V. All rights reserved.

  5. Group X hybrid histidine kinase Chk1 is dispensable for stress adaptation, host-pathogen interactions and virulence in the opportunistic yeast Candida guilliermondii.

    Science.gov (United States)

    Navarro-Arias, María J; Dementhon, Karine; Defosse, Tatiana A; Foureau, Emilien; Courdavault, Vincent; Clastre, Marc; Le Gal, Solène; Nevez, Gilles; Le Govic, Yohann; Bouchara, Jean-Philippe; Giglioli-Guivarc'h, Nathalie; Noël, Thierry; Mora-Montes, Hector M; Papon, Nicolas

    2017-09-01

    Hybrid histidine kinases (HHKs) progressively emerge as prominent sensing proteins in the fungal kingdom and as ideal targets for future therapeutics. The group X HHK is of major interest, since it was demonstrated to play an important role in stress adaptation, host-pathogen interactions and virulence in some yeast and mold models, and particularly Chk1, that corresponds to the sole group X HHK in Candida albicans. In the present work, we investigated the role of Chk1 in the low-virulence species Candida guilliermondii, in order to gain insight into putative conservation of the role of group X HHK in opportunistic yeasts. We demonstrated that disruption of the corresponding gene CHK1 does not influence growth, stress tolerance, drug susceptibility, protein glycosylation or cell wall composition in C. guilliermondii. In addition, we showed that loss of CHK1 does not affect C. guilliermondii ability to interact with macrophages and to stimulate cytokine production by human peripheral blood mononuclear cells. Finally, the C. guilliermondii chk1 null mutant was found to be as virulent as the wild-type strain in the experimental model Galleria mellonella. Taken together, our results demonstrate that group X HHK function is not conserved in Candida species. Copyright © 2017 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

  6. A single mutation in the 15S rRNA gene confers nonsense suppressor activity and interacts with mRF1 the release factor in yeast mitochondria

    Directory of Open Access Journals (Sweden)

    Ali Gargouri

    2015-08-01

    Full Text Available We have determined the nucleotide sequence of the mim3-1 mitochondrial ribosomal suppressor, acting on ochre mitochondrial mutations and one frameshift mutation in Saccharomyces cerevisiae. The 15s rRNA suppressor gene contains a G633 to C transversion. Yeast mitochondrial G633 corresponds to G517 of the E.coli 15S rRNA, which is occupied by an invariant G in all known small rRNA sequences. Interestingly, this mutation has occurred at the same position as the known MSU1 mitochondrial suppressor which changes G633 to A. The suppressor mutation lies in a highly conserved region of the rRNA, known in E.coli as the 530-loop, interacting with the S4, S5 and S12 ribosomal proteins. We also show an interesting interaction between the mitochondrial mim3-1 and the nuclear nam3-1 suppressors, both of which have the same action spectrum on mitochondrial mutations: nam3-1 abolishes the suppressor effect when present with mim3-1 in the same haploid cell. We discuss these results in the light of the nature of Nam3, identified by [1] as the yeast mitochondrial translation release factor. A hypothetical mechanism of suppression by "ribosome shifting" is also discussed in view of the nature of mutations suppressed and not suppressed.

  7. Disentangling the co-structure of multilayer interaction networks: degree distribution and module composition in two-layer bipartite networks.

    Science.gov (United States)

    Astegiano, Julia; Altermatt, Florian; Massol, François

    2017-11-13

    Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.

  8. Novel recurrent neural network for modelling biological networks: oscillatory p53 interaction dynamics.

    Science.gov (United States)

    Ling, Hong; Samarasinghe, Sandhya; Kulasiri, Don

    2013-12-01

    Understanding the control of cellular networks consisting of gene and protein interactions and their emergent properties is a central activity of Systems Biology research. For this, continuous, discrete, hybrid, and stochastic methods have been proposed. Currently, the most common approach to modelling accurate temporal dynamics of networks is ordinary differential equations (ODE). However, critical limitations of ODE models are difficulty in kinetic parameter estimation and numerical solution of a large number of equations, making them more suited to smaller systems. In this article, we introduce a novel recurrent artificial neural network (RNN) that addresses above limitations and produces a continuous model that easily estimates parameters from data, can handle a large number of molecular interactions and quantifies temporal dynamics and emergent systems properties. This RNN is based on a system of ODEs representing molecular interactions in a signalling network. Each neuron represents concentration change of one molecule represented by an ODE. Weights of the RNN correspond to kinetic parameters in the system and can be adjusted incrementally during network training. The method is applied to the p53-Mdm2 oscillation system - a crucial component of the DNA damage response pathways activated by a damage signal. Simulation results indicate that the proposed RNN can successfully represent the behaviour of the p53-Mdm2 oscillation system and solve the parameter estimation problem with high accuracy. Furthermore, we presented a modified form of the RNN that estimates parameters and captures systems dynamics from sparse data collected over relatively large time steps. We also investigate the robustness of the p53-Mdm2 system using the trained RNN under various levels of parameter perturbation to gain a greater understanding of the control of the p53-Mdm2 system. Its outcomes on robustness are consistent with the current biological knowledge of this system. As more

  9. Large scale genotype comparison of human papillomavirus E2-host interaction networks provides new insights for e2 molecular functions.

    Directory of Open Access Journals (Sweden)

    Mandy Muller

    Full Text Available Human Papillomaviruses (HPV cause widespread infections in humans, resulting in latent infections or diseases ranging from benign hyperplasia to cancers. HPV-induced pathologies result from complex interplays between viral proteins and the host proteome. Given the major public health concern due to HPV-associated cancers, most studies have focused on the early proteins expressed by HPV genotypes with high oncogenic potential (designated high-risk HPV or HR-HPV. To advance the global understanding of HPV pathogenesis, we mapped the virus/host interaction networks of the E2 regulatory protein from 12 genotypes representative of the range of HPV pathogenicity. Large-scale identification of E2-interaction partners was performed by yeast two-hybrid screenings of a HaCaT cDNA library. Based on a high-confidence scoring scheme, a subset of these partners was then validated for pair-wise interaction in mammalian cells with the whole range of the 12 E2 proteins, allowing a comparative interaction analysis. Hierarchical clustering of E2-host interaction profiles mostly recapitulated HPV phylogeny and provides clues to the involvement of E2 in HPV infection. A set of cellular proteins could thus be identified discriminating, among the mucosal HPV, E2 proteins of HR-HPV 16 or 18 from the non-oncogenic genital HPV. The study of the interaction networks revealed a preferential hijacking of highly connected cellular proteins and the targeting of several functional families. These include transcription regulation, regulation of apoptosis, RNA processing, ubiquitination and intracellular trafficking. The present work provides an overview of E2 biological functions across multiple HPV genotypes.

  10. Large scale genotype comparison of human papillomavirus E2-host interaction networks provides new insights for e2 molecular functions.

    Science.gov (United States)

    Muller, Mandy; Jacob, Yves; Jones, Louis; Weiss, Amélie; Brino, Laurent; Chantier, Thibault; Lotteau, Vincent; Favre, Michel; Demeret, Caroline

    2012-01-01

    Human Papillomaviruses (HPV) cause widespread infections in humans, resulting in latent infections or diseases ranging from benign hyperplasia to cancers. HPV-induced pathologies result from complex interplays between viral proteins and the host proteome. Given the major public health concern due to HPV-associated cancers, most studies have focused on the early proteins expressed by HPV genotypes with high oncogenic potential (designated high-risk HPV or HR-HPV). To advance the global understanding of HPV pathogenesis, we mapped the virus/host interaction networks of the E2 regulatory protein from 12 genotypes representative of the range of HPV pathogenicity. Large-scale identification of E2-interaction partners was performed by yeast two-hybrid screenings of a HaCaT cDNA library. Based on a high-confidence scoring scheme, a subset of these partners was then validated for pair-wise interaction in mammalian cells with the whole range of the 12 E2 proteins, allowing a comparative interaction analysis. Hierarchical clustering of E2-host interaction profiles mostly recapitulated HPV phylogeny and provides clues to the involvement of E2 in HPV infection. A set of cellular proteins could thus be identified discriminating, among the mucosal HPV, E2 proteins of HR-HPV 16 or 18 from the non-oncogenic genital HPV. The study of the interaction networks revealed a preferential hijacking of highly connected cellular proteins and the targeting of several functional families. These include transcription regulation, regulation of apoptosis, RNA processing, ubiquitination and intracellular trafficking. The present work provides an overview of E2 biological functions across multiple HPV genotypes.

  11. Social Networking Sites as Communication, Interaction, and Learning Environments: Perceptions and Preferences of Distance Education Students

    Science.gov (United States)

    Bozkurt, Aras; Karadeniz, Abdulkadir; Kocdar, Serpil

    2017-01-01

    The advent of Web 2.0 technologies transformed online networks into interactive spaces in which user-generated content has become the core material. With the possibilities that emerged from Web 2.0, social networking sites became very popular. The capability of social networking sites promises opportunities for communication and interaction,…

  12. User-Centric Secure Cross-Site Interaction Framework for Online Social Networking Services

    Science.gov (United States)

    Ko, Moo Nam

    2011-01-01

    Social networking service is one of major technological phenomena on Web 2.0. Hundreds of millions of users are posting message, photos, and videos on their profiles and interacting with other users, but the sharing and interaction are limited within the same social networking site. Although users can share some content on a social networking site…

  13. Towards a map of the Populus biomass protein-protein interaction network

    Energy Technology Data Exchange (ETDEWEB)

    Beers, Eric [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Brunner, Amy [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Helm, Richard [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States); Dickerman, Allan [Virginia Polytechnic Inst. and State Univ. (Virginia Tech), Blacksburg, VA (United States)

    2015-07-31

    Biofuels can be produced from a variety of plant feedstocks. The value of a particular feedstock for biofuels production depends in part on the degree of difficulty associated with the extraction of fermentable sugars from the plant biomass. The wood of trees is potentially a rich source fermentable sugars. However, the sugars in wood exist in a tightly cross-linked matrix of cellulose, hemicellulose, and lignin, making them largely recalcitrant to release and fermentation for biofuels production. Before breeders and genetic engineers can effectively develop plants with reduced recalcitrance to fermentation, it is necessary to gain a better understanding of the fundamental biology of the mechanisms responsible for wood formation. Regulatory, structural, and enzymatic proteins are required for the complicated process of wood formation. To function properly, proteins must interact with other proteins. Yet, very few of the protein-protein interactions necessary for wood formation are known. The main objectives of this project were to 1) identify new protein-protein interactions relevant to wood formation, and 2) perform in-depth characterizations of selected protein-protein interactions. To identify relevant protein-protein interactions, we cloned a set of approximately 400 genes that were highly expressed in the wood-forming tissue (known as secondary xylem) of poplar (Populus trichocarpa). We tested whether the proteins encoded by these biomass genes interacted with each other in a binary matrix design using the yeast two-hybrid (Y2H) method for protein-protein interaction discovery. We also tested a subset of the 400 biomass proteins for interactions with all proteins present in wood-forming tissue of poplar in a biomass library screen design using Y2H. Together, these two Y2H screens yielded over 270 interactions involving over 75 biomass proteins. For the second main objective we selected several interacting pairs or groups of interacting proteins for in

  14. Modeling attacker-defender interactions in information networks.

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Michael Joseph

    2010-09-01

    The simplest conceptual model of cybersecurity implicitly views attackers and defenders as acting in isolation from one another: an attacker seeks to penetrate or disrupt a system that has been protected to a given level, while a defender attempts to thwart particular attacks. Such a model also views all non-malicious parties as having the same goal of preventing all attacks. But in fact, attackers and defenders are interacting parts of the same system, and different defenders have their own individual interests: defenders may be willing to accept some risk of successful attack if the cost of defense is too high. We have used game theory to develop models of how non-cooperative but non-malicious players in a network interact when there is a substantial cost associated with effective defensive measures. Although game theory has been applied in this area before, we have introduced some novel aspects of player behavior in our work, including: (1) A model of how players attempt to avoid the costs of defense and force others to assume these costs; (2) A model of how players interact when the cost of defending one node can be shared by other nodes; and (3) A model of the incentives for a defender to choose less expensive, but less effective, defensive actions.

  15. TorsinA and the torsinA-interacting protein printor have no impact on endoplasmic reticulum stress or protein trafficking in yeast.

    Directory of Open Access Journals (Sweden)

    Julie S Valastyan

    Full Text Available Early-onset torsion dystonia is a severe, life-long disease that leads to loss of motor control and involuntary muscle contractions. While the molecular etiology of the disease is not fully understood, a mutation in an AAA+ ATPase, torsinA, has been linked to disease onset. Previous work on torsinA has shown that it localizes to the endoplasmic reticulum, where there is evidence that it plays roles in protein trafficking, and potentially also protein folding. Given the high level of evolutionary conservation among proteins involved in these processes, the ability of human such proteins to function effectively in yeast, as well as the previous successes achieved in examining other proteins involved in complex human diseases in yeast, we hypothesized that Saccharomyces cerevisiae might represent a useful model system for studying torsinA function and the effects of its mutants. Since torsinA is proposed to function in protein homeostasis, we tested cells for their ability to respond to various stressors, using a fluorescent reporter to measure the unfolded protein response, as well as their rate of protein secretion. TorsinA did not impact these processes, even after co-expression of its recently identified interacting partner, printor. In light of these findings, we propose that yeast may lack an additional cofactor necessary for torsinA function or proteins required for essential post-translational modifications of torsinA. Alternatively, torsinA may not function in endoplasmic reticulum protein homeostasis. The strains and assays we describe may provide useful tools for identifying and investigating these possibilities and are freely available.

  16. The tumor suppressor homolog in fission yeast, myh1{sup +}, displays a strong interaction with the checkpoint gene rad1{sup +}

    Energy Technology Data Exchange (ETDEWEB)

    Jansson, Kristina; Warringer, Jonas; Farewell, Anne [Department of Cell and Molecular Biology, Lundberg Laboratory, Goeteborg University, P.O. Box 462, Goeteborg SE-405 30 (Sweden); Park, Han-Oh [Bioneer Corporation, 49-3, Munpyeong-dong, Daedeok-gu, Daejon 306-220 (Korea, Republic of); Hoe, Kwang-Lae; Kim, Dong-Uk [Functional Genomics Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Yusong, Daejeon (Korea, Republic of); Hayles, Jacqueline [Cell Cycle Laboratory, Cancer Research UK, London Research Institute, 44 Lincoln' s Inn Fields, London WC2A 3PX (United Kingdom); Sunnerhagen, Per [Department of Cell and Molecular Biology, Lundberg Laboratory, Goeteborg University, P.O. Box 462, Goeteborg SE-405 30 (Sweden)], E-mail: per.sunnerhagen@cmb.gu.se

    2008-09-26

    The DNA glycosylase MutY is strongly conserved in evolution, and homologs are found in most eukaryotes and prokaryotes examined. This protein is implicated in repair of oxidative DNA damage, in particular adenine mispaired opposite 7,8-dihydro-8-oxoguanine. Previous investigations in Escherichia coli, fission yeast, and mammalian cells show an association of mutations in MutY homologs with a mutator phenotype and carcinogenesis. Eukaryotic MutY homologs physically associate with several proteins with a role in replication, DNA repair, and checkpoint signaling, specifically the trimeric 9-1-1 complex. In a genetic investigation of the fission yeast MutY homolog, myh1{sup +}, we show that the myh1 mutation confers a moderately increased UV sensitivity alone and in combination with mutations in several DNA repair genes. The myh1 rad1, and to a lesser degree myh1 rad9, double mutants display a synthetic interaction resulting in enhanced sensitivity to DNA damaging agents and hydroxyurea. UV irradiation of myh1 rad1 double mutants results in severe chromosome segregation defects and visible DNA fragmentation, and a failure to activate the checkpoint. Additionally, myh1 rad1 double mutants exhibit morphological defects in the absence of DNA damaging agents. We also found a moderate suppression of the slow growth and UV sensitivity of rhp51 mutants by the myh1 mutation. Our results implicate fission yeast Myh1 in repair of a wider range of DNA damage than previously thought, and functionally link it to the checkpoint pathway.

  17. NatalieQ: A web server for protein-protein interaction network querying

    NARCIS (Netherlands)

    El-Kebir, M.; Brandt, B.W.; Heringa, J.; Klau, G.W.

    2014-01-01

    Background Molecular interactions need to be taken into account to adequately model the complex behavior of biological systems. These interactions are captured by various types of biological networks, such as metabolic, gene-regulatory, signal transduction and protein-protein interaction networks.

  18. Drug-Drug Interaction Extraction via Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Shengyu Liu

    2016-01-01

    Full Text Available Drug-drug interaction (DDI extraction as a typical relation extraction task in natural language processing (NLP has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM with a large number of manually defined features. Recently, convolutional neural networks (CNN, a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%.

  19. Determine point-to-point networking interactions using regular expressions

    Directory of Open Access Journals (Sweden)

    Konstantin S. Deev

    2015-06-01

    Full Text Available As Internet growth and becoming more popular, the number of concurrent data flows start to increasing, which makes sense in bandwidth requested. Providers and corporate customers need ability to identify point-to-point interactions. The best is to use special software and hardware implementations that distribute the load in the internals of the complex, using the principles and approaches, in particular, described in this paper. This paper represent the principles of building system, which searches for a regular expression match using computing on graphics adapter in server station. A significant computing power and capability to parallel execution on modern graphic processor allows inspection of large amounts of data through sets of rules. Using the specified characteristics can lead to increased computing power in 30…40 times compared to the same setups on the central processing unit. The potential increase in bandwidth capacity could be used in systems that provide packet analysis, firewalls and network anomaly detectors.

  20. Specialization of mutualistic interaction networks decreases toward tropical latitudes

    DEFF Research Database (Denmark)

    Schleuning, M.; Fründ, J.; Klein, A.-M.

    2012-01-01

    that current conditions have a stronger effect on biotic specialization than historical community stability. Biotic specialization decreased with increasing local and regional plant diversity. This suggests that high specialization of mutualistic interactions is a response of pollinators and seed dispersers......] or differences in plant diversity [10, 11]. Thus, the direction of the latitudinal specialization gradient remains contentious. With an unprecedented global data set, we investigated how biotic specialization between plants and animal pollinators or seed dispersers is associated with latitude, past...... and contemporary climate, and plant diversity. We show that in contrast to expectation, biotic specialization of mutualistic networks is significantly lower at tropical than at temperate latitudes. Specialization was more closely related to contemporary climate than to past climate stability, suggesting...

