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Sample records for ranking protein decoys

  1. Improving decoy databases for protein folding algorithms

    KAUST Repository

    Lindsey, Aaron

    2014-01-01

    Copyright © 2014 ACM. Predicting protein structures and simulating protein folding are two of the most important problems in computational biology today. Simulation methods rely on a scoring function to distinguish the native structure (the most energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing redundant structures. We test our approach on 17 different decoy databases of varying size and type and show significant improvement across a variety of metrics. We also test our improved databases on a popular modern scoring function and show that they contain a greater number of native-like structures than the original databases, thereby producing a more rigorous database for testing scoring functions.

  2. Ranking beta sheet topologies of proteins

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2010-01-01

    One of the challenges of protein structure prediction is to identify long-range interactions between amino acids. To reliably predict such interactions, we enumerate, score and rank all beta-topologies (partitions of beta-strands into sheets, orderings of strands within sheets and orientations...... of paired strands) of a given protein. We show that the beta-topology corresponding to the native structure is, with high probability, among the top-ranked. Since full enumeration is very time-consuming, we also suggest a method to deal with proteins with many beta-strands. The results reported...... in this paper are highly relevant for ab initio protein structure prediction methods based on decoy generation. The top-ranked beta-topologies can be used to find initial conformations from which conformational searches can be started. They can also be used to filter decoys by removing those with poorly...

  3. Improving decoy databases for protein folding algorithms

    KAUST Repository

    Lindsey, Aaron; Yeh, Hsin-Yi (Cindy); Wu, Chih-Peng; Thomas, Shawna; Amato, Nancy M.

    2014-01-01

    energetically stable) from non-native structures. Decoy databases are collections of non-native structures used to test and verify these functions. We present a method to evaluate and improve the quality of decoy databases by adding novel structures and removing

  4. From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction.

    Science.gov (United States)

    Akhter, Nasrin; Shehu, Amarda

    2018-01-19

    Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

  5. From Extraction of Local Structures of Protein Energy Landscapes to Improved Decoy Selection in Template-Free Protein Structure Prediction

    Directory of Open Access Journals (Sweden)

    Nasrin Akhter

    2018-01-01

    Full Text Available Due to the essential role that the three-dimensional conformation of a protein plays in regulating interactions with molecular partners, wet and dry laboratories seek biologically-active conformations of a protein to decode its function. Computational approaches are gaining prominence due to the labor and cost demands of wet laboratory investigations. Template-free methods can now compute thousands of conformations known as decoys, but selecting native conformations from the generated decoys remains challenging. Repeatedly, research has shown that the protein energy functions whose minima are sought in the generation of decoys are unreliable indicators of nativeness. The prevalent approach ignores energy altogether and clusters decoys by conformational similarity. Complementary recent efforts design protein-specific scoring functions or train machine learning models on labeled decoys. In this paper, we show that an informative consideration of energy can be carried out under the energy landscape view. Specifically, we leverage local structures known as basins in the energy landscape probed by a template-free method. We propose and compare various strategies of basin-based decoy selection that we demonstrate are superior to clustering-based strategies. The presented results point to further directions of research for improving decoy selection, including the ability to properly consider the multiplicity of native conformations of proteins.

  6. Tumor endothelium marker-8 based decoys exhibit superiority over capillary morphogenesis protein-2 based decoys as anthrax toxin inhibitors.

    Directory of Open Access Journals (Sweden)

    Chenguang Cai

    Full Text Available Anthrax toxin is the major virulence factor produced by Bacillus anthracis. The toxin consists of three protein subunits: protective antigen (PA, lethal factor, and edema factor. Inhibition of PA binding to its receptors, tumor endothelium marker-8 (TEM8 and capillary morphogenesis protein-2 (CMG2 can effectively block anthrax intoxication, which is particularly valuable when the toxin has already been overproduced at the late stage of anthrax infection, thus rendering antibiotics ineffectual. Receptor-like agonists, such as the mammalian cell-expressed von Willebrand factor type A (vWA domain of CMG2 (sCMG2, have demonstrated potency against the anthrax toxin. However, the soluble vWA domain of TEM8 (sTEM8 was ruled out as an anthrax toxin inhibitor candidate due to its inferior affinity to PA. In the present study, we report that L56A, a PA-binding-affinity-elevated mutant of sTEM8, could inhibit anthrax intoxication as effectively as sCMG2 in Fisher 344 rats. Additionally, pharmacokinetics showed that L56A and sTEM8 exhibit advantages over sCMG2 with better lung-targeting and longer plasma retention time, which may contribute to their enhanced protective ability in vivo. Our results suggest that receptor decoys based on TEM8 are promising anthrax toxin inhibitors and, together with the pharmacokinetic studies in this report, may contribute to the development of novel anthrax drugs.

  7. Delayed Toxicity Associated with Soluble Anthrax Toxin Receptor Decoy-Ig Fusion Protein Treatment

    Science.gov (United States)

    Cote, Christopher; Welkos, Susan; Manchester, Marianne; Young, John A. T.

    2012-01-01

    Soluble receptor decoy inhibitors, including receptor-immunogloubulin (Ig) fusion proteins, have shown promise as candidate anthrax toxin therapeutics. These agents act by binding to the receptor-interaction site on the protective antigen (PA) toxin subunit, thereby blocking toxin binding to cell surface receptors. Here we have made the surprising observation that co-administration of receptor decoy-Ig fusion proteins significantly delayed, but did not protect, rats challenged with anthrax lethal toxin. The delayed toxicity was associated with the in vivo assembly of a long-lived complex comprised of anthrax lethal toxin and the receptor decoy-Ig inhibitor. Intoxication in this system presumably results from the slow dissociation of the toxin complex from the inhibitor following their prolonged circulation. We conclude that while receptor decoy-Ig proteins represent promising candidates for the early treatment of B. anthracis infection, they may not be suitable for therapeutic use at later stages when fatal levels of toxin have already accumulated in the bloodstream. PMID:22511955

  8. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-11-19

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  9. Multiple graph regularized protein domain ranking

    KAUST Repository

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2012-01-01

    Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

  10. Multiple graph regularized protein domain ranking.

    Science.gov (United States)

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2012-11-19

    Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  11. Multiple graph regularized protein domain ranking

    Directory of Open Access Journals (Sweden)

    Wang Jim

    2012-11-01

    Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

  12. Improving predicted protein loop structure ranking using a Pareto-optimality consensus method.

    Science.gov (United States)

    Li, Yaohang; Rata, Ionel; Chiu, See-wing; Jakobsson, Eric

    2010-07-20

    Accurate protein loop structure models are important to understand functions of many proteins. Identifying the native or near-native models by distinguishing them from the misfolded ones is a critical step in protein loop structure prediction. We have developed a Pareto Optimal Consensus (POC) method, which is a consensus model ranking approach to integrate multiple knowledge- or physics-based scoring functions. The procedure of identifying the models of best quality in a model set includes: 1) identifying the models at the Pareto optimal front with respect to a set of scoring functions, and 2) ranking them based on the fuzzy dominance relationship to the rest of the models. We apply the POC method to a large number of decoy sets for loops of 4- to 12-residue in length using a functional space composed of several carefully-selected scoring functions: Rosetta, DOPE, DDFIRE, OPLS-AA, and a triplet backbone dihedral potential developed in our lab. Our computational results show that the sets of Pareto-optimal decoys, which are typically composed of approximately 20% or less of the overall decoys in a set, have a good coverage of the best or near-best decoys in more than 99% of the loop targets. Compared to the individual scoring function yielding best selection accuracy in the decoy sets, the POC method yields 23%, 37%, and 64% less false positives in distinguishing the native conformation, indentifying a near-native model (RMSD Pareto optimality and fuzzy dominance, the POC method is effective in distinguishing the best loop models from the other ones within a loop model set.

  13. Scoring protein interaction decoys using exposed residues (SPIDER): a novel multibody interaction scoring function based on frequent geometric patterns of interfacial residues.

    Science.gov (United States)

    Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

    2012-08-01

    Accurate prediction of the structure of protein-protein complexes in computational docking experiments remains a formidable challenge. It has been recognized that identifying native or native-like poses among multiple decoys is the major bottleneck of the current scoring functions used in docking. We have developed a novel multibody pose-scoring function that has no theoretical limit on the number of residues contributing to the individual interaction terms. We use a coarse-grain representation of a protein-protein complex where each residue is represented by its side chain centroid. We apply a computational geometry approach called Almost-Delaunay tessellation that transforms protein-protein complexes into a residue contact network, or an undirectional graph where vertex-residues are nodes connected by edges. This treatment forms a family of interfacial graphs representing a dataset of protein-protein complexes. We then employ frequent subgraph mining approach to identify common interfacial residue patterns that appear in at least a subset of native protein-protein interfaces. The geometrical parameters and frequency of occurrence of each "native" pattern in the training set are used to develop the new SPIDER scoring function. SPIDER was validated using standard "ZDOCK" benchmark dataset that was not used in the development of SPIDER. We demonstrate that SPIDER scoring function ranks native and native-like poses above geometrical decoys and that it exceeds in performance a popular ZRANK scoring function. SPIDER was ranked among the top scoring functions in a recent round of CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods. Copyright © 2012 Wiley Periodicals, Inc.

  14. Can a pairwise contact potential stabilize native protein folds against decoys obtained by threading?

    Science.gov (United States)

    Vendruscolo, M; Najmanovich, R; Domany, E

    2000-02-01

    We present a method to derive contact energy parameters from large sets of proteins. The basic requirement on which our method is based is that for each protein in the database the native contact map has lower energy than all its decoy conformations that are obtained by threading. Only when this condition is satisfied one can use the proposed energy function for fold identification. Such a set of parameters can be found (by perceptron learning) if Mp, the number of proteins in the database, is not too large. Other aspects that influence the existence of such a solution are the exact definition of contact and the value of the critical distance Rc, below which two residues are considered to be in contact. Another important novel feature of our approach is its ability to determine whether an energy function of some suitable proposed form can or cannot be parameterized in a way that satisfies our basic requirement. As a demonstration of this, we determine the region in the (Rc, Mp) plane in which the problem is solvable, i.e., we can find a set of contact parameters that stabilize simultaneously all the native conformations. We show that for large enough databases the contact approximation to the energy cannot stabilize all the native folds even against the decoys obtained by gapless threading.

  15. A 7-mer knowledge-based potential for detecting native protein structures from decoys

    DEFF Research Database (Denmark)

    Røgen, Peter

    for faster sampling methods. Background: The C-alpha atoms define a polygonal curve in 3-space which is smoothened by the method presented in [1] and is illustrated below. The geometry of a 7-mer is described by two numbers that describe how stretched and curved the smoothening of the 7-mer is. These two...... numbers are called length and distance excess, c.f. [2], and give one point in the length - distance excess - plane, LDE-plane. Method: Given a sequence of amino acids, we break it down to all its 7-mers and search a database of known 3d-structures for similar 7-mer sequences. For the query 7-mer we...... define an energy function in the LDE-plane. This energy is given by the 7-mer found and depends linearly on some design parameters. The energy function of the full query sequence, F, is then a sum over all 7-mers. For a protein P and a decoy D we ideally want F(D)-F(P)=constant.RMSD( D , P ), where 0...

  16. The cis decoy against the estrogen response element suppresses breast cancer cells via target disrupting c-fos not mitogen-activated protein kinase activity.

    Science.gov (United States)

    Wang, Li Hua; Yang, Xiao Yi; Zhang, Xiaohu; Mihalic, Kelly; Xiao, Weihua; Farrar, William L

    2003-05-01

    Breast cancer, the most common malignancy in women, has been demonstrated to be associated with the steroid hormone estrogen and its receptor (ER), a ligand-activated transcription factor. Therefore, we developed a phosphorothiolate cis-element decoy against the estrogen response element (ERE decoy) to target disruption of ER DNA binding and transcriptional activity. Here, we showed that the ERE decoy potently ablated the 17beta-estrogen-inducible cell proliferation and induced apoptosis of human breast carcinoma cells by functionally affecting expression of c-fos gene and AP-1 luciferase gene reporter activity. Specificity of the decoy was demonstrated by its ability to directly block ER binding to a cis-element probe and transactivation. Moreover, the decoy failed to inhibit ER-mediated mitogen-activated protein kinase signaling pathways and cell growth of ER-negative breast cancer cells. Taken together, these data suggest that estrogen-mediated cell growth of breast cancer cells can be preferentially restricted via targeted disruption of ER at the level of DNA binding by a novel and specific decoy strategy applied to steroid nuclear receptors.

  17. Novel VEGF decoy receptor fusion protein conbercept targeting multiple VEGF isoforms provide remarkable anti-angiogenesis effect in vivo.

    Directory of Open Access Journals (Sweden)

    Qin Wang

    Full Text Available VEGF family factors are known to be the principal stimulators of abnormal angiogenesis, which play a fundamental role in tumor and various ocular diseases. Inhibition of VEGF is widely applied in antiangiogenic therapy. Conbercept is a novel decoy receptor protein constructed by fusing VEGF receptor 1 and VEGF receptor 2 extracellular domains with the Fc region of human immunoglobulin. In this study, we systematically evaluated the binding affinity of conbercept with VEGF isoforms and PlGF by using anti-VEGF antibody (Avastin as reference. BIACORE and ELISA assay results indicated that conbercept could bind different VEGF-A isoforms with higher affinity than reference. Furthermore, conbercept could also bind VEGF-B and PlGF, whereas Avastin showed no binding. Oxygen-induced retinopathy model showed that conbercept could inhibit the formation of neovasularizations. In tumor-bearing nude mice, conbercept could also suppress tumor growth very effectively in vivo. Overall, our study have demonstrated that conbercept could bind with high affinity to multiple VEGF isoforms and consequently provide remarkable anti-angiogenic effect, suggesting the possibility to treat angiogenesis-related diseases such as cancer and wet AMD etc.

  18. Creation of Polyvalent Decoys of Protein Cytotoxins as Therapeutics and Vaccines

    Science.gov (United States)

    2008-01-01

    bar = 100 nm. 225C. Hsu et al. / Virology 349 (2006) 222–229stain- permeated broken particles are seen (Fig. 3C). The observation of full particles is...were maintained in suspension on a shaker (100 rpm) in a 500-ml polypropylene bottle. Generation of recombinant baculoviruses expressing SV coat protein...temperature. The grids were washed three times by being transferred into drops of water placed on Parafilm, and the excess liquid was blotted off from the

  19. Ranking beta sheet topologies with applications to protein structure prediction

    DEFF Research Database (Denmark)

    Fonseca, Rasmus; Helles, Glennie; Winter, Pawel

    2011-01-01

    One reason why ab initio protein structure predictors do not perform very well is their inability to reliably identify long-range interactions between amino acids. To achieve reliable long-range interactions, all potential pairings of ß-strands (ß-topologies) of a given protein are enumerated......, including the native ß-topology. Two very different ß-topology scoring methods from the literature are then used to rank all potential ß-topologies. This has not previously been attempted for any scoring method. The main result of this paper is a justification that one of the scoring methods, in particular......, consistently top-ranks native ß-topologies. Since the number of potential ß-topologies grows exponentially with the number of ß-strands, it is unrealistic to expect that all potential ß-topologies can be enumerated for large proteins. The second result of this paper is an enumeration scheme of a subset of ß-topologies...

  20. AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

    Science.gov (United States)

    Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

    2017-06-15

    Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  1. Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes

    Directory of Open Access Journals (Sweden)

    Uchikoga Nobuyuki

    2010-05-01

    Full Text Available Abstract Background Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. Results To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG, CaM kinase kinase (CaMKK and the plasma membrane Ca2+ ATPase pump (PMCA, and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. Conclusions The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

  2. Camouflage, Concealment, and Decoys

    Science.gov (United States)

    2010-11-26

    otherwise dull Note. Use canned milk or powdered eggs to increase the binding properties of field-expedient paints. RADAR-ABSORBING MATERIAL 3-72. RAM... falsification of evidence, inducing him to react in a manner prejudicial to his interests. decoy An imitation in any sense of a person, an object

  3. Decoy State Quantum Key Distribution

    Science.gov (United States)

    Lo, Hoi-Kwong

    2005-10-01

    Quantum key distribution (QKD) allows two parties to communicate in absolute security based on the fundamental laws of physics. Up till now, it is widely believed that unconditionally secure QKD based on standard Bennett-Brassard (BB84) protocol is limited in both key generation rate and distance because of imperfect devices. Here, we solve these two problems directly by presenting new protocols that are feasible with only current technology. Surprisingly, our new protocols can make fiber-based QKD unconditionally secure at distances over 100km (for some experiments, such as GYS) and increase the key generation rate from O(η2) in prior art to O(η) where η is the overall transmittance. Our method is to develop the decoy state idea (first proposed by W.-Y. Hwang in "Quantum Key Distribution with High Loss: Toward Global Secure Communication", Phys. Rev. Lett. 91, 057901 (2003)) and consider simple extensions of the BB84 protocol. This part of work is published in "Decoy State Quantum Key Distribution", . We present a general theory of the decoy state protocol and propose a decoy method based on only one signal state and two decoy states. We perform optimization on the choice of intensities of the signal state and the two decoy states. Our result shows that a decoy state protocol with only two types of decoy states--a vacuum and a weak decoy state--asymptotically approaches the theoretical limit of the most general type of decoy state protocols (with an infinite number of decoy states). We also present a one-decoy-state protocol as a special case of Vacuum+Weak decoy method. Moreover, we provide estimations on the effects of statistical fluctuations and suggest that, even for long distance (larger than 100km) QKD, our two-decoy-state protocol can be implemented with only a few hours of experimental data. In conclusion, decoy state quantum key distribution is highly practical. This part of work is published in "Practical Decoy State for Quantum Key Distribution

  4. Heparin octasaccharide decoy liposomes inhibit replication of multiple viruses

    Science.gov (United States)

    Hendricks, Gabriel L.; Velazquez, Lourdes; Pham, Serena; Qaisar, Natasha; Delaney, James C.; Viswanathan, Karthik; Albers, Leila; Comolli, James C.; Shriver, Zachary; Knipe, David M.; Kurt-Jones, Evelyn A.; Fygenson, Deborah K.; Trevejo, Jose M.

    2016-01-01

    Heparan sulfate (HS) is a ubiquitous glycosaminoglycan that serves as a cellular attachment site for a number of significant human pathogens, including respiratory syncytial virus (RSV), human parainfluenza virus 3 (hPIV3), and herpes simplex virus (HSV). Decoy receptors can target pathogens by binding to the receptor pocket on viral attachment proteins, acting as ‘molecular sinks’ and preventing the pathogen from binding to susceptible host cells. Decoy receptors functionalized with HS could bind to pathogens and prevent infection, so we generated decoy liposomes displaying HS-octasaccharide (HS-octa). These decoy liposomes significantly inhibited RSV, hPIV3, and HSV infectivity in vitro to a greater degree than the original HS-octa building block. The degree of inhibition correlated with the density of HS-octa displayed on the liposome surface. Decoy liposomes with HS-octa inhibited infection of viruses to a greater extent than either full-length heparin or HS-octa alone. Decoy liposomes were effective when added prior to infection or following the initial infection of cells in vitro. By targeting the well-conserved receptor-binding sites of HS-binding viruses, decoy liposomes functionalized with HS-octa are a promising therapeutic antiviral agent and illustrate the utility of the liposome delivery platform. PMID:25637710

  5. Tracking the decoy: Maximizing the decoy effect through sequential experimentation

    NARCIS (Netherlands)

    Kaptein, M.C.; Emden, R. van; Iannuzzi, D.

    2016-01-01

    The decoy effect is one of the best known human biases violating rational choice theory. According to a large body of literature, people may be persuaded to switch from one offer to another by the presence of a third option (the decoy) that, rationally, should have no influence on the

  6. Tracking the decoy : Maximizing the decoy effect through sequential experimentation

    NARCIS (Netherlands)

    Kaptein, M.C; Van Emden, Robin; Iannuzzi, Davide

    2016-01-01

    The decoy effect is one of the best known human biases violating rational choice theory. According to a large body of literature, people may be persuaded to switch from one offer to another by the presence of a third option (the decoy) that, rationally, should have no influence on the

  7. Tracking the decoy: maximizing the decoy effect through sequential experimentation

    NARCIS (Netherlands)

    Kaptein, M.C.; van Emden, R.; Iannuzzi, D.

    2016-01-01

    The decoy effect is one of the best known human biases violating rational choice theory. According to a large body of literature, people may be persuaded to switch from one offer to another by the presence of a third option (the decoy) that, rationally, should have no influence on the

  8. Assessment of semiempirical enthalpy of formation in solution as an effective energy function to discriminate native-like structures in protein decoy sets.

    Science.gov (United States)

    Urquiza-Carvalho, Gabriel Aires; Fragoso, Wallace Duarte; Rocha, Gerd Bruno

    2016-08-05

    In this work, we tested the PM6, PM6-DH+, PM6-D3, and PM7 enthalpies of formation in aqueous solution as scoring functions across 33 decoy sets to discriminate native structures or good models in a decoy set. In each set these semiempirical quantum chemistry methods were compared according to enthalpic and geometric criteria. Enthalpically, we compared the methods according to how much lower was the enthalpy of each native, when compared with the mean enthalpy of its set. Geometrically, we compared the methods according to the fraction of native contacts (Q), which is a measure of geometric closeness between an arbitrary structure and the native. For each set and method, the Q of the best decoy was compared with the Q0 , which is the Q of the decoy closest to the native in the set. It was shown that the PM7 method is able to assign larger energy differences between the native structure and the decoys in a set, arguably because of a better description of dispersion interactions, however PM6-DH+ was slightly better than the rest at selecting geometrically good models in the absence of a native structure in the set. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  9. Identification of Top-ranked Proteins within a Directional Protein Interaction Network using the PageRank Algorithm: Applications in Humans and Plants.

    Science.gov (United States)

    Li, Xiu-Qing; Xing, Tim; Du, Donglei

    2016-01-01

    Somatic mutation of signal transduction genes or key nodes of the cellular protein network can cause severe diseases in humans but can sometimes genetically improve plants, likely because growth is determinate in animals but indeterminate in plants. This article reviews protein networks; human protein ranking; the mitogen-activated protein kinase (MAPK) and insulin (phospho- inositide 3kinase [PI3K]/phosphatase and tensin homolog [PTEN]/protein kinase B [AKT]) signaling pathways; human diseases caused by somatic mutations to the PI3K/PTEN/ AKT pathway; use of the MAPK pathway in plant molecular breeding; and protein domain evolution. Casitas B-lineage lymphoma (CBL), PTEN, MAPK1 and PIK3CA are among PIK3CA the top-ranked proteins in directional rankings. Eight proteins (ACVR1, CDC42, RAC1, RAF1, RHOA, TGFBR1, TRAF2, and TRAF6) are ranked in the top 50 key players in both signal emission and signal reception and in interaction with many other proteins. Top-ranked proteins likely have major impacts on the network function. Such proteins are targets for drug discovery, because their mutations are implicated in various cancers and overgrowth syndromes. Appropriately managing food intake may help reduce the growth of tumors or malformation of tissues. The role of the protein kinase C/ fatty acid synthase pathway in fat deposition in PTEN/PI3K patients should be investigated. Both the MAPK and insulin signaling pathways exist in plants, and MAPK pathway engineering can improve plant tolerance to biotic and abiotic stresses such as salinity.

  10. Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

    Directory of Open Access Journals (Sweden)

    Donglei Du

    Full Text Available Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A What is the general difference between signal emitting and receiving in a protein interactome? B Which proteins are among the top ranked in directional ranking? C Are high ranked proteins more evolutionarily conserved than low ranked ones? D Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

  11. Systematic differences in signal emitting and receiving revealed by PageRank analysis of a human protein interactome.

    Science.gov (United States)

    Du, Donglei; Lee, Connie F; Li, Xiu-Qing

    2012-01-01

    Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell.

  12. Protein complex finding and ranking: An application to Alzheimer's ...

    Indian Academy of Sciences (India)

    Pooja Sharma

    2017-07-07

    Jul 7, 2017 ... and a few other model organisms. .... form proteins) affect the protein formation process. Muta- ..... We implemented the ComFiR method in MATLAB run- ning on ..... Van Dongen SM 2001 Graph clustering by flow simulation.

  13. Protein complex finding and ranking: An application to Alzheimer's

    Indian Academy of Sciences (India)

    Protein complexes are known to play a major role in controlling cellular activity in a living being. Identifying complexesfrom raw protein–protein interactions (PPIs) is an important area of research. Earlier work has been limited mostly to yeastand a few other model organisms. Such protein complex identification methods, ...

  14. Identification of Protein Complexes Using Weighted PageRank-Nibble Algorithm and Core-Attachment Structure.

    Science.gov (United States)

    Peng, Wei; Wang, Jianxin; Zhao, Bihai; Wang, Lusheng

    2015-01-01

    Protein complexes play a significant role in understanding the underlying mechanism of most cellular functions. Recently, many researchers have explored computational methods to identify protein complexes from protein-protein interaction (PPI) networks. One group of researchers focus on detecting local dense subgraphs which correspond to protein complexes by considering local neighbors. The drawback of this kind of approach is that the global information of the networks is ignored. Some methods such as Markov Clustering algorithm (MCL), PageRank-Nibble are proposed to find protein complexes based on random walk technique which can exploit the global structure of networks. However, these methods ignore the inherent core-attachment structure of protein complexes and treat adjacent node equally. In this paper, we design a weighted PageRank-Nibble algorithm which assigns each adjacent node with different probability, and propose a novel method named WPNCA to detect protein complex from PPI networks by using weighted PageRank-Nibble algorithm and core-attachment structure. Firstly, WPNCA partitions the PPI networks into multiple dense clusters by using weighted PageRank-Nibble algorithm. Then the cores of these clusters are detected and the rest of proteins in the clusters will be selected as attachments to form the final predicted protein complexes. The experiments on yeast data show that WPNCA outperforms the existing methods in terms of both accuracy and p-value. The software for WPNCA is available at "http://netlab.csu.edu.cn/bioinfomatics/weipeng/WPNCA/download.html".

  15. CLUB-MARTINI: Selecting Favourable Interactions amongst Available Candidates, a Coarse-Grained Simulation Approach to Scoring Docking Decoys.

    Directory of Open Access Journals (Sweden)

    Qingzhen Hou

    Full Text Available Large-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in which proteins interact. In a recent study, we successfully applied coarse-grained molecular dynamics simulations to measure binding free energy for two protein complexes with similar accuracy to full-atomistic simulation, but 500-fold less time consuming. Here, we investigate the efficacy of this approach as a scoring method to identify stable binding conformations from thousands of docking decoys produced by protein docking programs. To test our method, we first applied it to calculate binding free energies of all protein conformations in a CAPRI (Critical Assessment of PRedicted Interactions benchmark dataset, which included over 19000 protein docking solutions for 15 benchmark targets. Based on the binding free energies, we ranked all docking solutions to select the near-native binding modes under the assumption that the native-solutions have lowest binding free energies. In our top 100 ranked structures, for the 'easy' targets that have many near-native conformations, we obtain a strong enrichment of acceptable or better quality structures; for the 'hard' targets without near-native decoys, our method is still able to retain structures which have native binding contacts. Moreover, in our top 10 selections, CLUB-MARTINI shows a comparable performance when compared with other state-of-the-art docking scoring functions. As a proof of concept, CLUB-MARTINI performs remarkably well for many targets and is able to pinpoint near-native binding modes in the top selections. To the best of our knowledge, this is the first time interaction free energy calculated from MD simulations have been used to rank docking solutions at a large scale.

  16. Protein structural model selection by combining consensus and single scoring methods.

    Directory of Open Access Journals (Sweden)

    Zhiquan He

    Full Text Available Quality assessment (QA for predicted protein structural models is an important and challenging research problem in protein structure prediction. Consensus Global Distance Test (CGDT methods assess each decoy (predicted structural model based on its structural similarity to all others in a decoy set and has been proved to work well when good decoys are in a majority cluster. Scoring functions evaluate each single decoy based on its structural properties. Both methods have their merits and limitations. In this paper, we present a novel method called PWCom, which consists of two neural networks sequentially to combine CGDT and single model scoring methods such as RW, DDFire and OPUS-Ca. Specifically, for every pair of decoys, the difference of the corresponding feature vectors is input to the first neural network which enables one to predict whether the decoy-pair are significantly different in terms of their GDT scores to the native. If yes, the second neural network is used to decide which one of the two is closer to the native structure. The quality score for each decoy in the pool is based on the number of winning times during the pairwise comparisons. Test results on three benchmark datasets from different model generation methods showed that PWCom significantly improves over consensus GDT and single scoring methods. The QA server (MUFOLD-Server applying this method in CASP 10 QA category was ranked the second place in terms of Pearson and Spearman correlation performance.

  17. Evaluation of the osteoclastogenic process associated with RANK / RANK-L / OPG in odontogenic myxomas

    Science.gov (United States)

    González-Galván, María del Carmen; Mosqueda-Taylor, Adalberto; Bologna-Molina, Ronell; Setien-Olarra, Amaia; Marichalar-Mendia, Xabier; Aguirre-Urizar, José-Manuel

    2018-01-01

    Background Odontogenic myxoma (OM) is a benign intraosseous neoplasm that exhibits local aggressiveness and high recurrence rates. Osteoclastogenesis is an important phenomenon in the tumor growth of maxillary neoplasms. RANK (Receptor Activator of Nuclear Factor κappa B) is the signaling receptor of RANK-L (Receptor activator of nuclear factor kappa-Β ligand) that activates the osteoclasts. OPG (osteoprotegerin) is a decoy receptor for RANK-L that inhibits pro-osteoclastogenesis. The RANK / RANKL / OPG system participates in the regulation of osteolytic activity under normal conditions, and its alteration has been associated with greater bone destruction, and also with tumor growth. Objectives To analyze the immunohistochemical expression of OPG, RANK and RANK-L proteins in odontogenic myxomas (OMs) and their relationship with the tumor size. Material and Methods Eighteen OMs, 4 small ( 3cm) and 18 dental follicles (DF) that were included as control were studied by means of standard immunohistochemical procedure with RANK, RANKL and OPG antibodies. For the evaluation, 5 fields (40x) of representative areas of OM and DF were selected where the expression of each antibody was determined. Descriptive and comparative statistical analyses were performed with the obtained data. Results There are significant differences in the expression of RANK in OM samples as compared to DF (p = 0.022) and among the OMSs and OMLs (p = 0.032). Also a strong association is recognized in the expression of RANK-L and OPG in OM samples. Conclusions Activation of the RANK / RANK-L / OPG triad seems to be involved in the mechanisms of bone balance and destruction, as well as associated with tumor growth in odontogenic myxomas. Key words:Odontogenic myxoma, dental follicle, RANK, RANK-L, OPG, osteoclastogenesis. PMID:29680857

  18. Ranking multiple docking solutions based on the conservation of inter-residue contacts

    KAUST Repository

    Oliva, Romina M.

    2013-06-17

    Molecular docking is the method of choice for investigating the molecular basis of recognition in a large number of functional protein complexes. However, correctly scoring the obtained docking solutions (decoys) to rank native-like (NL) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First it calculates a conservation rate for each inter-residue contact, then it ranks decoys according to their ability to match the more frequently observed contacts. We applied CONSRANK to 102 targets from three different benchmarks, RosettaDock, DOCKGROUND, and Critical Assessment of PRedicted Interactions (CAPRI). The method performs consistently well, both in terms of NL solutions ranked in the top positions and of values of the area under the receiver operating characteristic curve. Its ideal application is to solutions coming from different docking programs and procedures, as in the case of CAPRI targets. For all the analyzed CAPRI targets where a comparison is feasible, CONSRANK outperforms the CAPRI scorers. The fraction of NL solutions in the top ten positions in the RosettaDock, DOCKGROUND, and CAPRI benchmarks is enriched on average by a factor of 3.0, 1.9, and 9.9, respectively. Interestingly, CONSRANK is also able to specifically single out the high/medium quality (HMQ) solutions from the docking decoys ensemble: it ranks 46.2 and 70.8% of the total HMQ solutions available for the RosettaDock and CAPRI targets, respectively, within the top 20 positions. © 2013 Wiley Periodicals, Inc.

  19. 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.

  20. Detector decoy quantum key distribution

    International Nuclear Information System (INIS)

    Moroder, Tobias; Luetkenhaus, Norbert; Curty, Marcos

    2009-01-01

    Photon number resolving detectors can enhance the performance of many practical quantum cryptographic setups. In this paper, we employ a simple method to estimate the statistics provided by such a photon number resolving detector using only a threshold detector together with a variable attenuator. This idea is similar in spirit to that of the decoy state technique, and is especially suited to those scenarios where only a few parameters of the photon number statistics of the incoming signals have to be estimated. As an illustration of the potential applicability of the method in quantum communication protocols, we use it to prove security of an entanglement-based quantum key distribution scheme with an untrusted source without the need for a squash model and by solely using this extra idea. In this sense, this detector decoy method can be seen as a different conceptual approach to adapt a single-photon security proof to its physical, full optical implementation. We show that in this scenario, the legitimate users can now even discard the double click events from the raw key data without compromising the security of the scheme, and we present simulations on the performance of the BB84 and the 6-state quantum key distribution protocols.

  1. Inhibition of androgen receptor by decoy molecules delays progression to castration-recurrent prostate cancer.

    Directory of Open Access Journals (Sweden)

    Jae-Kyung Myung

    Full Text Available Androgen receptor (AR is a member of the steroid receptor family and a therapeutic target for all stages of prostate cancer. AR is activated by ligand binding within its C-terminus ligand-binding domain (LBD. Here we show that overexpression of the AR NTD to generate decoy molecules inhibited both the growth and progression of prostate cancer in castrated hosts. Specifically, it was shown that lentivirus delivery of decoys delayed hormonal progression in castrated hosts as indicated by increased doubling time of tumor volume, prolonged time to achieve pre-castrate levels of serum prostate-specific antigen (PSA and PSA nadir. These clinical parameters are indicative of delayed hormonal progression and improved therapeutic response and prognosis. Decoys reduced the expression of androgen-regulated genes that correlated with reduced in situ interaction of the AR with androgen response elements. Decoys did not reduce levels of AR protein or prevent nuclear localization of the AR. Nor did decoys interact directly with the AR. Thus decoys did not inhibit AR transactivation by a dominant negative mechanism. This work provides evidence that the AR NTD plays an important role in the hormonal progression of prostate cancer and supports the development of AR antagonists that target the AR NTD.

  2. Using a consensus approach based on the conservation of inter-residue contacts to rank CAPRI models

    KAUST Repository

    Vangone, Anna; Cavallo, Luigi; Oliva, Romina M.

    2013-01-01

    Herein we propose the use of a consensus approach, CONSRANK, for ranking CAPRI models. CONSRANK relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. Models are ranked according to their ability to match the most

  3. Improved efficacy of soluble human receptor activator of nuclear factor kappa B (RANK) fusion protein by site-directed mutagenesis.

    Science.gov (United States)

    Son, Young Jun; Han, Jihye; Lee, Jae Yeon; Kim, HaHyung; Chun, Taehoon

    2015-06-01

    Soluble human receptor activator of nuclear factor kappa B fusion immunoglobulin (hRANK-Ig) has been considered as one of the therapeutic agents to treat osteoporosis or diseases associated with bone destruction by blocking the interaction between RANK and the receptor activator of nuclear factor kappa B ligand (RANKL). However, no scientific record showing critical amino acid residues within the structural interface between the human RANKL and RANK complex is yet available. In this study, we produced several mutants of hRANK-Ig by replacement of amino acid residue(s) and tested whether the mutants had increased binding affinity to human RANKL. Based on the results from flow cytometry and surface plasmon resonance analyses, the replacement of E(125) with D(125), or E(125) and C(127) with D(125) and F(127) within loop 3 of cysteine-rich domain 3 of hRANK-Ig increases binding affinity to human RANKL over the wild-type hRANK-Ig. This result may provide the first example of improvement in the efficacy of hRANK-Ig by protein engineering and may give additional information to understand a more defined structural interface between hRANK and RANKL.

  4. Using hierarchical clustering of secreted protein families to classify and rank candidate effectors of rust fungi.

    Directory of Open Access Journals (Sweden)

    Diane G O Saunders

    Full Text Available Rust fungi are obligate biotrophic pathogens that cause considerable damage on crop plants. Puccinia graminis f. sp. tritici, the causal agent of wheat stem rust, and Melampsora larici-populina, the poplar leaf rust pathogen, have strong deleterious impacts on wheat and poplar wood production, respectively. Filamentous pathogens such as rust fungi secrete molecules called disease effectors that act as modulators of host cell physiology and can suppress or trigger host immunity. Current knowledge on effectors from other filamentous plant pathogens can be exploited for the characterisation of effectors in the genome of recently sequenced rust fungi. We designed a comprehensive in silico analysis pipeline to identify the putative effector repertoire from the genome of two plant pathogenic rust fungi. The pipeline is based on the observation that known effector proteins from filamentous pathogens have at least one of the following properties: (i contain a secretion signal, (ii are encoded by in planta induced genes, (iii have similarity to haustorial proteins, (iv are small and cysteine rich, (v contain a known effector motif or a nuclear localization signal, (vi are encoded by genes with long intergenic regions, (vii contain internal repeats, and (viii do not contain PFAM domains, except those associated with pathogenicity. We used Markov clustering and hierarchical clustering to classify protein families of rust pathogens and rank them according to their likelihood of being effectors. Using this approach, we identified eight families of candidate effectors that we consider of high value for functional characterization. This study revealed a diverse set of candidate effectors, including families of haustorial expressed secreted proteins and small cysteine-rich proteins. This comprehensive classification of candidate effectors from these devastating rust pathogens is an initial step towards probing plant germplasm for novel resistance components.

  5. Epstein-Barr virus-encoded BARF1 protein is a decoy receptor for macrophage colony stimulating factor and interferes with macrophage differentiation and activation

    NARCIS (Netherlands)

    Hoebe, Eveline K.; Le Large, Tessa Y. S.; Tarbouriech, Nicolas; Oosterhoff, Dinja; de Gruijl, Tanja D.; Middeldorp, Jaap M.; Greijer, Astrid E.

    2012-01-01

    Epstein-Barr virus (EBV), like many other persistent herpes viruses, has acquired numerous mechanisms for subverting or evading immune surveillance. This study investigates the role of secreted EBV-encoded BARF1 protein (sBARF1) in creating an immune evasive microenvironment. Wild-type consensus

  6. Ranking multiple docking solutions based on the conservation of inter-residue contacts

    KAUST Repository

    Oliva, Romina M.; Vangone, Anna; Cavallo, Luigi

    2013-01-01

    ) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First

  7. Structure and decoy-mediated inhibition of the SOX18/Prox1-DNA interaction.

    Science.gov (United States)

    Klaus, Miriam; Prokoph, Nina; Girbig, Mathias; Wang, Xuecong; Huang, Yong-Heng; Srivastava, Yogesh; Hou, Linlin; Narasimhan, Kamesh; Kolatkar, Prasanna R; Francois, Mathias; Jauch, Ralf

    2016-05-05

    The transcription factor (TF) SOX18 drives lymphatic vessel development in both embryogenesis and tumour-induced neo-lymphangiogenesis. Genetic disruption of Sox18 in a mouse model protects from tumour metastasis and established the SOX18 protein as a molecular target. Here, we report the crystal structure of the SOX18 DNA binding high-mobility group (HMG) box bound to a DNA element regulating Prox1 transcription. The crystals diffracted to 1.75Å presenting the highest resolution structure of a SOX/DNA complex presently available revealing water structure, structural adjustments at the DNA contact interface and non-canonical conformations of the DNA backbone. To explore alternatives to challenging small molecule approaches for targeting the DNA-binding activity of SOX18, we designed a set of five decoys based on modified Prox1-DNA. Four decoys potently inhibited DNA binding of SOX18 in vitro and did not interact with non-SOX TFs. Serum stability, nuclease resistance and thermal denaturation assays demonstrated that a decoy circularized with a hexaethylene glycol linker and terminal phosphorothioate modifications is most stable. This SOX decoy also interfered with the expression of a luciferase reporter under control of a SOX18-dependent VCAM1 promoter in COS7 cells. Collectively, we propose SOX decoys as potential strategy for inhibiting SOX18 activity to disrupt tumour-induced neo-lymphangiogenesis. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. DecoyFinder: an easy-to-use python GUI application for building target-specific decoy sets.

    Science.gov (United States)

    Cereto-Massagué, Adrià; Guasch, Laura; Valls, Cristina; Mulero, Miquel; Pujadas, Gerard; Garcia-Vallvé, Santiago

    2012-06-15

    Decoys are molecules that are presumed to be inactive against a target (i.e. will not likely bind to the target) and are used to validate the performance of molecular docking or a virtual screening workflow. The Directory of Useful Decoys database (http://dud.docking.org/) provides a free directory of decoys for use in virtual screening, though it only contains a limited set of decoys for 40 targets.To overcome this limitation, we have developed an application called DecoyFinder that selects, for a given collection of active ligands of a target, a set of decoys from a database of compounds. Decoys are selected if they are similar to active ligands according to five physical descriptors (molecular weight, number of rotational bonds, total hydrogen bond donors, total hydrogen bond acceptors and the octanol-water partition coefficient) without being chemically similar to any of the active ligands used as an input (according to the Tanimoto coefficient between MACCS fingerprints). To the best of our knowledge, DecoyFinder is the first application designed to build target-specific decoy sets. A complete description of the software is included on the application home page. A validation of DecoyFinder on 10 DUD targets is provided as Supplementary Table S1. DecoyFinder is freely available at http://URVnutrigenomica-CTNS.github.com/DecoyFinder.

  9. Myc Decoy Oligodeoxynucleotide Inhibits Growth and Modulates Differentiation of Mouse Embryonic Stem Cells as a Model of Cancer Stem Cells.

    Science.gov (United States)

    Johari, Behrooz; Ebrahimi-Rad, Mina; Maghsood, Faezeh; Lotfinia, Majid; Saltanatpouri, Zohreh; Teimoori-Toolabi, Ladan; Sharifzadeh, Zahra; Karimipoor, Morteza; Kadivar, Mehdi

    2017-01-01

    Myc (c-Myc) alone activates the embryonic stem cell-like transcriptional module in both normal and transformed cells. Its dysregulation might lead to increased cancer stem cells (CSCs) population in some tumor cells. In order to investigate the potential of Myc decoy oligodeoxynucleotides for differentiation therapy, mouse embryonic stem cells (mESCs) were used in this study as a model of CSCs. To our best of knowledge this is the first report outlining the application of Myc decoy in transcription factor decoy "TFD" strategy for inducing differentiation in mESCs. A 20-mer double-stranded Myc transcription factor decoy and scrambled oligodeoxynucleotides (ODNs) were designed, analyzed by electrophoretic mobility shift (EMSA) assay and transfected into the mESCs under 2 inhibitors (2i) condition. Further investigations were carried out using fluorescence and confocal microscopy, cell proliferation and apoptosis analysis, alkaline phosphatase and embryoid body formation assay, real-time PCR and western blotting. EMSA data showed that Myc decoy ODNs bound specifically to c-Myc protein. They were found to be localized in both cytoplasm and nucleus of mESCs. Our results revealed the potential capability of Myc decoy ODNs to decrease cell viability by (16.1±2%), to increase the number of cells arrested in G0/G1 phases and apoptosis by (14.2±3.1%) and (12.1±3.2%), respectively regarding the controls. Myc decoy could also modulate differentiation in mESCs despite the presence of 2i/LIF in our medium the presence of 2i/LIF in our medium. The optimized Myc decoy ODNs approach might be considered as a promising alternative strategy for differentiation therapy investigations. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  10. Protein structure modelling and evaluation based on a 4-distance description of side-chain interactions

    Directory of Open Access Journals (Sweden)

    Inbar Yuval

    2010-07-01

    Full Text Available Abstract Background Accurate evaluation and modelling of residue-residue interactions within and between proteins is a key aspect of computational structure prediction including homology modelling, protein-protein docking, refinement of low-resolution structures, and computational protein design. Results Here we introduce a method for accurate protein structure modelling and evaluation based on a novel 4-distance description of residue-residue interaction geometry. Statistical 4-distance preferences were extracted from high-resolution protein structures and were used as a basis for a knowledge-based potential, called Hunter. We demonstrate that 4-distance description of side chain interactions can be used reliably to discriminate the native structure from a set of decoys. Hunter ranked the native structure as the top one in 217 out of 220 high-resolution decoy sets, in 25 out of 28 "Decoys 'R' Us" decoy sets and in 24 out of 27 high-resolution CASP7/8 decoy sets. The same concept was applied to side chain modelling in protein structures. On a set of very high-resolution protein structures the average RMSD was 1.47 Å for all residues and 0.73 Å for buried residues, which is in the range of attainable accuracy for a model. Finally, we show that Hunter performs as good or better than other top methods in homology modelling based on results from the CASP7 experiment. The supporting web site http://bioinfo.weizmann.ac.il/hunter/ was developed to enable the use of Hunter and for visualization and interactive exploration of 4-distance distributions. Conclusions Our results suggest that Hunter can be used as a tool for evaluation and for accurate modelling of residue-residue interactions in protein structures. The same methodology is applicable to other areas involving high-resolution modelling of biomolecules.

  11. Colostrum and milk protein rankings and ratios of importance to neonatal calf health using a proteomics approach

    DEFF Research Database (Denmark)

    Nissen, Asger; Andersen, Pia Haubro; Bendixen, Emøke

    2017-01-01

    Administration of colostrum to the newborn calf before gut closure is pivotal to its health, because of the transfer of passive immunity. Traditionally, passive immunity has been attributed to the transfer of immunoglobulins although it is increasingly clear that multiple other factors contribute......, including innate immune proteins, developmental factors, immunomodulatory factors, and the presence of cellular immunity. The objective of this study was to produce a comprehensive comparison of the bovine colostrum proteome and the milk proteome by applying 2-dimensional liquid chromatography-tandem mass...... spectrometry. Further, the objectives were to rank proteins mutually and generate protein ratios from the spectral counts of the 2 proteomes and ELISA to gain insight into which proteins could be of most relevance to neonatal calf health. To obtain an in-depth picture of the bovine colostrum and milk proteome...

  12. Adenovirus-Mediated Delivery of Decoy Hyper Binding Sites Targeting Oncogenic HMGA1 Reduces Pancreatic and Liver Cancer Cell Viability.

    Science.gov (United States)

    Hassan, Faizule; Ni, Shuisong; Arnett, Tyler C; McKell, Melanie C; Kennedy, Michael A

    2018-03-30

    High mobility group AT-hook 1 (HMGA1) protein is an oncogenic architectural transcription factor that plays an essential role in early development, but it is also implicated in many human cancers. Elevated levels of HMGA1 in cancer cells cause misregulation of gene expression and are associated with increased cancer cell proliferation and increased chemotherapy resistance. We have devised a strategy of using engineered viruses to deliver decoy hyper binding sites for HMGA1 to the nucleus of cancer cells with the goal of sequestering excess HMGA1 at the decoy hyper binding sites due to binding competition. Sequestration of excess HMGA1 at the decoy binding sites is intended to reduce HMGA1 binding at the naturally occurring genomic HMGA1 binding sites, which should result in normalized gene expression and restored sensitivity to chemotherapy. As proof of principle, we engineered the replication defective adenovirus serotype 5 genome to contain hyper binding sites for HMGA1 composed of six copies of an individual HMGA1 binding site, referred to as HMGA-6. A 70%-80% reduction in cell viability and increased sensitivity to gemcitabine was observed in five different pancreatic and liver cancer cell lines 72 hr after infection with replication defective engineered adenovirus serotype 5 virus containing the HMGA-6 decoy hyper binding sites. The decoy hyper binding site strategy should be general for targeting overexpression of any double-stranded DNA-binding oncogenic transcription factor responsible for cancer cell proliferation.

  13. D3R Grand Challenge 2: blind prediction of protein-ligand poses, affinity rankings, and relative binding free energies

    Science.gov (United States)

    Gaieb, Zied; Liu, Shuai; Gathiaka, Symon; Chiu, Michael; Yang, Huanwang; Shao, Chenghua; Feher, Victoria A.; Walters, W. Patrick; Kuhn, Bernd; Rudolph, Markus G.; Burley, Stephen K.; Gilson, Michael K.; Amaro, Rommie E.

    2018-01-01

    The Drug Design Data Resource (D3R) ran Grand Challenge 2 (GC2) from September 2016 through February 2017. This challenge was based on a dataset of structures and affinities for the nuclear receptor farnesoid X receptor (FXR), contributed by F. Hoffmann-La Roche. The dataset contained 102 IC50 values, spanning six orders of magnitude, and 36 high-resolution co-crystal structures with representatives of four major ligand classes. Strong global participation was evident, with 49 participants submitting 262 prediction submission packages in total. Procedurally, GC2 mimicked Grand Challenge 2015 (GC2015), with a Stage 1 subchallenge testing ligand pose prediction methods and ranking and scoring methods, and a Stage 2 subchallenge testing only ligand ranking and scoring methods after the release of all blinded co-crystal structures. Two smaller curated sets of 18 and 15 ligands were developed to test alchemical free energy methods. This overview summarizes all aspects of GC2, including the dataset details, challenge procedures, and participant results. We also consider implications for progress in the field, while highlighting methodological areas that merit continued development. Similar to GC2015, the outcome of GC2 underscores the pressing need for methods development in pose prediction, particularly for ligand scaffolds not currently represented in the Protein Data Bank (http://www.pdb.org), and in affinity ranking and scoring of bound ligands.

  14. Recognizing protein–protein interfaces with empirical potentials and reduced amino acid alphabets

    Directory of Open Access Journals (Sweden)

    Wodak Shoshana

    2007-07-01

    Full Text Available Abstract Background In structural genomics, an important goal is the detection and classification of protein–protein interactions, given the structures of the interacting partners. We have developed empirical energy functions to identify native structures of protein–protein complexes among sets of decoy structures. To understand the role of amino acid diversity, we parameterized a series of functions, using a hierarchy of amino acid alphabets of increasing complexity, with 2, 3, 4, 6, and 20 amino acid groups. Compared to previous work, we used the simplest possible functional form, with residue–residue interactions and a stepwise distance-dependence. We used increased computational ressources, however, constructing 290,000 decoys for 219 protein–protein complexes, with a realistic docking protocol where the protein partners are flexible and interact through a molecular mechanics energy function. The energy parameters were optimized to correctly assign as many native complexes as possible. To resolve the multiple minimum problem in parameter space, over 64000 starting parameter guesses were tried for each energy function. The optimized functions were tested by cross validation on subsets of our native and decoy structures, by blind tests on series of native and decoy structures available on the Web, and on models for 13 complexes submitted to the CAPRI structure prediction experiment. Results Performance is similar to several other statistical potentials of the same complexity. For example, the CAPRI target structure is correctly ranked ahead of 90% of its decoys in 6 cases out of 13. The hierarchy of amino acid alphabets leads to a coherent hierarchy of energy functions, with qualitatively similar parameters for similar amino acid types at all levels. Most remarkably, the performance with six amino acid classes is equivalent to that of the most detailed, 20-class energy function. Conclusion This suggests that six carefully chosen amino

  15. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

    2015-01-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  16. Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

    KAUST Repository

    Oliva, Romina

    2015-07-01

    In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

  17. GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

    Science.gov (United States)

    You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

    2018-03-07

    Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

  18. Ranking candidate disease genes from gene expression and protein interaction: a Katz-centrality based approach.

    Directory of Open Access Journals (Sweden)

    Jing Zhao

    Full Text Available Many diseases have complex genetic causes, where a set of alleles can affect the propensity of getting the disease. The identification of such disease genes is important to understand the mechanistic and evolutionary aspects of pathogenesis, improve diagnosis and treatment of the disease, and aid in drug discovery. Current genetic studies typically identify chromosomal regions associated specific diseases. But picking out an unknown disease gene from hundreds of candidates located on the same genomic interval is still challenging. In this study, we propose an approach to prioritize candidate genes by integrating data of gene expression level, protein-protein interaction strength and known disease genes. Our method is based only on two, simple, biologically motivated assumptions--that a gene is a good disease-gene candidate if it is differentially expressed in cases and controls, or that it is close to other disease-gene candidates in its protein interaction network. We tested our method on 40 diseases in 58 gene expression datasets of the NCBI Gene Expression Omnibus database. On these datasets our method is able to predict unknown disease genes as well as identifying pleiotropic genes involved in the physiological cellular processes of many diseases. Our study not only provides an effective algorithm for prioritizing candidate disease genes but is also a way to discover phenotypic interdependency, cooccurrence and shared pathophysiology between different disorders.

  19. Rank Dynamics

    Science.gov (United States)

    Gershenson, Carlos

    Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

  20. Regret salience and accountability in the decoy effect

    Directory of Open Access Journals (Sweden)

    Terry Connolly

    2013-03-01

    Full Text Available Two experiments examined the impact on the decoy effect of making salient the possibility of post-decision regret, a manipulation that has been shown in several earlier studies to stimulate critical examination and improvement of decision process. Experiment 1 (N = 62 showed that making regret salient eliminated the decoy effect in a personal preference task. Experiment 2 (N = 242 replicated this finding for a different personal preference task and for a prediction task. It also replicated previous findings that external accountability demands do not reduce, and may exacerbate, the decoy effect. We interpret both effects in terms of decision justification, with different justification standards operating for different audiences. The decoy effect, in this account, turns on accepting a weak justification, which may be seen as adequate for an external audience or one's own inattentive self but inadequate under the more critical review triggered by making regret possibilities salient. Seeking justification to others (responding to accountability demands thus maintains or exacerbates the decoy effect; seeking justification to oneself (responding to regret salience reduces or eliminates it. The proposed mechanism provides a theoretical account both of the decoy effect itself and of how regret priming provides an effective debiasing procedure for it.