  1. Co-creating value through agents interaction within service network

    Energy Technology Data Exchange (ETDEWEB)

    Okdinawati, L.; Simatupang, T.M.; Sunitiyoso, Y.

    2017-07-01

    The purpose of this paper is to gives further understanding on value co-creation mechanisms in B-to-B service network by reinforcing the processes, the relationships, and influences of other agents where Collaborative Transportation Management (CTM) forms might be best employed. Design/methodology/approach: In order to model the interactions among agents in the collaboration processes and the value co-creation processes, this research used three collaboration cases in Indonesia. Then, the agent-based simulation was used to capture both the collaboration process and the value co-creation process of the three collaboration cases. Findings: The interactions among the agents both inside and outside their collaboration environment determined agent’s role as a value co-creator. The willingness of an agent to accept the opinion of another agent determined the degree of their willingness to co-operate and to change their strategies, and perceptions. Therefore, influenced the size of the value obtained by them in each collaboration process. Research limitations/implications: The findings of the simulations subject to assumptions based on the collaboration cases. Further research is related to how to encourage agents to co-operate and adjust their perceptions. Practical implications: It is crucial for the practitioners to interact with another agent both inside and outside their collaboration environment. The opinions of another agent inside the collaboration environment also need to be considered. Originality/value: This research is derived from its emphasis on how a value is co-created by reinforcing both the collaborative processes and the interactions among agents as well as on how CTM might be best employed.

  2. Co-creating value through agents interaction within service network

    International Nuclear Information System (INIS)

    Okdinawati, L.; Simatupang, T.M.; Sunitiyoso, Y.

    2017-01-01

    The purpose of this paper is to gives further understanding on value co-creation mechanisms in B-to-B service network by reinforcing the processes, the relationships, and influences of other agents where Collaborative Transportation Management (CTM) forms might be best employed. Design/methodology/approach: In order to model the interactions among agents in the collaboration processes and the value co-creation processes, this research used three collaboration cases in Indonesia. Then, the agent-based simulation was used to capture both the collaboration process and the value co-creation process of the three collaboration cases. Findings: The interactions among the agents both inside and outside their collaboration environment determined agent’s role as a value co-creator. The willingness of an agent to accept the opinion of another agent determined the degree of their willingness to co-operate and to change their strategies, and perceptions. Therefore, influenced the size of the value obtained by them in each collaboration process. Research limitations/implications: The findings of the simulations subject to assumptions based on the collaboration cases. Further research is related to how to encourage agents to co-operate and adjust their perceptions. Practical implications: It is crucial for the practitioners to interact with another agent both inside and outside their collaboration environment. The opinions of another agent inside the collaboration environment also need to be considered. Originality/value: This research is derived from its emphasis on how a value is co-created by reinforcing both the collaborative processes and the interactions among agents as well as on how CTM might be best employed.

  3. SLC25 Family Member Genetic Interactions Identify a Role for HEM25 in Yeast Electron Transport Chain Stability.

    Science.gov (United States)

    Dufay, J Noelia; Fernández-Murray, J Pedro; McMaster, Christopher R

    2017-06-07

    The SLC25 family member SLC25A38 (Hem25 in yeast) was recently identified as a mitochondrial glycine transporter that provides substrate to initiate heme/hemoglobin synthesis. Mutations in the human SLC25A38 gene cause congenital sideroblastic anemia. The full extent to which SLC25 family members coregulate heme synthesis with other mitochondrial functions is not clear. In this study, we surveyed 29 nonessential SLC25 family members in Saccharomyces cerevisiae for their ability to support growth in the presence and absence of HEM25 Six SLC25 family members were identified that were required for growth or for heme synthesis in cells lacking Hem25 function. Importantly, we determined that loss of function of the SLC25 family member Flx1, which imports FAD into mitochondria, together with loss of function of Hem25, resulted in inability to grow on media that required yeast cells to supply energy using mitochondrial respiration. We report that specific components of complexes of the electron transport chain are decreased in the absence of Flx1 and Hem25 function. In addition, we show that mitochondria from flx1 Δ hem25 Δ cells contain uncharacterized Cox2-containing high molecular weight aggregates. The functions of Flx1 and Hem25 provide a facile explanation for the decrease in heme level, and in specific electron transport chain complex components. Copyright © 2017 Dufay et al.

  4. SLC25 Family Member Genetic Interactions Identify a Role for HEM25 in Yeast Electron Transport Chain Stability

    Directory of Open Access Journals (Sweden)

    J. Noelia Dufay

    2017-06-01

    Full Text Available The SLC25 family member SLC25A38 (Hem25 in yeast was recently identified as a mitochondrial glycine transporter that provides substrate to initiate heme/hemoglobin synthesis. Mutations in the human SLC25A38 gene cause congenital sideroblastic anemia. The full extent to which SLC25 family members coregulate heme synthesis with other mitochondrial functions is not clear. In this study, we surveyed 29 nonessential SLC25 family members in Saccharomyces cerevisiae for their ability to support growth in the presence and absence of HEM25. Six SLC25 family members were identified that were required for growth or for heme synthesis in cells lacking Hem25 function. Importantly, we determined that loss of function of the SLC25 family member Flx1, which imports FAD into mitochondria, together with loss of function of Hem25, resulted in inability to grow on media that required yeast cells to supply energy using mitochondrial respiration. We report that specific components of complexes of the electron transport chain are decreased in the absence of Flx1 and Hem25 function. In addition, we show that mitochondria from flx1Δ hem25Δ cells contain uncharacterized Cox2-containing high molecular weight aggregates. The functions of Flx1 and Hem25 provide a facile explanation for the decrease in heme level, and in specific electron transport chain complex components.

  5. Pleistocene megafaunal interaction networks became more vulnerable after human arrival.

    Science.gov (United States)

    Pires, Mathias M; Koch, Paul L; Fariña, Richard A; de Aguiar, Marcus A M; dos Reis, Sérgio F; Guimarães, Paulo R

    2015-09-07

    The end of the Pleistocene was marked by the extinction of almost all large land mammals worldwide except in Africa. Although the debate on Pleistocene extinctions has focused on the roles of climate change and humans, the impact of perturbations depends on properties of ecological communities, such as species composition and the organization of ecological interactions. Here, we combined palaeoecological and ecological data, food-web models and community stability analysis to investigate if differences between Pleistocene and modern mammalian assemblages help us understand why the megafauna died out in the Americas while persisting in Africa. We show Pleistocene and modern assemblages share similar network topology, but differences in richness and body size distributions made Pleistocene communities significantly more vulnerable to the effects of human arrival. The structural changes promoted by humans in Pleistocene networks would have increased the likelihood of unstable dynamics, which may favour extinction cascades in communities facing extrinsic perturbations. Our findings suggest that the basic aspects of the organization of ecological communities may have played an important role in major extinction events in the past. Knowledge of community-level properties and their consequences to dynamics may be critical to understand past and future extinctions. © 2015 The Author(s).

  6. CombiMotif: A new algorithm for network motifs discovery in protein-protein interaction networks

    Science.gov (United States)

    Luo, Jiawei; Li, Guanghui; Song, Dan; Liang, Cheng

    2014-12-01

    Discovering motifs in protein-protein interaction networks is becoming a current major challenge in computational biology, since the distribution of the number of network motifs can reveal significant systemic differences among species. However, this task can be computationally expensive because of the involvement of graph isomorphic detection. In this paper, we present a new algorithm (CombiMotif) that incorporates combinatorial techniques to count non-induced occurrences of subgraph topologies in the form of trees. The efficiency of our algorithm is demonstrated by comparing the obtained results with the current state-of-the art subgraph counting algorithms. We also show major differences between unicellular and multicellular organisms. The datasets and source code of CombiMotif are freely available upon request.

  7. Synergistic interactions between RAD5, RAD16, and RAD54, three partially homologous yeast DNA repair genes each in a different repair pathway

    International Nuclear Information System (INIS)

    Glassner, B.J.; Mortimer, R.K.

    1994-01-01

    Considerable homology has recently been noted between the proteins encoded by the RAD5, RAD16 and RAD54 genes of Saccharomyces cerevisiae. These genes are members of the RAD6, RAD3 and RAD50 epistasis groups, respectively, which correspond to the three major DNA repair pathways in yeast. These proteins also share homology with other eucaryotic proteins, including those encoded by SNF2 and MO1 of yeast, brahma and lodestar of Drosophila and the human ERCC6 gene. The homology shares features with known helicases, suggesting a newly identified helicase subfamily. We have constructed a series of congenic single-, double- and triple-deletion mutants involving RAD5, RAD16 and RAD54 to examine the interactions between these genes. Each deletion mutation alone has only a moderate effect on survival after exposure to UV radiation. Each pairwise-double mutant exhibits marked synergism. The triple-deletion mutant displays further synergism. These results confirm the assignment of the RAD54 gene to the RAD50 epistasis group and suggest that the RAD16 gene plays a larger role in DNA repair after exposure to UV radiation than has been suggested previously. Additionally, the proteins encoded by RAD5, RAD16, and RAD54 may compete for the same substrate after damage induced by UV radiation, possibly at an early step in their respective pathways. 49 refs., 6 figs., 2 tabs

  8. Expression Patterns and Identified Protein-Protein Interactions Suggest That Cassava CBL-CIPK Signal Networks Function in Responses to Abiotic Stresses.

    Science.gov (United States)

    Mo, Chunyan; Wan, Shumin; Xia, Youquan; Ren, Ning; Zhou, Yang; Jiang, Xingyu

    2018-01-01

    Cassava is an energy crop that is tolerant of multiple abiotic stresses. It has been reported that the interaction between Calcineurin B-like (CBL) protein and CBL-interacting protein kinase (CIPK) is implicated in plant development and responses to various stresses. However, little is known about their functions in cassava. Herein, 8 CBL ( MeCBL ) and 26 CIPK ( MeCIPK ) genes were isolated from cassava by genome searching and cloning of cDNA sequences of Arabidopsis CBL s and CIPK s. Reverse-transcriptase polymerase chain reaction (RT-PCR) analysis showed that the expression levels of MeCBL and MeCIPK genes were different in different tissues throughout the life cycle. The expression patterns of 7 CBL and 26 CIPK genes in response to NaCl, PEG, heat and cold stresses were analyzed by quantitative real-time PCR (qRT-PCR), and it was found that the expression of each was induced by multiple stimuli. Furthermore, we found that many pairs of CBLs and CIPKs could interact with each other via investigating the interactions between 8 CBL and 25 CIPK proteins using a yeast two-hybrid system. Yeast cells co-transformed with cassava MeCIPK24, MeCBL10 , and Na + /H + antiporter MeSOS1 genes exhibited higher salt tolerance compared to those with one or two genes. These results suggest that the cassava CBL-CIPK signal network might play key roles in response to abiotic stresses.

  9. Opinion dynamics on interacting networks: media competition and social influence.

    Science.gov (United States)

    Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio

    2014-05-27

    The inner dynamics of the multiple actors of the informations systems - i.e, T.V., newspapers, blogs, social network platforms, - play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist.

  10. Opinion dynamics on interacting networks: media competition and social influence

    Science.gov (United States)

    Quattrociocchi, Walter; Caldarelli, Guido; Scala, Antonio

    2014-05-01

    The inner dynamics of the multiple actors of the informations systems - i.e, T.V., newspapers, blogs, social network platforms, - play a fundamental role on the evolution of the public opinion. Coherently with the recent history of the information system (from few main stream media to the massive diffusion of socio-technical system), in this work we investigate how main stream media signed interaction might shape the opinion space. In particular we focus on how different size (in the number of media) and interaction patterns of the information system may affect collective debates and thus the opinions' distribution. We introduce a sophisticated computational model of opinion dynamics which accounts for the coexistence of media and gossip as separated mechanisms and for their feedback loops. The model accounts also for the effect of the media communication patterns by considering both the simple case where each medium mimics the behavior of the most successful one (to maximize the audience) and the case where there is polarization and thus competition among media memes. We show that plurality and competition within information sources lead to stable configurations where several and distant cultures coexist.

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

    DEFF Research Database (Denmark)

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

    2017-01-01

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

  12. Involvement of the carboxyl-terminal region of the yeast peroxisomal half ABC transporter Pxa2p in its interaction with Pxa1p and in transporter function.

    Directory of Open Access Journals (Sweden)

    Cheng-Yi Chuang

    Full Text Available The peroxisome is a single membrane-bound organelle in eukaryotic cells involved in lipid metabolism, including β-oxidation of fatty acids. The human genetic disorder X-linked adrenoleukodystrophy (X-ALD is caused by mutations in the ABCD1 gene (encoding ALDP, a peroxisomal half ATP-binding cassette [ABC] transporter. This disease is characterized by defective peroxisomal β-oxidation and a large accumulation of very long-chain fatty acids in brain white matter, adrenal cortex, and testis. ALDP forms a homodimer proposed to be the functional transporter, whereas the peroxisomal transporter in yeast is a heterodimer comprising two half ABC transporters, Pxa1p and Pxa2p, both orthologs of human ALDP. While the carboxyl-terminal domain of ALDP is engaged in dimerization, it remains unknown whether the same region is involved in the interaction between Pxa1p and Pxa2p.Using a yeast two-hybrid assay, we found that the carboxyl-terminal region (CT of Pxa2p, but not of Pxa1p, is required for their interaction. Further analysis indicated that the central part of the CT (designated CT2 of Pxa2p was indispensable for its interaction with the carboxyl terminally truncated Pxa1_NBD. An interaction between the CT of Pxa2p and Pxa1_NBD was not detected, but could be identified in the presence of Pxa2_NBD-CT1. A single mutation of two conserved residues (aligned with X-ALD-associated mutations at the same positions in ALDP in the CT2 of the Pxa2_NBD-CT protein impaired its interaction with Pxa1_NBD or Pxa1_NBD-CT, resulting in a mutant protein that exhibited a proteinase K digestion profile different from that of the wild-type protein. Functional analysis of these mutant proteins on oleate plates indicated that they were defective in transporter function.The CT of Pxa2p is involved in its interaction with Pxa1p and in transporter function. This concept may be applied to human ALDP studies, helping to establish the pathological mechanism for CT-related X

  13. Multiple Taf subunits of TFIID interact with Ino2 activation domains and contribute to expression of genes required for yeast phospholipid biosynthesis.

    Science.gov (United States)

    Hintze, Stefan; Engelhardt, Maike; van Diepen, Laura; Witt, Eric; Schüller, Hans-Joachim

    2017-12-01

    Expression of phospholipid biosynthetic genes in yeast requires activator protein Ino2 which can bind to the UAS element inositol/choline-responsive element (ICRE) and trigger activation of target genes, using two separate transcriptional activation domains, TAD1 and TAD2. However, it is still unknown which cofactors mediate activation by TADs of Ino2. Here, we show that multiple subunits of basal transcription factor TFIID (TBP-associated factors Taf1, Taf4, Taf6, Taf10 and Taf12) are able to interact in vitro with activation domains of Ino2. Interaction was no longer observed with activation-defective variants of TAD1. We were able to identify two nonoverlapping regions in the N-terminus of Taf1 (aa 1-100 and aa 182-250) each of which could interact with TAD1 of Ino2 as well as with TAD4 of activator Adr1. Specific missense mutations within Taf1 domain aa 182-250 affecting basic and hydrophobic residues prevented interaction with wild-type TAD1 and caused reduced expression of INO1. Using chromatin immunoprecipitation we demonstrated Ino2-dependent recruitment of Taf1 and Taf6 to ICRE-containing promoters INO1 and CHO2. Transcriptional derepression of INO1 was no longer possible with temperature-sensitive taf1 and taf6 mutants cultivated under nonpermissive conditions. This result supports the hypothesis of Taf-dependent expression of structural genes activated by Ino2. © 2017 John Wiley & Sons Ltd.

  14. Interrogating the architecture of protein assemblies and protein interaction networks by cross-linking mass spectrometry

    NARCIS (Netherlands)

    Liu, Fan; Heck, Albert J R

    2015-01-01

    Proteins are involved in almost all processes of the living cell. They are organized through extensive networks of interaction, by tightly bound macromolecular assemblies or more transiently via signaling nodes. Therefore, revealing the architecture of protein complexes and protein interaction

  15. Lager Yeast Comes of Age

    Science.gov (United States)

    2014-01-01

    Alcoholic fermentations have accompanied human civilizations throughout our history. Lager yeasts have a several-century-long tradition of providing fresh beer with clean taste. The yeast strains used for lager beer fermentation have long been recognized as hybrids between two Saccharomyces species. We summarize the initial findings on this hybrid nature, the genomics/transcriptomics of lager yeasts, and established targets of strain improvements. Next-generation sequencing has provided fast access to yeast genomes. Its use in population genomics has uncovered many more hybridization events within Saccharomyces species, so that lager yeast hybrids are no longer the exception from the rule. These findings have led us to propose network evolution within Saccharomyces species. This “web of life” recognizes the ability of closely related species to exchange DNA and thus drain from a combined gene pool rather than be limited to a gene pool restricted by speciation. Within the domesticated lager yeasts, two groups, the Saaz and Frohberg groups, can be distinguished based on fermentation characteristics. Recent evidence suggests that these groups share an evolutionary history. We thus propose to refer to the Saaz group as Saccharomyces carlsbergensis and to the Frohberg group as Saccharomyces pastorianus based on their distinct genomes. New insight into the hybrid nature of lager yeast will provide novel directions for future strain improvement. PMID:25084862

  16. Structure-function analysis and genetic interactions of the SmG, SmE, and SmF subunits of the yeast Sm protein ring.

    Science.gov (United States)

    Schwer, Beate; Kruchten, Joshua; Shuman, Stewart

    2016-09-01

    A seven-subunit Sm protein ring forms a core scaffold of the U1, U2, U4, and U5 snRNPs that direct pre-mRNA splicing. Using human snRNP structures to guide mutagenesis in Saccharomyces cerevisiae, we gained new insights into structure-function relationships of the SmG, SmE, and SmF subunits. An alanine scan of 19 conserved amino acids of these three proteins, comprising the Sm RNA binding sites or inter-subunit interfaces, revealed that, with the exception of Arg74 in SmF, none are essential for yeast growth. Yet, for SmG, SmE, and SmF, as for many components of the yeast spliceosome, the effects of perturbing protein-RNA and protein-protein interactions are masked by built-in functional redundancies of the splicing machine. For example, tests for genetic interactions with non-Sm splicing factors showed that many benign mutations of SmG, SmE, and SmF (and of SmB and SmD3) were synthetically lethal with null alleles of U2 snRNP subunits Lea1 and Msl1. Tests of pairwise combinations of SmG, SmE, SmF, SmB, and SmD3 alleles highlighted the inherent redundancies within the Sm ring, whereby simultaneous mutations of the RNA binding sites of any two of the Sm subunits are lethal. Our results suggest that six intact RNA binding sites in the Sm ring suffice for function but five sites may not. © 2016 Schwer et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