  1. Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

    Science.gov (United States)

    da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

    2018-01-01

    A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

  2. IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking.

    Science.gov (United States)

    Su, Chinh; Nguyen, Thuy-Diem; Zheng, Jie; Kwoh, Chee-Keong

    2014-01-01

    Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near

  3. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Directory of Open Access Journals (Sweden)

    Dániel Bánky

    Full Text Available Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks that compensates for the low degree (non-hub vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well, but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus, and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures

  4. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Science.gov (United States)

    Bánky, Dániel; Iván, Gábor; Grolmusz, Vince

    2013-01-01

    Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks) that compensates for the low degree (non-hub) vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges) of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well), but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus), and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures importance in the

  5. Twin Screw Extruder Production of MTTP Decoy Flares SERDP WP-1240

    National Research Council Canada - National Science Library

    Campbell, Carol

    2005-01-01

    The objective of this effort is to develop an environmentally acceptable decoy flare formulation and process to produce aircraft decoy flares without the use of HAP or Volatile Organic Compounds (VOC...

  6. Lipid-modified G4-decoy oligonucleotide anchored to nanoparticles

    DEFF Research Database (Denmark)

    Cogoi, S; Jakobsen, U; Pedersen, E B

    2016-01-01

    KRAS is mutated in >90% of pancreatic ductal adenocarcinomas. As its inactivation leads to tumour regression, mutant KRAS is considered an attractive target for anticancer drugs. In this study we report a new delivery strategy for a G4-decoy oligonucleotide that sequesters MAZ, a transcription fa...

  7. Decoys Selection in Benchmarking Datasets: Overview and Perspectives

    Science.gov (United States)

    Réau, Manon; Langenfeld, Florent; Zagury, Jean-François; Lagarde, Nathalie; Montes, Matthieu

    2018-01-01

    Virtual Screening (VS) is designed to prospectively help identifying potential hits, i.e., compounds capable of interacting with a given target and potentially modulate its activity, out of large compound collections. Among the variety of methodologies, it is crucial to select the protocol that is the most adapted to the query/target system under study and that yields the most reliable output. To this aim, the performance of VS methods is commonly evaluated and compared by computing their ability to retrieve active compounds in benchmarking datasets. The benchmarking datasets contain a subset of known active compounds together with a subset of decoys, i.e., assumed non-active molecules. The composition of both the active and the decoy compounds subsets is critical to limit the biases in the evaluation of the VS methods. In this review, we focus on the selection of decoy compounds that has considerably changed over the years, from randomly selected compounds to highly customized or experimentally validated negative compounds. We first outline the evolution of decoys selection in benchmarking databases as well as current benchmarking databases that tend to minimize the introduction of biases, and secondly, we propose recommendations for the selection and the design of benchmarking datasets. PMID:29416509

  8. Towards creating believable decoy project folders for detecting data theft

    NARCIS (Netherlands)

    Thaler, S.; den Hartog, J.; Petkovic, M.

    2016-01-01

    Digital data theft is difficult to detect and typically it also takes a long time to discover that data has been stolen. This paper introduces a data-driven approach based on Markov chains to create believable decoy project folders which can assist in detecting potentially ongoing attacks. This can

  9. Binding free energy analysis of protein-protein docking model structures by evERdock.

    Science.gov (United States)

    Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

    2018-03-14

    To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

  10. Protein model discrimination using mutational sensitivity derived from deep sequencing.

    Science.gov (United States)

    Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

    2012-02-08

    A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

  11. University Rankings: The Web Ranking

    Science.gov (United States)

    Aguillo, Isidro F.

    2012-01-01

    The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

  12. A decoy set for the thermostable subdomain from chicken villin headpiece, comparison of different free energy estimators

    Directory of Open Access Journals (Sweden)

    Tosatto Silvio CE

    2005-12-01

    Full Text Available Abstract Background Estimators of free energies are routinely used to judge the quality of protein structural models. As these estimators still present inaccuracies, they are frequently evaluated by discriminating native or native-like conformations from large ensembles of so-called decoy structures. Results A decoy set is obtained from snapshots taken from 5 long (100 ns molecular dynamics (MD simulations of the thermostable subdomain from chicken villin headpiece. An evaluation of the energy of the decoys is given using: i a residue based contact potential supplemented by a term for the quality of dihedral angles; ii a recently introduced combination of four statistical scoring functions for model quality estimation (FRST; iii molecular mechanics with solvation energy estimated either according to the generalized Born surface area (GBSA or iv the Poisson-Boltzmann surface area (PBSA method. Conclusion The decoy set presented here has the following features which make it attractive for testing energy scoring functions: 1 it covers a broad range of RMSD values (from less than 2.0 Å to more than 12 Å; 2 it has been obtained from molecular dynamics trajectories, starting from different non-native-like conformations which have diverse behaviour, with secondary structure elements correctly or incorrectly formed, and in one case folding to a native-like structure. This allows not only for scoring of static structures, but also for studying, using free energy estimators, the kinetics of folding; 3 all structures have been obtained from accurate MD simulations in explicit solvent and after molecular mechanics (MM energy minimization using an implicit solvent method. The quality of the covalent structure therefore does not suffer from steric or covalent problems. The statistical and physical effective energy functions tested on the set behave differently when native simulation snapshots are included or not in the set and when averaging over the

  13. The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text.

    Science.gov (United States)

    Krallinger, Martin; Vazquez, Miguel; Leitner, Florian; Salgado, David; Chatr-Aryamontri, Andrew; Winter, Andrew; Perfetto, Livia; Briganti, Leonardo; Licata, Luana; Iannuccelli, Marta; Castagnoli, Luisa; Cesareni, Gianni; Tyers, Mike; Schneider, Gerold; Rinaldi, Fabio; Leaman, Robert; Gonzalez, Graciela; Matos, Sergio; Kim, Sun; Wilbur, W John; Rocha, Luis; Shatkay, Hagit; Tendulkar, Ashish V; Agarwal, Shashank; Liu, Feifan; Wang, Xinglong; Rak, Rafal; Noto, Keith; Elkan, Charles; Lu, Zhiyong; Dogan, Rezarta Islamaj; Fontaine, Jean-Fred; Andrade-Navarro, Miguel A; Valencia, Alfonso

    2011-10-03

    Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were evaluated by comparing

  14. The Protein-Protein Interaction tasks of BioCreative III: classification/ranking of articles and linking bio-ontology concepts to full text

    Science.gov (United States)

    2011-01-01

    Background Determining usefulness of biomedical text mining systems requires realistic task definition and data selection criteria without artificial constraints, measuring performance aspects that go beyond traditional metrics. The BioCreative III Protein-Protein Interaction (PPI) tasks were motivated by such considerations, trying to address aspects including how the end user would oversee the generated output, for instance by providing ranked results, textual evidence for human interpretation or measuring time savings by using automated systems. Detecting articles describing complex biological events like PPIs was addressed in the Article Classification Task (ACT), where participants were asked to implement tools for detecting PPI-describing abstracts. Therefore the BCIII-ACT corpus was provided, which includes a training, development and test set of over 12,000 PPI relevant and non-relevant PubMed abstracts labeled manually by domain experts and recording also the human classification times. The Interaction Method Task (IMT) went beyond abstracts and required mining for associations between more than 3,500 full text articles and interaction detection method ontology concepts that had been applied to detect the PPIs reported in them. Results A total of 11 teams participated in at least one of the two PPI tasks (10 in ACT and 8 in the IMT) and a total of 62 persons were involved either as participants or in preparing data sets/evaluating these tasks. Per task, each team was allowed to submit five runs offline and another five online via the BioCreative Meta-Server. From the 52 runs submitted for the ACT, the highest Matthew's Correlation Coefficient (MCC) score measured was 0.55 at an accuracy of 89% and the best AUC iP/R was 68%. Most ACT teams explored machine learning methods, some of them also used lexical resources like MeSH terms, PSI-MI concepts or particular lists of verbs and nouns, some integrated NER approaches. For the IMT, a total of 42 runs were

  15. Exploring decoy effects on computerized task preferences in rhesus monkeys (Macaca mulatta.

    Directory of Open Access Journals (Sweden)

    Audrey E. Parrish

    2018-05-01

    Full Text Available The asymmetric dominance effect or decoy effect emerges when a third inferior option is introduced to a choice set. The decoy option, although typically not chosen, impacts relative preference for the original two options. This decisional bias stands in contrast with rational choice theory, which dictates that choice behavior should remain consistent for the original options with the addition of different alternatives to a choice set such as the decoy. In the current study, we assessed the decoy effect in rhesus monkeys using a computerized task battery that introduced two different computerized tasks, including a matching-to-sample task and a psychomotor task called PURSUIT. Decoy tasks were designed such that they were inferior versions of these original task options, requiring longer time to completion (via slowed cursor speeds and subsequently reduced reinforcement rates. Monkeys learned to associate unique icons for each task (including for decoy tasks, and used these icons to select their preferred task from a choice set of two to three task options. Monkeys learned to perform all tasks, but did not show evidence of the decoy effect using this task preference paradigm. We discuss the role of initial task preference (and task biases, task type (symbolic vs. perceptual, and decoy effect sizes in light of these findings. We contrast the current results to previous findings of the decoy effect in rhesus monkeys using a perceptual paradigm as well as to other evidence of the decoy effect in non-primate animal species.

  16. DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

    Directory of Open Access Journals (Sweden)

    Vakser Ilya A

    2011-07-01

    Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

  17. 2006-2008 annual review on aerial infrared decoy flares

    Energy Technology Data Exchange (ETDEWEB)

    Koch, Ernst-Christian [NATO Munitions Safety Information Analysis Center, Brussels (Belgium)

    2009-02-15

    The most recent progress in the field of advanced aerial infrared decoy flare technology is documented. 71 references from the public domain are given. Recently, two reviews on progress in the field of aerial infrared decoy flares have been prepared by the author. The fast development in the field already delayed the preparation of the second report by nearly a year.Hence, the objective of the present paper is to report about recent advances in the field of aerial infrared countermeasures and related topics. The paper treats information published between January, 2005 and September, 30, 2008. Depending on the progress, it is intended to report occasionally in the future about new developments and scientific findings in this field. (Abstract Copyright [2009], Wiley Periodicals, Inc.)

  18. An Effectiveness Analysis of the Tactical Employment of Decoys

    Science.gov (United States)

    1994-06-03

    desert made it impossible to hide the dense concentration of vehicles in the three assembly areas: 1st Armoured Division in Assembly Area (AA) Murrayfield...North, 24th Armoured Brigade in AA Murrayfield South, and 10th Armoured Division in AA Melting Pot. However, an ingenious combination of decoys and...hood, configured to resemble an ammo carrier, was often draped over tanks to disguise thenm12 To reinforce the story that the British main attack would

  19. Effects of towed-decoys against an anti-air missile with a monopulse seeker

    OpenAIRE

    Yeh, Jia-Hsin

    1995-01-01

    This thesis evaluates the protection provided by towed decoys deployed by an aircraft during an engagement against an anti-air missile equipped with a monopulse seeker. The research emphasizes the use of passive decoys. Many of the operational parameters required before the deployment of towed-decoy are investigated, including the strength of reflection, the tether length, the direction of release, under different missile incoming directions. This thesis evaluated two reflection cases. One is...

  20. Antineoplastic Effect of Decoy Oligonucleotide Derived from MGMT Enhancer

    Science.gov (United States)

    Refael, Miri; Zrihan, Daniel; Siegal, Tali; Lavon, Iris

    2014-01-01

    Silencing of O(6)-methylguanine-DNA-methyltransferase (MGMT) in tumors, mainly through promoter methylation, correlates with a better therapeutic response and with increased survival. Therefore, it is conceivable to consider MGMT as a potential therapeutic target for the treatment of cancers. Our previous results demonstrated the pivotal role of NF-kappaB in MGMT expression, mediated mainly through p65/NF-kappaB homodimers. Here we show that the non-canonical NF-KappaB motif (MGMT-kappaB1) within MGMT enhancer is probably the major inducer of MGMT expression following NF-kappaB activation. Thus, in an attempt to attenuate the transcription activity of MGMT in tumors we designed locked nucleic acids (LNA) modified decoy oligonucleotides corresponding to the specific sequence of MGMT-kappaB1 (MGMT-kB1-LODN). Following confirmation of the ability of MGMT-kB1-LODN to interfere with the binding of p65/NF-kappaB to the NF-KappaB motif within MGMT enhancer, the efficacy of the decoy was studied in-vitro and in-vivo. The results of these experiments show that the decoy MGMT-kB1-LODN have a substantial antineoplastic effect when used either in combination with temozolomide or as monotherapy. Our results suggest that MGMT-kB1-LODN may provide a novel strategy for cancer therapy. PMID:25460932

  1. Antineoplastic effect of decoy oligonucleotide derived from MGMT enhancer.

    Directory of Open Access Journals (Sweden)

    Tamar Canello

    Full Text Available Silencing of O(6-methylguanine-DNA-methyltransferase (MGMT in tumors, mainly through promoter methylation, correlates with a better therapeutic response and with increased survival. Therefore, it is conceivable to consider MGMT as a potential therapeutic target for the treatment of cancers. Our previous results demonstrated the pivotal role of NF-kappaB in MGMT expression, mediated mainly through p65/NF-kappaB homodimers. Here we show that the non-canonical NF-KappaB motif (MGMT-kappaB1 within MGMT enhancer is probably the major inducer of MGMT expression following NF-kappaB activation. Thus, in an attempt to attenuate the transcription activity of MGMT in tumors we designed locked nucleic acids (LNA modified decoy oligonucleotides corresponding to the specific sequence of MGMT-kappaB1 (MGMT-kB1-LODN. Following confirmation of the ability of MGMT-kB1-LODN to interfere with the binding of p65/NF-kappaB to the NF-KappaB motif within MGMT enhancer, the efficacy of the decoy was studied in-vitro and in-vivo. The results of these experiments show that the decoy MGMT-kB1-LODN have a substantial antineoplastic effect when used either in combination with temozolomide or as monotherapy. Our results suggest that MGMT-kB1-LODN may provide a novel strategy for cancer therapy.

  2. Contextual effects and psychological features influencing decoy options: A review and research agenda

    Directory of Open Access Journals (Sweden)

    David Gonzalez-Prieto

    2013-01-01

    Full Text Available Purpose: The purpose of this paper is to develop future research proposals aiming to contribute the extant theory which explains decoy effects.Design/methodology/approach: Firstly, a review of the existing literature about decoy options and its interactions with contextual effects that could affect their performance is presented. Next, two research proposals are presented: the introduction of a double decoy choice set and the evaluation of decoy effect under different levels of cognitive effort in a purchasing process.Findings and Originality/value: For the research proposal concerning double decoy choice sets, different hypothesis are introduced based on the different theories aiming to explain the effect of simple decoy choice sets. This hypothesis predict different outcomes for the same experimental design, fact that could provide further support for at least one of the current explanations for decoy effects. Regarding the effect of decoy options under different levels of cognitive effort, implications for experimental design for sequential purchasing process are expected. Especially for those designed with complex options, with many steps or high number of options.Originality/value: Two new research proposal approaches are presented in order enhance the current theory. Moreover, both have managerial implications concerning the real usage of decoy options in reduced choice sets as well as in sequential purchasing processes.

  3. Inhibition of cyclic AMP response element-directed transcription by decoy oligonucleotides enhances tumor-specific radiosensitivity

    Energy Technology Data Exchange (ETDEWEB)

    Park, Serk In, E-mail: serkin@korea.edu [Department of Biochemistry and Molecular Biology, Korea University College of Medicine, Seoul (Korea, Republic of); The BK21 Plus Program for Biomedical Sciences, Korea University College of Medicine, Seoul (Korea, Republic of); Department of Medicine and Center for Bone Biology, Vanderbilt University School of Medicine, Nashville, TN (United States); Park, Sung-Jun [Department of Biochemistry and Molecular Biology, Korea University College of Medicine, Seoul (Korea, Republic of); Laboratory of Obesity and Aging Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD (United States); Lee, Junghan; Kim, Hye Eun; Park, Su Jin; Sohn, Jeong-Won [Department of Biochemistry and Molecular Biology, Korea University College of Medicine, Seoul (Korea, Republic of); Park, Yun Gyu, E-mail: parkyg@korea.ac.kr [Department of Biochemistry and Molecular Biology, Korea University College of Medicine, Seoul (Korea, Republic of)

    2016-01-15

    The radiation stress induces cytotoxic responses of cell death as well as cytoprotective responses of cell survival. Understanding exact cellular mechanism and signal transduction pathways is important in improving cancer radiotherapy. Increasing evidence suggests that cyclic AMP response element binding protein (CREB)/activating transcription factor (ATF) family proteins act as a survival factor and a signaling molecule in response to stress. We postulated that CREB inhibition via CRE decoy oligonucleotide increases tumor cell sensitization to γ-irradiation-induced cytotoxic stress. In the present study, we demonstrate that CREB phosphorylation and CREB DNA-protein complex formation increased in time- and radiation dose-dependent manners, while there was no significant change in total protein level of CREB. In addition, CREB was phosphorylated in response to γ-irradiation through p38 MAPK pathway. Further investigation revealed that CREB blockade by decoy oligonucleotides functionally inhibited transactivation of CREB, and significantly increased radiosensitivity of multiple human cancer cell lines including TP53- and/or RB-mutated cells with minimal effects on normal cells. We also demonstrate that tumor cells ectopically expressing dominant negative mutant CREB (KCREB) and the cells treated with p38 MAPK inhibitors were more sensitive to γ-irradiation than wild type parental cells or control-treated cells. Taken together, we conclude that CREB protects tumor cells from γ-irradiation, and combination of CREB inhibition plus ionizing radiation will be a promising radiotherapeutic approach. - Highlights: • γ-Irradiation induced CREB phosphorylation and CRE-directed transcription in tumor. • γ-Irradiation-induced transcriptional activation of CREB was via p38 MAPK pathway. • CRE blockade increased radiosensitivity of tumor cells but not of normal cells. • CRE decoy oligonucleotides or p38 MAPK inhibitors can be used as radiosensitizers.

  4. Inhibition of cyclic AMP response element-directed transcription by decoy oligonucleotides enhances tumor-specific radiosensitivity

    International Nuclear Information System (INIS)

    Park, Serk In; Park, Sung-Jun; Lee, Junghan; Kim, Hye Eun; Park, Su Jin; Sohn, Jeong-Won; Park, Yun Gyu

    2016-01-01

    The radiation stress induces cytotoxic responses of cell death as well as cytoprotective responses of cell survival. Understanding exact cellular mechanism and signal transduction pathways is important in improving cancer radiotherapy. Increasing evidence suggests that cyclic AMP response element binding protein (CREB)/activating transcription factor (ATF) family proteins act as a survival factor and a signaling molecule in response to stress. We postulated that CREB inhibition via CRE decoy oligonucleotide increases tumor cell sensitization to γ-irradiation-induced cytotoxic stress. In the present study, we demonstrate that CREB phosphorylation and CREB DNA-protein complex formation increased in time- and radiation dose-dependent manners, while there was no significant change in total protein level of CREB. In addition, CREB was phosphorylated in response to γ-irradiation through p38 MAPK pathway. Further investigation revealed that CREB blockade by decoy oligonucleotides functionally inhibited transactivation of CREB, and significantly increased radiosensitivity of multiple human cancer cell lines including TP53- and/or RB-mutated cells with minimal effects on normal cells. We also demonstrate that tumor cells ectopically expressing dominant negative mutant CREB (KCREB) and the cells treated with p38 MAPK inhibitors were more sensitive to γ-irradiation than wild type parental cells or control-treated cells. Taken together, we conclude that CREB protects tumor cells from γ-irradiation, and combination of CREB inhibition plus ionizing radiation will be a promising radiotherapeutic approach. - Highlights: • γ-Irradiation induced CREB phosphorylation and CRE-directed transcription in tumor. • γ-Irradiation-induced transcriptional activation of CREB was via p38 MAPK pathway. • CRE blockade increased radiosensitivity of tumor cells but not of normal cells. • CRE decoy oligonucleotides or p38 MAPK inhibitors can be used as radiosensitizers.

  5. Using a consensus approach based on the conservation of inter-residue contacts to rank CAPRI models

    KAUST Repository

    Vangone, Anna

    2013-10-17

    Herein we propose the use of a consensus approach, CONSRANK, for ranking CAPRI models. CONSRANK relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. Models are ranked according to their ability to match the most frequently observed contacts. We applied CONSRANK to 19 CAPRI protein-protein targets, covering a wide range of prediction difficulty and involved in a variety of biological functions. CONSRANK results are consistently good, both in terms of native-like (NL) solutions ranked in the top positions and of values of the Area Under the receiver operating characteristic Curve (AUC). For targets having a percentage of NL solutions above 3%, an excellent performance is found, with AUC values approaching 1. For the difficult target T46, having only 3.4% NL solutions, the number of NL solutions in the top 5 and 10 ranked positions is enriched by a factor 30, and the AUC value is as high as 0.997. AUC values below 0.8 are only found for targets featuring a percentage of NL solutions within 1.1%. Remarkably, a false consensus emerges only in one case, T42, which happens to be an artificial protein, whose assembly details remain uncertain, based on controversial experimental data. We also show that CONSRANK still performs very well on a limited number of models, provided that more than 1 NL solution is included in the ensemble, thus extending its applicability to cases where few dozens of models are available.© 2013 Wiley Periodicals, Inc.

  6. Identifying diabetes-related important protein targets with few interacting partners with the PageRank algorithm.

    Science.gov (United States)

    Grolmusz, Vince I

    2015-04-01

    Diabetes is a growing concern for the developed nations worldwide. New genomic, metagenomic and gene-technologic approaches may yield considerable results in the next several years in its early diagnosis, or in advances in therapy and management. In this work, we highlight some human proteins that may serve as new targets in the early diagnosis and therapy. With the help of a very successful mathematical tool for network analysis that formed the basis of the early successes of Google(TM), Inc., we analyse the human protein-protein interaction network gained from the IntAct database with a mathematical algorithm. The novelty of our approach is that the new protein targets suggested do not have many interacting partners (so, they are not hubs or super-hubs), so their inhibition or promotion probably will not have serious side effects. We have identified numerous possible protein targets for diabetes therapy and/or management; some of these have been well known for a long time (these validate our method), some of them appeared in the literature in the last 12 months (these show the cutting edge of the algorithm), and the remainder are still unknown to be connected with diabetes, witnessing completely new hits of the method.

  7. Binding affinity toward human prion protein of some anti-prion compounds - Assessment based on QSAR modeling, molecular docking and non-parametric ranking.

    Science.gov (United States)

    Kovačević, Strahinja; Karadžić, Milica; Podunavac-Kuzmanović, Sanja; Jevrić, Lidija

    2018-01-01

    The present study is based on the quantitative structure-activity relationship (QSAR) analysis of binding affinity toward human prion protein (huPrP C ) of quinacrine, pyridine dicarbonitrile, diphenylthiazole and diphenyloxazole analogs applying different linear and non-linear chemometric regression techniques, including univariate linear regression, multiple linear regression, partial least squares regression and artificial neural networks. The QSAR analysis distinguished molecular lipophilicity as an important factor that contributes to the binding affinity. Principal component analysis was used in order to reveal similarities or dissimilarities among the studied compounds. The analysis of in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) parameters was conducted. The ranking of the studied analogs on the basis of their ADMET parameters was done applying the sum of ranking differences, as a relatively new chemometric method. The main aim of the study was to reveal the most important molecular features whose changes lead to the changes in the binding affinities of the studied compounds. Another point of view on the binding affinity of the most promising analogs was established by application of molecular docking analysis. The results of the molecular docking were proven to be in agreement with the experimental outcome. Copyright © 2017 Elsevier B.V. All rights reserved.

  8. The Decoy Effect as a Nudge: Boosting Hand Hygiene With a Worse Option.

    Science.gov (United States)

    Li, Meng; Sun, Yan; Chen, Hui

    2018-05-01

    This article provides the first test of the decoy effect as a nudge to influence real-world behavior. The decoy effect is the phenomenon that an additional but worse option can boost the appeal of an existing option. It has been widely demonstrated in hypothetical choices, but its usefulness in real-world settings has been subject to debate. In three longitudinal experiments in food-processing factories, we tested two decoy sanitation options that were worse than the existing sanitizer spray bottle. Results showed that the presence of a decoy, but not an additional copy of the original sanitizer bottle in a different color, drastically increased food workers' hand sanitizer use from the original sanitizer bottle and, consequently, improved workers' passing rate in hand sanitary tests from 60% to 70% to above 90% for 20 days. These findings indicate that the decoy effect can be a powerful nudge technique to influence real-world behavior.

  9. Decoy-state quantum key distribution with two-way classical postprocessing

    International Nuclear Information System (INIS)

    Ma Xiongfeng; Fung, C.-H.F.; Chen Kai; Lo, H.-K.; Dupuis, Frederic; Tamaki, Kiyoshi

    2006-01-01

    Decoy states have recently been proposed as a useful method for substantially improving the performance of quantum key distribution (QKD) protocols when a coherent-state source is used. Previously, data postprocessing schemes based on one-way classical communications were considered for use with decoy states. In this paper, we develop two data postprocessing schemes for the decoy-state method using two-way classical communications. Our numerical simulation (using parameters from a specific QKD experiment as an example) results show that our scheme is able to extend the maximal secure distance from 142 km (using only one-way classical communications with decoy states) to 181 km. The second scheme is able to achieve a 10% greater key generation rate in the whole regime of distances. We conclude that decoy-state QKD with two-way classical postprocessing is of practical interest

  10. Fine-scale features on bioreplicated decoys of the emerald ash borer provide necessary visual verisimilitude

    Science.gov (United States)

    Domingue, Michael J.; Pulsifer, Drew P.; Narkhede, Mahesh S.; Engel, Leland G.; Martín-Palma, Raúl J.; Kumar, Jayant; Baker, Thomas C.; Lakhtakia, Akhlesh

    2014-03-01

    The emerald ash borer (EAB), Agrilus planipennis, is an invasive tree-killing pest in North America. Like other buprestid beetles, it has an iridescent coloring, produced by a periodically layered cuticle whose reflectance peaks at 540 nm wavelength. The males perform a visually mediated ritualistic mating flight directly onto females poised on sunlit leaves. We attempted to evoke this behavior using artificial visual decoys of three types. To fabricate decoys of the first type, a polymer sheet coated with a Bragg-stack reflector was loosely stamped by a bioreplicating die. For decoys of the second type, a polymer sheet coated with a Bragg-stack reflector was heavily stamped by the same die and then painted green. Every decoy of these two types had an underlying black absorber layer. Decoys of the third type were produced by a rapid prototyping machine and painted green. Fine-scale features were absent on the third type. Experiments were performed in an American ash forest infested with EAB, and a European oak forest home to a similar pest, the two-spotted oak borer (TSOB), Agrilus biguttatus. When pinned to leaves, dead EAB females, dead TSOB females, and bioreplicated decoys of both types often evoked the complete ritualized flight behavior. Males also initiated approaches to the rapidly prototyped decoy, but would divert elsewhere without making contact. The attraction of the bioreplicated decoys was also demonstrated by providing a high dc voltage across the decoys that stunned and killed approaching beetles. Thus, true bioreplication with fine-scale features is necessary to fully evoke ritualized visual responses in insects, and provides an opportunity for developing insecttrapping technologies.

  11. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

    2014-01-01

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

  12. General Theory of Decoy-State Quantum Cryptography with Dark Count Rate Fluctuation

    International Nuclear Information System (INIS)

    Xiang, Gao; Shi-Hai, Sun; Lin-Mei, Liang

    2009-01-01

    The existing theory of decoy-state quantum cryptography assumes that the dark count rate is a constant, but in practice there exists fluctuation. We develop a new scheme of the decoy state, achieve a more practical key generation rate in the presence of fluctuation of the dark count rate, and compare the result with the result of the decoy-state without fluctuation. It is found that the key generation rate and maximal secure distance will be decreased under the influence of the fluctuation of the dark count rate

  13. Reduced Rank Regression

    DEFF Research Database (Denmark)

    Johansen, Søren

    2008-01-01

    The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

  14. A paralogous decoy protects Phytophthora sojae apoplastic effector PsXEG1 from a host inhibitor.

    Science.gov (United States)

    Ma, Zhenchuan; Zhu, Lin; Song, Tianqiao; Wang, Yang; Zhang, Qi; Xia, Yeqiang; Qiu, Min; Lin, Yachun; Li, Haiyang; Kong, Liang; Fang, Yufeng; Ye, Wenwu; Wang, Yan; Dong, Suomeng; Zheng, Xiaobo; Tyler, Brett M; Wang, Yuanchao

    2017-02-17

    The extracellular space (apoplast) of plant tissue represents a critical battleground between plants and attacking microbes. Here we show that a pathogen-secreted apoplastic xyloglucan-specific endoglucanase, PsXEG1, is a focus of this struggle in the Phytophthora sojae -soybean interaction. We show that soybean produces an apoplastic glucanase inhibitor protein, GmGIP1, that binds to PsXEG1 to block its contribution to virulence. P. sojae , however, secretes a paralogous PsXEG1-like protein, PsXLP1, that has lost enzyme activity but binds to GmGIP1 more tightly than does PsXEG1, thus freeing PsXEG1 to support P. sojae infection. The gene pair encoding PsXEG1 and PsXLP1 is conserved in many Phytophthora species, and the P. parasitica orthologs PpXEG1 and PpXLP1 have similar functions. Thus, this apoplastic decoy strategy may be widely used in Phytophthora pathosystems. Copyright © 2017, American Association for the Advancement of Science.

  15. Comparison of four species of snails as potential decoys to intercept schistosome miracidia.

    Science.gov (United States)

    Laracuente, A; Brown, R A; Jobin, W

    1979-01-01

    Preliminary studies have shown that various species of aquatic snails may be used as decoys or "sponges" to intercept schistosome miracidia, thereby preventing the miracidia from reaching the snails which normally serve as their intermediate host. In this study, four species of snails were evaluated as candidate decoys for field trials: Marisa cornuarietis, Pomacea australis, Helisoma caribaeum, and Tarebia granifera. In the laboratory all four species caused considerable reductions in the proportion of Biomphalaria glabrata infected by miracidia of Schistosoma mansoni. The most effective decoys were M. cornuarietis and H. caribaeum, both of which caused experimental infection levels of 90% to decrease to 25% when five decoy snails were present for each target snail. When ten decoy snails were present for each target snail, the proportion infected decreased to 1%. M. cornuarietis was chosen as the candidate for field trials because it was found more frequently in Puerto Rico than was H. caribaeum. Initial field trials in two ponds showed that M. cornuarietis blocked infections at a ratio of 6 decoys to 1 target snail, confirming the laboratory results. Further studies in flowing water are needed before the technique can be generally evaluated in an endemic area.

  16. Poxvirus-encoded TNF decoy receptors inhibit the biological activity of transmembrane TNF.

    Science.gov (United States)

    Pontejo, Sergio M; Alejo, Ali; Alcami, Antonio

    2015-10-01

    Poxviruses encode up to four different soluble TNF receptors, named cytokine response modifier B (CrmB), CrmC, CrmD and CrmE. These proteins mimic the extracellular domain of the cellular TNF receptors to bind and inhibit the activity of TNF and, in some cases, other TNF superfamily ligands. Most of these ligands are released after the enzymic cleavage of a membrane precursor. However, transmembrane TNF (tmTNF) is not only a precursor of soluble TNF but also exerts specific pro-inflammatory and immunological activities. Here, we report that viral TNF receptors bound and inhibited tmTNF and describe some interesting differences in their activity against the soluble cytokine. Thus, CrmE, which does not inhibit mouse soluble TNF, could block murine tmTNF-induced cytotoxicity. We propose that this anti-tmTNF effect should be taken into consideration when assessing the role of viral TNF decoy receptors in the pathogenesis of poxvirus.

  17. Ranking Operations Management conferences

    NARCIS (Netherlands)

    Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

    2007-01-01

    Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

  18. Sparse structure regularized ranking

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-04-17

    Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

  19. Human Milk Contains Novel Glycans That Are Potential Decoy Receptors for Neonatal Rotaviruses*

    Science.gov (United States)

    Yu, Ying; Lasanajak, Yi; Song, Xuezheng; Hu, Liya; Ramani, Sasirekha; Mickum, Megan L.; Ashline, David J.; Prasad, B. V. Venkataram; Estes, Mary K.; Reinhold, Vernon N.; Cummings, Richard D.; Smith, David F.

    2014-01-01

    Human milk contains a rich set of soluble, reducing glycans whose functions and bioactivities are not well understood. Because human milk glycans (HMGs) have been implicated as receptors for various pathogens, we explored the functional glycome of human milk using shotgun glycomics. The free glycans from pooled milk samples of donors with mixed Lewis and Secretor phenotypes were labeled with a fluorescent tag and separated via multidimensional HPLC to generate a tagged glycan library containing 247 HMG targets that were printed to generate the HMG shotgun glycan microarray (SGM). To investigate the potential role of HMGs as decoy receptors for rotavirus (RV), a leading cause of severe gastroenteritis in children, we interrogated the HMG SGM with recombinant forms of VP8* domains of the RV outer capsid spike protein VP4 from human neonatal strains N155(G10P[11]) and RV3(G3P[6]) and a bovine strain, B223(G10P[11]). Glycans that were bound by RV attachment proteins were selected for detailed structural analyses using metadata-assisted glycan sequencing, which compiles data on each glycan based on its binding by antibodies and lectins before and after exo- and endo-glycosidase digestion of the SGM, coupled with independent MSn analyses. These complementary structural approaches resulted in the identification of 32 glycans based on RV VP8* binding, many of which are novel HMGs, whose detailed structural assignments by MSn are described in a companion report. Although sialic acid has been thought to be important as a surface receptor for RVs, our studies indicated that sialic acid is not required for binding of glycans to individual VP8* domains. Remarkably, each VP8* recognized specific glycan determinants within a unique subset of related glycan structures where specificity differences arise from subtle differences in glycan structures. PMID:25048705

  20. Parameter optimization in biased decoy-state quantum key distribution with both source errors and statistical fluctuations

    Science.gov (United States)

    Zhu, Jian-Rong; Li, Jian; Zhang, Chun-Mei; Wang, Qin

    2017-10-01

    The decoy-state method has been widely used in commercial quantum key distribution (QKD) systems. In view of the practical decoy-state QKD with both source errors and statistical fluctuations, we propose a universal model of full parameter optimization in biased decoy-state QKD with phase-randomized sources. Besides, we adopt this model to carry out simulations of two widely used sources: weak coherent source (WCS) and heralded single-photon source (HSPS). Results show that full parameter optimization can significantly improve not only the secure transmission distance but also the final key generation rate. And when taking source errors and statistical fluctuations into account, the performance of decoy-state QKD using HSPS suffered less than that of decoy-state QKD using WCS.

  1. Influence of Simultaneous Targeting of the Bone Morphogenetic Protein Pathway and RANK-RANKL Axis in Osteolytic Prostate Cancer Lesion in Bone

    Science.gov (United States)

    Virk, Mandeep S.; Petrigliano, Frank A.; Liu, Nancy Q.; Chatziioannou, Arion F.; Stout, David; Kang, Christine O.; Dougall, William C.; Lieberman, Jay R.

    2009-01-01

    Metastasis to bone is the leading cause of morbidity and mortality in advanced prostate cancer patients. Considering the complex reciprocal interactions between the tumor cells and the bone microenvironment, there is increasing interest in developing combination therapies targeting both the tumor growth and the bone microenvironment. In this study, we investigated the effect of simultaneous blockade of BMP pathway and RANK-RANKL axis in an osteolytic prostate cancer lesion in bone. We used a retroviral vector encoding noggin (Retronoggin) to antagonize the effect of BMPs and RANK: Fc, which is a recombinant RANKL antagonist was used to inhibit RANK-RANKL axis. The tumor growth and bone loss were evaluated using plain radiographs, hind limb tumor measurements, micro PET-CT (18F- fluorodeoxyglucose [FDG] and 18F-fluoride tracer), and histology. Tibias implanted with PC-3 cells developed pure osteolytic lesions at 2 weeks with progressive increase in cortical bone destruction at successive time points. Tibias implanted with PC-3 cells over expressing noggin (Retronoggin) resulted in reduced tumor size and decreased bone loss compared to the implanted tibias in untreated control animals. RANK: Fc administration inhibited the formation of osteoclasts, delayed the development of osteolytic lesions, decreased bone loss and reduced tumor size in tibias implanted with PC-3 cells. The combination therapy with RANK: Fc and noggin over expression effectively delayed the radiographic development of osteolytic lesions, and decreased the bone loss and tumor burden compared to implanted tibias treated with noggin over expression alone. Furthermore, the animals treated with the combination strategy exhibited decreased bone loss (micro CT) and lower tumor burden (FDG micro PET) compared to animals treated with RANK: Fc alone. Combined blockade of RANK-RANKL axis and BMP pathway resulted in reduced tumor burden and decreased bone loss compared to inhibition of either individual

  2. Testing the effect of time pressure on asymmetric dominance and compromise decoys in choice

    Directory of Open Access Journals (Sweden)

    Jonathan Pettibone

    2012-07-01

    Full Text Available Dynamic, connectionist models of decision making, such as decision field theory (Roe, Busemeyer, and Townsend, 2001, propose that the effect of context on choice arises from a series of pairwise comparisons between attributes of alternatives across time. As such, they predict that limiting the amount of time to make a decision should decrease rather than increase the size of contextual effects. This prediction was tested across four levels of time pressure on both the asymmetric dominance (Huber, Payne, and Puto, 1982 and compromise (Simonson, 1989 decoy effects in choice. Overall, results supported this prediction, with both types of decoy effects found to be larger as time pressure decreased.

  3. How to Rank Journals.

    Science.gov (United States)

    Bradshaw, Corey J A; Brook, Barry W

    2016-01-01

    There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

  4. On Page Rank

    NARCIS (Netherlands)

    Hoede, C.

    In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

  5. On Rank and Nullity

    Science.gov (United States)

    Dobbs, David E.

    2012-01-01

    This note explains how Emil Artin's proof that row rank equals column rank for a matrix with entries in a field leads naturally to the formula for the nullity of a matrix and also to an algorithm for solving any system of linear equations in any number of variables. This material could be used in any course on matrix theory or linear algebra.

  6. Hitting the Rankings Jackpot

    Science.gov (United States)

    Chapman, David W.

    2008-01-01

    Recently, Samford University was ranked 27th in the nation in a report released by "Forbes" magazine. In this article, the author relates how the people working at Samford University were surprised at its ranking. Although Samford is the largest privately institution in Alabama, its distinguished academic achievements aren't even…

  7. Die Rolle von RANK-Ligand und Osteoprotegerin bei Osteoporose

    Directory of Open Access Journals (Sweden)

    Hofbauer LC

    2004-01-01

    Full Text Available Receptor activator of nuclear factor (NF- κB ligand (RANKL, sein zellulärer Rezeptor RANK und der Decoy-Rezeptor Osteoprotegerin (OPG stellen ein essentielles Zytokinsystem für die Zellbiologie von Osteoklasten dar. Verschiedene Untersuchungen belegen die Bedeutung von Störungen des OPG/RANKL/RANK-Systems bei der Pathogenese metabolischer Knochenerkrankungen. In dieser Arbeit werden die wichtigsten Störungen des OPG/RANKL/RANK-Systems bei verschiedenen Osteoporoseformen dargestellt. Östrogenrezeptor- (ER- Agonisten wie 17 β-Östradiol, Raloxifen und Genistein stimulieren die osteoblastäre Produktion von OPG durch Aktivierung von ER- α in vitro, während Lymphozyten von Patientinnen mit Östrogenmangel RANKL überexprimieren. Die parenterale Gabe von OPG vermag den mit Östrogenmangel assoziierten Knochenverlust im Tiermodell und in einer kleineren klinischen Studie zu verhindern. Glukokortikoide und Immunsuppressiva steigern gleichzeitig die RANKL-Expression und hemmen die OPG-Produktion in osteoblastären Zellen in vitro. Glukokortikoide sind auch in vivo imstande, die OPG-Serumspiegel deutlich zu reduzieren. Dagegen hemmen biomechanische Reize in vitro die RANKL-Produktion und steigern die OPG-Produktion. Ein Fehlen dieser biomechanischen Reize bei längerer Immobilisierung kann daher den RANKL/OPG-Quotienten steigern, während die tierexperimentelle Immobilisierungs-Osteoporose durch die parenterale Gabe von OPG gemildert werden kann.

  8. Virus encoded MHC-like decoys diversify the inhibitory KIR repertoire.

    Directory of Open Access Journals (Sweden)

    Paola Carrillo-Bustamante

    Full Text Available Natural killer (NK cells are circulating lymphocytes that play an important role in the control of viral infections and tumors. Their functions are regulated by several activating and inhibitory receptors. A subset of these receptors in human NK cells are the killer immunoglobulin-like receptors (KIRs, which interact with the highly polymorphic MHC class I molecules. One important function of NK cells is to detect cells that have down-regulated MHC expression (missing-self. Because MHC molecules have non polymorphic regions, their expression could have been monitored with a limited set of monomorphic receptors. Surprisingly, the KIR family has a remarkable genetic diversity, the function of which remains poorly understood. The mouse cytomegalovirus (MCMV is able to evade NK cell responses by coding "decoy" molecules that mimic MHC class I. This interaction was suggested to have driven the evolution of novel NK cell receptors. Inspired by the MCMV system, we develop an agent-based model of a host population infected with viruses that are able to evolve MHC down-regulation and decoy molecules. Our simulations show that specific recognition of MHC class I molecules by inhibitory KIRs provides excellent protection against viruses evolving decoys, and that the diversity of inhibitory KIRs will subsequently evolve as a result of the required discrimination between host MHC molecules and decoy molecules.

  9. Modeling, Simulation, and Analysis of a Decoy State Enabled Quantum Key Distribution System

    Science.gov (United States)

    2015-03-26

    ltsnet.net Colin V. McLaughlin Research Physicist, Advanced Photonics Naval Research Laboratory, Washington, DC 20375 Colin.Mclaughlin@nrl.navy.mil...and dirty version. In this figure, the green and red decoy Y1 yields appear to vary more than the black and blue signal Y1 yields. As illustrated

  10. Genetic diversity and antimicrobial resistance of Campylobacter and Salmonella strains isolated from decoys and raptors.

    Science.gov (United States)

    Jurado-Tarifa, E; Torralbo, A; Borge, C; Cerdà-Cuéllar, M; Ayats, T; Carbonero, A; García-Bocanegra, I

    2016-10-01

    Infections caused by thermotolerant Campylobacter spp. and Salmonella spp. are the leading causes of human gastroenteritis worldwide. Wild birds can act as reservoirs of both pathogens. A survey was carried out to determine the prevalence, genetic diversity and antimicrobial resistance of thermotolerant Campylobacter and Salmonella in waterfowl used as decoys and wild raptors in Andalusia (Southern Spain). The overall prevalence detected for Campylobacter was 5.9% (18/306; CI95%: 3.25-8.52) in decoys and 2.3% (9/387; CI95%: 0.82-3.83) in wild raptors. Isolates were identified as C. jejuni, C. coli and C. lari in both bird groups. Salmonella was isolated in 3.3% (10/306; CI95%: 2.3-4.3) and 4.6% (18/394; CI95%: 3.5-5.6) of the decoys and raptors, respectively. Salmonella Enteritidis and Typhimurium were the most frequently identified serovars, although Salmonella serovars Anatum, Bredeney, London and Mikawasima were also isolated. Pulsed-field gel electrophoresis analysis of isolates showed higher genetic diversity within Campylobacter species compared to Salmonella serovars. Campylobacter isolates showed resistance to gentamicin, ciprofloxacin and tetracycline, while resistance to erythromycin and tetracycline was found in Salmonella isolates. The results indicate that both decoys and raptors can act as natural carriers of Campylobacter and Salmonella in Spain, which may have important implications for public and animal health. Copyright © 2016 Elsevier Ltd. All rights reserved.

  11. Decoy-state quantum key distribution with both source errors and statistical fluctuations

    International Nuclear Information System (INIS)

    Wang Xiangbin; Yang Lin; Peng Chengzhi; Pan Jianwei

    2009-01-01

    We show how to calculate the fraction of single-photon counts of the 3-intensity decoy-state quantum cryptography faithfully with both statistical fluctuations and source errors. Our results rely only on the bound values of a few parameters of the states of pulses.

  12. Recurrent fuzzy ranking methods

    Science.gov (United States)

    Hajjari, Tayebeh

    2012-11-01

    With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

  13. Ranking as parameter estimation

    Czech Academy of Sciences Publication Activity Database

    Kárný, Miroslav; Guy, Tatiana Valentine

    2009-01-01

    Roč. 4, č. 2 (2009), s. 142-158 ISSN 1745-7645 R&D Projects: GA MŠk 2C06001; GA AV ČR 1ET100750401; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : ranking * Bayesian estimation * negotiation * modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2009/AS/karny- ranking as parameter estimation.pdf

  14. Hierarchical partial order ranking

    International Nuclear Information System (INIS)

    Carlsen, Lars

    2008-01-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

  15. Multiplex PageRank.

    Science.gov (United States)

    Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

    2013-01-01

    Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  16. Multiplex PageRank.

    Directory of Open Access Journals (Sweden)

    Arda Halu

    Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

  17. Groundwater contaminant plume ranking

    International Nuclear Information System (INIS)

    1988-08-01

    Containment plumes at Uranium Mill Tailings Remedial Action (UMTRA) Project sites were ranked to assist in Subpart B (i.e., restoration requirements of 40 CFR Part 192) compliance strategies for each site, to prioritize aquifer restoration, and to budget future requests and allocations. The rankings roughly estimate hazards to the environment and human health, and thus assist in determining for which sites cleanup, if appropriate, will provide the greatest benefits for funds available. The rankings are based on the scores that were obtained using the US Department of Energy's (DOE) Modified Hazard Ranking System (MHRS). The MHRS and HRS consider and score three hazard modes for a site: migration, fire and explosion, and direct contact. The migration hazard mode score reflects the potential for harm to humans or the environment from migration of a hazardous substance off a site by groundwater, surface water, and air; it is a composite of separate scores for each of these routes. For ranking the containment plumes at UMTRA Project sites, it was assumed that each site had been remediated in compliance with the EPA standards and that relict contaminant plumes were present. Therefore, only the groundwater route was scored, and the surface water and air routes were not considered. Section 2.0 of this document describes the assumptions and procedures used to score the groundwater route, and Section 3.0 provides the resulting scores for each site. 40 tabs

  18. Ranking economic history journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    2010-01-01

    This study ranks-for the first time-12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We also...... compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential for economic...... history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

  19. Ranking Economic History Journals

    DEFF Research Database (Denmark)

    Di Vaio, Gianfranco; Weisdorf, Jacob Louis

    This study ranks - for the first time - 12 international academic journals that have economic history as their main topic. The ranking is based on data collected for the year 2007. Journals are ranked using standard citation analysis where we adjust for age, size and self-citation of journals. We...... also compare the leading economic history journals with the leading journals in economics in order to measure the influence on economics of economic history, and vice versa. With a few exceptions, our results confirm the general idea about what economic history journals are the most influential...... for economic history, and that, although economic history is quite independent from economics as a whole, knowledge exchange between the two fields is indeed going on....

  20. Dynamic Matrix Rank

    DEFF Research Database (Denmark)

    Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

    2009-01-01

    We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

  1. Quantum secure direct communication network with superdense coding and decoy photons

    International Nuclear Information System (INIS)

    Deng Fuguo; Li Xihan; Li Chunyan; Zhou Ping; Zhou Hongyu

    2007-01-01

    A quantum secure direct communication network scheme is proposed with quantum superdense coding and decoy photons. The servers on a passive optical network prepare and measure the quantum signal, i.e. a sequence of the d-dimensional Bell states. After confirming the security of the photons received from the receiver, the sender codes his secret message on them directly. For preventing a dishonest server from eavesdropping, some decoy photons prepared by measuring one photon in the Bell states are used to replace some original photons. One of the users on the network can communicate to any other one. This scheme has the advantage of high capacity, and it is more convenient than others as only a sequence of photons is transmitted in quantum line

  2. DECOY: Documenting Experiences with Cigarettes and Other Tobacco in Young Adults

    Science.gov (United States)

    Berg, Carla J.; Haardörfer, Regine; Lewis, Michael; Getachew, Betelihem; Lloyd, Steven A.; Thomas, Sarah Fretti; Lanier, Angela; Trepanier, Kelleigh; Johnston, Teresa; Grimsley, Linda; Foster, Bruce; Benson, Stephanie; Smith, Alicia; Barr, Dana Boyd; Windle, Michael

    2016-01-01

    Objectives We examined psychographic characteristics associated with tobacco use among Project DECOY participants. Methods Project DECOY is a 2-year longitudinal mixed-methods study examining risk for tobacco use among 3418 young adults across 7 Georgia colleges/universities. Baseline measures included sociodemographics, tobacco use, and psychographics using the Values, Attitudes, and Lifestyle Scale. Bivariate and multivariable analyses were conducted to identify correlates of tobacco use. Results Past 30-day use prevalence was: 13.3% cigarettes; 11.3% little cigars/cigarillos (LCCs); 3.6% smokeless tobacco; 10.9% e-cigarettes; and 12.2% hookah. Controlling for sociodemographics, correlates of cigarette use included greater novelty seeking (p fashion orientation (p = .007). Correlates of smokeless tobacco use included greater novelty seeking (p = .006) and less intellectual curiosity (p fashion orientation (p = .044), and self-focused thinking (p = .002), and less social conservatism (p products. PMID:27103410

  3. Benchmark of four popular virtual screening programs: construction of the active/decoy dataset remains a major determinant of measured performance.

    Science.gov (United States)

    Chaput, Ludovic; Martinez-Sanz, Juan; Saettel, Nicolas; Mouawad, Liliane

    2016-01-01

    In a structure-based virtual screening, the choice of the docking program is essential for the success of a hit identification. Benchmarks are meant to help in guiding this choice, especially when undertaken on a large variety of protein targets. Here, the performance of four popular virtual screening programs, Gold, Glide, Surflex and FlexX, is compared using the Directory of Useful Decoys-Enhanced database (DUD-E), which includes 102 targets with an average of 224 ligands per target and 50 decoys per ligand, generated to avoid biases in the benchmarking. Then, a relationship between these program performances and the properties of the targets or the small molecules was investigated. The comparison was based on two metrics, with three different parameters each. The BEDROC scores with α = 80.5, indicated that, on the overall database, Glide succeeded (score > 0.5) for 30 targets, Gold for 27, FlexX for 14 and Surflex for 11. The performance did not depend on the hydrophobicity nor the openness of the protein cavities, neither on the families to which the proteins belong. However, despite the care in the construction of the DUD-E database, the small differences that remain between the actives and the decoys likely explain the successes of Gold, Surflex and FlexX. Moreover, the similarity between the actives of a target and its crystal structure ligand seems to be at the basis of the good performance of Glide. When all targets with significant biases are removed from the benchmarking, a subset of 47 targets remains, for which Glide succeeded for only 5 targets, Gold for 4 and FlexX and Surflex for 2. The performance dramatic drop of all four programs when the biases are removed shows that we should beware of virtual screening benchmarks, because good performances may be due to wrong reasons. Therefore, benchmarking would hardly provide guidelines for virtual screening experiments, despite the tendency that is maintained, i.e., Glide and Gold display better

  4. Protein-protein docking using region-based 3D Zernike descriptors.

    Science.gov (United States)

    Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

    2009-12-09

    Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

  5. Surveillance of Influenza Viruses in Waterfowl Used As Decoys in Andalusia, Spain

    Science.gov (United States)

    Jurado-Tarifa, Estefanía; Napp, Sebastian; Gómez-Pacheco, Juan Manuel; Fernández-Morente, Manuel; Jaén-Téllez, Juan Antonio; Arenas, Antonio; García-Bocanegra, Ignacio

    2014-01-01

    A longitudinal study was carried out to determine the seroprevalence of avian influenza viruses (AIVs) in waterfowl used as decoys in Andalusia, southern Spain. A total of 2319 aquatic birds from 193 flocks were analyzed before and after the hunting season 2011–2012. In the first sampling, 403 out of 2319 (18.0%, CI95%: 15.8–19.0) decoys showed antibodies against AIVs by ELISA. The AI seroprevalence was significantly higher in geese (21.0%) than in ducks (11.7%) (P<0.001). Besides, the spatial distribution of AIVs was not homogeneous as significant differences among regions were observed. The prevalence of antibodies against AIVs subtypes H5 and H7 were 1.1% and 0.3%, respectively, using hemagglutination inhibition test (HI). The overall and H5 seroprevalences slightly increased after the hunting period (to 19.2% and 1.4%, respectively), while the H7 seroprevalence remained at the same level (0.3%). The proportion of flocks infected by AIVs was 65.3%, while 11.2% and 4.9% of flocks were positive for H5 and H7, respectively. Viral shedding was not detected in any of the 47 samples positive by both ELISA and HI, tested by RRT-PCR. The individual incidence after the hunting season was 3.4%. The fact that 57 animals seroconverted, 15 of which were confirmed by HI (12 H5 and 3 H7), was indication of contact with AIVs during the hunting period. The results indicate that waterfowl used as decoys are frequently exposed to AIVs and may be potentially useful as sentinels for AIVs monitoring. The seroprevalence detected and the seropositivity against AIVs H5 and H7, suggest that decoys can act as reservoirs of AIVs, which may be of animal and public health concern. PMID:24901946

  6. Diversifying customer review rankings.

    Science.gov (United States)

    Krestel, Ralf; Dokoohaki, Nima

    2015-06-01

    E-commerce Web sites owe much of their popularity to consumer reviews accompanying product descriptions. On-line customers spend hours and hours going through heaps of textual reviews to decide which products to buy. At the same time, each popular product has thousands of user-generated reviews, making it impossible for a buyer to read everything. Current approaches to display reviews to users or recommend an individual review for a product are based on the recency or helpfulness of each review. In this paper, we present a framework to rank product reviews by optimizing the coverage of the ranking with respect to sentiment or aspects, or by summarizing all reviews with the top-K reviews in the ranking. To accomplish this, we make use of the assigned star rating for a product as an indicator for a review's sentiment polarity and compare bag-of-words (language model) with topic models (latent Dirichlet allocation) as a mean to represent aspects. Our evaluation on manually annotated review data from a commercial review Web site demonstrates the effectiveness of our approach, outperforming plain recency ranking by 30% and obtaining best results by combining language and topic model representations. Copyright © 2015 Elsevier Ltd. All rights reserved.