  17. Structure–function analysis and genetic interactions of the SmG, SmE, and SmF subunits of the yeast Sm protein ring

    Science.gov (United States)

    Schwer, Beate; Kruchten, Joshua; Shuman, Stewart

    2016-01-01

    A seven-subunit Sm protein ring forms a core scaffold of the U1, U2, U4, and U5 snRNPs that direct pre-mRNA splicing. Using human snRNP structures to guide mutagenesis in Saccharomyces cerevisiae, we gained new insights into structure–function relationships of the SmG, SmE, and SmF subunits. An alanine scan of 19 conserved amino acids of these three proteins, comprising the Sm RNA binding sites or inter-subunit interfaces, revealed that, with the exception of Arg74 in SmF, none are essential for yeast growth. Yet, for SmG, SmE, and SmF, as for many components of the yeast spliceosome, the effects of perturbing protein–RNA and protein–protein interactions are masked by built-in functional redundancies of the splicing machine. For example, tests for genetic interactions with non-Sm splicing factors showed that many benign mutations of SmG, SmE, and SmF (and of SmB and SmD3) were synthetically lethal with null alleles of U2 snRNP subunits Lea1 and Msl1. Tests of pairwise combinations of SmG, SmE, SmF, SmB, and SmD3 alleles highlighted the inherent redundancies within the Sm ring, whereby simultaneous mutations of the RNA binding sites of any two of the Sm subunits are lethal. Our results suggest that six intact RNA binding sites in the Sm ring suffice for function but five sites may not. PMID:27417296

  18. Weighted Protein Interaction Network Analysis of Frontotemporal Dementia.

    Science.gov (United States)

    Ferrari, Raffaele; Lovering, Ruth C; Hardy, John; Lewis, Patrick A; Manzoni, Claudia

    2017-02-03

    The genetic analysis of complex disorders has undoubtedly led to the identification of a wealth of associations between genes and specific traits. However, moving from genetics to biochemistry one gene at a time has, to date, rather proved inefficient and under-powered to comprehensively explain the molecular basis of phenotypes. Here we present a novel approach, weighted protein-protein interaction network analysis (W-PPI-NA), to highlight key functional players within relevant biological processes associated with a given trait. This is exemplified in the current study by applying W-PPI-NA to frontotemporal dementia (FTD): We first built the state of the art FTD protein network (FTD-PN) and then analyzed both its topological and functional features. The FTD-PN resulted from the sum of the individual interactomes built around FTD-spectrum genes, leading to a total of 4198 nodes. Twenty nine of 4198 nodes, called inter-interactome hubs (IIHs), represented those interactors able to bridge over 60% of the individual interactomes. Functional annotation analysis not only reiterated and reinforced previous findings from single genes and gene-coexpression analyses but also indicated a number of novel potential disease related mechanisms, including DNA damage response, gene expression regulation, and cell waste disposal and potential biomarkers or therapeutic targets including EP300. These processes and targets likely represent the functional core impacted in FTD, reflecting the underlying genetic architecture contributing to disease. The approach presented in this study can be applied to other complex traits for which risk-causative genes are known as it provides a promising tool for setting the foundations for collating genomics and wet laboratory data in a bidirectional manner. This is and will be critical to accelerate molecular target prioritization and drug discovery.

  19. Effect of interaction strength on robustness of controlling edge dynamics in complex networks

    Science.gov (United States)

    Pang, Shao-Peng; Hao, Fei

    2018-05-01

    Robustness plays a critical role in the controllability of complex networks to withstand failures and perturbations. Recent advances in the edge controllability show that the interaction strength among edges plays a more important role than network structure. Therefore, we focus on the effect of interaction strength on the robustness of edge controllability. Using three categories of all edges to quantify the robustness, we develop a universal framework to evaluate and analyze the robustness in complex networks with arbitrary structures and interaction strengths. Applying our framework to a large number of model and real-world networks, we find that the interaction strength is a dominant factor for the robustness in undirected networks. Meanwhile, the strongest robustness and the optimal edge controllability in undirected networks can be achieved simultaneously. Different from the case of undirected networks, the robustness in directed networks is determined jointly by the interaction strength and the network's degree distribution. Moreover, a stronger robustness is usually associated with a larger number of driver nodes required to maintain full control in directed networks. This prompts us to provide an optimization method by adjusting the interaction strength to optimize the robustness of edge controllability.

  20. Role of the Small GTPase Rho3 in Golgi/Endosome trafficking through functional interaction with adaptin in Fission Yeast.

    Directory of Open Access Journals (Sweden)

    Ayako Kita

    Full Text Available BACKGROUND: We had previously identified the mutant allele of apm1(+ that encodes a homolog of the mammalian µ1A subunit of the clathrin-associated adaptor protein-1 (AP-1 complex, and we demonstrated the role of Apm1 in Golgi/endosome trafficking, secretion, and vacuole fusion in fission yeast. METHODOLOGY/PRINCIPAL FINDINGS: In the present study, we isolated rho3(+, which encodes a Rho-family small GTPase, an important regulator of exocystosis, as a multicopy-suppressor of the temperature-sensitive growth of the apm1-1 mutant cells. Overexpression of Rho3 suppressed the Cl(- sensitivity and immunosuppressant sensitivity of the apm1-1 mutant cells. Overexpression of Rho3 also suppressed the fragmentation of vacuoles, and the accumulation of v-SNARE Syb1 in Golgi/endosomes and partially suppressed the defective secretion associated with apm1-deletion cells. Notably, electron microscopic observation of the rho3-deletion cells revealed the accumulation of abnormal Golgi-like structures, vacuole fragmentation, and accumulation of secretory vesicles; these phenotypes were very similar to those of the apm1-deletion cells. Furthermore, the rho3-deletion cells and apm1-deletion cells showed very similar phenotypic characteristics, including the sensitivity to the immunosuppressant FK506, the cell wall-damaging agent micafungin, Cl(-, and valproic acid. Green fluorescent protein (GFP-Rho3 was localized at Golgi/endosomes as well as the plasma membrane and division site. Finally, Rho3 was shown to form a complex with Apm1 as well as with other subunits of the clathrin-associated AP-1 complex in a GTP- and effector domain-dependent manner. CONCLUSIONS/SIGNIFICANCE: Taken together, our findings reveal a novel role of Rho3 in the regulation of Golgi/endosome trafficking and suggest that clathrin-associated adaptor protein-1 and Rho3 co-ordinate in intracellular transport in fission yeast. To the best of our knowledge, this study provides the first evidence

  1. Direct interaction of the Golgi V-ATPase a-subunit isoform with PI(4)P drives localization of Golgi V-ATPases in yeast.

    Science.gov (United States)

    Banerjee, Subhrajit; Kane, Patricia M

    2017-09-15

    Luminal pH and phosphoinositide content are fundamental features of organelle identity. Vacuolar H + -ATPases (V-ATPases) drive organelle acidification in all eukaryotes, and membrane-bound a-subunit isoforms of the V-ATPase are implicated in organelle-specific targeting and regulation. Earlier work demonstrated that the endolysosomal lipid PI(3,5)P 2 activates V-ATPases containing the vacuolar a-subunit isoform in Saccharomyces cerevisiae Here we demonstrate that PI(4)P, the predominant Golgi phosphatidylinositol (PI) species, directly interacts with the cytosolic amino terminal (NT) domain of the yeast Golgi V-ATPase a-isoform Stv1. Lysine-84 of Stv1NT is essential for interaction with PI(4)P in vitro and in vivo, and interaction with PI(4)P is required for efficient localization of Stv1-containing V-ATPases. The cytosolic NT domain of the human V-ATPase a2 isoform specifically interacts with PI(4)P in vitro, consistent with its Golgi localization and function. We propose that NT domains of V o a-subunit isoforms interact specifically with PI lipids in their organelles of residence. These interactions can transmit organelle-specific targeting or regulation information to V-ATPases. © 2017 Banerjee and Kane. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  2. Multi-domain CGFS-type glutaredoxin Grx4 regulates iron homeostasis via direct interaction with a repressor Fep1 in fission yeast

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kyoung-Dong; Kim, Hyo-Jin; Lee, Kyung-Chang [Laboratory of Molecular Microbiology, School of Biological Sciences and Institute of Microbiology, Seoul National University, Seoul 151-742 (Korea, Republic of); Roe, Jung-Hye, E-mail: jhroe@snu.ac.kr [Laboratory of Molecular Microbiology, School of Biological Sciences and Institute of Microbiology, Seoul National University, Seoul 151-742 (Korea, Republic of)

    2011-05-20

    Research highlights: {yields} Monothiol glutaredoxin Grx4 allows Fep1-mediated de-repression of iron uptake genes at low iron. {yields} Grx4 directly interacts with Fep1 in vivo and in vitro. {yields} The Cys172 in the CGFS motif of Grx4 is necessary for cell proliferation and iron regulation. {yields} The Cys172 of Grx4 is required for normal interaction with Fep1. -- Abstract: The fission yeast Schizosaccharomyces pombe contains two CGFS-type monothiol glutaredoxins, Grx4 and Grx5, which are localized primarily in the nucleus and mitochondria, respectively. We observed involvement of Grx4 in regulating iron-responsive gene expression, which is modulated by a repressor Fep1. Lack of Grx4 caused defects not only in growth but also in the expression of both iron-uptake and iron-utilizing genes regardless of iron availability. In order to unravel how Grx4 is involved in Fep1-mediated regulation, interaction between them was investigated. Co-immunoprecipitation and bimolecular fluorescence complementation (BiFC) revealed that Grx4 physically interacts with Fep1 in vivo. BiFC revealed localized nuclear dots produced by interaction of Grx4 with Fep1. Mutation of cysteine-172 in the CGFS motif to serine (C172S) produced effects similarly observed under Grx4 depletion, such as the loss of iron-dependent gene regulation and the absence of nuclear dots in BiFC analysis. These results suggest that the ability of Grx4 to bind iron, most likely Fe-S cofactor, could be critical in interacting with and modulating the activity of Fep1.

  3. The interaction between network ties and business modeling : Case studies of sustainability-oriented innovations

    NARCIS (Netherlands)

    Oskam, Inge; Bossink, Bart; de Man, Ard Pieter

    2018-01-01

    A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

  4. The Interaction between network ties and business modeling : case studies of sustainability-oriented innovations

    NARCIS (Netherlands)

    Oskam, Inge; Bossink, Bart; de Man, Ard-Pieter

    2018-01-01

    A stream of literature is emerging where network development and business modeling intersect. Various authors emphasize that networks influence business models. This paper extends this stream of literature by studying two cases in which we analyze how business modeling and networking interact over

  5. Structural Fine-Tuning of MIT-Interacting Motif 2 (MIM2) and Allosteric Regulation of ESCRT-III by Vps4 in Yeast.

    Science.gov (United States)

    Kojima, Rieko; Obita, Takayuki; Onoue, Kousuke; Mizuguchi, Mineyuki

    2016-06-05

    The endosomal sorting complex required for transport (ESCRT) facilitates roles in membrane remodeling, such as multivesicular body biogenesis, enveloped virus budding and cell division. In yeast, Vps4 plays a crucial role in intraluminal vesicle formation by disassembling ESCRT proteins. Vps4 is recruited by ESCRT-III proteins to the endosomal membrane through the interaction between the microtubule interacting and trafficking (MIT) domain of Vps4 and the C-terminal MIT-interacting motif (MIM) of ESCRT-III proteins. Here, we have determined the crystal structure of Vps4-MIT in a complex with Vps20, a member of ESCRT-III, and revealed that Vps20 adopts a unique MIM2 conformation. Based on structural comparisons with other known MIM2s, we have refined the consensus sequence of MIM2. We have shown that another ESCRT-III protein, Ist1, binds to Vps4-MIT via its C-terminal MIM1 with higher affinity than Vps2, but lacks MIM2 by surface plasmon resonance. Surprisingly, the Ist1 MIM1 competed with the MIM2 of Vfa1, a regulator of Vps4, for binding to Vps4-MIT, even though these MIMs bind in non-overlapping sites on the MIT. These findings provide insight into the allosteric recognition of MIMs of ESCRT-III by Vps4 and also the regulation of ESCRT machinery at the last step of membrane remodeling. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Strategic interactions in DRAM and RISC technology: A network approach

    NARCIS (Netherlands)

    Duysters, G.M.; Vanhaverbeke, W.P.M.

    1996-01-01

    Interorganizational cooperation in some high-tech industries is no longer confined to two-company alliances, but entails industry-wide alliance networks. This article examines how industry analysis and network analysis can be combined to provide a thorough understanding of how network positions, and

  7. Interaction in agent-based economics: A survey on the network approach

    Science.gov (United States)

    Bargigli, Leonardo; Tedeschi, Gabriele

    2014-04-01

    In this paper we aim to introduce the reader to some basic concepts and instruments used in a wide range of economic networks models. In particular, we adopt the theory of random networks as the main tool to describe the relationship between the organization of interaction among individuals within different components of the economy and overall aggregate behavior. The focus is on the ways in which economic agents interact and the possible consequences of their interaction on the system. We show that network models are able to introduce complex phenomena in economic systems by allowing for the endogenous evolution of networks.

  8. Analysis of protein-protein interaction networks by means of annotated graph mining algorithms

    NARCIS (Netherlands)

    Rahmani, Hossein

    2012-01-01

    This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large

  9. Impedance-Based Harmonic Instability Assessment in Multiple Electric Trains and Traction Network Interaction System

    DEFF Research Database (Denmark)

    Tao, Haidong; Hu, Haitao; Wang, Xiongfei

    2018-01-01

    This paper presents an impedance-based method to systematically investigate the interaction between multi-train and traction networks, focusing on evaluating the harmonic instability problems. Firstly, the interaction mechanism of multi-train and the traction network is represented as a feedback ...

  10. Non-criticality of interaction network over system's crises: A percolation analysis.

    Science.gov (United States)

    Shirazi, Amir Hossein; Saberi, Abbas Ali; Hosseiny, Ali; Amirzadeh, Ehsan; Toranj Simin, Pourya

    2017-11-20

    Extraction of interaction networks from multi-variate time-series is one of the topics of broad interest in complex systems. Although this method has a wide range of applications, most of the previous analyses have focused on the pairwise relations. Here we establish the potential of such a method to elicit aggregated behavior of the system by making a connection with the concepts from percolation theory. We study the dynamical interaction networks of a financial market extracted from the correlation network of indices, and build a weighted network. In correspondence with the percolation model, we find that away from financial crises the interaction network behaves like a critical random network of Erdős-Rényi, while close to a financial crisis, our model deviates from the critical random network and behaves differently at different size scales. We perform further analysis to clarify that our observation is not a simple consequence of the growth in correlations over the crises.

  11. Macrophage Interaction with Paracoccidioides brasiliensis Yeast Cells Modulates Fungal Metabolism and Generates a Response to Oxidative Stress.

    Directory of Open Access Journals (Sweden)

    Juliana Alves Parente-Rocha

    Full Text Available Macrophages are key players during Paracoccidioides brasiliensis infection. However, the relative contribution of the fungal response to counteracting macrophage activity remains poorly understood. In this work, we evaluated the P. brasiliensis proteomic response to macrophage internalization. A total of 308 differentially expressed proteins were detected in P. brasiliensis during infection. The positively regulated proteins included those involved in alternative carbon metabolism, such as enzymes involved in gluconeogenesis, beta-oxidation of fatty acids and amino acids catabolism. The down-regulated proteins during P. brasiliensis internalization in macrophages included those related to glycolysis and protein synthesis. Proteins involved in the oxidative stress response in P. brasiliensis yeast cells were also up-regulated during macrophage infection, including superoxide dismutases (SOD, thioredoxins (THX and cytochrome c peroxidase (CCP. Antisense knockdown mutants evaluated the importance of CCP during macrophage infection. The results suggested that CCP is involved in a complex system of protection against oxidative stress and that gene silencing of this component of the antioxidant system diminished the survival of P. brasiliensis in macrophages and in a murine model of infection.

  12. Interactions between neural networks: a mechanism for tuning chaos and oscillations.

    Science.gov (United States)

    Wang, Lipo

    2007-06-01

    We show that chaos and oscillations in a higher-order binary neural network can be tuned effectively using interactions between neural networks. Our results suggest that network interactions may be useful as a means of adjusting the level of dynamic activities in systems that employ chaos and oscillations for information processing, or as a means of suppressing oscillatory behaviors in systems that require stability.

  13. Interacting with Networks : How Does Structure Relate to Controllability in Single-Leader, Consensus Networks?

    NARCIS (Netherlands)

    Egerstedt, Magnus; Martini, Simone; Cao, Ming; Camlibel, Kanat; Bicchi, Antonio

    As networked dynamical systems appear around us at an increasing rate, questions concerning how to manage and control such systems are becoming more important. Examples include multiagent robotics, distributed sensor networks, interconnected manufacturing chains, and data networks. In response to

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

    Directory of Open Access Journals (Sweden)

    Ramanathan Murali

    2007-07-01

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

  15. Application of an artificial neural network in the enumeration of yeasts and bacteria adhering to solid substrata

    NARCIS (Netherlands)

    Wit, P; Busscher, HJ

    Artificial neural networks (ANNs) combined with automated image processing are bring used in a growing number of applications, ranging from car license plate identification to speech recognition. ANN analysis is capable of handling complicated images that cannot be dealt with using conventional

  16. Bowling alone but tweeting together: the evolution of human interaction in the social networking era

    OpenAIRE

    Antoci, Angelo; Sabatini, Fabio; Sodini, Mauro

    2011-01-01

    The objective of this paper is to theoretically analyze how human interaction may evolve in a world characterized by the explosion of online networking and other Web-mediated ways of building and nurturing relationships. The analysis shows that online networking yields a storage mechanism through which any individual contribution - e.g. a blog post, a comment, or a photo - is stored within a particular network and ready for virtual access by each member who connects to the network. When someo...

  17. Evidence that yeast SGS1, DNA2, SRS2, and FOB1 interact to maintain rDNA stability

    International Nuclear Information System (INIS)

    Tao Weitao; Budd, Martin; Campbell, Judith L.