  7. College Rankings. ERIC Digest.

    Science.gov (United States)

    Holub, Tamara

    The popularity of college ranking surveys published by "U.S. News and World Report" and other magazines is indisputable, but the methodologies used to measure the quality of higher education institutions have come under fire by scholars and college officials. Criticisms have focused on methodological flaws, such as failure to consider…

  8. OutRank

    DEFF Research Database (Denmark)

    Müller, Emmanuel; Assent, Ira; Steinhausen, Uwe

    2008-01-01

    Outlier detection is an important data mining task for consistency checks, fraud detection, etc. Binary decision making on whether or not an object is an outlier is not appropriate in many applications and moreover hard to parametrize. Thus, recently, methods for outlier ranking have been proposed...

  9. Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

    International Nuclear Information System (INIS)

    Xiao, Xiao; Gang, Yi; Wang, Honghong; Wang, Jiayin; Zhao, Lina; Xu, Li; Liu, Zhiguo

    2015-01-01

    Highlights: • A shRNA vector based transcription factor decoy, VB-ODN, was designed. • VB-ODN for NF-κB inhibited cell viability in HEK293 cells. • VB-ODN inhibited expression of downstream genes of target transcription factors. • VB-ODN may enhance nuclear entry ratio for its feasibility of virus production. - Abstract: In this study, we designed a short hairpin RNA vector-based oligodeoxynucleotide (VB-ODN) carrying transcription factor (TF) consensus sequence which could function as a decoy to block TF activity. Specifically, VB-ODN for Nuclear factor-κB (NF-κB) could inhibit cell viability and decrease downstream gene expression in HEK293 cells without affecting expression of NF-κB itself. The specific binding between VB-ODN produced double-stranded RNA and NF-κB was evidenced by electrophoretic mobility shift assay. Moreover, similar VB-ODNs designed for three other TFs also inhibit their downstream gene expression but not that of themselves. Our study provides a new design of decoy for blocking TF activity

  10. Double-stranded RNA transcribed from vector-based oligodeoxynucleotide acts as transcription factor decoy

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Xiao [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Gang, Yi [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Department of Infectious Diseases, Tangdu Hospital, Fourth Military Medical University, Xi’an 710038, Shaanxi Province (China); Wang, Honghong [No. 518 Hospital of Chinese People’s Liberation Army, Xi’an 710043, Shaanxi Province (China); Wang, Jiayin [The Genome Institute, Washington University in St. Louis, St. Louis, MO 63108 (United States); Zhao, Lina [Department of Radiation Oncology, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Xu, Li, E-mail: lxuhelen@163.com [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China); Liu, Zhiguo, E-mail: liuzhiguo@fmmu.edu.cn [State Key Laboratory of Cancer Biology and Xijing Hospital of Digestive Diseases, Xijing Hospital, Fourth Military Medical University, Xi’an 710032, Shaanxi Province (China)

    2015-02-06

    Highlights: • A shRNA vector based transcription factor decoy, VB-ODN, was designed. • VB-ODN for NF-κB inhibited cell viability in HEK293 cells. • VB-ODN inhibited expression of downstream genes of target transcription factors. • VB-ODN may enhance nuclear entry ratio for its feasibility of virus production. - Abstract: In this study, we designed a short hairpin RNA vector-based oligodeoxynucleotide (VB-ODN) carrying transcription factor (TF) consensus sequence which could function as a decoy to block TF activity. Specifically, VB-ODN for Nuclear factor-κB (NF-κB) could inhibit cell viability and decrease downstream gene expression in HEK293 cells without affecting expression of NF-κB itself. The specific binding between VB-ODN produced double-stranded RNA and NF-κB was evidenced by electrophoretic mobility shift assay. Moreover, similar VB-ODNs designed for three other TFs also inhibit their downstream gene expression but not that of themselves. Our study provides a new design of decoy for blocking TF activity.

  11. Improving Ranking Using Quantum Probability

    OpenAIRE

    Melucci, Massimo

    2011-01-01

    The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

  12. Targeting the MET oncogene by concomitant inhibition of receptor and ligand via an antibody-"decoy" strategy.

    Science.gov (United States)

    Basilico, Cristina; Modica, Chiara; Maione, Federica; Vigna, Elisa; Comoglio, Paolo M

    2018-04-25

    MET, a master gene sustaining "invasive growth," is a relevant target for cancer precision therapy. In the vast majority of tumors, wild-type MET behaves as a "stress-response" gene and relies on the ligand (HGF) to sustain cell "scattering," invasive growth and apoptosis protection (oncogene "expedience"). In this context, concomitant targeting of MET and HGF could be crucial to reach effective inhibition. To test this hypothesis, we combined an anti-MET antibody (MvDN30) inducing "shedding" (i.e., removal of MET from the cell surface), with a "decoy" (i.e., the soluble extracellular domain of the MET receptor) endowed with HGF-sequestering ability. To avoid antibody/decoy interaction-and subsequent neutralization-we identified a single aminoacid in the extracellular domain of MET-lysine 842-that is critical for MvDN30 binding and engineered the corresponding recombinant decoyMET (K842E). DecoyMET K842E retains the ability to bind HGF with high affinity and inhibits HGF-induced MET phosphorylation. In HGF-dependent cellular models, MvDN30 antibody and decoyMET K842E used in combination cooperate in restraining invasive growth, and synergize in blocking cancer cell "scattering." The antibody and the decoy unbridle apoptosis of colon cancer stem cells grown in vitro as spheroids. In a preclinical model, built by orthotopic transplantation of a human pancreatic carcinoma in SCID mice engineered to express human HGF, concomitant treatment with antibody and decoy significantly reduces metastatic spread. The data reported indicate that vertical targeting of the MET/HGF axis results in powerful inhibition of ligand-dependent MET activation, providing proof of concept in favor of combined target therapy of MET "expedience." © 2018 UICC.

  13. Importance of dispersion and electron correlation in ab initio protein folding.

    Science.gov (United States)

    He, Xiao; Fusti-Molnar, Laszlo; Cui, Guanglei; Merz, Kenneth M

    2009-04-16

    Dispersion is well-known to be important in biological systems, but the effect of electron correlation in such systems remains unclear. In order to assess the relationship between the structure of a protein and its electron correlation energy, we employed both full system Hartree-Fock (HF) and second-order Møller-Plesset perturbation (MP2) calculations in conjunction with the Polarizable Continuum Model (PCM) on the native structures of two proteins and their corresponding computer-generated decoy sets. Because of the expense of the MP2 calculation, we have utilized the fragment molecular orbital method (FMO) in this study. We show that the sum of the Hartree-Fock (HF) energy and force field (LJ6)-derived dispersion energy (HF + LJ6) is well correlated with the energies obtained using second-order Møller-Plesset perturbation (MP2) theory. In one of the two examples studied, the correlation energy as well as the empirical dispersive energy term was able to discriminate between native and decoy structures. On the other hand, for the second protein we studied, neither the correlation energy nor dispersion energy showed discrimination capabilities; however, the ab initio MP2 energy and the HF+LJ6 both ranked the native structure correctly. Furthermore, when we randomly scrambled the Lennard-Jones parameters, the correlation between the MP2 energy and the sum of the HF energy and dispersive energy (HF+LJ6) significantly drops, which indicates that the choice of Lennard-Jones parameters is important.

  14. Protein-protein docking using region-based 3D Zernike descriptors

    Directory of Open Access Journals (Sweden)

    Sael Lee

    2009-12-01

    Full Text Available Abstract Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for

  15. 1991 Acceptance priority ranking

    International Nuclear Information System (INIS)

    1991-12-01

    The Standard Contract for Disposal of Spent Nuclear Fuel and/or High- Level Radioactive Waste (10 CFR Part 961) that the Department of Energy (DOE) has executed with the owners and generators of civilian spent nuclear fuel requires annual publication of the Acceptance Priority Ranking (APR). The 1991 APR details the order in which DOE will allocate Federal waste acceptance capacity. As required by the Standard Contract, the ranking is based on the age of permanently discharged spent nuclear fuel (SNF), with the owners of the oldest SNF, on an industry-wide basis, given the highest priority. the 1991 APR will be the basis for the annual allocation of waste acceptance capacity to the Purchasers in the 1991 Annual Capacity Report (ACR), to be issued later this year. This document is based on SNF discharges as of December 31, 1990, and reflects Purchaser comments and corrections, as appropriate, to the draft APR issued on May 15, 1991

  16. Immunization of Pigs by DNA Prime and Recombinant Vaccinia Virus Boost To Identify and Rank African Swine Fever Virus Immunogenic and Protective Proteins.

    Science.gov (United States)

    Jancovich, James K; Chapman, Dave; Hansen, Debra T; Robida, Mark D; Loskutov, Andrey; Craciunescu, Felicia; Borovkov, Alex; Kibler, Karen; Goatley, Lynnette; King, Katherine; Netherton, Christopher L; Taylor, Geraldine; Jacobs, Bertram; Sykes, Kathryn; Dixon, Linda K

    2018-04-15

    African swine fever virus (ASFV) causes an acute hemorrhagic fever in domestic pigs, with high socioeconomic impact. No vaccine is available, limiting options for control. Although live attenuated ASFV can induce up to 100% protection against lethal challenge, little is known of the antigens which induce this protective response. To identify additional ASFV immunogenic and potentially protective antigens, we cloned 47 viral genes in individual plasmids for gene vaccination and in recombinant vaccinia viruses. These antigens were selected to include proteins with different functions and timing of expression. Pools of up to 22 antigens were delivered by DNA prime and recombinant vaccinia virus boost to groups of pigs. Responses of immune lymphocytes from pigs to individual recombinant proteins and to ASFV were measured by interferon gamma enzyme-linked immunosorbent spot (ELISpot) assays to identify a subset of the antigens that consistently induced the highest responses. All 47 antigens were then delivered to pigs by DNA prime and recombinant vaccinia virus boost, and pigs were challenged with a lethal dose of ASFV isolate Georgia 2007/1. Although pigs developed clinical and pathological signs consistent with acute ASFV, viral genome levels were significantly reduced in blood and several lymph tissues in those pigs immunized with vectors expressing ASFV antigens compared with the levels in control pigs. IMPORTANCE The lack of a vaccine limits the options to control African swine fever. Advances have been made in the development of genetically modified live attenuated ASFV that can induce protection against challenge. However, there may be safety issues relating to the use of these in the field. There is little information about ASFV antigens that can induce a protective immune response against challenge. We carried out a large screen of 30% of ASFV antigens by delivering individual genes in different pools to pigs by DNA immunization prime and recombinant vaccinia

  17. Ranking Baltic States Researchers

    Directory of Open Access Journals (Sweden)

    Gyula Mester

    2017-10-01

    Full Text Available In this article, using the h-index and the total number of citations, the best 10 Lithuanian, Latvian and Estonian researchers from several disciplines are ranked. The list may be formed based on the h-index and the total number of citations, given in Web of Science, Scopus, Publish or Perish Program and Google Scholar database. Data for the first 10 researchers are presented. Google Scholar is the most complete. Therefore, to define a single indicator, h-index calculated by Google Scholar may be a good and simple one. The author chooses the Google Scholar database as it is the broadest one.

  18. Fourth-rank cosmology

    International Nuclear Information System (INIS)

    Marrakchi, A.E.L.; Tapia, V.

    1992-05-01

    Some cosmological implications of the recently proposed fourth-rank theory of gravitation are studied. The model exhibits the possibility of being free from the horizon and flatness problems at the price of introducing a negative pressure. The field equations we obtain are compatible with k obs =0 and Ω obs t clas approx. 10 20 t Planck approx. 10 -23 s. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. Hence, an interpretation of the negative pressure hypothesis is provided. (author). 8 refs

  19. University Rankings and Social Science

    OpenAIRE

    Marginson, S.

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

  20. University Rankings and Social Science

    Science.gov (United States)

    Marginson, Simon

    2014-01-01

    University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

  1. Aptamer-Mediated Codelivery of Doxorubicin and NF-κB Decoy Enhances Chemosensitivity of Pancreatic Tumor Cells

    Directory of Open Access Journals (Sweden)

    David Porciani

    2015-01-01

    Full Text Available Aptamers able to bind efficiently cell-surface receptors differentially expressed in tumor and in healthy cells are emerging as powerful tools to perform targeted anticancer therapy. Here, we present a novel oligonucleotide chimera, composed by an RNA aptamer and a DNA decoy. Our assembly is able to (i target tumor cells via an antitransferrin receptor RNA aptamer and (ii perform selective codelivery of a chemotherapeutic drug (Doxorubicin and of an inhibitor of a cell-survival factor, the nuclear factor κB decoy oligonucleotide. Both payloads are released under conditions found in endolysosomal compartments (low pH and reductive environment. Targeting and cytotoxicity of the oligonucleotidic chimera were assessed by confocal microscopy, cell viability, and Western blot analysis. These data indicated that the nuclear factor κB decoy does inhibit nuclear factor κB activity and ultimately leads to an increased therapeutic efficacy of Doxorubicin selectively in tumor cells.

  2. Field test of a practical secure communication network with decoy-state quantum cryptography.

    Science.gov (United States)

    Chen, Teng-Yun; Liang, Hao; Liu, Yang; Cai, Wen-Qi; Ju, Lei; Liu, Wei-Yue; Wang, Jian; Yin, Hao; Chen, Kai; Chen, Zeng-Bing; Peng, Cheng-Zhi; Pan, Jian-Wei

    2009-04-13

    We present a secure network communication system that operated with decoy-state quantum cryptography in a real-world application scenario. The full key exchange and application protocols were performed in real time among three nodes, in which two adjacent nodes were connected by approximate 20 km of commercial telecom optical fiber. The generated quantum keys were immediately employed and demonstrated for communication applications, including unbreakable real-time voice telephone between any two of the three communication nodes, or a broadcast from one node to the other two nodes by using one-time pad encryption.

  3. NF-κB decoy oligodeoxynucleotide mitigates wear particle-associated bone loss in the murine continuous infusion model.

    Science.gov (United States)

    Lin, Tzu-Hua; Pajarinen, Jukka; Sato, Taishi; Loi, Florence; Fan, Changchun; Córdova, Luis A; Nabeshima, Akira; Gibon, Emmanuel; Zhang, Ruth; Yao, Zhenyu; Goodman, Stuart B

    2016-09-01

    Total joint replacement is a cost-effective surgical procedure for patients with end-stage arthritis. Wear particle-induced chronic inflammation is associated with the development of periprosthetic osteolysis. Modulation of NF-κB signaling in macrophages, osteoclasts, and mesenchymal stem cells could potentially mitigate this disease. In the current study, we examined the effects of local delivery of decoy NF-κB oligo-deoxynucleotide (ODN) on wear particle-induced bone loss in a murine continuous femoral particle infusion model. Ultra-high molecular weight polyethylene particles (UHMWPE) with or without lipopolysaccharide (LPS) were infused via osmotic pumps into hollow titanium rods placed in the distal femur of mice for 4weeks. Particle-induced bone loss was evaluated by μCT, and immunohistochemical analysis of sections from the femur. Particle infusion alone resulted in reduced bone mineral density and trabecular bone volume fraction in the distal femur. The decoy ODN reversed the particle-associated bone volume fraction loss around the implant, irrespective of the presence of LPS. Particle-infusion with LPS increased bone mineral density in the distal femur compared with particle-infusion alone. NF-κB decoy ODN reversed or further increased the bone mineral density in the femur (3-6mm from the distal end) exposed to particles alone or particles plus LPS. NF-κB decoy ODN also inhibited macrophage infiltration and osteoclast number, but had no significant effects on osteoblast numbers in femurs exposed to wear particles and LPS. Our study suggests that targeting NF-κB activity via local delivery of decoy ODN has great potential to mitigate wear particle-induced osteolysis. Total joint replacement is a cost-effective surgical procedure for patients with end-stage arthritis. Chronic inflammation is crucial for the development of wear particle-associated bone loss. Modulation of NF-κB signaling in macrophages (pro-inflammatory cells), osteoclasts (bone

  4. The electrostatic profile of consecutive Cβ atoms applied to protein structure quality assessment [v2; ref status: indexed, http://f1000r.es/2cf

    Directory of Open Access Journals (Sweden)

    Sandeep Chakraborty

    2013-11-01

    Full Text Available The structure of a protein provides insight into its physiological interactions with other components of the cellular soup. Methods that predict putative structures from sequences typically yield multiple, closely-ranked possibilities. A critical component in the process is the model quality assessing program (MQAP, which selects the best candidate from this pool of structures. Here, we present a novel MQAP based on the physical properties of sidechain atoms. We propose a method for assessing the quality of protein structures based on the electrostatic potential difference (EPD of Cβ atoms in consecutive residues. We demonstrate that the EPDs of Cβ atoms on consecutive residues provide unique signatures of the amino acid types. The EPD of Cβ atoms are learnt from a set of 1000 non-homologous protein structures with a resolution cuto of 1.6 Å obtained from the PISCES database. Based on the Boltzmann hypothesis that lower energy conformations are proportionately sampled more, and on Annsen's thermodynamic hypothesis that the native structure of a protein is the minimum free energy state, we hypothesize that the deviation of observed EPD values from the mean values obtained in the learning phase is minimized in the native structure. We achieved an average specificity of 0.91, 0.94 and 0.93 on hg_structal, 4state_reduced and ig_structal decoy sets, respectively, taken from the Decoys `R' Us database. The source code and manual is made available at https://github.com/sanchak/mqap and permanently available on 10.5281/zenodo.7134.

  5. Fractional cointegration rank estimation

    DEFF Research Database (Denmark)

    Lasak, Katarzyna; Velasco, Carlos

    the parameters of the model under the null hypothesis of the cointegration rank r = 1, 2, ..., p-1. This step provides consistent estimates of the cointegration degree, the cointegration vectors, the speed of adjustment to the equilibrium parameters and the common trends. In the second step we carry out a sup......-likelihood ratio test of no-cointegration on the estimated p - r common trends that are not cointegrated under the null. The cointegration degree is re-estimated in the second step to allow for new cointegration relationships with different memory. We augment the error correction model in the second step...... to control for stochastic trend estimation effects from the first step. The critical values of the tests proposed depend only on the number of common trends under the null, p - r, and on the interval of the cointegration degrees b allowed, but not on the true cointegration degree b0. Hence, no additional...

  6. Rankings, creatividad y urbanismo

    Directory of Open Access Journals (Sweden)

    JOAQUÍN SABATÉ

    2008-08-01

    Full Text Available La competencia entre ciudades constituye uno de los factores impulsores de procesos de renovación urbana y los rankings han devenido instrumentos de medida de la calidad de las ciudades. Nos detendremos en el caso de un antiguo barrio industrial hoy en vías de transformación en distrito "creativo" por medio de una intervención urbanística de gran escala. Su análisis nos descubre tres claves críticas. En primer lugar, nos obliga a plantearnos la definición de innovación urbana y cómo se integran el pasado, la identidad y la memoria en la construcción del futuro. Nos lleva a comprender que la innovación y el conocimiento no se "dan" casualmente, sino que son el fruto de una larga y compleja red en la que participan saberes, espacios, actores e instituciones diversas en naturaleza, escala y magnitud. Por último nos obliga a reflexionar sobre el valor que se le otorga a lo local en los procesos de renovación urbana.Competition among cities constitutes one ofthe main factors o furban renewal, and rankings have become instruments to indícate cities quality. Studying the transformation of an old industrial quarter into a "creative district" by the means ofa large scale urban project we highlight three main conclusions. First, itasks us to reconsider the notion ofurban innovation and hoto past, identity and memory should intégrate the future development. Second, it shows that innovation and knowledge doesn't yield per chance, but are the result ofa large and complex grid of diverse knowledges, spaces, agents and institutions. Finally itforces us to reflect about the valué attributed to the "local" in urban renewalprocesses.

  7. A ranking method for the concurrent learning of compounds with various activity profiles.

    Science.gov (United States)

    Dörr, Alexander; Rosenbaum, Lars; Zell, Andreas

    2015-01-01

    In this study, we present a SVM-based ranking algorithm for the concurrent learning of compounds with different activity profiles and their varying prioritization. To this end, a specific labeling of each compound was elaborated in order to infer virtual screening models against multiple targets. We compared the method with several state-of-the-art SVM classification techniques that are capable of inferring multi-target screening models on three chemical data sets (cytochrome P450s, dehydrogenases, and a trypsin-like protease data set) containing three different biological targets each. The experiments show that ranking-based algorithms show an increased performance for single- and multi-target virtual screening. Moreover, compounds that do not completely fulfill the desired activity profile are still ranked higher than decoys or compounds with an entirely undesired profile, compared to other multi-target SVM methods. SVM-based ranking methods constitute a valuable approach for virtual screening in multi-target drug design. The utilization of such methods is most helpful when dealing with compounds with various activity profiles and the finding of many ligands with an already perfectly matching activity profile is not to be expected.

  8. Ranking nodes in growing networks: When PageRank fails.

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-10

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  9. Neophilia Ranking of Scientific Journals.

    Science.gov (United States)

    Packalen, Mikko; Bhattacharya, Jay

    2017-01-01

    The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

  10. Low-rank coal research

    Energy Technology Data Exchange (ETDEWEB)

    Weber, G. F.; Laudal, D. L.

    1989-01-01

    This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

  11. Ranking Specific Sets of Objects.

    Science.gov (United States)

    Maly, Jan; Woltran, Stefan

    2017-01-01

    Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

  12. Wikipedia ranking of world universities

    Science.gov (United States)

    Lages, José; Patt, Antoine; Shepelyansky, Dima L.

    2016-03-01

    We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

  13. New treatment of periodontal diseases by using NF-kappaB decoy oligodeoxynucleotides via prevention of bone resorption and promotion of wound healing.

    Science.gov (United States)

    Shimizu, Hideo; Nakagami, Hironori; Morita, Shosuke; Tsukamoto, Ikuyo; Osako, Mariana Kiomy; Nakagami, Futoshi; Shimosato, Takashi; Minobe, Noriko; Morishita, Ryuichi

    2009-09-01

    Nuclear factor-kappa B (NF-kappaB) is involved in osteoclast differentiation and activation. Thus, the blockade of the NF-kappaB pathway might be a novel therapeutic strategy for treating bone metabolic diseases. Periodontitis is subgingival inflammation caused by bacterial infection; this disease also is thought to be a chronic focal point responsible for systemic diseases. In this study, NF-kappaB decoy oligodeoxynucleotides (ODNs) were topically applied for experimental periodontitis in a debris-accumulation model and wound healing in a bone-defect model of beagle dogs to investigate the effect of decoy ODN on bone metabolism. Application of NF-kappaB decoy ODN significantly reduced interleukin-6 activity in crevicular fluid and improved alveolar bone loss in the analysis of dental radiographs and DEXA. Direct measurement of exposed root that lost alveolar bone support revealed that NF-kappaB decoy treatment dramatically protected bone from loss. In a bone-defect model, NF-kappaB decoy ODN promoted the healing process as compared with control scrambled decoy in micro-CT analysis. Overall, inhibition of NF-kappaB by decoy strategy prevented the progression of bone loss in periodontitis and promoted the wound healing in bone defects through the inhibition of osteoclastic bone resorption. Targeting of NF-kappaB might be a potential therapy in various bone metabolic diseases.

  14. Statistical methods for ranking data

    CERN Document Server

    Alvo, Mayer

    2014-01-01

    This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

  15. Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs.

    Science.gov (United States)

    Várnai, Csilla; Burkoff, Nikolas S; Wild, David L

    2017-01-01

    Evolutionary information stored in multiple sequence alignments (MSAs) has been used to identify the interaction interface of protein complexes, by measuring either co-conservation or co-mutation of amino acid residues across the interface. Recently, maximum entropy related correlated mutation measures (CMMs) such as direct information, decoupling direct from indirect interactions, have been developed to identify residue pairs interacting across the protein complex interface. These studies have focussed on carefully selected protein complexes with large, good-quality MSAs. In this work, we study protein complexes with a more typical MSA consisting of fewer than 400 sequences, using a set of 79 intramolecular protein complexes. Using a maximum entropy based CMM at the residue level, we develop an interface level CMM score to be used in re-ranking docking decoys. We demonstrate that our interface level CMM score compares favourably to the complementarity trace score, an evolutionary information-based score measuring co-conservation, when combined with the number of interface residues, a knowledge-based potential and the variability score of individual amino acid sites. We also demonstrate, that, since co-mutation and co-complementarity in the MSA contain orthogonal information, the best prediction performance using evolutionary information can be achieved by combining the co-mutation information of the CMM with co-conservation information of a complementarity trace score, predicting a near-native structure as the top prediction for 41% of the dataset. The method presented is not restricted to small MSAs, and will likely improve interface prediction also for complexes with large and good-quality MSAs.

  16. Ranking nodes in growing networks: When PageRank fails

    Science.gov (United States)

    Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

    2015-11-01

    PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

  17. PageRank tracker: from ranking to tracking.

    Science.gov (United States)

    Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

    2014-06-01

    Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

  18. Hacking on decoy-state quantum key distribution system with partial phase randomization

    Science.gov (United States)

    Sun, Shi-Hai; Jiang, Mu-Sheng; Ma, Xiang-Chun; Li, Chun-Yan; Liang, Lin-Mei

    2014-04-01

    Quantum key distribution (QKD) provides means for unconditional secure key transmission between two distant parties. However, in practical implementations, it suffers from quantum hacking due to device imperfections. Here we propose a hybrid measurement attack, with only linear optics, homodyne detection, and single photon detection, to the widely used vacuum + weak decoy state QKD system when the phase of source is partially randomized. Our analysis shows that, in some parameter regimes, the proposed attack would result in an entanglement breaking channel but still be able to trick the legitimate users to believe they have transmitted secure keys. That is, the eavesdropper is able to steal all the key information without discovered by the users. Thus, our proposal reveals that partial phase randomization is not sufficient to guarantee the security of phase-encoding QKD systems with weak coherent states.

  19. Hacking on decoy-state quantum key distribution system with partial phase randomization.

    Science.gov (United States)

    Sun, Shi-Hai; Jiang, Mu-Sheng; Ma, Xiang-Chun; Li, Chun-Yan; Liang, Lin-Mei

    2014-04-23

    Quantum key distribution (QKD) provides means for unconditional secure key transmission between two distant parties. However, in practical implementations, it suffers from quantum hacking due to device imperfections. Here we propose a hybrid measurement attack, with only linear optics, homodyne detection, and single photon detection, to the widely used vacuum + weak decoy state QKD system when the phase of source is partially randomized. Our analysis shows that, in some parameter regimes, the proposed attack would result in an entanglement breaking channel but still be able to trick the legitimate users to believe they have transmitted secure keys. That is, the eavesdropper is able to steal all the key information without discovered by the users. Thus, our proposal reveals that partial phase randomization is not sufficient to guarantee the security of phase-encoding QKD systems with weak coherent states.