    2003-01-01

    We and others have proposed that faulty processing of arrested replication forks leads to increases in recombination and chromosome instability in Saccharomyces cerevisiae. Now we use the ribosomal DNA locus, which is a good model for all stages of DNA replication, to test this hypothesis. We showed previously that DNA replication pausing at the ribosomal DNA replication fork barrier (RFB) is accompanied by the occurrence of double-strand breaks near the RFB. Both pausing and breakage are elevated in the hypomorphic dna2-2 helicase mutant. Deletion of FOB1 suppresses the elevated pausing and DSB formation. Our current work shows that mutation inactivating Sgs1, the yeast RecQ helicase ortholog, also causes accumulation of stalled replication forks and DSBs at the rDNA RFB. Either deletion of FOB1, which suppresses fork blocking and certain types of rDNA recombination, or an increase in SIR2 gene dosage, which suppresses rDNA recombination, reduces the number of forks persisting at the RFB. Although dna2-2 sgs1Δ double mutants are conditionally lethal, they do not show enhanced rDNA defects compared to sgs1Δ alone. However, surprisingly, the dna2-2 sgs1Δ lethality is suppressed by deletion of FOB1. On the other hand, the dna2-2 sgs1Δ lethality is only partially suppressed by deletion of rad51Δ. We propose that the replication-associated defects that we document in the rDNA are characteristic of similar events occurring either stochastically throughout the genome or at other regions where replication forks move slowly or stall, such as telomeres, centromeres, or replication slow zones

  18. Evidence that yeast SGS1, DNA2, SRS2, and FOB1 interact to maintain rDNA stability

    Energy Technology Data Exchange (ETDEWEB)

    Tao Weitao; Budd, Martin; Campbell, Judith L

    2003-11-27

    We and others have proposed that faulty processing of arrested replication forks leads to increases in recombination and chromosome instability in Saccharomyces cerevisiae. Now we use the ribosomal DNA locus, which is a good model for all stages of DNA replication, to test this hypothesis. We showed previously that DNA replication pausing at the ribosomal DNA replication fork barrier (RFB) is accompanied by the occurrence of double-strand breaks near the RFB. Both pausing and breakage are elevated in the hypomorphic dna2-2 helicase mutant. Deletion of FOB1 suppresses the elevated pausing and DSB formation. Our current work shows that mutation inactivating Sgs1, the yeast RecQ helicase ortholog, also causes accumulation of stalled replication forks and DSBs at the rDNA RFB. Either deletion of FOB1, which suppresses fork blocking and certain types of rDNA recombination, or an increase in SIR2 gene dosage, which suppresses rDNA recombination, reduces the number of forks persisting at the RFB. Although dna2-2 sgs1{delta} double mutants are conditionally lethal, they do not show enhanced rDNA defects compared to sgs1{delta} alone. However, surprisingly, the dna2-2 sgs1{delta} lethality is suppressed by deletion of FOB1. On the other hand, the dna2-2 sgs1{delta} lethality is only partially suppressed by deletion of rad51{delta}. We propose that the replication-associated defects that we document in the rDNA are characteristic of similar events occurring either stochastically throughout the genome or at other regions where replication forks move slowly or stall, such as telomeres, centromeres, or replication slow zones.

  19. The management of interaction networks. The ???in-between??? concept within social work and counseling

    OpenAIRE

    Hern??ndez-Aristu, Jes??s

    2015-01-01

    We are familiar with the field of group interaction through the traditional work of Kurt Lewin and also systemic thinking talks about network interaction that builds up the system. Martin Buber also discusses the ???in-between??? concept as the third element.The therapist or counselor, social worker and clients are part of an interaction network, representing therapeutic and social working situations. Success in treatment and reflective processes, depends on the perception and managemen...

  20. Hsp40 interacts directly with the native state of the yeast prion protein Ure2 and inhibits formation of amyloid-like fibrils.

    Science.gov (United States)

    Lian, Hui-Yong; Zhang, Hong; Zhang, Zai-Rong; Loovers, Harriët M; Jones, Gary W; Rowling, Pamela J E; Itzhaki, Laura S; Zhou, Jun-Mei; Perrett, Sarah

    2007-04-20

    Ure2 is the protein determinant of the [URE3] prion phenotype in Saccharomyces cerevisiae and consists of a flexible N-terminal prion-determining domain and a globular C-terminal glutathione transferase-like domain. Overexpression of the type I Hsp40 member Ydj1 in yeast cells has been found to result in the loss of [URE3]. However, the mechanism of prion curing by Ydj1 remains unclear. Here we tested the effect of overexpression of Hsp40 members Ydj1, Sis1, and Apj1 and also Hsp70 co-chaperones Cpr7, Cns1, Sti1, and Fes1 in vivo and found that only Ydj1 showed a strong curing effect on [URE3]. We also investigated the interaction of Ydj1 with Ure2 in vitro. We found that Ydj1 was able to suppress formation of amyloid-like fibrils of Ure2 by delaying the process of fibril formation, as monitored by thioflavin T binding and atomic force microscopy imaging. Controls using bovine serum albumin, Sis1, or the human Hsp40 homologues Hdj1 or Hdj2 showed no significant inhibitory effect. Ydj1 was only effective when added during the lag phase of fibril formation, suggesting that it interacts with Ure2 at an early stage in fibril formation and delays the nucleation process. Using surface plasmon resonance and size exclusion chromatography, we demonstrated a direct interaction between Ydj1 and both wild type and N-terminally truncated Ure2. In contrast, Hdj2, which did not suppress fibril formation, did not show this interaction. The results suggest that Ydj1 inhibits Ure2 fibril formation by binding to the native state of Ure2, thus delaying the onset of oligomerization.

  1. Dynamics of Moment Neuronal Networks with Intra- and Inter-Interactions

    Directory of Open Access Journals (Sweden)

    Xuyan Xiang

    2015-01-01

    Full Text Available A framework of moment neuronal networks with intra- and inter-interactions is presented. It is to show how the spontaneous activity is propagated across the homogeneous and heterogeneous network. The input-output firing relationship and the stability are first explored for a homogeneous network. For heterogeneous network without the constraint of the correlation coefficients between neurons, a more sophisticated dynamics is then explored. With random interactions, the network gets easily synchronized. However, desynchronization is produced by a lateral interaction such as Mexico hat function. It is the external intralayer input unit that offers a more sophisticated and unexpected dynamics over the predecessors. Hence, the work further opens up the possibility of carrying out a stochastic computation in neuronal networks.

  2. Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

    Directory of Open Access Journals (Sweden)

    Oyang Yen-Jen

    2010-10-01

    Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

  3. Deciphering microbial interactions and detecting keystone species with co-occurrence networks

    Directory of Open Access Journals (Sweden)

    David eBerry

    2014-05-01

    Full Text Available Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics, construct co-occurrence networks, and evaluate how well networks reveal the underlying interactions, and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

  4. Deciphering microbial interactions and detecting keystone species with co-occurrence networks.

    Science.gov (United States)

    Berry, David; Widder, Stefanie

    2014-01-01

    Co-occurrence networks produced from microbial survey sequencing data are frequently used to identify interactions between community members. While this approach has potential to reveal ecological processes, it has been insufficiently validated due to the technical limitations inherent in studying complex microbial ecosystems. Here, we simulate multi-species microbial communities with known interaction patterns using generalized Lotka-Volterra dynamics. We then construct co-occurrence networks and evaluate how well networks reveal the underlying interactions and how experimental and ecological parameters can affect network inference and interpretation. We find that co-occurrence networks can recapitulate interaction networks under certain conditions, but that they lose interpretability when the effects of habitat filtering become significant. We demonstrate that networks suffer from local hot spots of spurious correlation in the neighborhood of hub species that engage in many interactions. We also identify topological features associated with keystone species in co-occurrence networks. This study provides a substantiated framework to guide environmental microbiologists in the construction and interpretation of co-occurrence networks from microbial survey datasets.

  5. DyNet: visualization and analysis of dynamic molecular interaction networks.

    Science.gov (United States)

    Goenawan, Ivan H; Bryan, Kenneth; Lynn, David J

    2016-09-01

    : The ability to experimentally determine molecular interactions on an almost proteome-wide scale under different conditions is enabling researchers to move from static to dynamic network analysis, uncovering new insights into how interaction networks are physically rewired in response to different stimuli and in disease. Dynamic interaction data presents a special challenge in network biology. Here, we present DyNet, a Cytoscape application that provides a range of functionalities for the visualization, real-time synchronization and analysis of large multi-state dynamic molecular interaction networks enabling users to quickly identify and analyze the most 'rewired' nodes across many network states. DyNet is available at the Cytoscape (3.2+) App Store (http://apps.cytoscape.org/apps/dynet). david.lynn@sahmri.com Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  6. Transcriptional Waves in the Yeast Cell Cycle

    OpenAIRE

    Oliva, Anna; Rosebrock, Adam; Ferrezuelo, Francisco; Pyne, Saumyadipta; Chen, Haiying; Skiena, Steve; Futcher, Bruce; Leatherwood, Janet

    2005-01-01

    Many genes are regulated as an innate part of the eukaryotic cell cycle, and a complex transcriptional network helps enable the cyclic behavior of dividing cells. This transcriptional network has been studied in Saccharomyces cerevisiae (budding yeast) and elsewhere. To provide more perspective on these regulatory mechanisms, we have used microarrays to measure gene expression through the cell cycle of Schizosaccharomyces pombe (fission yeast). The 750 genes with the most significant oscillat...

  7. An evolvable oestrogen receptor activity sensor: development of a modular system for integrating multiple genes into the yeast genome

    NARCIS (Netherlands)

    Fox, J.E.; Bridgham, J.T.; Bovee, T.F.H.; Thornton, J.W.

    2007-01-01

    To study a gene interaction network, we developed a gene-targeting strategy that allows efficient and stable genomic integration of multiple genetic constructs at distinct target loci in the yeast genome. This gene-targeting strategy uses a modular plasmid with a recyclable selectable marker and a

  8. A global genetic interaction network maps a wiring diagram of cellular function.

    Science.gov (United States)

    Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D; Pelechano, Vicent; Styles, Erin B; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F; Li, Sheena C; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; San Luis, Bryan-Joseph; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M; Moore, Claire L; Rosebrock, Adam P; Caudy, Amy A; Myers, Chad L; Andrews, Brenda; Boone, Charles

    2016-09-23

    We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. Copyright © 2016, American Association for the Advancement of Science.

  9. A global interaction network maps a wiring diagram of cellular function

    Science.gov (United States)

    Costanzo, Michael; VanderSluis, Benjamin; Koch, Elizabeth N.; Baryshnikova, Anastasia; Pons, Carles; Tan, Guihong; Wang, Wen; Usaj, Matej; Hanchard, Julia; Lee, Susan D.; Pelechano, Vicent; Styles, Erin B.; Billmann, Maximilian; van Leeuwen, Jolanda; van Dyk, Nydia; Lin, Zhen-Yuan; Kuzmin, Elena; Nelson, Justin; Piotrowski, Jeff S.; Srikumar, Tharan; Bahr, Sondra; Chen, Yiqun; Deshpande, Raamesh; Kurat, Christoph F.; Li, Sheena C.; Li, Zhijian; Usaj, Mojca Mattiazzi; Okada, Hiroki; Pascoe, Natasha; Luis, Bryan-Joseph San; Sharifpoor, Sara; Shuteriqi, Emira; Simpkins, Scott W.; Snider, Jamie; Suresh, Harsha Garadi; Tan, Yizhao; Zhu, Hongwei; Malod-Dognin, Noel; Janjic, Vuk; Przulj, Natasa; Troyanskaya, Olga G.; Stagljar, Igor; Xia, Tian; Ohya, Yoshikazu; Gingras, Anne-Claude; Raught, Brian; Boutros, Michael; Steinmetz, Lars M.; Moore, Claire L.; Rosebrock, Adam P.; Caudy, Amy A.; Myers, Chad L.; Andrews, Brenda; Boone, Charles

    2017-01-01

    We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing over 23 million double mutants, identifying ~550,000 negative and ~350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell. PMID:27708008

  10. Self-organized criticality in a network of interacting neurons

    NARCIS (Netherlands)

    Cowan, J.D.; Neuman, J.; Kiewiet, B.; van Drongelen, W.

    2013-01-01

    This paper contains an analysis of a simple neural network that exhibits self-organized criticality. Such criticality follows from the combination of a simple neural network with an excitatory feedback loop that generates bistability, in combination with an anti-Hebbian synapse in its input pathway.

  11. Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

    Science.gov (United States)

    Ammenwerth, Elske; Hackl, Werner O

    2017-01-01

    Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

  12. Limitation of degree information for analyzing the interaction evolution in online social networks

    Science.gov (United States)

    Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

    2014-04-01

    Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

  13. Networking for proteins : A yeast two-hybrid and RNAi profiling approach to uncover C. elegans cell polarity regulators

    NARCIS (Netherlands)

    Koorman, T.|info:eu-repo/dai/nl/337456038

    2016-01-01

    Cell polarity is a near universal trait of life and guides many aspects of animal development. Although a number of key polarity proteins have been identified, many interactions with proteins acting downstream likely remain to be elucidated. Mutations in polarity proteins or deregulation of polarity

  14. Assessing Group Interaction with Social Language Network Analysis

    Science.gov (United States)

    Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  15. Unravelling Darwin's entangled bank: architecture and robustness of mutualistic networks with multiple interaction types.

    Science.gov (United States)

    Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor

    2016-11-30

    Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).

  16. Detection of protein complex from protein-protein interaction network using Markov clustering

    International Nuclear Information System (INIS)

    Ochieng, P J; Kusuma, W A; Haryanto, T

    2017-01-01

    Detection of complexes, or groups of functionally related proteins, is an important challenge while analysing biological networks. However, existing algorithms to identify protein complexes are insufficient when applied to dense networks of experimentally derived interaction data. Therefore, we introduced a graph clustering method based on Markov clustering algorithm to identify protein complex within highly interconnected protein-protein interaction networks. Protein-protein interaction network was first constructed to develop geometrical network, the network was then partitioned using Markov clustering to detect protein complexes. The interest of the proposed method was illustrated by its application to Human Proteins associated to type II diabetes mellitus. Flow simulation of MCL algorithm was initially performed and topological properties of the resultant network were analysed for detection of the protein complex. The results indicated the proposed method successfully detect an overall of 34 complexes with 11 complexes consisting of overlapping modules and 20 non-overlapping modules. The major complex consisted of 102 proteins and 521 interactions with cluster modularity and density of 0.745 and 0.101 respectively. The comparison analysis revealed MCL out perform AP, MCODE and SCPS algorithms with high clustering coefficient (0.751) network density and modularity index (0.630). This demonstrated MCL was the most reliable and efficient graph clustering algorithm for detection of protein complexes from PPI networks. (paper)

  17. An attempt to understand glioma stem cell biology through centrality analysis of a protein interaction network.

    Science.gov (United States)

    Mallik, Mrinmay Kumar

    2018-02-07

    Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that

  18. Method for designing networking adaptive interactive hybrid systems

    NARCIS (Netherlands)

    Kester, L. J.H.M.

    2010-01-01

    Advances in network technologies enable distributed systems, operating in complex physical environments, to co-ordinate their activities over larger areas within shorter time intervals. Some envisioned application domains for such systems are defence, crisis management, traffic management and public

  19. Creating networking adaptive interactive hybrid systems : A methodic approach

    NARCIS (Netherlands)

    Kester, L.J.

    2011-01-01

    Advances in network technologies enable distributed systems, operating in complex physical environments, to coordinate their activities over larger areas within shorter time intervals. Some envisioned application domains for such systems are defense, crisis management, traffic management, public

  20. KNOWNET: Exploring Interactive Knowledge Networking across Insurance Supply Chains

    OpenAIRE

    Grant, Susan

    2014-01-01

    [EN] Social media has become an extremely powerful phenomenon with millions of users who post status updates, blog, links and pictures on social networking sites such as Facebook, LinkedIn, and Twitter. However, social networking has so far spread mainly among consumers. Businesses are only now beginning to acknowledge the benefits of using social media to enhance employee and supplier collaboration to support new ideas and innovation through knowledge sharing across functions and organizatio...

  1. Organization of Multi-controller Interaction in Software Defined Networks

    Directory of Open Access Journals (Sweden)

    Sergey V. Morzhov

    2018-01-01

    Full Text Available Software Defined Networking (SDN is a promising paradigm for network management. It is a centralized network intelligence on a dedicated server, which runs network operating system, and is called SDN controller. It was assumed that such an architecture should have an improved network performance and monitoring. However, the centralized control architecture of the SDNs brings novel challenges to reliability, scalability, fault tolerance and interoperability. These problems are especially acute for large data center networks and can be solved by combining SDN controllers into clusters, called multi-controllers. Multi-controller architecture became very important for SDN-enabled networks nowadays. This paper gives a comprehensive overview of SDN multi-controller architectures. The authors review several most popular distributed controllers in order to indicate their strengths and weaknesses. They also investigate and classify approaches used. This paper explains in details the difference among various types of multi-controller architectures, the distribution method and the communication system. Furthermore, it provides already implemented architectures and some examples of architectures under consideration by describing their design, communication process, and performance results. In this paper, the authors show their own classification of multi-controllers and claim that, despite the existence of undeniable advantages, all reviewed controllers have serious drawbacks, which must be eliminated. These drawbacks hamper the development of multi-controllers and their widespread adoption in corporate networks. In the end, the authors conclude that now it is impossible to find a solution capable to solve all the tasks assigned to it adequately and fully. The article is published in the authors’ wording.

  2. Exploring drug-target interaction networks of illicit drugs

    OpenAIRE

    Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming

    2013-01-01

    Background Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit dru...

  3. Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

    Directory of Open Access Journals (Sweden)

    Boucher Charles AB

    2010-07-01

    Full Text Available Abstract Background The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics. Results Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems. Conclusions HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another.