  20. Decoy-state BB84 protocol using space division multiplexing in silicon photonics

    DEFF Research Database (Denmark)

    Bacco, Davide; Ding, Yunhong; Dalgaard, Kjeld

    2017-01-01

    Quantum key distribution (QKD), a technique based on quantum physics, provides unconditional secure quantum keys to be shared between two or more clients (Alice and Bob) [1]. Most QKD systems are implemented in a point-to-point link using bulky and expensive devices. Consequently a large scale...... experiments have already demonstrated conventional binary QKD systems, using polarization and phase reference degrees of freedom [2, 3]. In this paper, we show the first silicon chip-to-chip decoy-state BB84 protocol based on spatial degrees of freedom (the cores of a multi-core fiber-MCF-). By tuning...... the superposition of the quantum state between cores, combined with a positive/negative phase relation. A train of weak coherent pulses (5 kHz repetition and 10 ns wide) are injected into the transmitter chip (Alice), where multiple variable optical attenuators (VOAs) are used to decrease the number of photons per...

  1. Practical long-distance quantum key distribution system using decoy levels

    International Nuclear Information System (INIS)

    Rosenberg, D; Peterson, C G; Harrington, J W; Rice, P R; Dallmann, N; Tyagi, K T; McCabe, K P; Hughes, R J; Nordholt, J E; Nam, S; Baek, B; Hadfield, R H

    2009-01-01

    Quantum key distribution (QKD) has the potential for widespread real-world applications, but no secure long-distance experiment has demonstrated the truly practical operation needed to move QKD from the laboratory to the real world due largely to limitations in synchronization and poor detector performance. Here, we report results obtained using a fully automated, robust QKD system based on the Bennett Brassard 1984 (BB84) protocol with low-noise superconducting nanowire single-photon detectors (SNSPDs) and decoy levels to produce a secret key with unconditional security over a record 140.6 km of optical fibre, an increase of more than a factor of five compared with the previous record for unconditionally secure key generation in a practical QKD system.

  2. Comparative Biochemical and Functional Analysis of Viral and Human Secreted Tumor Necrosis Factor (TNF) Decoy Receptors*

    Science.gov (United States)

    Pontejo, Sergio M.; Alejo, Ali; Alcami, Antonio

    2015-01-01

    The blockade of tumor necrosis factor (TNF) by etanercept, a soluble version of the human TNF receptor 2 (hTNFR2), is a well established strategy to inhibit adverse TNF-mediated inflammatory responses in the clinic. A similar strategy is employed by poxviruses, encoding four viral TNF decoy receptor homologues (vTNFRs) named cytokine response modifier B (CrmB), CrmC, CrmD, and CrmE. These vTNFRs are differentially expressed by poxviral species, suggesting distinct immunomodulatory properties. Whereas the human variola virus and mouse ectromelia virus encode one vTNFR, the broad host range cowpox virus encodes all vTNFRs. We report the first comprehensive study of the functional and binding properties of these four vTNFRs, providing an explanation for their expression profile among different poxviruses. In addition, the vTNFRs activities were compared with the hTNFR2 used in the clinic. Interestingly, CrmB from variola virus, the causative agent of smallpox, is the most potent TNFR of those tested here including hTNFR2. Furthermore, we demonstrate a new immunomodulatory activity of vTNFRs, showing that CrmB and CrmD also inhibit the activity of lymphotoxin β. Similarly, we report for the first time that the hTNFR2 blocks the biological activity of lymphotoxin β. The characterization of vTNFRs optimized during virus-host evolution to modulate the host immune response provides relevant information about their potential role in pathogenesis and may be used to improve anti-inflammatory therapies based on soluble decoy TNFRs. PMID:25940088

  3. Comparative Biochemical and Functional Analysis of Viral and Human Secreted Tumor Necrosis Factor (TNF) Decoy Receptors.

    Science.gov (United States)

    Pontejo, Sergio M; Alejo, Ali; Alcami, Antonio

    2015-06-26

    The blockade of tumor necrosis factor (TNF) by etanercept, a soluble version of the human TNF receptor 2 (hTNFR2), is a well established strategy to inhibit adverse TNF-mediated inflammatory responses in the clinic. A similar strategy is employed by poxviruses, encoding four viral TNF decoy receptor homologues (vTNFRs) named cytokine response modifier B (CrmB), CrmC, CrmD, and CrmE. These vTNFRs are differentially expressed by poxviral species, suggesting distinct immunomodulatory properties. Whereas the human variola virus and mouse ectromelia virus encode one vTNFR, the broad host range cowpox virus encodes all vTNFRs. We report the first comprehensive study of the functional and binding properties of these four vTNFRs, providing an explanation for their expression profile among different poxviruses. In addition, the vTNFRs activities were compared with the hTNFR2 used in the clinic. Interestingly, CrmB from variola virus, the causative agent of smallpox, is the most potent TNFR of those tested here including hTNFR2. Furthermore, we demonstrate a new immunomodulatory activity of vTNFRs, showing that CrmB and CrmD also inhibit the activity of lymphotoxin β. Similarly, we report for the first time that the hTNFR2 blocks the biological activity of lymphotoxin β. The characterization of vTNFRs optimized during virus-host evolution to modulate the host immune response provides relevant information about their potential role in pathogenesis and may be used to improve anti-inflammatory therapies based on soluble decoy TNFRs. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  4. Decoy receptor 3 suppresses FasL-induced apoptosis via ERK1/2 activation in pancreatic cancer cells

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Yi; Li, Dechun; Zhao, Xin; Song, Shiduo; Zhang, Lifeng; Zhu, Dongming [Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou 215006 (China); Wang, Zhenxin [Department of Oncology, The First Affiliated Hospital of Soochow University, Suzhou 215006 (China); Chen, Xiaochen [Department of Pathology, The Obstetrics & Gynecology Hospital of Fudan University, Shanghai 200090 (China); Zhou, Jian, E-mail: zhoujian20150602@126.com [Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou 215006 (China)

    2015-08-07

    Resistance to Fas Ligand (FasL) mediated apoptosis plays an important role in tumorigenesis. Decoy receptor 3 (DcR3) is reported to interact with FasL and is overexpressed in some malignant tumors. We sought to investigate the role of DcR3 in resistance to FasL in pancreatic cancer. We compared expression of apoptosis related genes between FasL-resistant SW1990 and FasL-sensitive Patu8988 pancreatic cell lines by microarray analysis. We explored the impact of siRNA knockdown of, or exogenous supplementation with, DcR3 on FasL-induced cell growth inhibition in pancreatic cancer cell lines and expression of proteins involved in apoptotic signaling. We assessed the level of DcR3 protein and ERK1/2 phosphorylation in tumor and non-tumor tissue samples of 66 patients with pancreatic carcinoma. RNAi knockdown of DcR3 expression in SW1990 cells reduced resistance to FasL-induced apoptosis, and supplementation of Patu8988 with rDcR3 had the opposite effect. RNAi knockdown of DcR3 in SW1990 cells elevated expression of caspase 3, 8 and 9, and reduced ERK1/2 phosphorylation (P < 0.05), but did not alter phosphorylated-Akt expression. 47 tumor tissue specimens, but only 15 matched non-tumor specimens stained for DcR3 (χ{sup 2} = 31.1447, P < 0.001). The proliferation index of DcR3 positive specimens (14.26  ±  2.67%) was significantly higher than that of DcR3 negative specimens (43.58  ±  7.88%, P < 0.01). DcR3 expression positively correlated with p-ERK1/2 expression in pancreatic cancer tissues (r = 0.607, P < 0.001). DcR3 enhances ERK1/2 phosphorylation and opposes FasL signaling in pancreatic cancer cells. - Highlights: • We investigated the role of DcR3 in FasL resistance in pancreatic cancer. • Knockdown of DcR3 in SW1990 cells reduced resistance to FasL-induced apoptosis. • DcR3 knockdown also elevated caspase expression, and reduced ERK1/2 phosphorylation. • Tumor and non-tumor tissues were collected from 66 pancreatic carcinoma patients

  5. Universal scaling in sports ranking

    International Nuclear Information System (INIS)

    Deng Weibing; Li Wei; Cai Xu; Bulou, Alain; Wang Qiuping A

    2012-01-01

    Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

  6. A probabilistic fragment-based protein structure prediction algorithm.

    Directory of Open Access Journals (Sweden)

    David Simoncini

    Full Text Available Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].

  7. PageRank of integers

    International Nuclear Information System (INIS)

    Frahm, K M; Shepelyansky, D L; Chepelianskii, A D

    2012-01-01

    We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

  8. Freudenthal ranks: GHZ versus W

    International Nuclear Information System (INIS)

    Borsten, L

    2013-01-01

    The Hilbert space of three-qubit pure states may be identified with a Freudenthal triple system. Every state has an unique Freudenthal rank ranging from 1 to 4, which is determined by a set of automorphism group covariants. It is shown here that the optimal success rates for winning a three-player non-local game, varying over all local strategies, are strictly ordered by the Freudenthal rank of the shared three-qubit resource. (paper)

  9. Ranking Queries on Uncertain Data

    CERN Document Server

    Hua, Ming

    2011-01-01

    Uncertain data is inherent in many important applications, such as environmental surveillance, market analysis, and quantitative economics research. Due to the importance of those applications and rapidly increasing amounts of uncertain data collected and accumulated, analyzing large collections of uncertain data has become an important task. Ranking queries (also known as top-k queries) are often natural and useful in analyzing uncertain data. Ranking Queries on Uncertain Data discusses the motivations/applications, challenging problems, the fundamental principles, and the evaluation algorith

  10. Ranking in evolving complex networks

    Science.gov (United States)

    Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

    2017-05-01

    Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

  11. RANK and RANK ligand expression in primary human osteosarcoma

    Directory of Open Access Journals (Sweden)

    Daniel Branstetter

    2015-09-01

    Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

  12. Security analysis of the decoy method with the Bennett–Brassard 1984 protocol for finite key lengths

    International Nuclear Information System (INIS)

    Hayashi, Masahito; Nakayama, Ryota

    2014-01-01

    This paper provides a formula for the sacrifice bit-length for privacy amplification with the Bennett–Brassard 1984 protocol for finite key lengths, when we employ the decoy method. Using the formula, we can guarantee the security parameter for a realizable quantum key distribution system. The key generation rates with finite key lengths are numerically evaluated. The proposed method improves the existing key generation rate even in the asymptotic setting. (paper)

  13. Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

    Science.gov (United States)

    Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

    2014-04-01

    Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

  14. Protein Structure Refinement by Optimization

    DEFF Research Database (Denmark)

    Carlsen, Martin

    on whether the three-dimensional structure of a homologous sequence is known. Whether or not a protein model can be used for industrial purposes depends on the quality of the predicted structure. A model can be used to design a drug when the quality is high. The overall goal of this project is to assess...... that correlates maximally to a native-decoy distance. The main contribution of this thesis is methods developed for analyzing the performance of metrically trained knowledge-based potentials and for optimizing their performance while making them less dependent on the decoy set used to define them. We focus...... being at-least a local minimum of the potential. To address how far the current functional form of the potential is from an ideal potential we present two methods for finding the optimal metrically trained potential that simultaneous has a number of native structures as a local minimum. Our results...

  15. G4-DNA formation in the HRAS promoter and rational design of decoy oligonucleotides for cancer therapy.

    Directory of Open Access Journals (Sweden)

    Alexandro Membrino

    Full Text Available HRAS is a proto-oncogene involved in the tumorigenesis of urinary bladder cancer. In the HRAS promoter we identified two G-rich elements, hras-1 and hras-2, that fold, respectively, into an antiparallel and a parallel quadruplex (qhras-1, qhras-2. When we introduced in sequence hras-1 or hras-2 two point mutations that block quadruplex formation, transcription increased 5-fold, but when we stabilized the G-quadruplexes by guanidinium phthalocyanines, transcription decreased to 20% of control. By ChIP we found that sequence hras-1 is bound only by MAZ, while hras-2 is bound by MAZ and Sp1: two transcription factors recognizing guanine boxes. We also discovered by EMSA that recombinant MAZ-GST binds to both HRAS quadruplexes, while Sp1-GST only binds to qhras-1. The over-expression of MAZ and Sp1 synergistically activates HRAS transcription, while silencing each gene by RNAi results in a strong down-regulation of transcription. All these data indicate that the HRAS G-quadruplexes behave as transcription repressors. Finally, we designed decoy oligonucleotides mimicking the HRAS quadruplexes, bearing (R-1-O-[4-(1-Pyrenylethynyl phenylmethyl] glycerol and LNA modifications to increase their stability and nuclease resistance (G4-decoys. The G4-decoys repressed HRAS transcription and caused a strong antiproliferative effect, mediated by apoptosis, in T24 bladder cancer cells where HRAS is mutated.

  16. Evaluation of multiple protein docking structures using correctly predicted pairwise subunits

    Directory of Open Access Journals (Sweden)

    Esquivel-Rodríguez Juan

    2012-03-01

    Full Text Available Abstract Background Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. Methods We generated a series of predicted models (decoys of various accuracies by our multiple protein docking pipeline, Multi-LZerD, for three multi-chain complexes with 3, 4, and 6 chains. We analyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys. Results and conclusion We found that pairs of chains with the correct mutual orientation exist even in the decoys with a large overall root mean square deviation (RMSD to the native. Therefore, in addition to a global structure similarity measure, such as the global RMSD, the quality of models for multiple chain complexes can be better evaluated by using the local measurement, the number of chain pairs with correct mutual orientation. We termed the fraction of correctly predicted pairs (RMSD at the interface of less than 4.0Å as fpair and propose to use it for evaluation of the accuracy of multiple protein docking.

  17. Ranking species in mutualistic networks

    Science.gov (United States)

    Domínguez-García, Virginia; Muñoz, Miguel A.

    2015-02-01

    Understanding the architectural subtleties of ecological networks, believed to confer them enhanced stability and robustness, is a subject of outmost relevance. Mutualistic interactions have been profusely studied and their corresponding bipartite networks, such as plant-pollinator networks, have been reported to exhibit a characteristic ``nested'' structure. Assessing the importance of any given species in mutualistic networks is a key task when evaluating extinction risks and possible cascade effects. Inspired in a recently introduced algorithm -similar in spirit to Google's PageRank but with a built-in non-linearity- here we propose a method which -by exploiting their nested architecture- allows us to derive a sound ranking of species importance in mutualistic networks. This method clearly outperforms other existing ranking schemes and can become very useful for ecosystem management and biodiversity preservation, where decisions on what aspects of ecosystems to explicitly protect need to be made.

  18. Ranking Theory and Conditional Reasoning.

    Science.gov (United States)

    Skovgaard-Olsen, Niels

    2016-05-01

    Ranking theory is a formal epistemology that has been developed in over 600 pages in Spohn's recent book The Laws of Belief, which aims to provide a normative account of the dynamics of beliefs that presents an alternative to current probabilistic approaches. It has long been received in the AI community, but it has not yet found application in experimental psychology. The purpose of this paper is to derive clear, quantitative predictions by exploiting a parallel between ranking theory and a statistical model called logistic regression. This approach is illustrated by the development of a model for the conditional inference task using Spohn's (2013) ranking theoretic approach to conditionals. Copyright © 2015 Cognitive Science Society, Inc.

  19. University rankings in computer science

    DEFF Research Database (Denmark)

    Ehret, Philip; Zuccala, Alesia Ann; Gipp, Bela

    2017-01-01

    This is a research-in-progress paper concerning two types of institutional rankings, the Leiden and QS World ranking, and their relationship to a list of universities’ ‘geo-based’ impact scores, and Computing Research and Education Conference (CORE) participation scores in the field of computer...... science. A ‘geo-based’ impact measure examines the geographical distribution of incoming citations to a particular university’s journal articles for a specific period of time. It takes into account both the number of citations and the geographical variability in these citations. The CORE participation...... score is calculated on the basis of the number of weighted proceedings papers that a university has contributed to either an A*, A, B, or C conference as ranked by the Computing Research and Education Association of Australasia. In addition to calculating the correlations between the distinct university...

  20. Subtracting a best rank-1 approximation may increase tensor rank

    NARCIS (Netherlands)

    Stegeman, Alwin; Comon, Pierre

    2010-01-01

    It has been shown that a best rank-R approximation of an order-k tensor may not exist when R >= 2 and k >= 3. This poses a serious problem to data analysts using tensor decompositions it has been observed numerically that, generally, this issue cannot be solved by consecutively computing and

  1. Consistent ranking of volatility models

    DEFF Research Database (Denmark)

    Hansen, Peter Reinhard; Lunde, Asger

    2006-01-01

    We show that the empirical ranking of volatility models can be inconsistent for the true ranking if the evaluation is based on a proxy for the population measure of volatility. For example, the substitution of a squared return for the conditional variance in the evaluation of ARCH-type models can...... variance in out-of-sample evaluations rather than the squared return. We derive the theoretical results in a general framework that is not specific to the comparison of volatility models. Similar problems can arise in comparisons of forecasting models whenever the predicted variable is a latent variable....

  2. Virtual Screening of M3 Protein Antagonists for Finding a Model to Study the Gammaherpesvirus Damaged Immune System and Chemokine Related Diseases

    Directory of Open Access Journals (Sweden)

    Ibrahim Torktaz

    2013-12-01

    Full Text Available Introduction: M3 protein is a chemokine decoy receptor involved in pathogenesis of persistent infection with gammaherpesvirus and complications related to the latency of this pathogen. We proposed that antagonists of the M3 would provide a unique opportunity for studying new therapeutic strategies in disordered immune system, immune-deficient states and role of chemokines in pathogenesis development. Methods: Comparative modeling and fold recognition algorithms have been used for prediction of M3 protein 3-D model. Evaluation of the models using Q-mean and ProSA-web score, has led to choosing predicted model by fold recognition algorithm as the best model which was minimized regarding energy level using Molegro Virtual Docker 2011.4.3.0 (MVD software. Pockets and active sites of model were recognized using MVD cavity detection, and MetaPocket algorithms. Ten thousand compounds accessible on KEGG database were screened; MVD was used for computer simulated docking study; MolDock SE was selected as docking scoring function and final results were evaluated based on MolDock and Re-rank score. Results: Docking data suggested that prilocaine, which is generally applied as a topical anesthetic, binds strongly to 3-D model of M3 protein. Conclusion: This study proposes that prilocaine is a potential inhibitor of M3 protein and possibly has immune enhancing properties.

  3. Genetic deletion of muscle RANK or selective inhibition of RANKL is not as effective as full-length OPG-fc in mitigating muscular dystrophy.

    Science.gov (United States)

    Dufresne, Sébastien S; Boulanger-Piette, Antoine; Bossé, Sabrina; Argaw, Anteneh; Hamoudi, Dounia; Marcadet, Laetitia; Gamu, Daniel; Fajardo, Val A; Yagita, Hideo; Penninger, Josef M; Russell Tupling, A; Frenette, Jérôme

    2018-04-24

    Although there is a strong association between osteoporosis and skeletal muscle atrophy/dysfunction, the functional relevance of a particular biological pathway that regulates synchronously bone and skeletal muscle physiopathology is still elusive. Receptor-activator of nuclear factor κB (RANK), its ligand RANKL and the soluble decoy receptor osteoprotegerin (OPG) are the key regulators of osteoclast differentiation and bone remodelling. We thus hypothesized that RANK/RANKL/OPG, which is a key pathway for bone regulation, is involved in Duchenne muscular dystrophy (DMD) physiopathology. Our results show that muscle-specific RANK deletion (mdx-RANK mko ) in dystrophin deficient mdx mice improves significantly specific force [54% gain in force] of EDL muscles with no protective effect against eccentric contraction-induced muscle dysfunction. In contrast, full-length OPG-Fc injections restore the force of dystrophic EDL muscles [162% gain in force], protect against eccentric contraction-induced muscle dysfunction ex vivo and significantly improve functional performance on downhill treadmill and post-exercise physical activity. Since OPG serves a soluble receptor for RANKL and as a decoy receptor for TRAIL, mdx mice were injected with anti-RANKL and anti-TRAIL antibodies to decipher the dual function of OPG. Injections of anti-RANKL and/or anti-TRAIL increase significantly the force of dystrophic EDL muscle [45% and 17% gains in force, respectively]. In agreement, truncated OPG-Fc that contains only RANKL domains produces similar gains, in terms of force production, than anti-RANKL treatments. To corroborate that full-length OPG-Fc also acts independently of RANK/RANKL pathway, dystrophin/RANK double-deficient mice were treated with full-length OPG-Fc for 10 days. Dystrophic EDL muscles exhibited a significant gain in force relative to untreated dystrophin/RANK double-deficient mice, indicating that the effect of full-length OPG-Fc is in part independent of the RANKL/RANK

  4. Let Us Rank Journalism Programs

    Science.gov (United States)

    Weber, Joseph

    2014-01-01

    Unlike law, business, and medical schools, as well as universities in general, journalism schools and journalism programs have rarely been ranked. Publishers such as "U.S. News & World Report," "Forbes," "Bloomberg Businessweek," and "Washington Monthly" do not pay them much mind. What is the best…

  5. On Rank Driven Dynamical Systems

    Science.gov (United States)

    Veerman, J. J. P.; Prieto, F. J.

    2014-08-01

    We investigate a class of models related to the Bak-Sneppen (BS) model, initially proposed to study evolution. The BS model is extremely simple and yet captures some forms of "complex behavior" such as self-organized criticality that is often observed in physical and biological systems. In this model, random fitnesses in are associated to agents located at the vertices of a graph . Their fitnesses are ranked from worst (0) to best (1). At every time-step the agent with the worst fitness and some others with a priori given rank probabilities are replaced by new agents with random fitnesses. We consider two cases: The exogenous case where the new fitnesses are taken from an a priori fixed distribution, and the endogenous case where the new fitnesses are taken from the current distribution as it evolves. We approximate the dynamics by making a simplifying independence assumption. We use Order Statistics and Dynamical Systems to define a rank-driven dynamical system that approximates the evolution of the distribution of the fitnesses in these rank-driven models, as well as in the BS model. For this simplified model we can find the limiting marginal distribution as a function of the initial conditions. Agreement with experimental results of the BS model is excellent.

  6. PageRank (II): Mathematics

    African Journals Online (AJOL)

    maths/stats

    ... GAUSS SEIDEL'S. NUMERICAL ALGORITHMS IN PAGE RANK ANALYSIS. ... The convergence is guaranteed, if the absolute value of the largest eigen ... improved Gauss-Seidel iteration algorithm, based on the decomposition. U. L. D. M. +. +. = ..... This corresponds to determine the eigen vector of T with eigen value 1.

  7. Protein Loop Structure Prediction Using Conformational Space Annealing.

    Science.gov (United States)

    Heo, Seungryong; Lee, Juyong; Joo, Keehyoung; Shin, Hang-Cheol; Lee, Jooyoung

    2017-05-22

    We have developed a protein loop structure prediction method by combining a new energy function, which we call E PLM (energy for protein loop modeling), with the conformational space annealing (CSA) global optimization algorithm. The energy function includes stereochemistry, dynamic fragment assembly, distance-scaled finite ideal gas reference (DFIRE), and generalized orientation- and distance-dependent terms. For the conformational search of loop structures, we used the CSA algorithm, which has been quite successful in dealing with various hard global optimization problems. We assessed the performance of E PLM with two widely used loop-decoy sets, Jacobson and RAPPER, and compared the results against the DFIRE potential. The accuracy of model selection from a pool of loop decoys as well as de novo loop modeling starting from randomly generated structures was examined separately. For the selection of a nativelike structure from a decoy set, E PLM was more accurate than DFIRE in the case of the Jacobson set and had similar accuracy in the case of the RAPPER set. In terms of sampling more nativelike loop structures, E PLM outperformed E DFIRE for both decoy sets. This new approach equipped with E PLM and CSA can serve as the state-of-the-art de novo loop modeling method.

  8. 14 CFR 1214.1105 - Final ranking.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

  9. A Survey on PageRank Computing

    OpenAIRE

    Berkhin, Pavel

    2005-01-01

    This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

  10. Time evolution of Wikipedia network ranking

    Science.gov (United States)

    Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

    2013-12-01

    We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

  11. Validating rankings in soccer championships

    Directory of Open Access Journals (Sweden)

    Annibal Parracho Sant'Anna

    2012-08-01

    Full Text Available The final ranking of a championship is determined by quality attributes combined with other factors which should be filtered out of any decision on relegation or draft for upper level tournaments. Factors like referees' mistakes and difficulty of certain matches due to its accidental importance to the opponents should have their influence reduced. This work tests approaches to combine classification rules considering the imprecision of the number of points as a measure of quality and of the variables that provide reliable explanation for it. Two home-advantage variables are tested and shown to be apt to enter as explanatory variables. Independence between the criteria is checked against the hypothesis of maximal correlation. The importance of factors and of composition rules is evaluated on the basis of correlation between rank vectors, number of classes and number of clubs in tail classes. Data from five years of the Brazilian Soccer Championship are analyzed.

  12. Minkowski metrics in creating universal ranking algorithms

    Directory of Open Access Journals (Sweden)

    Andrzej Ameljańczyk

    2014-06-01

    Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

  13. Functional Multiplex PageRank

    Science.gov (United States)

    Iacovacci, Jacopo; Rahmede, Christoph; Arenas, Alex; Bianconi, Ginestra

    2016-10-01

    Recently it has been recognized that many complex social, technological and biological networks have a multilayer nature and can be described by multiplex networks. Multiplex networks are formed by a set of nodes connected by links having different connotations forming the different layers of the multiplex. Characterizing the centrality of the nodes in a multiplex network is a challenging task since the centrality of the node naturally depends on the importance associated to links of a certain type. Here we propose to assign to each node of a multiplex network a centrality called Functional Multiplex PageRank that is a function of the weights given to every different pattern of connections (multilinks) existent in the multiplex network between any two nodes. Since multilinks distinguish all the possible ways in which the links in different layers can overlap, the Functional Multiplex PageRank can describe important non-linear effects when large relevance or small relevance is assigned to multilinks with overlap. Here we apply the Functional Page Rank to the multiplex airport networks, to the neuronal network of the nematode C. elegans, and to social collaboration and citation networks between scientists. This analysis reveals important differences existing between the most central nodes of these networks, and the correlations between their so-called pattern to success.

  14. Low rank magnetic resonance fingerprinting.

    Science.gov (United States)

    Mazor, Gal; Weizman, Lior; Tal, Assaf; Eldar, Yonina C

    2016-08-01

    Magnetic Resonance Fingerprinting (MRF) is a relatively new approach that provides quantitative MRI using randomized acquisition. Extraction of physical quantitative tissue values is preformed off-line, based on acquisition with varying parameters and a dictionary generated according to the Bloch equations. MRF uses hundreds of radio frequency (RF) excitation pulses for acquisition, and therefore high under-sampling ratio in the sampling domain (k-space) is required. This under-sampling causes spatial artifacts that hamper the ability to accurately estimate the quantitative tissue values. In this work, we introduce a new approach for quantitative MRI using MRF, called Low Rank MRF. We exploit the low rank property of the temporal domain, on top of the well-known sparsity of the MRF signal in the generated dictionary domain. We present an iterative scheme that consists of a gradient step followed by a low rank projection using the singular value decomposition. Experiments on real MRI data demonstrate superior results compared to conventional implementation of compressed sensing for MRF at 15% sampling ratio.