  4. Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; He, Yongqun

    2017-03-14

    Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

  5. Structural Modeling and Characteristics Analysis of Flow Interaction Networks in the Internet

    International Nuclear Information System (INIS)

    Wu Xiao-Yu; Gu Ren-Tao; Pan Zhuo-Ya; Jin Wei-Qi; Ji Yue-Feng

    2015-01-01

    Applying network duality and elastic mechanics, we investigate the interactions among Internet flows by constructing a weighted undirected network, where the vertices and the edges represent the flows and the mutual dependence between flows, respectively. Based on the obtained flow interaction network, we find the existence of ‘super flow’ in the Internet, indicating that some flows have a great impact on a huge number of other flows; moreover, one flow can spread its influence to another through a limited quantity of flows (less than 5 in the experimental simulations), which shows strong small-world characteristics like the social network. To reflect the flow interactions in the physical network congestion evaluation, the ‘congestion coefficient’ is proposed as a new metric which shows a finer observation on congestion than the conventional one. (paper)

  6. Interaction between Red Yeast Rice and CYP450 Enzymes/P-Glycoprotein and Its Implication for the Clinical Pharmacokinetics of Lovastatin

    Directory of Open Access Journals (Sweden)

    Chia-Hao Chen

    2012-01-01

    Full Text Available Red yeast rice (RYR can reduce cholesterol through its active component, lovastatin. This study was to investigate the pharmacokinetic properties of lovastatin in RYR products and potential RYR-drug interactions. Extracts of three registered RYR products (LipoCol Forte, Cholestin, and Xuezhikang were more effective than pure lovastatin in inhibiting the activities of cytochrome P450 enzymes and P-glycoprotein. Among CYP450 enzymes, RYR showed the highest inhibition on CYP1A2 and CYP2C19, with comparable inhibitory potencies to the corresponding typical inhibitors. In healthy volunteers taking the RYR product LipoCol Forte, the pharmacokinetic properties of lovastatin and lovastatin acid were linear in the dose range of 1 to 4 capsules taken as a single dose and no significant accumulation was observed after multiple dosing. Concomitant use of one LipoCol Forte capsule with nifedipine did not change the pharmacokinetics of nifedipine. Yet, concomitant use of gemfibrozil with LipoCol Forte resulted in a significant increase in the plasma concentration of lovastatin acid. These findings suggest that the use of RYR products may not have effects on the pharmacokinetics of concomitant comedications despite their effects to inhibit the activities of CYP450 enzymes and P-gp, whereas gemfibrozil affects the pharmacokinetics of lovastatin acid when used concomitantly with RYR products.

  7. Reconstructing consensus Bayesian network structures with application to learning molecular interaction networks

    NARCIS (Netherlands)

    Fröhlich, H.; Klau, G.W.

    2013-01-01

    Bayesian Networks are an established computational approach for data driven network inference. However, experimental data is limited in its availability and corrupted by noise. This leads to an unavoidable uncertainty about the correct network structure. Thus sampling or bootstrap based strategies

  8. Changes in the interaction of resting-state neural networks from adolescence to adulthood.

    Science.gov (United States)

    Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

    2009-08-01

    This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

  9. NASCENT: an automatic protein interaction network generation tool for non-model organisms.

    Science.gov (United States)

    Banky, Daniel; Ordog, Rafael; Grolmusz, Vince

    2009-04-24

    Large quantity of reliable protein interaction data are available for model organisms in public depositories (e.g., MINT, DIP, HPRD, INTERACT). Most data correspond to experiments with the proteins of Saccharomyces cerevisiae, Drosophila melanogaster, Homo sapiens, Caenorhabditis elegans, Escherichia coli and Mus musculus. For other important organisms the data availability is poor or non-existent. Here we present NASCENT, a completely automatic web-based tool and also a downloadable Java program, capable of modeling and generating protein interaction networks even for non-model organisms. The tool performs protein interaction network modeling through gene-name mapping, and outputs the resulting network in graphical form and also in computer-readable graph-forms, directly applicable by popular network modeling software. http://nascent.pitgroup.org.

  10. Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

    KAUST Repository

    Cannistraci, Carlo; Alanis Lobato, Gregorio; Ravasi, Timothy

    2013-01-01

    Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness

  11. ANSIBLE: A Network of Social Interactions for Bilateral Life Enhancement, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ANSIBLE (A Network of Social Interactions for Bilateral Life Enhancement) can be used pre, during, and post flight to connect the flight crew with their family,...

  12. On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions.

    Science.gov (United States)

    Schmitt, Michael

    2004-09-01

    We study networks of spiking neurons that use the timing of pulses to encode information. Nonlinear interactions model the spatial groupings of synapses on the neural dendrites and describe the computations performed at local branches. Within a theoretical framework of learning we analyze the question of how many training examples these networks must receive to be able to generalize well. Bounds for this sample complexity of learning can be obtained in terms of a combinatorial parameter known as the pseudodimension. This dimension characterizes the computational richness of a neural network and is given in terms of the number of network parameters. Two types of feedforward architectures are considered: constant-depth networks and networks of unconstrained depth. We derive asymptotically tight bounds for each of these network types. Constant depth networks are shown to have an almost linear pseudodimension, whereas the pseudodimension of general networks is quadratic. Networks of spiking neurons that use temporal coding are becoming increasingly more important in practical tasks such as computer vision, speech recognition, and motor control. The question of how well these networks generalize from a given set of training examples is a central issue for their successful application as adaptive systems. The results show that, although coding and computation in these networks is quite different and in many cases more powerful, their generalization capabilities are at least as good as those of traditional neural network models.

  13. Network graph analysis of gene-gene interactions in genome-wide association study data.

    Science.gov (United States)

    Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

    2012-12-01

    Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

  14. The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

    Science.gov (United States)

    Özgür, Arzucan; Hur, Junguk; He, Yongqun

    2016-01-01

    The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A

  15. Interaction of chimera states in a multilayered network of nonlocally coupled oscillators

    Science.gov (United States)

    Goremyko, M. V.; Maksimenko, V. A.; Makarov, V. V.; Ghosh, D.; Bera, B.; Dana, S. K.; Hramov, A. E.

    2017-08-01

    The processes of formation and evolution of chimera states in the model of a multilayered network of nonlinear elements with complex coupling topology are studied. A two-layered network of nonlocally intralayer-coupled Kuramoto-Sakaguchi phase oscillators is taken as the object of investigation. Different modes implemented in this system upon variation of the degree of interlayer interaction are demonstrated.

  16. Study of Personalized Network Tutoring System Based on Emotional-cognitive Interaction

    Science.gov (United States)

    Qi, Manfei; Ma, Ding; Wang, Wansen

    Aiming at emotion deficiency in present Network tutoring system, a lot of negative effects is analyzed and corresponding countermeasures are proposed. The model of Personalized Network tutoring system based on Emotional-cognitive interaction is constructed in the paper. The key techniques of realizing the system such as constructing emotional model and adjusting teaching strategies are also introduced.

  17. The Social Fabric of Elementary Schools: A Network Typology of Social Interaction among Teachers

    Science.gov (United States)

    Moolenaar, Nienke M.; Sleegers, Peter J. C.; Karsten, Sjoerd; Daly, Alan J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality that may underlie various types of social networks…

  18. The social fabric of elementary schools: a network typology of social interaction among teachers

    NARCIS (Netherlands)

    Moolenaar, N.M.; Sleegers, P.J.C.; Karsten, S.; Daly, A.J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality

  19. The Effect of Social Interaction on Learning Engagement in a Social Networking Environment

    Science.gov (United States)

    Lu, Jie; Churchill, Daniel

    2014-01-01

    This study investigated the impact of social interactions among a class of undergraduate students on their learning engagement in a social networking environment. Thirteen undergraduate students enrolled in a course in a university in Hong Kong used an Elgg-based social networking platform throughout a semester to develop their digital portfolios…

  20. The social fabric of elementary schools: A network typology of social interaction among teachers

    NARCIS (Netherlands)

    Moolenaar, Nienke; Sleegers, P.J.C.; Karsten, Sjoerd; Daly, Alan J.; Daly, A.J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality

  1. Flower-Visiting Social Wasps and Plants Interaction: Network Pattern and Environmental Complexity

    Directory of Open Access Journals (Sweden)

    Mateus Aparecido Clemente

    2012-01-01

    Full Text Available Network analysis as a tool for ecological interactions studies has been widely used since last decade. However, there are few studies on the factors that shape network patterns in communities. In this sense, we compared the topological properties of the interaction network between flower-visiting social wasps and plants in two distinct phytophysiognomies in a Brazilian savanna (Riparian Forest and Rocky Grassland. Results showed that the landscapes differed in species richness and composition, and also the interaction networks between wasps and plants had different patterns. The network was more complex in the Riparian Forest, with a larger number of species and individuals and a greater amount of connections between them. The network specialization degree was more generalist in the Riparian Forest than in the Rocky Grassland. This result was corroborated by means of the nestedness index. In both networks was found asymmetry, with a large number of wasps per plant species. In general aspects, most wasps had low niche amplitude, visiting from one to three plant species. Our results suggest that differences in structural complexity of the environment directly influence the structure of the interaction network between flower-visiting social wasps and plants.

  2. Financial Stability and Interacting Networks of Financial Institutions and Market Infrastructures

    NARCIS (Netherlands)

    Léon, C.; Berndsen, R.J.; Renneboog, L.D.R.

    2014-01-01

    An interacting network coupling financial institutions’ multiplex (i.e. multi-layer) and financial market infrastructures’ single-layer networks gives an accurate picture of a financial system’s true connective architecture. We examine and compare the main properties of Colombian multiplex and

  3. Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

    Science.gov (United States)

    Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

  4. Predicting drug?drug interactions through drug structural similarities and interaction networks incorporating pharmacokinetics and pharmacodynamics knowledge

    OpenAIRE

    Takeda, Takako; Hao, Ming; Cheng, Tiejun; Bryant, Stephen H.; Wang, Yanli

    2017-01-01

    Drug?drug interactions (DDIs) may lead to adverse effects and potentially result in drug withdrawal from the market. Predicting DDIs during drug development would help reduce development costs and time by rigorous evaluation of drug candidates. The primary mechanisms of DDIs are based on pharmacokinetics (PK) and pharmacodynamics (PD). This study examines the effects of 2D structural similarities of drugs on DDI prediction through interaction networks including both PD and PK knowledge. Our a...

  5. Linking plant specialization to dependence in interactions for seed set in pollination networks.

    Science.gov (United States)

    Tur, Cristina; Castro-Urgal, Rocío; Traveset, Anna

    2013-01-01

    Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled) can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them). Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i) linkage level (number of interactions), (ii) diversity of interactions, and (iii) closeness centrality (a measure of how much a species is connected to other plants via shared pollinators). Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent.

  6. Linking plant specialization to dependence in interactions for seed set in pollination networks.

    Directory of Open Access Journals (Sweden)

    Cristina Tur

    Full Text Available Studies on pollination networks have provided valuable information on the number, frequency, distribution and identity of interactions between plants and pollinators. However, little is still known on the functional effect of these interactions on plant reproductive success. Information on the extent to which plants depend on such interactions will help to make more realistic predictions of the potential impacts of disturbances on plant-pollinator networks. Plant functional dependence on pollinators (all interactions pooled can be estimated by comparing seed set with and without pollinators (i.e. bagging flowers to exclude them. Our main goal in this study was thus to determine whether plant dependence on current insect interactions is related to plant specialization in a pollination network. We studied two networks from different communities, one in a coastal dune and one in a mountain. For ca. 30% of plant species in each community, we obtained the following specialization measures: (i linkage level (number of interactions, (ii diversity of interactions, and (iii closeness centrality (a measure of how much a species is connected to other plants via shared pollinators. Phylogenetically controlled regression analyses revealed that, for the largest and most diverse coastal community, plants highly dependent on pollinators were the most generalists showing the highest number and diversity of interactions as well as occupying central positions in the network. The mountain community, by contrast, did not show such functional relationship, what might be attributable to their lower flower-resource heterogeneity and diversity of interactions. We conclude that plants with a wide array of pollinator interactions tend to be those that are more strongly dependent upon them for seed production and thus might be those more functionally vulnerable to the loss of network interaction, although these outcomes might be context-dependent.

  7. Network Analysis Reveals a Common Host–Pathogen Interaction Pattern in Arabidopsis Immune Responses

    Directory of Open Access Journals (Sweden)

    Hong Li

    2017-05-01

    Full Text Available Many plant pathogens secrete virulence effectors into host cells to target important proteins in host cellular network. However, the dynamic interactions between effectors and host cellular network have not been fully understood. Here, an integrative network analysis was conducted by combining Arabidopsis thaliana protein–protein interaction network, known targets of Pseudomonas syringae and Hyaloperonospora arabidopsidis effectors, and gene expression profiles in the immune response. In particular, we focused on the characteristic network topology of the effector targets and differentially expressed genes (DEGs. We found that effectors tended to manipulate key network positions with higher betweenness centrality. The effector targets, especially those that are common targets of an individual effector, tended to be clustered together in the network. Moreover, the distances between the effector targets and DEGs increased over time during infection. In line with this observation, pathogen-susceptible mutants tended to have more DEGs surrounding the effector targets compared with resistant mutants. Our results suggest a common plant–pathogen interaction pattern at the cellular network level, where pathogens employ potent local impact mode to interfere with key positions in the host network, and plant organizes an in-depth defense by sequentially activating genes distal to the effector targets.

  8. Inferring gene and protein interactions using PubMed citations and consensus Bayesian networks.

    Science.gov (United States)

    Deeter, Anthony; Dalman, Mark; Haddad, Joseph; Duan, Zhong-Hui

    2017-01-01

    The PubMed database offers an extensive set of publication data that can be useful, yet inherently complex to use without automated computational techniques. Data repositories such as the Genomic Data Commons (GDC) and the Gene Expression Omnibus (GEO) offer experimental data storage and retrieval as well as curated gene expression profiles. Genetic interaction databases, including Reactome and Ingenuity Pathway Analysis, offer pathway and experiment data analysis using data curated from these publications and data repositories. We have created a method to generate and analyze consensus networks, inferring potential gene interactions, using large numbers of Bayesian networks generated by data mining publications in the PubMed database. Through the concept of network resolution, these consensus networks can be tailored to represent possible genetic interactions. We designed a set of experiments to confirm that our method is stable across variation in both sample and topological input sizes. Using gene product interactions from the KEGG pathway database and data mining PubMed publication abstracts, we verify that regardless of the network resolution or the inferred consensus network, our method is capable of inferring meaningful gene interactions through consensus Bayesian network generation with multiple, randomized topological orderings. Our method can not only confirm the existence of currently accepted interactions, but has the potential to hypothesize new ones as well. We show our method confirms the existence of known gene interactions such as JAK-STAT-PI3K-AKT-mTOR, infers novel gene interactions such as RAS- Bcl-2 and RAS-AKT, and found significant pathway-pathway interactions between the JAK-STAT signaling and Cardiac Muscle Contraction KEGG pathways.

  9. The IRIS network of excellence : Integrating research in interactive storytelling

    NARCIS (Netherlands)

    Cavazza, Marc; Donikian, Stéphane; Christie, Marc; Spierling, Ulrike; Szilas, Nicolas; Vorderer, Peter; Hartmann, Tilo; Klimmt, Christoph; André, Elisabeth; Champagnat, Ronan; Petta, Paolo; Olivier, Patrick

    2008-01-01

    Interactive Storytelling is a major endeavour to develop new media which could offer a radically new user experience, with a potential to revolutionise digital entertainment. European research in Interactive Storytelling has played a leading role in the development of the field, and this creates a

  10. RAIN: RNA-protein Association and Interaction Networks

    DEFF Research Database (Denmark)

    Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian

    2017-01-01

    is challenging due to data heterogeneity. Here, we present a database of ncRNA-RNA and ncRNA-protein interactions and its integration with the STRING database of protein-protein interactions. These ncRNA associations cover four organisms and have been established from curated examples, experimental data...

  11. Estimating the Local Size and Coverage of Interaction Network Regions

    Science.gov (United States)

    Eagle, Michael; Barnes, Tiffany

    2015-01-01

    Interactive problem solving environments, such as intelligent tutoring systems and educational video games, produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled the student-tutor interactions using complex network…

  12. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh

    2012-04-06

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  13. Context-specific protein network miner - an online system for exploring context-specific protein interaction networks from the literature

    KAUST Repository

    Chowdhary, Rajesh; Tan, Sin Lam; Zhang, Jinfeng; Karnik, Shreyas; Bajic, Vladimir B.; Liu, Jun S.

    2012-01-01

    Background: Protein interaction networks (PINs) specific within a particular context contain crucial information regarding many cellular biological processes. For example, PINs may include information on the type and directionality of interaction (e.g. phosphorylation), location of interaction (i.e. tissues, cells), and related diseases. Currently, very few tools are capable of deriving context-specific PINs for conducting exploratory analysis. Results: We developed a literature-based online system, Context-specific Protein Network Miner (CPNM), which derives context-specific PINs in real-time from the PubMed database based on a set of user-input keywords and enhanced PubMed query system. CPNM reports enriched information on protein interactions (with type and directionality), their network topology with summary statistics (e.g. most densely connected proteins in the network; most densely connected protein-pairs; and proteins connected by most inbound/outbound links) that can be explored via a user-friendly interface. Some of the novel features of the CPNM system include PIN generation, ontology-based PubMed query enhancement, real-time, user-queried, up-to-date PubMed document processing, and prediction of PIN directionality. Conclusions: CPNM provides a tool for biologists to explore PINs. It is freely accessible at http://www.biotextminer.com/CPNM/. © 2012 Chowdhary et al.

  14. Expression Patterns and Identified Protein-Protein Interactions Suggest That Cassava CBL-CIPK Signal Networks Function in Responses to Abiotic Stresses

    Directory of Open Access Journals (Sweden)

    Chunyan Mo

    2018-03-01

    Full Text Available Cassava is an energy crop that is tolerant of multiple abiotic stresses. It has been reported that the interaction between Calcineurin B-like (CBL protein and CBL-interacting protein kinase (CIPK is implicated in plant development and responses to various stresses. However, little is known about their functions in cassava. Herein, 8 CBL (MeCBL and 26 CIPK (MeCIPK genes were isolated from cassava by genome searching and cloning of cDNA sequences of Arabidopsis CBLs and CIPKs. Reverse-transcriptase polymerase chain reaction (RT-PCR analysis showed that the expression levels of MeCBL and MeCIPK genes were different in different tissues throughout the life cycle. The expression patterns of 7 CBL and 26 CIPK genes in response to NaCl, PEG, heat and cold stresses were analyzed by quantitative real-time PCR (qRT-PCR, and it was found that the expression of each was induced by multiple stimuli. Furthermore, we found that many pairs of CBLs and CIPKs could interact with each other via investigating the interactions between 8 CBL and 25 CIPK proteins using a yeast two-hybrid system. Yeast cells co-transformed with cassava MeCIPK24, MeCBL10, and Na+/H+ antiporter MeSOS1 genes exhibited higher salt tolerance compared to those with one or two genes. These results suggest that the cassava CBL-CIPK signal network might play key roles in response to abiotic stresses.

  15. Dynamic interactions of the cortical networks during thought suppression.

    Science.gov (United States)

    Aso, Toshihiko; Nishimura, Kazuo; Kiyonaka, Takashi; Aoki, Takaaki; Inagawa, Michiyo; Matsuhashi, Masao; Tobinaga, Yoshikazu; Fukuyama, Hidenao

    2016-08-01

    Thought suppression has spurred extensive research in clinical and preclinical fields, particularly with regard to the paradoxical aspects of this behavior. However, the involvement of the brain's inhibitory system in the dynamics underlying the continuous effort to suppress thoughts has yet to be clarified. This study aims to provide a unified perspective for the volitional suppression of internal events incorporating the current understanding of the brain's inhibitory system. Twenty healthy volunteers underwent functional magnetic resonance imaging while they performed thought suppression blocks alternating with visual imagery blocks. The whole dataset was decomposed by group-independent component analysis into 30 components. After discarding noise components, the 20 valid components were subjected to further analysis of their temporal properties including task-relatedness and between-component residual correlation. Combining a long task period and a data-driven approach, we observed a right-side-dominant, lateral frontoparietal network to be strongly suppression related. This network exhibited increased fluctuation during suppression, which is compatible with the well-known difficulty of suppression maintenance. Between-network correlation provided further insight into the coordinated engagement of the executive control and dorsal attention networks, as well as the reciprocal activation of imagery-related components, thus revealing neural substrates associated with the rivalry between intrusive thoughts and the suppression process.

  16. Effects of residential move on interaction frequency with social network

    NARCIS (Netherlands)

    Sharmeen, F.; Timmermans, H.J.P.; Sze, N.N.; Szeto, W.Y.; Wong, S.C.

    2011-01-01

    Size and composition of social networks have recently been identified in the transportation literature as important triggers of travel demand in general and travel generation in particular. With the field of activity-based modeling of travel demand moving from static to dynamic models, this implies

  17. Frameworks for Understanding the Nature of Interactions, Networking, and Community in a Social Networking Site for Academic Practice

    Directory of Open Access Journals (Sweden)

    Grainne Conole

    2011-03-01

    Full Text Available This paper describes a new social networking site, Cloudworks, which has been developed to enable discussion and sharing of learning and teaching ideas/designs and to promote reflective academic practice. The site aims to foster new forms of social and participatory practices (peer critiquing, sharing, user-generated content, aggregation, and personalisation within an educational context. One of the key challenges in the development of the site has been to understand the user interactions and the changing patterns of user behaviour as it evolves. The paper explores the extent to which four frameworks that have been used in researching networked learning contexts can provide insights into the patterns of user behaviour that we see in Cloudworks. The paper considers this within the current debate about the new types of interactions, networking, and community being observed as users adapt to and appropriate new technologies.

  18. An integrated approach to elucidate the intra-viral and viral-cellular protein interaction networks of a gamma-herpesvirus.

    Directory of Open Access Journals (Sweden)

    Shaoying Lee

    2011-10-01

    Full Text Available Genome-wide yeast two-hybrid (Y2H screens were conducted to elucidate the molecular functions of open reading frames (ORFs encoded by murine γ-herpesvirus 68 (MHV-68. A library of 84 MHV-68 genes and gene fragments was generated in a Gateway entry plasmid and transferred to Y2H vectors. All possible pair-wise interactions between viral proteins were tested in the Y2H assay, resulting in the identification of 23 intra-viral protein-protein interactions (PPIs. Seventy percent of the interactions between viral proteins were confirmed by co-immunoprecipitation experiments. To systematically investigate virus-cellular protein interactions, the MHV-68 Y2H constructs were screened against a cellular cDNA library, yielding 243 viral-cellular PPIs involving 197 distinct cellar proteins. Network analyses indicated that cellular proteins targeted by MHV-68 had more partners in the cellular PPI network and were located closer to each other than expected by chance. Taking advantage of this observation, we scored the cellular proteins based on their network distances from other MHV-68-interacting proteins and segregated them into high (Y2H-HP and low priority/not-scored (Y2H-LP/NS groups. Significantly more genes from Y2H-HP altered MHV-68 replication when their expression was inhibited with siRNAs (53% of genes from Y2H-HP, 21% of genes from Y2H-LP/NS, and 16% of genes randomly chosen from the human PPI network; p<0.05. Enriched Gene Ontology (GO terms in the Y2H-HP group included regulation of apoptosis, protein kinase cascade, post-translational protein modification, transcription from RNA polymerase II promoter, and IκB kinase/NFκB cascade. Functional validation assays indicated that PCBP1, which interacted with MHV-68 ORF34, may be involved in regulating late virus gene expression in a manner consistent with the effects of its viral interacting partner. Our study integrated Y2H screening with multiple functional validation approaches to create

  19. Prions in yeast

    OpenAIRE

    Bezdíčka, Martin

    2013-01-01

    The thesis describes yeast prions and their biological effects on yeast in general. It defines the basic characteristics of yeast prions, that distinguish prions from other proteins. The thesis introduces various possibilities of prion formation, and propagation as well as specific types of yeast prions, including various functions of most studied types of prions. The thesis also focuses on chaperones that affect the state of yeast prions in cells. Lastly, the thesis indicates similarities be...

  20. LETTER TO THE EDITOR: Dynamics of interacting neural networks

    Science.gov (United States)

    Kinzel, W.; Metzler, R.; Kanter, I.

    2000-04-01

    The dynamics of interacting perceptrons is solved analytically. For a directed flow of information the system runs into a state which has a higher symmetry than the topology of the model. A symmetry-breaking phase transition is found with increasing learning rate. In addition, it is shown that a system of interacting perceptrons which is trained on the history of its minority decisions develops a good strategy for the problem of adaptive competition known as the bar problem or minority game.

  1. An analysis pipeline for the inference of protein-protein interaction networks

    Energy Technology Data Exchange (ETDEWEB)

    Taylor, Ronald C.; Singhal, Mudita; Daly, Don S.; Gilmore, Jason M.; Cannon, William R.; Domico, Kelly O.; White, Amanda M.; Auberry, Deanna L.; Auberry, Kenneth J.; Hooker, Brian S.; Hurst, G. B.; McDermott, Jason E.; McDonald, W. H.; Pelletier, Dale A.; Schmoyer, Denise A.; Wiley, H. S.

    2009-12-01

    An analysis pipeline has been created for deployment of a novel algorithm, the Bayesian Estimator of Protein-Protein Association Probabilities (BEPro), for use in the reconstruction of protein-protein interaction networks. We have combined the Software Environment for BIological Network Inference (SEBINI), an interactive environment for the deployment and testing of network inference algorithms that use high-throughput data, and the Collective Analysis of Biological Interaction Networks (CABIN), software that allows integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources, to allow interactions computed by BEPro to be stored, visualized, and further analyzed. Incorporating BEPro into SEBINI and automatically feeding the resulting inferred network into CABIN, we have created a structured workflow for protein-protein network inference and supplemental analysis from sets of mass spectrometry bait-prey experiment data. SEBINI demo site: https://www.emsl.pnl.gov /SEBINI/ Contact: ronald.taylor@pnl.gov. BEPro is available at http://www.pnl.gov/statistics/BEPro3/index.htm. Contact: ds.daly@pnl.gov. CABIN is available at http://www.sysbio.org/dataresources/cabin.stm. Contact: mudita.singhal@pnl.gov.

  2. Multilayer networks reveal the spatial structure of seed-dispersal interactions across the Great Rift landscapes.

    Science.gov (United States)

    Timóteo, Sérgio; Correia, Marta; Rodríguez-Echeverría, Susana; Freitas, Helena; Heleno, Ruben

    2018-01-10

    Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.

  3. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections

    Science.gov (United States)

    de Vos, Marjon G. J.; Bollenbach, Tobias

    2017-01-01

    Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. PMID:28923953

  4. Crucial role of strategy updating for coexistence of strategies in interaction networks

    NARCIS (Netherlands)

    Zhang, Jianlei; Zhang, Chunyan; Cao, Ming; Weissing, Franz J.

    2015-01-01

    Network models are useful tools for studying the dynamics of social interactions in a structured population. After a round of interactions with the players in their local neighborhood, players update their strategy based on the comparison of their own payoff with the payoff of one of their

  5. Social networks, social interactions, and activity-travel behavior: a framework for microsimulation

    NARCIS (Netherlands)

    Arentze, T.A.; Timmermans, H.J.P.

    2007-01-01

    We argue that the social networks and activity-travel patterns of people interact and coevolve over time. Through social interaction, people exchange information about activity-travel choice alternatives and adapt their latent and overt preferences for alternatives to each other. At the same time,

  6. QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

    Directory of Open Access Journals (Sweden)

    Asa Thibodeau

    2016-06-01

    Full Text Available Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1 building and visualizing chromatin interaction networks, 2 annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3 querying network components based on gene name or chromosome location, and 4 utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

  7. QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

    Science.gov (United States)

    Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

    2016-06-01

    Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

  8. Asymmetrically interacting spreading dynamics on complex layered networks.

    Science.gov (United States)

    Wang, Wei; Tang, Ming; Yang, Hui; Younghae Do; Lai, Ying-Cheng; Lee, GyuWon

    2014-05-29

    The spread of disease through a physical-contact network and the spread of information about the disease on a communication network are two intimately related dynamical processes. We investigate the asymmetrical interplay between the two types of spreading dynamics, each occurring on its own layer, by focusing on the two fundamental quantities underlying any spreading process: epidemic threshold and the final infection ratio. We find that an epidemic outbreak on the contact layer can induce an outbreak on the communication layer, and information spreading can effectively raise the epidemic threshold. When structural correlation exists between the two layers, the information threshold remains unchanged but the epidemic threshold can be enhanced, making the contact layer more resilient to epidemic outbreak. We develop a physical theory to understand the intricate interplay between the two types of spreading dynamics.

  9. Characterization of Schizophrenia Adverse Drug Interactions through a Network Approach and Drug Classification

    Directory of Open Access Journals (Sweden)

    Jingchun Sun

    2013-01-01

    Full Text Available Antipsychotic drugs are medications commonly for schizophrenia (SCZ treatment, which include two groups: typical and atypical. SCZ patients have multiple comorbidities, and the coadministration of drugs is quite common. This may result in adverse drug-drug interactions, which are events that occur when the effect of a drug is altered by the coadministration of another drug. Therefore, it is important to provide a comprehensive view of these interactions for further coadministration improvement. Here, we extracted SCZ drugs and their adverse drug interactions from the DrugBank and compiled a SCZ-specific adverse drug interaction network. This network included 28 SCZ drugs, 241 non-SCZs, and 991 interactions. By integrating the Anatomical Therapeutic Chemical (ATC classification with the network analysis, we characterized those interactions. Our results indicated that SCZ drugs tended to have more adverse drug interactions than other drugs. Furthermore, SCZ typical drugs had significant interactions with drugs of the “alimentary tract and metabolism” category while SCZ atypical drugs had significant interactions with drugs of the categories “nervous system” and “antiinfectives for systemic uses.” This study is the first to characterize the adverse drug interactions in the course of SCZ treatment and might provide useful information for the future SCZ treatment.

  10. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    International Nuclear Information System (INIS)

    Ba, Qian; Li, Junyang; Huang, Chao; Li, Jingquan; Chu, Ruiai; Wu, Yongning; Wang, Hui

    2015-01-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified

  11. Topological, functional, and dynamic properties of the protein interaction networks rewired by benzo(a)pyrene

    Energy Technology Data Exchange (ETDEWEB)

    Ba, Qian [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Li, Junyang; Huang, Chao [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Li, Jingquan; Chu, Ruiai [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wu, Yongning, E-mail: wuyongning@cfsa.net.cn [Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); Wang, Hui, E-mail: huiwang@sibs.ac.cn [Key Laboratory of Food Safety Research, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai (China); Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing (China); School of Life Science and Technology, ShanghaiTech University, Shanghai (China)

    2015-03-01

    Benzo(a)pyrene is a common environmental and foodborne pollutant that has been identified as a human carcinogen. Although the carcinogenicity of benzo(a)pyrene has been extensively reported, its precise molecular mechanisms and the influence on system-level protein networks are not well understood. To investigate the system-level influence of benzo(a)pyrene on protein interactions and regulatory networks, a benzo(a)pyrene-rewired protein interaction network was constructed based on 769 key proteins derived from more than 500 literature reports. The protein interaction network rewired by benzo(a)pyrene was a scale-free, highly-connected biological system. Ten modules were identified, and 25 signaling pathways were enriched, most of which belong to the human diseases category, especially cancer and infectious disease. In addition, two lung-specific and two liver-specific pathways were identified. Three pathways were specific in short and medium-term networks (< 48 h), and five pathways were enriched only in the medium-term network (6 h–48 h). Finally, the expression of linker genes in the network was validated by Western blotting. These findings establish the overall, tissue- and time-specific benzo(a)pyrene-rewired protein interaction networks and provide insights into the biological effects and molecular mechanisms of action of benzo(a)pyrene. - Highlights: • Benzo(a)pyrene induced scale-free, highly-connected protein interaction networks. • 25 signaling pathways were enriched through modular analysis. • Tissue- and time-specific pathways were identified.

  12. Evaluating the Network: A Workflow for Tracking Twitter Interactions Using Social Networking Analysis

    Science.gov (United States)

    Goodier, Sarah

    2018-01-01

    Networking plays an important role in research projects to build a community and audience around a research area. Using social media is popular in project communication as it provides the ability to engage with a group of followers daily. Such online networking tools provide the advantage of providing nearrealtime data, which can be used to…

  13. NEURAL NETWORK INTERACTIONS AND INGESTIVE BEHAVIOR CONTROL DURING ANOREXIA

    Science.gov (United States)

    Watts, Alan G.; Salter, Dawna S.; Neuner, Christina M.

    2007-01-01

    Many models have been proposed over the years to explain how motivated feeding behavior is controlled. One of the most compelling is based on the original concepts of Eliot Stellar whereby sets of interosensory and exterosensory inputs converge on a hypothalamic control network that can either stimulate or inhibit feeding. These inputs arise from information originating in the blood, the viscera, and the telencephalon. In this manner the relative strengths of the hypothalamic stimulatory and inhibitory networks at a particular time dictates how an animal feeds. Anorexia occurs when the balance within the networks consistently favors the restraint of feeding. This article discusses experimental evidence supporting a model whereby the increases in plasma osmolality that result from drinking hypertonic saline activate pathways projecting to neurons in the paraventricular nucleus of the hypothalamus (PVH) and lateral hypothalamic area (LHA). These neurons constitute the hypothalamic controller for ingestive behavior, and receive a set of afferent inputs from regions of the brain that process sensory information that is critical for different aspects of feeding. Important sets of inputs arise in the arcuate nucleus, the hindbrain, and in the telencephalon. Anorexia is generated in dehydrated animals by way of osmosensitive projections to the behavior control neurons in the PVH and LHA, rather than by actions on their afferent inputs. PMID:17531275

  14. The Gcn2 Regulator Yih1 Interacts with the Cyclin Dependent Kinase Cdc28 and Promotes Cell Cycle Progression through G2/M in Budding Yeast.

    Directory of Open Access Journals (Sweden)

    Richard C Silva

    Full Text Available The Saccharomyces cerevisiae protein Yih1, when overexpressed, inhibits the eIF2 alpha kinase Gcn2 by competing for Gcn1 binding. However, deletion of YIH1 has no detectable effect on Gcn2 activity, suggesting that Yih1 is not a general inhibitor of Gcn2, and has no phenotypic defect identified so far. Thus, its physiological role is largely unknown. Here, we show that Yih1 is involved in the cell cycle. Yeast lacking Yih1 displays morphological patterns and DNA content indicative of a delay in the G2/M phases of the cell cycle, and this phenotype is independent of Gcn1 and Gcn2. Accordingly, the levels of phosphorylated eIF2α, which show a cell cycle-dependent fluctuation, are not altered in cells devoid of Yih1. We present several lines of evidence indicating that Yih1 is in a complex with Cdc28. Yih1 pulls down endogenous Cdc28 in vivo and this interaction is enhanced when Cdc28 is active, suggesting that Yih1 modulates the function of Cdc28 in specific stages of the cell cycle. We also demonstrate, by Bimolecular Fluorescence Complementation, that endogenous Yih1 and Cdc28 interact with each other, confirming Yih1 as a bona fide Cdc28 binding partner. Amino acid substitutions within helix H2 of the RWD domain of Yih1 enhance Yih1-Cdc28 association. Overexpression of this mutant, but not of wild type Yih1, leads to a phenotype similar to that of YIH1 deletion, supporting the view that Yih1 is involved through Cdc28 in the regulation of the cell cycle. We further show that IMPACT, the mammalian homologue of Yih1, interacts with CDK1, the mammalian counterpart of Cdc28, indicating that the involvement with the cell cycle is conserved. Together, these data provide insights into the cellular function of Yih1/IMPACT, and provide the basis for future studies on the role of this protein in the cell cycle.

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

    Science.gov (United States)

    Rouault, Hervé; Hakim, Vincent

    2012-02-08

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

  16. Integration and visualization of non-coding RNA and protein interaction networks

    OpenAIRE

    Junge, Alexander; Refsgaard, Jan Christian; Garde, Christian; Pan, Xiaoyong; Santos Delgado, Alberto; Anthon, Christian; Alkan, Ferhat; von Mering, Christian; Workman, Christopher; Jensen, Lars Juhl; Gorodkin, Jan

    2015-01-01

    Non-coding RNAs (ncRNAs) fulfill a diverse set of biological functions relying on interactions with other molecular entities. The advent of new experimental and computational approaches makes it possible to study ncRNAs and their associations on an unprecedented scale. We present RAIN (RNA Association and Interaction Networks) - a database that combines ncRNA-ncRNA, ncRNA-mRNA and ncRNA-protein interactions with large-scale protein association networks available in the STRING database. By int...

  17. Modeling and Detecting Feature Interactions among Integrated Services of Home Network Systems

    Science.gov (United States)

    Igaki, Hiroshi; Nakamura, Masahide

    This paper presents a framework for formalizing and detecting feature interactions (FIs) in the emerging smart home domain. We first establish a model of home network system (HNS), where every networked appliance (or the HNS environment) is characterized as an object consisting of properties and methods. Then, every HNS service is defined as a sequence of method invocations of the appliances. Within the model, we next formalize two kinds of FIs: (a) appliance interactions and (b) environment interactions. An appliance interaction occurs when two method invocations conflict on the same appliance, whereas an environment interaction arises when two method invocations conflict indirectly via the environment. Finally, we propose offline and online methods that detect FIs before service deployment and during execution, respectively. Through a case study with seven practical services, it is shown that the proposed framework is generic enough to capture feature interactions in HNS integrated services. We also discuss several FI resolution schemes within the proposed framework.