  15. Ranking Support Vector Machine with Kernel Approximation

    Directory of Open Access Journals (Sweden)

    Kai Chen

    2017-01-01

    Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  16. Ranking Support Vector Machine with Kernel Approximation.

    Science.gov (United States)

    Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

    2017-01-01

    Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

  17. Identification of significant features by the Global Mean Rank test.

    Science.gov (United States)

    Klammer, Martin; Dybowski, J Nikolaj; Hoffmann, Daniel; Schaab, Christoph

    2014-01-01

    With the introduction of omics-technologies such as transcriptomics and proteomics, numerous methods for the reliable identification of significantly regulated features (genes, proteins, etc.) have been developed. Experimental practice requires these tests to successfully deal with conditions such as small numbers of replicates, missing values, non-normally distributed expression levels, and non-identical distributions of features. With the MeanRank test we aimed at developing a test that performs robustly under these conditions, while favorably scaling with the number of replicates. The test proposed here is a global one-sample location test, which is based on the mean ranks across replicates, and internally estimates and controls the false discovery rate. Furthermore, missing data is accounted for without the need of imputation. In extensive simulations comparing MeanRank to other frequently used methods, we found that it performs well with small and large numbers of replicates, feature dependent variance between replicates, and variable regulation across features on simulation data and a recent two-color microarray spike-in dataset. The tests were then used to identify significant changes in the phosphoproteomes of cancer cells induced by the kinase inhibitors erlotinib and 3-MB-PP1 in two independently published mass spectrometry-based studies. MeanRank outperformed the other global rank-based methods applied in this study. Compared to the popular Significance Analysis of Microarrays and Linear Models for Microarray methods, MeanRank performed similar or better. Furthermore, MeanRank exhibits more consistent behavior regarding the degree of regulation and is robust against the choice of preprocessing methods. MeanRank does not require any imputation of missing values, is easy to understand, and yields results that are easy to interpret. The software implementing the algorithm is freely available for academic and commercial use.

  18. Cell adhesion signaling regulates RANK expression in osteoclast precursors.

    Directory of Open Access Journals (Sweden)

    Ayako Mochizuki

    Full Text Available Cells with monocyte/macrophage lineage expressing receptor activator of NF-κB (RANK differentiate into osteoclasts following stimulation with the RANK ligand (RANKL. Cell adhesion signaling is also required for osteoclast differentiation from precursors. However, details of the mechanism by which cell adhesion signals induce osteoclast differentiation have not been fully elucidated. To investigate the participation of cell adhesion signaling in osteoclast differentiation, mouse bone marrow-derived macrophages (BMMs were used as osteoclast precursors, and cultured on either plastic cell culture dishes (adherent condition or the top surface of semisolid methylcellulose gel loaded in culture tubes (non-adherent condition. BMMs cultured under the adherent condition differentiated into osteoclasts in response to RANKL stimulation. However, under the non-adherent condition, the efficiency of osteoclast differentiation was markedly reduced even in the presence of RANKL. These BMMs retained macrophage characteristics including phagocytic function and gene expression profile. Lipopolysaccharide (LPS and tumor necrosis factor -αTNF-α activated the NF-κB-mediated signaling pathways under both the adherent and non-adherent conditions, while RANKL activated the pathways only under the adherent condition. BMMs highly expressed RANK mRNA and protein under the adherent condition as compared to the non-adherent condition. Also, BMMs transferred from the adherent to non-adherent condition showed downregulated RANK expression within 24 hours. In contrast, transferring those from the non-adherent to adherent condition significantly increased the level of RANK expression. Moreover, interruption of cell adhesion signaling by echistatin, an RGD-containing disintegrin, decreased RANK expression in BMMs, while forced expression of either RANK or TNFR-associated factor 6 (TRAF6 in BMMs induced their differentiation into osteoclasts even under the non

  19. Monitoring of West Nile virus, Usutu virus and Meaban virus in waterfowl used as decoys and wild raptors in southern Spain.

    Science.gov (United States)

    Jurado-Tarifa, E; Napp, S; Lecollinet, S; Arenas, A; Beck, C; Cerdà-Cuéllar, M; Fernández-Morente, M; García-Bocanegra, I

    2016-12-01

    In the last decade, the number of emerging flaviviruses described worldwide has increased considerably, with wild birds acting as the main reservoir hosts of these viruses. We carried out an epidemiological survey to determine the seroprevalence of antigenically related flaviviruses, particularly West Nile virus (WNV), Usutu virus (USUV) and Meaban virus (MBV), in waterfowl used as decoys and wild raptors in Andalusia (southern Spain), the region considered to have the highest risk of flaviviruses circulation in Spain. The overall flaviviruses seroprevalence according to bELISA was 13.0% in both in decoys (n=1052) and wild raptors (n=123). Specific antibodies against WNV, USUV and MBV were confirmed by micro virus neutralization tests in 12, 38 and 4 of the seropositive decoys, respectively. This is the first study on WNV and USUV infections in decoys and the first report of MBV infections in waterfowl and raptors. Moreover we report the first description of WNV infections in short-toed snake eagle (Circaetus gallicus) and Montagu's harrier (Circus pygargus). The seropositivity obtained indicates widespread but not homogeneous distribution of WNV and USUV in Andalusia. The results also confirm endemic circulation of WNV, USUV and MBV in both decoys and wild raptors in southern Spain. Our results highlight the need to implement surveillance and control programs not only for WNV but also for other related flaviviruses. Further research is needed to determine the eco-epidemiological role that waterfowl and wild raptors play in the transmission of emerging flaviviruses, especially in decoys, given their close interactions with humans. Copyright © 2016 Elsevier Ltd. All rights reserved.

  20. Efficacy of a Cell-Cycle Decoying Killer Adenovirus on 3-D Gelfoam®-Histoculture and Tumor-Sphere Models of Chemo-Resistant Stomach Carcinomatosis Visualized by FUCCI Imaging.

    Directory of Open Access Journals (Sweden)

    Shuya Yano

    Full Text Available Stomach cancer carcinomatosis peritonitis (SCCP is a recalcitrant disease. The goal of the present study was to establish an in vitro-in vivo-like imageable model of SCCP to develop cell-cycle-based therapeutics of SCCP. We established 3-D Gelfoam® histoculture and tumor-sphere models of SCCP. FUCCI-expressing MKN-45 stomach cancer cells were transferred to express the fluorescence ubiquinized cell-cycle indicator (FUCCI. FUCCI-expressing MKN-45 cells formed spheres on agarose or on Gelfoam® grew into tumor-like structures with G0/G1 cancer cells in the center and S/G2 cancer cells located in the surface as indicated by FUCCI imaging when the cells fluoresced red or green, respectively. We treated FUCCI-expressing cancer cells forming SCCP tumors in Gelfoam® histoculture with OBP-301, cisplatinum (CDDP, or paclitaxel. CDDP or paclitaxel killed only cycling cancer cells and were ineffective against G1/G2 MKN-45 cells in tumors growing on Gelfoam®. In contrast, the telomerase-dependent adenovirus OBP-301 decoyed the MKN-45 cells in tumors on Gelfoam® to cycle from G0/G1 phase to S/G2 phase and reduced their viability. CDDP- or paclitaxel-treated MKN-45 tumors remained quiescent and did not change in size. In contrast, OB-301 reduced the size of the MKN-45 tumors on Gelfoam®. We examined the cell cycle-related proteins using Western blotting. CDDP increased the expression of p53 and p21 indicating cell cycle arrest. In contrast, OBP-301 decreased the expression of p53 and p21 Furthermore, OBP-301 increased the expression of E2F and pAkt as further indication of cell cycle decoy. This 3-D Gelfoam® histoculture and FUCCI imaging are powerful tools to discover effective therapy of SCCP such as OBP-301.

  1. Efficacy of a Cell-Cycle Decoying Killer Adenovirus on 3-D Gelfoam®-Histoculture and Tumor-Sphere Models of Chemo-Resistant Stomach Carcinomatosis Visualized by FUCCI Imaging

    Science.gov (United States)

    Yano, Shuya; Takehara, Kiyoto; Tazawa, Hiroshi; Kishimoto, Hiroyuki; Urata, Yasuo; Kagawa, Shunsuke; Fujiwara, Toshiyoshi; Hoffman, Robert M.

    2016-01-01

    Stomach cancer carcinomatosis peritonitis (SCCP) is a recalcitrant disease. The goal of the present study was to establish an in vitro-in vivo-like imageable model of SCCP to develop cell-cycle-based therapeutics of SCCP. We established 3-D Gelfoam® histoculture and tumor-sphere models of SCCP. FUCCI-expressing MKN-45 stomach cancer cells were transferred to express the fluorescence ubiquinized cell-cycle indicator (FUCCI). FUCCI-expressing MKN-45 cells formed spheres on agarose or on Gelfoam® grew into tumor-like structures with G0/G1 cancer cells in the center and S/G2 cancer cells located in the surface as indicated by FUCCI imaging when the cells fluoresced red or green, respectively. We treated FUCCI-expressing cancer cells forming SCCP tumors in Gelfoam® histoculture with OBP-301, cisplatinum (CDDP), or paclitaxel. CDDP or paclitaxel killed only cycling cancer cells and were ineffective against G1/G2 MKN-45 cells in tumors growing on Gelfoam®. In contrast, the telomerase-dependent adenovirus OBP-301 decoyed the MKN-45 cells in tumors on Gelfoam® to cycle from G0/G1 phase to S/G2 phase and reduced their viability. CDDP- or paclitaxel-treated MKN-45 tumors remained quiescent and did not change in size. In contrast, OB-301 reduced the size of the MKN-45 tumors on Gelfoam®. We examined the cell cycle-related proteins using Western blotting. CDDP increased the expression of p53 and p21 indicating cell cycle arrest. In contrast, OBP-301 decreased the expression of p53 and p21 Furthermore, OBP-301 increased the expression of E2F and pAkt as further indication of cell cycle decoy. This 3-D Gelfoam® histoculture and FUCCI imaging are powerful tools to discover effective therapy of SCCP such as OBP-301. PMID:27673332

  2. GPCR-Bench: A Benchmarking Set and Practitioners' Guide for G Protein-Coupled Receptor Docking.

    Science.gov (United States)

    Weiss, Dahlia R; Bortolato, Andrea; Tehan, Benjamin; Mason, Jonathan S

    2016-04-25

    Virtual screening is routinely used to discover new ligands and in particular new ligand chemotypes for G protein-coupled receptors (GPCRs). To prepare for a virtual screen, we often tailor a docking protocol that will enable us to select the best candidates for further screening. To aid this, we created GPCR-Bench, a publically available docking benchmarking set in the spirit of the DUD and DUD-E reference data sets for validation studies, containing 25 nonredundant high-resolution GPCR costructures with an accompanying set of diverse ligands and computational decoy molecules for each target. Benchmarking sets are often used to compare docking protocols; however, it is important to evaluate docking methods not by "retrospective" hit rates but by the actual likelihood that they will produce novel prospective hits. Therefore, docking protocols must not only rank active molecules highly but also produce good poses that a chemist will select for purchase and screening. Currently, no simple objective machine-scriptable function exists that can do this; instead, docking hit lists must be subjectively examined in a consistent way to compare between docking methods. We present here a case study highlighting considerations we feel are of importance when evaluating a method, intended to be useful as a practitioners' guide.

  3. SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

    Science.gov (United States)

    Shams, Bita; Haratizadeh, Saman

    2016-09-01

    Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

  4. Rank Two Affine Manifolds in Genus 3

    OpenAIRE

    Aulicino, David; Nguyen, Duc-Manh

    2016-01-01

    We complete the classification of rank two affine manifolds in the moduli space of translation surfaces in genus three. Combined with a recent result of Mirzakhani and Wright, this completes the classification of higher rank affine manifolds in genus three.

  5. The relationship of plasma decoy receptor 3 and coronary collateral circulation in patients with coronary artery disease.

    Science.gov (United States)

    Yan, Youyou; Song, Dandan; Liu, Lulu; Meng, Xiuping; Qi, Chao; Wang, Junnan

    2017-11-15

    Previously, decoy receptor 3 (DcR3) was found to be a potential angiogenetic factor, while the relationship of DcR3 with coronary collateral circulation formation has not been investigated. In this study, we aimed to investigate whether plasma decoy receptor 3 levels was associated with CCC formation and evaluate its predictive power for CCC status in patients with coronary artery disease. Among patients who underwent coronary angiography with coronary artery disease and had a stenosis of ≥90% were included in our study. Collateral degree was graded according to Rentrope Cohen classification. Patients with grade 2 or 3 collateral degree were enrolled in good CCC group and patients with grade 0 or 1 collateral degree were enrolled in poor CCC group. Plasma DcR3 level was significantly higher in good CCC group (328.00±230.82 vs 194.84±130.63ng/l, p<0.01) and positively correlated with Rentrope grade (p<0.01). In addition, plasma DcR3 was also positively correlated with VEGF-A. Both ROC (receiver operating characteristic curve) and multinomial logistical regression analysis showed that plasma DcR3 displayed potent predictive power for CCC status. Higher plasma DcR3 level was related to better CCC formation and displayed potent predictive power for CCC status. Copyright © 2017. Published by Elsevier Inc.

  6. TRAM-Derived Decoy Peptides inhibits the inflammatory response in mouse mammary epithelial cells and a mastitis model in mice.

    Science.gov (United States)

    Hu, Xiaoyu; Tian, Yuan; Wang, Tiancheng; Zhang, Wenlong; Wang, Wei; Gao, Xuejiao; Qu, Shihui; Cao, Yongguo; Zhang, Naisheng

    2015-10-05

    It has been proved that TRAM-Derived Decoy peptides have anti-inflammatory properties. In this study, we synthesized a TRAM-Derived decoy peptide (TM6), belongs to TRAM TIR domain, of which sequence is "N"-RQIKIWFQNRRMKWK, KENFLRDTWCNFQFY-"C" and evaluated the effects of TM6 on lipopolysaccharide-induced mastitis in mice. In vivo, LPS-induced mice mastitis model was established by injection of LPS through the duct of mammary gland. TM6 was injected 1h before or after LPS treatment. In vitro, primary mouse mammary epithelial cells were used to investigate the effects of TM6 on LPS-induced inflammatory responses. The results showed that TM6 inhibited LPS-induced mammary gland histopathologic changes, MPO activity, and TNF-α, IL-1β and IL-6 production in mice. In vitro, TM6 significantly inhibited LPS-induced TNF-α and IL-6 production, as well as NF-κB and MAPKs activation. In conclusion, this study demonstrated that TM6 had protective effects on LPS-mastitis and may be a promising therapeutic reagent for mastitis treatment. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. A PCR-Based Method to Construct Lentiviral Vector Expressing Double Tough Decoy for miRNA Inhibition.

    Directory of Open Access Journals (Sweden)

    Huiling Qiu

    Full Text Available DNA vector-encoded Tough Decoy (TuD miRNA inhibitor is attracting increased attention due to its high efficiency in miRNA suppression. The current methods used to construct TuD vectors are based on synthesizing long oligonucleotides (~90 mer, which have been costly and problematic because of mutations during synthesis. In this study, we report a PCR-based method for the generation of double Tough Decoy (dTuD vector in which only two sets of shorter oligonucleotides (< 60 mer were used. Different approaches were employed to test the inhibitory potency of dTuDs. We demonstrated that dTuD is the most efficient method in miRNA inhibition in vitro and in vivo. Using this method, a mini dTuD library against 88 human miRNAs was constructed and used for a high-throughput screening (HTS of AP-1 pathway-related miRNAs. Seven miRNAs (miR-18b-5p, -101-3p, -148b-3p, -130b-3p, -186-3p, -187-3p and -1324 were identified as candidates involved in AP-1 pathway regulation. This novel method allows for an accurate and cost-effective generation of dTuD miRNA inhibitor, providing a powerful tool for efficient miRNA suppression in vitro and in vivo.

  8. Free-space measurement-device-independent quantum-key-distribution protocol using decoy states with orbital angular momentum

    International Nuclear Information System (INIS)

    Wang Le; Zhao Sheng-Mei; Cheng Wei-Wen; Gong Long-Yan

    2015-01-01

    In this paper, we propose a measurement-device-independent quantum-key-distribution (MDI-QKD) protocol using orbital angular momentum (OAM) in free space links, named the OAM-MDI-QKD protocol. In the proposed protocol, the OAM states of photons, instead of polarization states, are used as the information carriers to avoid the reference frame alignment, the decoy-state is adopted to overcome the security loophole caused by the weak coherent pulse source, and the high efficient OAM-sorter is adopted as the measurement tool for Charlie to obtain the output OAM state. Here, Charlie may be an untrusted third party. The results show that the authorized users, Alice and Bob, could distill a secret key with Charlie’s successful measurements, and the key generation performance is slightly better than that of the polarization-based MDI-QKD protocol in the two-dimensional OAM cases. Simultaneously, Alice and Bob can reduce the number of flipping the bits in the secure key distillation. It is indicated that a higher key generation rate performance could be obtained by a high dimensional OAM-MDI-QKD protocol because of the unlimited degree of freedom on OAM states. Moreover, the results show that the key generation rate and the transmission distance will decrease as the growth of the strength of atmospheric turbulence (AT) and the link attenuation. In addition, the decoy states used in the proposed protocol can get a considerable good performance without the need for an ideal source. (paper)

  9. The Privilege of Ranking: Google Plays Ball.

    Science.gov (United States)

    Wiggins, Richard

    2003-01-01

    Discussion of ranking systems used in various settings, including college football and academic admissions, focuses on the Google search engine. Explains the PageRank mathematical formula that scores Web pages by connecting the number of links; limitations, including authenticity and accuracy of ranked Web pages; relevancy; adjusting algorithms;…

  10. A Comprehensive Analysis of Marketing Journal Rankings

    Science.gov (United States)

    Steward, Michelle D.; Lewis, Bruce R.

    2010-01-01

    The purpose of this study is to offer a comprehensive assessment of journal standings in Marketing from two perspectives. The discipline perspective of rankings is obtained from a collection of published journal ranking studies during the past 15 years. The studies in the published ranking stream are assessed for reliability by examining internal…

  11. Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

    Directory of Open Access Journals (Sweden)

    Felix Simkovic

    2016-07-01

    Full Text Available For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based structure prediction. Such models can be used in structure solution by molecular replacement (MR where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (`decoys', is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing.

  12. Two-dimensional ranking of Wikipedia articles

    Science.gov (United States)

    Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

    2010-10-01

    The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

  13. Systemic levels of the anti-inflammatory decoy receptor soluble RAGE (receptor for advanced glycation end products) are decreased in dogs with inflammatory bowel disease.

    Science.gov (United States)

    Heilmann, Romy M; Otoni, Cristiane C; Jergens, Albert E; Grützner, Niels; Suchodolski, Jan S; Steiner, Jörg M

    2014-10-15

    Inflammatory bowel disease (IBD) is a common condition in dogs, and a dysregulated innate immunity is believed to play a major role in its pathogenesis. S100A12 is an endogenous damage-associated molecular pattern molecule, which is involved in phagocyte activation and is increased in serum/fecal samples from dogs with IBD. S100A12 binds to the receptor of advanced glycation end products (RAGE), a pattern-recognition receptor, and results of studies in human patients with IBD and other conditions suggest a role of RAGE in chronic inflammation. Soluble RAGE (sRAGE), a decoy receptor for inflammatory proteins (e.g., S100A12) that appears to function as an anti-inflammatory molecule, was shown to be decreased in human IBD patients. This study aimed to evaluate serum sRAGE and serum/fecal S100A12 concentrations in dogs with IBD. Serum and fecal samples were collected from 20 dogs with IBD before and after initiation of medical treatment and from 15 healthy control dogs. Serum sRAGE and serum and fecal S100A12 concentrations were measured by ELISA, and were compared between dogs with IBD and healthy controls, and between dogs with a positive outcome (i.e., clinical remission, n=13) and those that were euthanized (n=6). The relationship of serum sRAGE concentrations with clinical disease activity (using the CIBDAI scoring system), serum and fecal S100A12 concentrations, and histologic disease severity (using a 4-point semi-quantitative grading system) was tested. Serum sRAGE concentrations were significantly lower in dogs with IBD than in healthy controls (p=0.0003), but were not correlated with the severity of histologic lesions (p=0.4241), the CIBDAI score before (p=0.0967) or after treatment (p=0.1067), the serum S100A12 concentration before (p=0.9214) and after treatment (p=0.4411), or with the individual outcome (p=0.4066). Clinical remission and the change in serum sRAGE concentration after treatment were not significantly associated (p=0.5727); however, serum s

  14. 24 CFR 599.401 - Ranking of applications.

    Science.gov (United States)

    2010-04-01

    ... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false Ranking of applications. 599.401... Communities § 599.401 Ranking of applications. (a) Ranking order. Rural and urban applications will be ranked... applications ranked first. (b) Separate ranking categories. After initial ranking, both rural and urban...

  15. Agro-tourism and ranking

    Science.gov (United States)

    Cioca, L. I.; Giurea, R.; Precazzini, I.; Ragazzi, M.; Achim, M. I.; Schiavon, M.; Rada, E. C.

    2018-05-01

    Nowadays the global tourism growth has caused a significant interest in research focused on the impact of the tourism on environment and community. The purpose of this study is to introduce a new ranking for the classification of tourist accommodation establishments with the functions of agro-tourism boarding house type by examining the sector of agro-tourism based on a research aimed to improve the economic, socio-cultural and environmental performance of agrotourism structures. This paper links the criteria for the classification of agro-tourism boarding houses (ABHs) to the impact of agro-tourism activities on the environment, enhancing an eco-friendly approach on agro-tourism activities by increasing the quality reputation of the agro-tourism products and services. Taking into account the impact on the environment, agrotourism can play an important role by protecting and conserving it.

  16. A STAT3-decoy oligonucleotide induces cell death in a human colorectal carcinoma cell line by blocking nuclear transfer of STAT3 and STAT3-bound NF-κB

    Directory of Open Access Journals (Sweden)

    Le Coquil Stéphanie

    2011-04-01

    Full Text Available Abstract Background The transcription factor STAT3 (signal transducer and activator of transcription 3 is frequently activated in tumor cells. Activated STAT3 forms homodimers, or heterodimers with other TFs such as NF-κB, which becomes activated. Cytoplasmic STAT3 dimers are activated by tyrosine phosphorylation; they interact with importins via a nuclear localization signal (NLS one of which is located within the DNA-binding domain formed by the dimer. In the nucleus, STAT3 regulates target gene expression by binding a consensus sequence within the promoter. STAT3-specific decoy oligonucleotides (STAT3-decoy ODN that contain this consensus sequence inhibit the transcriptional activity of STAT3, leading to cell death; however, their mechanism of action is unclear. Results The mechanism of action of a STAT3-decoy ODN was analyzed in the colon carcinoma cell line SW 480. These cells' dependence on activated STAT3 was verified by showing that cell death is induced by STAT3-specific siRNAs or Stattic. STAT3-decoy ODN was shown to bind activated STAT3 within the cytoplasm, and to prevent its translocation to the nucleus, as well as that of STAT3-associated NF-κB, but it did not prevent the nuclear transfer of STAT3 with mutations in its DNA-binding domain. The complex formed by STAT3 and the STAT3-decoy ODN did not associate with importin, while STAT3 alone was found to co-immunoprecipitate with importin. Leptomycin B and vanadate both trap STAT3 in the nucleus. They were found here to oppose the cytoplasmic trapping of STAT3 by the STAT3-decoy ODN. Control decoys consisting of either a mutated STAT3-decoy ODN or a NF-κB-specific decoy ODN had no effect on STAT3 nuclear translocation. Finally, blockage of STAT3 nuclear transfer correlated with the induction of SW 480 cell death. Conclusions The inhibition of STAT3 by a STAT3-decoy ODN, leading to cell death, involves the entrapment of activated STAT3 dimers in the cytoplasm. A mechanism is

  17. Surface TRAIL decoy receptor-4 expression is correlated with TRAIL resistance in MCF7 breast cancer cells

    International Nuclear Information System (INIS)

    Sanlioglu, Ahter D; Dirice, Ercument; Aydin, Cigdem; Erin, Nuray; Koksoy, Sadi; Sanlioglu, Salih

    2005-01-01

    Tumor Necrosis Factor (TNF)-Related Apoptosis-Inducing Ligand (TRAIL) selectively induces apoptosis in cancer cells but not in normal cells. Despite this promising feature, TRAIL resistance observed in cancer cells seriously challenged the use of TRAIL as a death ligand in gene therapy. The current dispute concerns whether or not TRAIL receptor expression pattern is the primary determinant of TRAIL sensitivity in cancer cells. This study investigates TRAIL receptor expression pattern and its connection to TRAIL resistance in breast cancer cells. In addition, a DcR2 siRNA approach and a complementary gene therapy modality involving IKK inhibition (AdIKKβKA) were also tested to verify if these approaches could sensitize MCF7 breast cancer cells to adenovirus delivery of TRAIL (Ad5hTRAIL). TRAIL sensitivity assays were conducted using Molecular Probe's Live/Dead Cellular Viability/Cytotoxicity Kit following the infection of breast cancer cells with Ad5hTRAIL. The molecular mechanism of TRAIL induced cell death under the setting of IKK inhibition was revealed by Annexin V binding. Novel quantitative Real Time RT-PCR and flow cytometry analysis were performed to disclose TRAIL receptor composition in breast cancer cells. MCF7 but not MDA-MB-231 breast cancer cells displayed strong resistance to adenovirus delivery of TRAIL. Only the combinatorial use of Ad5hTRAIL and AdIKKβKA infection sensitized MCF7 breast cancer cells to TRAIL induced cell death. Moreover, novel quantitative Real Time RT-PCR assays suggested that while the level of TRAIL Decoy Receptor-4 (TRAIL-R4) expression was the highest in MCF7 cells, it was the lowest TRAIL receptor expressed in MDA-MB-231 cells. In addition, conventional flow cytometry analysis demonstrated that TRAIL resistant MCF7 cells exhibited substantial levels of TRAIL-R4 expression but not TRAIL decoy receptor-3 (TRAIL-R3) on surface. On the contrary, TRAIL sensitive MDA-MB-231 cells displayed very low levels of surface TRAIL-R4

  18. Error analysis of stochastic gradient descent ranking.

    Science.gov (United States)

    Chen, Hong; Tang, Yi; Li, Luoqing; Yuan, Yuan; Li, Xuelong; Tang, Yuanyan

    2013-06-01

    Ranking is always an important task in machine learning and information retrieval, e.g., collaborative filtering, recommender systems, drug discovery, etc. A kernel-based stochastic gradient descent algorithm with the least squares loss is proposed for ranking in this paper. The implementation of this algorithm is simple, and an expression of the solution is derived via a sampling operator and an integral operator. An explicit convergence rate for leaning a ranking function is given in terms of the suitable choices of the step size and the regularization parameter. The analysis technique used here is capacity independent and is novel in error analysis of ranking learning. Experimental results on real-world data have shown the effectiveness of the proposed algorithm in ranking tasks, which verifies the theoretical analysis in ranking error.