  18. Identification of human disease genes from interactome network using graphlet interaction.

    Directory of Open Access Journals (Sweden)

    Xiao-Dong Wang

    Full Text Available Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes.

  19. Identification of Human Disease Genes from Interactome Network Using Graphlet Interaction

    Science.gov (United States)

    Yang, Lun; Wei, Dong-Qing; Qi, Ying-Xin; Jiang, Zong-Lai

    2014-01-01

    Identifying genes related to human diseases, such as cancer and cardiovascular disease, etc., is an important task in biomedical research because of its applications in disease diagnosis and treatment. Interactome networks, especially protein-protein interaction networks, had been used to disease genes identification based on the hypothesis that strong candidate genes tend to closely relate to each other in some kinds of measure on the network. We proposed a new measure to analyze the relationship between network nodes which was called graphlet interaction. The graphlet interaction contained 28 different isomers. The results showed that the numbers of the graphlet interaction isomers between disease genes in interactome networks were significantly larger than random picked genes, while graphlet signatures were not. Then, we designed a new type of score, based on the network properties, to identify disease genes using graphlet interaction. The genes with higher scores were more likely to be disease genes, and all candidate genes were ranked according to their scores. Then the approach was evaluated by leave-one-out cross-validation. The precision of the current approach achieved 90% at about 10% recall, which was apparently higher than the previous three predominant algorithms, random walk, Endeavour and neighborhood based method. Finally, the approach was applied to predict new disease genes related to 4 common diseases, most of which were identified by other independent experimental researches. In conclusion, we demonstrate that the graphlet interaction is an effective tool to analyze the network properties of disease genes, and the scores calculated by graphlet interaction is more precise in identifying disease genes. PMID:24465923

  20. Fluctuating interaction network and time-varying stability of a natural fish community

    Science.gov (United States)

    Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

    2018-02-01

    Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

  1. Protein complex prediction based on k-connected subgraphs in protein interaction network

    OpenAIRE

    Habibi, Mahnaz; Eslahchi, Changiz; Wong, Limsoon

    2010-01-01

    Abstract Background Protein complexes play an important role in cellular mechanisms. Recently, several methods have been presented to predict protein complexes in a protein interaction network. In these methods, a protein complex is predicted as a dense subgraph of protein interactions. However, interactions data are incomplete and a protein complex does not have to be a complete or dense subgraph. Results We propose a more appropriate protein complex prediction method, CFA, that is based on ...

  2. Systematic discovery of new recognition peptides mediating protein interaction networks

    DEFF Research Database (Denmark)

    Neduva, Victor; Linding, Rune; Su-Angrand, Isabelle

    2005-01-01

    Many aspects of cell signalling, trafficking, and targeting are governed by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains...... by interactions between globular protein domains and short peptide segments. These domains often bind multiple peptides that share a common sequence pattern, or "linear motif" (e.g., SH3 binding to PxxP). Many domains are known, though comparatively few linear motifs have been discovered. Their short length...

  3. Discovering disease-associated genes in weighted protein-protein interaction networks

    Science.gov (United States)

    Cui, Ying; Cai, Meng; Stanley, H. Eugene

    2018-04-01

    Although there have been many network-based attempts to discover disease-associated genes, most of them have not taken edge weight - which quantifies their relative strength - into consideration. We use connection weights in a protein-protein interaction (PPI) network to locate disease-related genes. We analyze the topological properties of both weighted and unweighted PPI networks and design an improved random forest classifier to distinguish disease genes from non-disease genes. We use a cross-validation test to confirm that weighted networks are better able to discover disease-associated genes than unweighted networks, which indicates that including link weight in the analysis of network properties provides a better model of complex genotype-phenotype associations.

  4. Establishing Interaction between Machine and Medaka using Deep Q-Network

    Directory of Open Access Journals (Sweden)

    Ryo Nishimura

    2016-05-01

    Full Text Available Social interaction is the basic ability for animals to survive. It is difficult for a machine to interact with human or other animals because it is not clear how the machine should interact. This paper examines whether an artificial dot controlled by a machine can interact with a medaka and induce a desired behavior. The dot is displayed on a monitor. We use deep Q network (DQN to learn how to move the dot. As a result, the DQN could learn some basic elements to interact with the medaka and the desired behavior could be induced.

  5. Synergistic interactions promote behavior spreading and alter phase transitions on multiplex networks

    Science.gov (United States)

    Liu, Quan-Hui; Wang, Wei; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

    2018-02-01

    Synergistic interactions are ubiquitous in the real world. Recent studies have revealed that, for a single-layer network, synergy can enhance spreading and even induce an explosive contagion. There is at the present a growing interest in behavior spreading dynamics on multiplex networks. What is the role of synergistic interactions in behavior spreading in such networked systems? To address this question, we articulate a synergistic behavior spreading model on a double layer network, where the key manifestation of the synergistic interactions is that the adoption of one behavior by a node in one layer enhances its probability of adopting the behavior in the other layer. A general result is that synergistic interactions can greatly enhance the spreading of the behaviors in both layers. A remarkable phenomenon is that the interactions can alter the nature of the phase transition associated with behavior adoption or spreading dynamics. In particular, depending on the transmission rate of one behavior in a network layer, synergistic interactions can lead to a discontinuous (first-order) or a continuous (second-order) transition in the adoption scope of the other behavior with respect to its transmission rate. A surprising two-stage spreading process can arise: due to synergy, nodes having adopted one behavior in one layer adopt the other behavior in the other layer and then prompt the remaining nodes in this layer to quickly adopt the behavior. Analytically, we develop an edge-based compartmental theory and perform a bifurcation analysis to fully understand, in the weak synergistic interaction regime where the dynamical correlation between the network layers is negligible, the role of the interactions in promoting the social behavioral spreading dynamics in the whole system.

  6. Depressive Symptoms and Their Interactions With Emotions and Personality Traits Over Time: Interaction Networks in a Psychiatric Clinic.

    Science.gov (United States)

    Semino, Laura N; Marksteiner, Josef; Brauchle, Gernot; Danay, Erik

    2017-04-13

    Associations between depression, personality traits, and emotions are complex and reciprocal. The aim of this study is to explore these interactions in dynamical networks and in a linear way over time depending on the severity of depression. Participants included 110 patients with depressive symptoms (DSM-5 criteria) who were recruited between October 2015 and February 2016 during their inpatient stay in a general psychiatric hospital in Hall in Tyrol, Austria. The patients filled out the Beck Depression Inventory-II, a German emotional competence questionnaire (Emotionale Kompetenz Fragebogen), Positive and Negative Affect Schedule, and the German versions of the Big Five Inventory-short form and State-Trait-Anxiety-Depression Inventory regarding symptoms, emotions, and personality during their inpatient stay and at a 3-month follow-up by mail. Network and regression analyses were performed to explore interactions both in a linear and a dynamical way at baseline and 3 months later. Regression analyses showed that emotions and personality traits gain importance for the prediction of depressive symptoms with decreasing symptomatology at follow-up (personality: baseline, adjusted R2 = 0.24, P personality traits is significantly denser and more interconnected (network comparison test: P = .03) at follow-up than at baseline, meaning that with decreased symptoms interconnections get stronger. During depression, personality traits and emotions are walled off and not strongly interconnected with depressive symptoms in networks. With decreasing depressive symptomatology, interfusing of these areas begins and interconnections become stronger. This finding has practical implications for interventions in an acute depressive state and with decreased symptoms. The network approach offers a new perspective on interactions and is a way to make the complexity of these interactions more tangible. © Copyright 2017 Physicians Postgraduate Press, Inc.

  7. The MicroRNA Interaction Network of Lipid Diseases

    Science.gov (United States)

    Kandhro, Abdul H.; Shoombuatong, Watshara; Nantasenamat, Chanin; Prachayasittikul, Virapong; Nuchnoi, Pornlada

    2017-01-01

    Background: Dyslipidemia is one of the major forms of lipid disorder, characterized by increased triglycerides (TGs), increased low-density lipoprotein-cholesterol (LDL-C), and decreased high-density lipoprotein-cholesterol (HDL-C) levels in blood. Recently, MicroRNAs (miRNAs) have been reported to involve in various biological processes; their potential usage being a biomarkers and in diagnosis of various diseases. Computational approaches including text mining have been used recently to analyze abstracts from the public databases to observe the relationships/associations between the biological molecules, miRNAs, and disease phenotypes. Materials and Methods: In the present study, significance of text mined extracted pair associations (miRNA-lipid disease) were estimated by one-sided Fisher's exact test. The top 20 significant miRNA-disease associations were visualized on Cytoscape. The CyTargetLinker plug-in tool on Cytoscape was used to extend the network and predicts new miRNA target genes. The Biological Networks Gene Ontology (BiNGO) plug-in tool on Cytoscape was used to retrieve gene ontology (GO) annotations for the targeted genes. Results: We retrieved 227 miRNA-lipid disease associations including 148 miRNAs. The top 20 significant miRNAs analysis on CyTargetLinker provides defined, predicted and validated gene targets, further targeted genes analyzed by BiNGO showed targeted genes were significantly associated with lipid, cholesterol, apolipoprotein, and fatty acids GO terms. Conclusion: We are the first to provide a reliable miRNA-lipid disease association network based on text mining. This could help future experimental studies that aim to validate predicted gene targets. PMID:29018475

  8. The yeast replicative aging model.

    Science.gov (United States)

    He, Chong; Zhou, Chuankai; Kennedy, Brian K

    2018-03-08

    It has been nearly three decades since the budding yeast Saccharomyces cerevisiae became a significant model organism for aging research and it has emerged as both simple and powerful. The replicative aging assay, which interrogates the number of times a "mother" cell can divide and produce "daughters", has been a stalwart in these studies, and genetic approaches have led to the identification of hundreds of genes impacting lifespan. More recently, cell biological and biochemical approaches have been developed to determine how cellular processes become altered with age. Together, the tools are in place to develop a holistic view of aging in this single-celled organism. Here, we summarize the current state of understanding of yeast replicative aging with a focus on the recent studies that shed new light on how aging pathways interact to modulate lifespan in yeast. Copyright © 2018. Published by Elsevier B.V.

  9. Networked Mobilities and new sites of mediated interaction

    DEFF Research Database (Denmark)

    Jensen, Ole B.

    2008-01-01

    everyday life experiences the movement is much more than a travel from point A to point B. The mobile experiences of the contemporary society are practices that are meaningful and normatively embedded. That is to say, mobility is seen as a cultural phenomenon shaping notions of self and other as well......This paper takes point of departure in an understanding of mobility as an important cultural dimension to contemporary life. The movement of objects, signs, and people constitutes material sites of networked relationships. However, as an increasing number of mobility practices are making up our...

  10. Experimental FSO network availability estimation using interactive fog condition monitoring

    Science.gov (United States)

    Turán, Ján.; Ovseník, Łuboš

    2016-12-01

    Free Space Optics (FSO) is a license free Line of Sight (LOS) telecommunication technology which offers full duplex connectivity. FSO uses infrared beams of light to provide optical broadband connection and it can be installed literally in a few hours. Data rates go through from several hundreds of Mb/s to several Gb/s and range is from several 100 m up to several km. FSO link advantages: Easy connection establishment, License free communication, No excavation are needed, Highly secure and safe, Allows through window connectivity and single customer service and Compliments fiber by accelerating the first and last mile. FSO link disadvantages: Transmission media is air, Weather and climate dependence, Attenuation due to rain, snow and fog, Scattering of laser beam, Absorption of laser beam, Building motion and Air pollution. In this paper FSO availability evaluation is based on long term measured data from Fog sensor developed and installed at TUKE experimental FSO network in TUKE campus, Košice, Slovakia. Our FSO experimental network has three links with different physical distances between each FSO heads. Weather conditions have a tremendous impact on FSO operation in terms of FSO availability. FSO link availability is the percentage of time over a year that the FSO link will be operational. It is necessary to evaluate the climate and weather at the actual geographical location where FSO link is going to be mounted. It is important to determine the impact of a light scattering, absorption, turbulence and receiving optical power at the particular FSO link. Visibility has one of the most critical influences on the quality of an FSO optical transmission channel. FSO link availability is usually estimated using visibility information collected from nearby airport weather stations. Raw data from fog sensor (Fog Density, Relative Humidity, Temperature measured at each ms) are collected and processed by FSO Simulator software package developed at our Department. Based

  11. Diversity in a complex ecological network with two interaction types

    Czech Academy of Sciences Publication Activity Database

    Melián, C. J.; Bascompte, J.; Jordano, P.; Křivan, Vlastimil

    2009-01-01

    Roč. 118, č. 1 (2009), s. 122-130 ISSN 0030-1299 R&D Projects: GA AV ČR IAA100070601 Grant - others:University of California(US) DEB-0553768; The Spanish Ministry of Science and Technology (ES) REN2003-04774; The Spanish Ministry of Science and Technology (ES) REN2003-00273 Institutional research plan: CEZ:AV0Z50070508 Keywords : complex ecological network Subject RIV: EH - Ecology, Behaviour Impact factor: 3.147, year: 2009

  12. Interaction between fatty acid and the elastin network

    NARCIS (Netherlands)

    Vreeswijk, van J.

    1995-01-01

    The aim of the present study was to investigate the interaction between salts of fatty acids (FAS) and elastin. Absorption of fatty acids in elastin may affect the elasticity of elastin-containing tissue. Such phenomena could, for instance, be of relevance for the understanding of the

  13. Protein-lipid interactions: from membrane domains to cellular networks

    National Research Council Canada - National Science Library

    Tamm, Lukas K

    2005-01-01

    ... membranes is the lipid bilayer. Embedded in the fluid lipid bilayer are proteins of various shapes and traits. This volume illuminates from physical, chemical and biological angles the numerous - mostly quite weak - interactions between lipids, proteins, and proteins and lipids that define the delicate, highly dynamic and yet so stable fabri...

  14. Ariadne's Thread - Interactive Navigation in a World of Networked Information

    NARCIS (Netherlands)

    Koopman, Rob; Wang, Shenghui; Scharnhorst, Andrea; Englebienne, Gwenn

    2015-01-01

    This work-in-progress paper introduces an interface for the interactive visual exploration of the context of queries using the ArticleFirst database, a product of OCLC. We describe a workflow which allows the user to browse live entities associated with 65 million articles. In the on-line interface,

  15. Bird-plant interaction networks: a study on frugivory in Brazilian urban areas

    Directory of Open Access Journals (Sweden)

    Diego Silva Freitas Oliveira

    2015-12-01

    Full Text Available In Brazil, few studies compare the consumption of native and exotic fruits, especially in an urban environment. The Network Theory may be useful in such studies, because it allows evaluating many bird and plant species involved in interactions. The goals of this study were: evaluate a bird frugivory interaction network in an urban environment; checking the role played by native and exotic plants in the network and comparing the consumer assemblies of these two plant groups. A literature review on bird frugivory in Brazilian urban areas was conducted, as well as an analysis to create an interaction network on a regional scale. The analysis included 15 papers with 70 bird species eating fruits from 15 plant species (6 exotic and 9 native. The exotic and native fruit consumers did not form different groups and the interaction network was significantly nested (NODF = 0.30; p < 0.01 and not modular (M = 0.36; p = 0.16. Two exotic plant species are in the generalist core of the frugivory network (Ficus microcarpa and Michelia champaca. The results point out that a relatively diversified bird group eats fruits in Brazilian urban areas in an opportunistic way, with no preference for native or exotic plants.

  16. Prediction and characterization of protein-protein interaction networks in swine

    Directory of Open Access Journals (Sweden)

    Wang Fen

    2012-01-01

    Full Text Available Abstract Background Studying the large-scale protein-protein interaction (PPI network is important in understanding biological processes. The current research presents the first PPI map of swine, which aims to give new insights into understanding their biological processes. Results We used three methods, Interolog-based prediction of porcine PPI network, domain-motif interactions from structural topology-based prediction of porcine PPI network and motif-motif interactions from structural topology-based prediction of porcine PPI network, to predict porcine protein interactions among 25,767 porcine proteins. We predicted 20,213, 331,484, and 218,705 porcine PPIs respectively, merged the three results into 567,441 PPIs, constructed four PPI networks, and analyzed the topological properties of the porcine PPI networks. Our predictions were validated with Pfam domain annotations and GO annotations. Averages of 70, 10,495, and 863 interactions were related to the Pfam domain-interacting pairs in iPfam database. For comparison, randomized networks were generated, and averages of only 4.24, 66.79, and 44.26 interactions were associated with Pfam domain-interacting pairs in iPfam database. In GO annotations, we found 52.68%, 75.54%, 27.20% of the predicted PPIs sharing GO terms respectively. However, the number of PPI pairs sharing GO terms in the 10,000 randomized networks reached 52.68%, 75.54%, 27.20% is 0. Finally, we determined the accuracy and precision of the methods. The methods yielded accuracies of 0.92, 0.53, and 0.50 at precisions of about 0.93, 0.74, and 0.75, respectively. Conclusion The results reveal that the predicted PPI networks are considerably reliable. The present research is an important pioneering work on protein function research. The porcine PPI data set, the confidence score of each interaction and a list of related data are available at (http://pppid.biositemap.com/.

  17. Interaction between hopping and static spins in a discrete network

    Energy Technology Data Exchange (ETDEWEB)

    Ciccarello, Francesco, E-mail: francesco.ciccarello@sns.it [CNISM and Dipartimento di Fisica, Universita' degli Studi di Palermo, Viale delle Scienze, Edificio 18, I-90128 Palermo (Italy); NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR, Piazza dei Cavalieri 7, I-56126 Pisa (Italy)

    2011-06-27

    We consider a process where a spin hops across a discrete network and at certain sites couples to static spins. While this setting is implementable in various scenarios (e.g. quantum dots or coupled cavities) the physics of such processes is still basically unknown. Here, we take a first step along this line by scrutinizing a two-site and a three-site lattices, each with two static spins. Despite a generally complex dynamics occurs, we show a regime such that the spin dynamics is described by an effective three-spin chain. Tasks such as entanglement generation and quantum state transfer can be achieved accordingly. -- Highlights: → We study mobile spins hopping in a discrete network and coupled to static spins. → This setting can be implemented in various scenarios. → We address a two-site and a three-site lattice, each with two static spins. → We show a regime where the setup can be described by an effective three-spin chain. → Accordingly, it is prone to be exploited for some QIP applications.

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

    Science.gov (United States)

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

    2003-11-01

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

  19. Responses to olfactory signals reflect network structure of flower-visitor interactions.

    Science.gov (United States)

    Junker, Robert R; Höcherl, Nicole; Blüthgen, Nico

    2010-07-01

    1. Network analyses provide insights into the diversity and complexity of ecological interactions and have motivated conclusions about community stability and co-evolution. However, biological traits and mechanisms such as chemical signals regulating the interactions between individual species--the microstructure of a network--are poorly understood. 2. We linked the responses of receivers (flower visitors) towards signals (flower scent) to the structure of a highly diverse natural flower-insect network. For each interaction, we define link temperature--a newly developed metric--as the deviation of the observed interaction strength from neutrality, assuming that animals randomly interact with flowers. 3. Link temperature was positively correlated to the specific visitors' responses to floral scents, experimentally examined in a mobile olfactometer. Thus, communication between plants and consumers via phytochemical signals reflects a significant part of the microstructure in a complex network. Negative as well as positive responses towards floral scents contributed to these results, where individual experience was important apart from innate behaviour. 4. Our results indicate that: (1) biological mechanisms have a profound impact on the microstructure of complex networks that underlies the outcome of aggregate statistics, and (2) floral scents act as a filter, promoting the visitation of some flower visitors, but also inhibiting the visitation of others.

  20. Cytoprophet: a Cytoscape plug-in for protein and domain interaction networks inference.

    Science.gov (United States)

    Morcos, Faruck; Lamanna, Charles; Sikora, Marcin; Izaguirre, Jesús

    2008-10-01

    Cytoprophet is a software tool that allows prediction and visualization of protein and domain interaction networks. It is implemented as a plug-in of Cytoscape, an open source software framework for analysis and visualization of molecular networks. Cytoprophet implements three algorithms that predict new potential physical interactions using the domain composition of proteins and experimental assays. The algorithms for protein and domain interaction inference include maximum likelihood estimation (MLE) using expectation maximization (EM); the set cover approach maximum specificity set cover (MSSC) and the sum-product algorithm (SPA). After accepting an input set of proteins with Uniprot ID/Accession numbers and a selected prediction algorithm, Cytoprophet draws a network of potential interactions with probability scores and GO distances as edge attributes. A network of domain interactions between the domains of the initial protein list can also be generated. Cytoprophet was designed to take advantage of the visual capabilities of Cytoscape and be simple to use. An example of inference in a signaling network of myxobacterium Myxococcus xanthus is presented and available at Cytoprophet's website. http://cytoprophet.cse.nd.edu.

  1. Interactions of the Salience Network and Its Subsystems with the Default-Mode and the Central-Executive Networks in Normal Aging and Mild Cognitive Impairment.

    Science.gov (United States)

    Chand, Ganesh B; Wu, Junjie; Hajjar, Ihab; Qiu, Deqiang

    2017-09-01

    Previous functional magnetic resonance imaging (fMRI) investigations suggest that the intrinsically organized large-scale networks and the interaction between them might be crucial for cognitive activities. A triple network model, which consists of the default-mode network, salience network, and central-executive network, has been recently used to understand the connectivity patterns of the cognitively normal brains versus the brains with disorders. This model suggests that the salience network dynamically controls the default-mode and central-executive networks in healthy young individuals. However, the patterns of interactions have remained largely unknown in healthy aging or those with cognitive decline. In this study, we assess the patterns of interactions between the three networks using dynamical causal modeling in resting state fMRI data and compare them between subjects with normal cognition and mild cognitive impairment (MCI). In healthy elderly subjects, our analysis showed that the salience network, especially its dorsal subnetwork, modulates the interaction between the default-mode network and the central-executive network (Mann-Whitney U test; p control correlated significantly with lower overall cognitive performance measured by Montreal Cognitive Assessment (r = 0.295; p control, especially the dorsal salience network, over other networks provides a neuronal basis for cognitive decline and may be a candidate neuroimaging biomarker of cognitive impairment.

  2. Temporal variation in bat-fruit interactions: Foraging strategies influence network structure over time

    Science.gov (United States)

    Zapata-Mesa, Natalya; Montoya-Bustamante, Sebastián; Murillo-García, Oscar E.

    2017-11-01

    Mutualistic interactions, such as seed dispersal, are important for the maintenance of structure and stability of tropical communities. However, there is a lack of information about spatial and temporal variation in plant-animal interaction networks. Thus, our goal was to assess the effect of bat's foraging strategies on temporal variation in the structure and robustness of bat-fruit networks in both a dry and a rain tropical forest. We evaluated monthly variation in bat-fruit networks by using seven structure metrics: network size, average path length, nestedness, modularity, complementary specialization, normalized degree and betweenness centrality. Seed dispersal networks showed variations in size, species composition and modularity; did not present nested structures and their complementary specialization was high compared to other studies. Both networks presented short path lengths, and a constantly high robustness, despite their monthly variations. Sedentary bat species were recorded during all the study periods and occupied more central positions than nomadic species. We conclude that foraging strategies are important structuring factors that affect the dynamic of networks by determining the functional roles of frugivorous bats over time; thus sedentary bats are more important than nomadic species for the maintenance of the network structure, and their conservation is a must.

  3. Social network analysis of character interaction in the Stargate and Star Trek television series

    Science.gov (United States)

    Tan, Melody Shi Ai; Ujum, Ephrance Abu; Ratnavelu, Kuru

    This paper undertakes a social network analysis of two science fiction television series, Stargate and Star Trek. Television series convey stories in the form of character interaction, which can be represented as “character networks”. We connect each pair of characters that exchanged spoken dialogue in any given scene demarcated in the television series transcripts. These networks are then used to characterize the overall structure and topology of each series. We find that the character networks of both series have similar structure and topology to that found in previous work on mythological and fictional networks. The character networks exhibit the small-world effects but found no significant support for power-law. Since the progression of an episode depends to a large extent on the interaction between each of its characters, the underlying network structure tells us something about the complexity of that episode’s storyline. We assessed the complexity using techniques from spectral graph theory. We found that the episode networks are structured either as (1) closed networks, (2) those containing bottlenecks that connect otherwise disconnected clusters or (3) a mixture of both.

  4. Reconstructing past ecological networks: the reconfiguration of seed-dispersal interactions after megafaunal extinction.

    Science.gov (United States)

    Pires, Mathias M; Galetti, Mauro; Donatti, Camila I; Pizo, Marco A; Dirzo, Rodolfo; Guimarães, Paulo R

    2014-08-01

    The late Quaternary megafaunal extinction impacted ecological communities worldwide, and affected key ecological processes such as seed dispersal. The traits of several species of large-seeded plants are thought to have evolved in response to interactions with extinct megafauna, but how these extinctions affected the organization of interactions in seed-dispersal systems is poorly understood. Here, we combined ecological and paleontological data and network analyses to investigate how the structure of a species-rich seed-dispersal network could have changed from the Pleistocene to the present and examine the possible consequences of such changes. Our results indicate that the seed-dispersal network was organized into modules across the different time periods but has been reconfigured in different ways over time. The episode of megafaunal extinction and the arrival of humans changed how seed dispersers were distributed among network modules. However, the recent introduction of livestock into the seed-dispersal system partially restored the original network organization by strengthening the modular configuration. Moreover, after megafaunal extinctions, introduced species and some smaller native mammals became key components for the structure of the seed-dispersal network. We hypothesize that such changes in network structure affected both animal and plant assemblages, potentially contributing to the shaping of modern ecological communities. The ongoing extinction of key large vertebrates will lead to a variety of context-dependent rearranged ecological networks, most certainly affecting ecological and evolutionary processes.

  5. Spatial interactions reveal inhibitory cortical networks in human amblyopia.

    Science.gov (United States)

    Wong, Erwin H; Levi, Dennis M; McGraw, Paul V

    2005-10-01

    Humans with amblyopia have a well-documented loss of sensitivity for first-order, or luminance defined, visual information. Recent studies show that they also display a specific loss of sensitivity for second-order, or contrast defined, visual information; a type of image structure encoded by neurons found predominantly in visual area A18/V2. In the present study, we investigate whether amblyopia disrupts the normal architecture of spatial interactions in V2 by determining the contrast detection threshold of a second-order target in the presence of second-order flanking stimuli. Adjacent flanks facilitated second-order detectability in normal observers. However, in marked contrast, they suppressed detection in each eye of the majority of amblyopic observers. Furthermore, strabismic observers with no loss of visual acuity show a similar pattern of detection suppression. We speculate that amblyopia results in predominantly inhibitory cortical interactions between second-order neurons.

  6. INCAS—Interactive Teleconsultation Network for Worldwide Healthcare Services

    Science.gov (United States)

    Castelli, A.; Colombo, C.; Garlaschelli, A.; Pepe, G.

    2001-01-01

    The INCAS Project arises from the needs of an Italian oil company in order to support the doctors responsible for the healthcare in remote drilling sites. The INCAS telemedicine1 system implements a prototype of teleconsultation medical service allowing for the interactive on-line connection with Italian healthcare reference centres in order to: • provide support to the expatriate doctor with the diagnoses and treatment of routine complaints; • contribute to the general improvement of healthcare in remote areas.

  7. Generalist Bee Species on Brazilian Bee-Plant Interaction Networks

    Directory of Open Access Journals (Sweden)

    Astrid de Matos Peixoto Kleinert

    2012-01-01

    Full Text Available Determining bee and plant interactions has an important role on understanding general biology of bee species as well as the potential pollinating relationship between them. Bee surveys have been conducted in Brazil since the end of the 1960s. Most of them applied standardized methods and had identified the plant species where the bees were collected. To analyze the most generalist bees on Brazilian surveys, we built a matrix of bee-plant interactions. We estimated the most generalist bees determining the three bee species of each surveyed locality that presented the highest number of interactions. We found 47 localities and 39 species of bees. Most of them belong to Apidae (31 species and Halictidae (6 families and to Meliponini (14 and Xylocopini (6 tribes. However, most of the surveys presented Apis mellifera and/or Trigona spinipes as the most generalist species. Apis mellifera is an exotic bee species and Trigona spinipes, a native species, is also widespread and presents broad diet breath and high number of individuals per colony.

  8. Model-free inference of direct network interactions from nonlinear collective dynamics.

    Science.gov (United States)

    Casadiego, Jose; Nitzan, Mor; Hallerberg, Sarah; Timme, Marc

    2017-12-19

    The topology of interactions in network dynamical systems fundamentally underlies their function. Accelerating technological progress creates massively available data about collective nonlinear dynamics in physical, biological, and technological systems. Detecting direct interaction patterns from those dynamics still constitutes a major open problem. In particular, current nonlinear dynamics approaches mostly require to know a priori a model of the (often high dimensional) system dynamics. Here we develop a model-independent framework for inferring direct interactions solely from recording the nonlinear collective dynamics generated. Introducing an explicit dependency matrix in combination with a block-orthogonal regression algorithm, the approach works reliably across many dynamical regimes, including transient dynamics toward steady states, periodic and non-periodic dynamics, and chaos. Together with its capabilities to reveal network (two point) as well as hypernetwork (e.g., three point) interactions, this framework may thus open up nonlinear dynamics options of inferring direct interaction patterns across systems where no model is known.

  9. Emergence of structural patterns out of synchronization in networks with competitive interactions

    Science.gov (United States)

    Assenza, Salvatore; Gutiérrez, Ricardo; Gómez-Gardeñes, Jesús; Latora, Vito; Boccaletti, Stefano

    2011-09-01

    Synchronization is a collective phenomenon occurring in systems of interacting units, and is ubiquitous in nature, society and technology. Recent studies have enlightened the important role played by the interaction topology on the emergence of synchronized states. However, most of these studies neglect that real world systems change their interaction patterns in time. Here, we analyze synchronization features in networks in which structural and dynamical features co-evolve. The feedback of the node dynamics on the interaction pattern is ruled by the competition of two mechanisms: homophily (reinforcing those interactions with other correlated units in the graph) and homeostasis (preserving the value of the input strength received by each unit). The competition between these two adaptive principles leads to the emergence of key structural properties observed in real world networks, such as modular and scale-free structures, together with a striking enhancement of local synchronization in systems with no global order.

  10. Network interactions: non-geniculate input to V1.

    Science.gov (United States)

    Muckli, Lars; Petro, Lucy S

    2013-04-01

    The strongest connections to V1 are fed back from neighbouring area V2 and from a network of higher cortical areas (e.g. V3, V5, LOC, IPS and A1), transmitting the results of cognitive operations such as prediction, attention and imagination. V1 is therefore at the receiving end of a complex cortical processing cascade and not only at the entrance stage of cortical processing of retinal input. One elegant strategy to investigate this information-rich feedback to V1 is to eliminate feedforward input, that is, exploit V1's retinotopic organisation to isolate subregions receiving no direct bottom-up stimulation. We highlight the diverse mechanisms of cortical feedback, ranging from gain control to predictive coding, and conclude that V1 is involved in rich internal communication processes. Copyright © 2013 Elsevier Ltd. All rights reserved.

  11. The missing part of seed dispersal networks: structure and robustness of bat-fruit interactions.

    Directory of Open Access Journals (Sweden)

    Marco Aurelio Ribeiro Mello

    2011-02-01

    Full Text Available Mutualistic networks are crucial to the maintenance of ecosystem services. Unfortunately, what we know about seed dispersal networks is based only on bird-fruit interactions. Therefore, we aimed at filling part of this gap by investigating bat-fruit networks. It is known from population studies that: (i some bat species depend more on fruits than others, and (ii that some specialized frugivorous bats prefer particular plant genera. We tested whether those preferences affected the structure and robustness of the whole network and the functional roles of species. Nine bat-fruit datasets from the literature were analyzed and all networks showed lower complementary specialization (H(2' = 0.37±0.10, mean ± SD and similar nestedness (NODF = 0.56±0.12 than pollination networks. All networks were modular (M = 0.32±0.07, and had on average four cohesive subgroups (modules of tightly connected bats and plants. The composition of those modules followed the genus-genus associations observed at population level (Artibeus-Ficus, Carollia-Piper, and Sturnira-Solanum, although a few of those plant genera were dispersed also by other bats. Bat-fruit networks showed high robustness to simulated cumulative removals of both bats (R = 0.55±0.10 and plants (R = 0.68±0.09. Primary frugivores interacted with a larger proportion of the plants available and also occupied more central positions; furthermore, their extinction caused larger changes in network structure. We conclude that bat-fruit networks are highly cohesive and robust mutualistic systems, in which redundancy is high within modules, although modules are complementary to each other. Dietary specialization seems to be an important structuring factor that affects the topology, the guild structure and functional roles in bat-fruit networks.

  12. A Preliminary Examination of the Relationship Between Social Networking Interactions, Internet Use, and Thwarted Belongingness.

    Science.gov (United States)

    Moberg, Fallon B; Anestis, Michael D

    2015-01-01

    Joiner's (2005) interpersonal-psychological theory of suicide hypothesizes that suicidal desire develops in response to the joint presence of thwarted belongingness and perceived burdensomeness. To consider the potential influence of online interactions and behaviors on these outcomes. To address this, we administered an online protocol assessing suicidal desire and online interactions in a sample of 305 undergraduates (83.6% female). We hypothesized negative interactions on social networking sites and a preference for online social interactions would be associated with thwarted belongingness. We also conducted an exploratory analysis examining the associations between Internet usage and perceived burdensomeness. Higher levels of negative interactions on social networking sites, but no other variables, significantly predicted thwarted belongingness. Our exploratory analysis showed that none of our predictors were associated with perceived burdensomeness after accounting for demographics, depression, and thwarted belongingness. Our findings indicate that a general tendency to have negative interactions on social networking sites could possibly impact suicidal desire and that these effects are significant above and beyond depression symptoms. Furthermore, no other aspect of problematic Internet use significantly predicted our outcomes in multivariate analyses, indicating that social networking in particular may have a robust effect on thwarted belongingness.

  13. Limitations of a metabolic network-based reverse ecology method for inferring host-pathogen interactions.

    Science.gov (United States)

    Takemoto, Kazuhiro; Aie, Kazuki

    2017-05-25

    Host-pathogen interactions are important in a wide range of research fields. Given the importance of metabolic crosstalk between hosts and pathogens, a metabolic network-based reverse ecology method was proposed to infer these interactions. However, the validity of this method remains unclear because of the various explanations presented and the influence of potentially confounding factors that have thus far been neglected. We re-evaluated the importance of the reverse ecology method for evaluating host-pathogen interactions while statistically controlling for confounding effects using oxygen requirement, genome, metabolic network, and phylogeny data. Our data analyses showed that host-pathogen interactions were more strongly influenced by genome size, primary network parameters (e.g., number of edges), oxygen requirement, and phylogeny than the reserve ecology-based measures. These results indicate the limitations of the reverse ecology method; however, they do not discount the importance of adopting reverse ecology approaches altogether. Rather, we highlight the need for developing more suitable methods for inferring host-pathogen interactions and conducting more careful examinations of the relationships between metabolic networks and host-pathogen interactions.

  14. HPIminer: A text mining system for building and visualizing human protein interaction networks and pathways.

    Science.gov (United States)

    Subramani, Suresh; Kalpana, Raja; Monickaraj, Pankaj Moses; Natarajan, Jeyakumar

    2015-04-01

    The knowledge on protein-protein interactions (PPI) and their related pathways are equally important to understand the biological functions of the living cell. Such information on human proteins is highly desirable to understand the mechanism of several diseases such as cancer, diabetes, and Alzheimer's disease. Because much of that information is buried in biomedical literature, an automated text mining system for visualizing human PPI and pathways is highly desirable. In this paper, we present HPIminer, a text mining system for visualizing human protein interactions and pathways from biomedical literature. HPIminer extracts human PPI information and PPI pairs from biomedical literature, and visualize their associated interactions, networks and pathways using two curated databases HPRD and KEGG. To our knowledge, HPIminer is the first system to build interaction networks from literature as well as curated databases. Further, the new interactions mined only from literature and not reported earlier in databases are highlighted as new. A comparative study with other similar tools shows that the resultant network is more informative and provides additional information on interacting proteins and their associated networks. Copyright © 2015 Elsevier Inc. All rights reserved.

  15. When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.

    Science.gov (United States)

    Iván, Gábor; Grolmusz, Vince

    2011-02-01

    Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip.

  16. Exploitation of genetic interaction network topology for the prediction of epistatic behavior

    KAUST Repository

    Alanis Lobato, Gregorio

    2013-10-01

    Genetic interaction (GI) detection impacts the understanding of human disease and the ability to design personalized treatment. The mapping of every GI in most organisms is far from complete due to the combinatorial amount of gene deletions and knockdowns required. Computational techniques to predict new interactions based only on network topology have been developed in network science but never applied to GI networks.We show that topological prediction of GIs is possible with high precision and propose a graph dissimilarity index that is able to provide robust predictio