  19. Methodology for ranking restoration options

    International Nuclear Information System (INIS)

    Hedemann Jensen, Per

    1999-04-01

    The work described in this report has been performed as a part of the RESTRAT Project FI4P-CT95-0021a (PL 950128) co-funded by the Nuclear Fission Safety Programme of the European Commission. The RESTRAT project has the overall objective of developing generic methodologies for ranking restoration techniques as a function of contamination and site characteristics. The project includes analyses of existing remediation methodologies and contaminated sites, and is structured in the following steps: characterisation of relevant contaminated sites; identification and characterisation of relevant restoration techniques; assessment of the radiological impact; development and application of a selection methodology for restoration options; formulation of generic conclusions and development of a manual. The project is intended to apply to situations in which sites with nuclear installations have been contaminated with radioactive materials as a result of the operation of these installations. The areas considered for remedial measures include contaminated land areas, rivers and sediments in rivers, lakes, and sea areas. Five contaminated European sites have been studied. Various remedial measures have been envisaged with respect to the optimisation of the protection of the populations being exposed to the radionuclides at the sites. Cost-benefit analysis and multi-attribute utility analysis have been applied for optimisation. Health, economic and social attributes have been included and weighting factors for the different attributes have been determined by the use of scaling constants. (au)

  20. Citation graph based ranking in Invenio

    CERN Document Server

    Marian, Ludmila; Rajman, Martin; Vesely, Martin

    2010-01-01

    Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

  1. Communities in Large Networks: Identification and Ranking

    DEFF Research Database (Denmark)

    Olsen, Martin

    2008-01-01

    We study the problem of identifying and ranking the members of a community in a very large network with link analysis only, given a set of representatives of the community. We define the concept of a community justified by a formal analysis of a simple model of the evolution of a directed graph. ...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

  2. Ranking Entities in Networks via Lefschetz Duality

    DEFF Research Database (Denmark)

    Aabrandt, Andreas; Hansen, Vagn Lundsgaard; Poulsen, Bjarne

    2014-01-01

    then be ranked according to how essential their positions are in the network by considering the effect of their respective absences. Defining a ranking of a network which takes the individual position of each entity into account has the purpose of assigning different roles to the entities, e.g. agents......, in the network. In this paper it is shown that the topology of a given network induces a ranking of the entities in the network. Further, it is demonstrated how to calculate this ranking and thus how to identify weak sub-networks in any given network....

  3. A pairwise residue contact area-based mean force potential for discrimination of native protein structure

    Directory of Open Access Journals (Sweden)

    Pezeshk Hamid

    2010-01-01

    Full Text Available Abstract Background Considering energy function to detect a correct protein fold from incorrect ones is very important for protein structure prediction and protein folding. Knowledge-based mean force potentials are certainly the most popular type of interaction function for protein threading. They are derived from statistical analyses of interacting groups in experimentally determined protein structures. These potentials are developed at the atom or the amino acid level. Based on orientation dependent contact area, a new type of knowledge-based mean force potential has been developed. Results We developed a new approach to calculate a knowledge-based potential of mean-force, using pairwise residue contact area. To test the performance of our approach, we performed it on several decoy sets to measure its ability to discriminate native structure from decoys. This potential has been able to distinguish native structures from the decoys in the most cases. Further, the calculated Z-scores were quite high for all protein datasets. Conclusions This knowledge-based potential of mean force can be used in protein structure prediction, fold recognition, comparative modelling and molecular recognition. The program is available at http://www.bioinf.cs.ipm.ac.ir/softwares/surfield

  4. Ranking scientific publications: the effect of nonlinearity

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

    2014-10-01

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  5. Ranking scientific publications: the effect of nonlinearity.

    Science.gov (United States)

    Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; Di, Zengru

    2014-10-17

    Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.

  6. Neural Ranking Models with Weak Supervision

    NARCIS (Netherlands)

    Dehghani, M.; Zamani, H.; Severyn, A.; Kamps, J.; Croft, W.B.

    2017-01-01

    Despite the impressive improvements achieved by unsupervised deep neural networks in computer vision and NLP tasks, such improvements have not yet been observed in ranking for information retrieval. The reason may be the complexity of the ranking problem, as it is not obvious how to learn from

  7. A Rational Method for Ranking Engineering Programs.

    Science.gov (United States)

    Glower, Donald D.

    1980-01-01

    Compares two methods for ranking academic programs, the opinion poll v examination of career successes of the program's alumni. For the latter, "Who's Who in Engineering" and levels of research funding provided data. Tables display resulting data and compare rankings by the two methods for chemical engineering and civil engineering. (CS)

  8. Lerot: An Online Learning to Rank Framework

    NARCIS (Netherlands)

    Schuth, A.; Hofmann, K.; Whiteson, S.; de Rijke, M.

    2013-01-01

    Online learning to rank methods for IR allow retrieval systems to optimize their own performance directly from interactions with users via click feedback. In the software package Lerot, presented in this paper, we have bundled all ingredients needed for experimenting with online learning to rank for

  9. Adaptive distributional extensions to DFR ranking

    DEFF Research Database (Denmark)

    Petersen, Casper; Simonsen, Jakob Grue; Järvelin, Kalervo

    2016-01-01

    -fitting distribution. We call this model Adaptive Distributional Ranking (ADR) because it adapts the ranking to the statistics of the specific dataset being processed each time. Experiments on TREC data show ADR to outperform DFR models (and their extensions) and be comparable in performance to a query likelihood...

  10. Contests with rank-order spillovers

    NARCIS (Netherlands)

    M.R. Baye (Michael); D. Kovenock (Dan); C.G. de Vries (Casper)

    2012-01-01

    textabstractThis paper presents a unified framework for characterizing symmetric equilibrium in simultaneous move, two-player, rank-order contests with complete information, in which each player's strategy generates direct or indirect affine "spillover" effects that depend on the rank-order of her

  11. Classification of rank 2 cluster varieties

    DEFF Research Database (Denmark)

    Mandel, Travis

    We classify rank 2 cluster varieties (those whose corresponding skew-form has rank 2) according to the deformation type of a generic fiber U of their X-spaces, as defined by Fock and Goncharov. Our approach is based on the work of Gross, Hacking, and Keel for cluster varieties and log Calabi...

  12. Using centrality to rank web snippets

    NARCIS (Netherlands)

    Jijkoun, V.; de Rijke, M.; Peters, C.; Jijkoun, V.; Mandl, T.; Müller, H.; Oard, D.W.; Peñas, A.; Petras, V.; Santos, D.

    2008-01-01

    We describe our participation in the WebCLEF 2007 task, targeted at snippet retrieval from web data. Our system ranks snippets based on a simple similarity-based centrality, inspired by the web page ranking algorithms. We experimented with retrieval units (sentences and paragraphs) and with the

  13. Mining Feedback in Ranking and Recommendation Systems

    Science.gov (United States)

    Zhuang, Ziming

    2009-01-01

    The amount of online information has grown exponentially over the past few decades, and users become more and more dependent on ranking and recommendation systems to address their information seeking needs. The advance in information technologies has enabled users to provide feedback on the utilities of the underlying ranking and recommendation…

  14. Entity Ranking using Wikipedia as a Pivot

    NARCIS (Netherlands)

    R. Kaptein; P. Serdyukov; A.P. de Vries (Arjen); J. Kamps

    2010-01-01

    htmlabstractIn this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about

  15. Entity ranking using Wikipedia as a pivot

    NARCIS (Netherlands)

    Kaptein, R.; Serdyukov, P.; de Vries, A.; Kamps, J.; Huang, X.J.; Jones, G.; Koudas, N.; Wu, X.; Collins-Thompson, K.

    2010-01-01

    In this paper we investigate the task of Entity Ranking on the Web. Searchers looking for entities are arguably better served by presenting a ranked list of entities directly, rather than a list of web pages with relevant but also potentially redundant information about these entities. Since

  16. Rank 2 fusion rings are complete intersections

    DEFF Research Database (Denmark)

    Andersen, Troels Bak

    We give a non-constructive proof that fusion rings attached to a simple complex Lie algebra of rank 2 are complete intersections.......We give a non-constructive proof that fusion rings attached to a simple complex Lie algebra of rank 2 are complete intersections....

  17. A Ranking Method for Evaluating Constructed Responses

    Science.gov (United States)

    Attali, Yigal

    2014-01-01

    This article presents a comparative judgment approach for holistically scored constructed response tasks. In this approach, the grader rank orders (rather than rate) the quality of a small set of responses. A prior automated evaluation of responses guides both set formation and scaling of rankings. Sets are formed to have similar prior scores and…

  18. Ranking Music Data by Relevance and Importance

    DEFF Research Database (Denmark)

    Ruxanda, Maria Magdalena; Nanopoulos, Alexandros; Jensen, Christian Søndergaard

    2008-01-01

    Due to the rapidly increasing availability of audio files on the Web, it is relevant to augment search engines with advanced audio search functionality. In this context, the ranking of the retrieved music is an important issue. This paper proposes a music ranking method capable of flexibly fusing...

  19. Ranking of Unwarranted Variations in Healthcare Treatments

    NARCIS (Netherlands)

    Moes, Herry; Brekelmans, Ruud; Hamers, Herbert; Hasaart, F.

    2017-01-01

    In this paper, we introduce a framework designed to identify and rank possible unwarranted variation of treatments in healthcare. The innovative aspect of this framework is a ranking procedure that aims to identify healthcare institutions where unwarranted variation is most severe, and diagnosis

  20. The Rankings Game: Who's Playing Whom?

    Science.gov (United States)

    Burness, John F.

    2008-01-01

    This summer, Forbes magazine published its new rankings of "America's Best Colleges," implying that it had developed a methodology that would give the public the information that it needed to choose a college wisely. "U.S. News & World Report," which in 1983 published the first annual ranking, just announced its latest ratings last week--including…

  1. Dynamic collective entity representations for entity ranking

    NARCIS (Netherlands)

    Graus, D.; Tsagkias, M.; Weerkamp, W.; Meij, E.; de Rijke, M.

    2016-01-01

    Entity ranking, i.e., successfully positioning a relevant entity at the top of the ranking for a given query, is inherently difficult due to the potential mismatch between the entity's description in a knowledge base, and the way people refer to the entity when searching for it. To counter this

  2. Comparing side chain packing in soluble proteins, protein-protein interfaces, and transmembrane proteins.

    Science.gov (United States)

    Gaines, J C; Acebes, S; Virrueta, A; Butler, M; Regan, L; O'Hern, C S

    2018-05-01

    We compare side chain prediction and packing of core and non-core regions of soluble proteins, protein-protein interfaces, and transmembrane proteins. We first identified or created comparable databases of high-resolution crystal structures of these 3 protein classes. We show that the solvent-inaccessible cores of the 3 classes of proteins are equally densely packed. As a result, the side chains of core residues at protein-protein interfaces and in the membrane-exposed regions of transmembrane proteins can be predicted by the hard-sphere plus stereochemical constraint model with the same high prediction accuracies (>90%) as core residues in soluble proteins. We also find that for all 3 classes of proteins, as one moves away from the solvent-inaccessible core, the packing fraction decreases as the solvent accessibility increases. However, the side chain predictability remains high (80% within 30°) up to a relative solvent accessibility, rSASA≲0.3, for all 3 protein classes. Our results show that ≈40% of the interface regions in protein complexes are "core", that is, densely packed with side chain conformations that can be accurately predicted using the hard-sphere model. We propose packing fraction as a metric that can be used to distinguish real protein-protein interactions from designed, non-binding, decoys. Our results also show that cores of membrane proteins are the same as cores of soluble proteins. Thus, the computational methods we are developing for the analysis of the effect of hydrophobic core mutations in soluble proteins will be equally applicable to analyses of mutations in membrane proteins. © 2018 Wiley Periodicals, Inc.

  3. Comparing classical and quantum PageRanks

    Science.gov (United States)

    Loke, T.; Tang, J. W.; Rodriguez, J.; Small, M.; Wang, J. B.

    2017-01-01

    Following recent developments in quantum PageRanking, we present a comparative analysis of discrete-time and continuous-time quantum-walk-based PageRank algorithms. Relative to classical PageRank and to different extents, the quantum measures better highlight secondary hubs and resolve ranking degeneracy among peripheral nodes for all networks we studied in this paper. For the discrete-time case, we investigated the periodic nature of the walker's probability distribution for a wide range of networks and found that the dominant period does not grow with the size of these networks. Based on this observation, we introduce a new quantum measure using the maximum probabilities of the associated walker during the first couple of periods. This is particularly important, since it leads to a quantum PageRanking scheme that is scalable with respect to network size.

  4. Universal emergence of PageRank

    Energy Technology Data Exchange (ETDEWEB)

    Frahm, K M; Georgeot, B; Shepelyansky, D L, E-mail: frahm@irsamc.ups-tlse.fr, E-mail: georgeot@irsamc.ups-tlse.fr, E-mail: dima@irsamc.ups-tlse.fr [Laboratoire de Physique Theorique du CNRS, IRSAMC, Universite de Toulouse, UPS, 31062 Toulouse (France)

    2011-11-18

    The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter {alpha} Element-Of ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when {alpha} {yields} 1. The whole network can be divided into a core part and a group of invariant subspaces. For {alpha} {yields} 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at {alpha} {yields} 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

  5. Universal emergence of PageRank

    International Nuclear Information System (INIS)

    Frahm, K M; Georgeot, B; Shepelyansky, D L

    2011-01-01

    The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter α ∈ ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when α → 1. The whole network can be divided into a core part and a group of invariant subspaces. For α → 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at α → 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

  6. PageRank and rank-reversal dependence on the damping factor

    Science.gov (United States)

    Son, S.-W.; Christensen, C.; Grassberger, P.; Paczuski, M.

    2012-12-01

    PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d0=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d0.

  7. PageRank and rank-reversal dependence on the damping factor.

    Science.gov (United States)

    Son, S-W; Christensen, C; Grassberger, P; Paczuski, M

    2012-12-01

    PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d_{0}=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d_{0}.

  8. A tilting approach to ranking influence

    KAUST Repository

    Genton, Marc G.

    2014-12-01

    We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

  9. A Ranking Approach to Genomic Selection.

    Science.gov (United States)

    Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

    2015-01-01

    Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

  10. First rank symptoms for schizophrenia.

    Science.gov (United States)

    Soares-Weiser, Karla; Maayan, Nicola; Bergman, Hanna; Davenport, Clare; Kirkham, Amanda J; Grabowski, Sarah; Adams, Clive E

    2015-01-25

    Early and accurate diagnosis and treatment of schizophrenia may have long-term advantages for the patient; the longer psychosis goes untreated the more severe the repercussions for relapse and recovery. If the correct diagnosis is not schizophrenia, but another psychotic disorder with some symptoms similar to schizophrenia, appropriate treatment might be delayed, with possible severe repercussions for the person involved and their family. There is widespread uncertainty about the diagnostic accuracy of First Rank Symptoms (FRS); we examined whether they are a useful diagnostic tool to differentiate schizophrenia from other psychotic disorders. To determine the diagnostic accuracy of one or multiple FRS for diagnosing schizophrenia, verified by clinical history and examination by a qualified professional (e.g. psychiatrists, nurses, social workers), with or without the use of operational criteria and checklists, in people thought to have non-organic psychotic symptoms. We conducted searches in MEDLINE, EMBASE, and PsycInfo using OvidSP in April, June, July 2011 and December 2012. We also searched MEDION in December 2013. We selected studies that consecutively enrolled or randomly selected adults and adolescents with symptoms of psychosis, and assessed the diagnostic accuracy of FRS for schizophrenia compared to history and clinical examination performed by a qualified professional, which may or may not involve the use of symptom checklists or based on operational criteria such as ICD and DSM. Two review authors independently screened all references for inclusion. Risk of bias in included studies were assessed using the QUADAS-2 instrument. We recorded the number of true positives (TP), true negatives (TN), false positives (FP), and false negatives (FN) for constructing a 2 x 2 table for each study or derived 2 x 2 data from reported summary statistics such as sensitivity, specificity, and/or likelihood ratios. We included 21 studies with a total of 6253 participants

  11. Adiabatic quantum algorithm for search engine ranking.

    Science.gov (United States)

    Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A

    2012-06-08

    We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

  12. Ranking Adverse Drug Reactions With Crowdsourcing

    KAUST Repository

    Gottlieb, Assaf

    2015-03-23

    Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  13. Ranking adverse drug reactions with crowdsourcing.

    Science.gov (United States)

    Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

    2015-03-23

    There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

  14. RankExplorer: Visualization of Ranking Changes in Large Time Series Data.

    Science.gov (United States)

    Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin

    2012-12-01

    For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.

  15. Augmenting the Deliberative Method for Ranking Risks.

    Science.gov (United States)

    Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

    2016-01-01

    The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

  16. Communities in Large Networks: Identification and Ranking

    DEFF Research Database (Denmark)

    Olsen, Martin

    2008-01-01

    show that the problem of deciding whether a non trivial community exists is NP complete. Nevertheless, experiments show that a very simple greedy approach can identify members of a community in the Danish part of the web graph with time complexity only dependent on the size of the found community...... and its immediate surroundings. The members are ranked with a “local” variant of the PageRank algorithm. Results are reported from successful experiments on identifying and ranking Danish Computer Science sites and Danish Chess pages using only a few representatives....

  17. A Universal Rank-Size Law

    Science.gov (United States)

    2016-01-01

    A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

  18. Free-space measurement-device-independent quantum-key-distribution protocol using decoy states with orbital angular momentum

    Science.gov (United States)

    Wang, Le; Zhao, Sheng-Mei; Gong, Long-Yan; Cheng, Wei-Wen

    2015-12-01

    In this paper, we propose a measurement-device-independent quantum-key-distribution (MDI-QKD) protocol using orbital angular momentum (OAM) in free space links, named the OAM-MDI-QKD protocol. In the proposed protocol, the OAM states of photons, instead of polarization states, are used as the information carriers to avoid the reference frame alignment, the decoy-state is adopted to overcome the security loophole caused by the weak coherent pulse source, and the high efficient OAM-sorter is adopted as the measurement tool for Charlie to obtain the output OAM state. Here, Charlie may be an untrusted third party. The results show that the authorized users, Alice and Bob, could distill a secret key with Charlie’s successful measurements, and the key generation performance is slightly better than that of the polarization-based MDI-QKD protocol in the two-dimensional OAM cases. Simultaneously, Alice and Bob can reduce the number of flipping the bits in the secure key distillation. It is indicated that a higher key generation rate performance could be obtained by a high dimensional OAM-MDI-QKD protocol because of the unlimited degree of freedom on OAM states. Moreover, the results show that the key generation rate and the transmission distance will decrease as the growth of the strength of atmospheric turbulence (AT) and the link attenuation. In addition, the decoy states used in the proposed protocol can get a considerable good performance without the need for an ideal source. Project supported by the National Natural Science Foundation of China (Grant Nos. 61271238 and 61475075), the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20123223110003), the Natural Science Research Foundation for Universities of Jiangsu Province of China (Grant No. 11KJA510002), the Open Research Fund of Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, China (Grant No. NYKL2015011), and the

  19. Scalable Faceted Ranking in Tagging Systems

    Science.gov (United States)

    Orlicki, José I.; Alvarez-Hamelin, J. Ignacio; Fierens, Pablo I.

    Nowadays, web collaborative tagging systems which allow users to upload, comment on and recommend contents, are growing. Such systems can be represented as graphs where nodes correspond to users and tagged-links to recommendations. In this paper we analyze the problem of computing a ranking of users with respect to a facet described as a set of tags. A straightforward solution is to compute a PageRank-like algorithm on a facet-related graph, but it is not feasible for online computation. We propose an alternative: (i) a ranking for each tag is computed offline on the basis of tag-related subgraphs; (ii) a faceted order is generated online by merging rankings corresponding to all the tags in the facet. Based on the graph analysis of YouTube and Flickr, we show that step (i) is scalable. We also present efficient algorithms for step (ii), which are evaluated by comparing their results with two gold standards.

  20. Evaluation of treatment effects by ranking

    DEFF Research Database (Denmark)

    Halekoh, U; Kristensen, K

    2008-01-01

    In crop experiments measurements are often made by a judge evaluating the crops' conditions after treatment. In the present paper an analysis is proposed for experiments where plots of crops treated differently are mutually ranked. In the experimental layout the crops are treated on consecutive...... plots usually placed side by side in one or more rows. In the proposed method a judge ranks several neighbouring plots, say three, by ranking them from best to worst. For the next observation the judge moves on by no more than two plots, such that up to two plots will be re-evaluated again...... in a comparison with the new plot(s). Data from studies using this set-up were analysed by a Thurstonian random utility model, which assumed that the judge's rankings were obtained by comparing latent continuous utilities or treatment effects. For the latent utilities a variance component model was considered...

  1. Superfund Hazard Ranking System Training Course

    Science.gov (United States)

    The Hazard Ranking System (HRS) training course is a four and ½ day, intermediate-level course designed for personnel who are required to compile, draft, and review preliminary assessments (PAs), site inspections (SIs), and HRS documentation records/packag

  2. Who's bigger? where historical figures really rank

    CERN Document Server

    Skiena, Steven

    2014-01-01

    Is Hitler bigger than Napoleon? Washington bigger than Lincoln? Picasso bigger than Einstein? Quantitative analysts are rapidly finding homes in social and cultural domains, from finance to politics. What about history? In this fascinating book, Steve Skiena and Charles Ward bring quantitative analysis to bear on ranking and comparing historical reputations. They evaluate each person by aggregating the traces of millions of opinions, just as Google ranks webpages. The book includes a technical discussion for readers interested in the details of the methods, but no mathematical or computational background is necessary to understand the rankings or conclusions. Along the way, the authors present the rankings of more than one thousand of history's most significant people in science, politics, entertainment, and all areas of human endeavor. Anyone interested in history or biography can see where their favorite figures place in the grand scheme of things.

  3. Ranking Forestry Investments With Parametric Linear Programming

    Science.gov (United States)

    Paul A. Murphy

    1976-01-01

    Parametric linear programming is introduced as a technique for ranking forestry investments under multiple constraints; it combines the advantages of simple tanking and linear programming as capital budgeting tools.

  4. Block models and personalized PageRank.

    Science.gov (United States)

    Kloumann, Isabel M; Ugander, Johan; Kleinberg, Jon

    2017-01-03

    Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods through the "seed set expansion problem": given a subset [Formula: see text] of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate in the space of "landing probabilities" of a random walk rooted at the seed set, ranking nodes according to weighted sums of landing probabilities of different length walks. Both schemes, however, lack an a priori relationship to the seed set objective. In this work, we develop a principled framework for evaluating ranking methods by studying seed set expansion applied to the stochastic block model. We derive the optimal gradient for separating the landing probabilities of two classes in a stochastic block model and find, surprisingly, that under reasonable assumptions the gradient is asymptotically equivalent to personalized PageRank for a specific choice of the PageRank parameter [Formula: see text] that depends on the block model parameters. This connection provides a formal motivation for the success of personalized PageRank in seed set expansion and node ranking generally. We use this connection to propose more advanced techniques incorporating higher moments of landing probabilities; our advanced methods exhibit greatly improved performance, despite being simple linear classification rules, and are even competitive with belief propagation.

  5. Block models and personalized PageRank

    OpenAIRE

    Kloumann, Isabel M.; Ugander, Johan; Kleinberg, Jon

    2016-01-01

    Methods for ranking the importance of nodes in a network have a rich history in machine learning and across domains that analyze structured data. Recent work has evaluated these methods though the seed set expansion problem: given a subset $S$ of nodes from a community of interest in an underlying graph, can we reliably identify the rest of the community? We start from the observation that the most widely used techniques for this problem, personalized PageRank and heat kernel methods, operate...

  6. How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

    Science.gov (United States)

    Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

    2016-01-01

    To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

  7. Rank distributions: A panoramic macroscopic outlook

    Science.gov (United States)

    Eliazar, Iddo I.; Cohen, Morrel H.

    2014-01-01

    This paper presents a panoramic macroscopic outlook of rank distributions. We establish a general framework for the analysis of rank distributions, which classifies them into five macroscopic "socioeconomic" states: monarchy, oligarchy-feudalism, criticality, socialism-capitalism, and communism. Oligarchy-feudalism is shown to be characterized by discrete macroscopic rank distributions, and socialism-capitalism is shown to be characterized by continuous macroscopic size distributions. Criticality is a transition state between oligarchy-feudalism and socialism-capitalism, which can manifest allometric scaling with multifractal spectra. Monarchy and communism are extreme forms of oligarchy-feudalism and socialism-capitalism, respectively, in which the intrinsic randomness vanishes. The general framework is applied to three different models of rank distributions—top-down, bottom-up, and global—and unveils each model's macroscopic universality and versatility. The global model yields a macroscopic classification of the generalized Zipf law, an omnipresent form of rank distributions observed across the sciences. An amalgamation of the three models establishes a universal rank-distribution explanation for the macroscopic emergence of a prevalent class of continuous size distributions, ones governed by unimodal densities with both Pareto and inverse-Pareto power-law tails.

  8. Fair ranking of researchers and research teams.

    Science.gov (United States)

    Vavryčuk, Václav

    2018-01-01

    The main drawback of ranking of researchers by the number of papers, citations or by the Hirsch index is ignoring the problem of distributing authorship among authors in multi-author publications. So far, the single-author or multi-author publications contribute to the publication record of a researcher equally. This full counting scheme is apparently unfair and causes unjust disproportions, in particular, if ranked researchers have distinctly different collaboration profiles. These disproportions are removed by less common fractional or authorship-weighted counting schemes, which can distribute the authorship credit more properly and suppress a tendency to unjustified inflation of co-authors. The urgent need of widely adopting a fair ranking scheme in practise is exemplified by analysing citation profiles of several highly-cited astronomers and astrophysicists. While the full counting scheme often leads to completely incorrect and misleading ranking, the fractional or authorship-weighted schemes are more accurate and applicable to ranking of researchers as well as research teams. In addition, they suppress differences in ranking among scientific disciplines. These more appropriate schemes should urgently be adopted by scientific publication databases as the Web of Science (Thomson Reuters) or the Scopus (Elsevier).

  9. How to implement decoy-state quantum key distribution for a satellite uplink with 50-dB channel loss

    International Nuclear Information System (INIS)

    Meyer-Scott, Evan; Yan, Zhizhong; MacDonald, Allison; Bourgoin, Jean-Philippe; Huebel, Hannes; Jennewein, Thomas

    2011-01-01

    Quantum key distribution (QKD) takes advantage of fundamental properties of quantum physics to allow two distant parties to share a secret key; however, QKD is hampered by a distance limitation of a few hundred kilometers on Earth. The most immediate solution for global coverage is to use a satellite, which can receive separate QKD transmissions from two or more ground stations and act as a trusted node to link these ground stations. In this article we report on a system capable of performing QKD in the high loss regime expected in an uplink to a satellite using weak coherent pulses and decoy states. Such a scenario profits from the simplicity of its receiver payload, but has so far been considered to be infeasible due to very high transmission losses (40-50 dB). The high loss is overcome by implementing an innovative photon source and advanced timing analysis. Our system handles up to 57 dB photon loss in the infinite key limit, confirming the viability of the satellite uplink scenario. We emphasize that while this system was designed with a satellite uplink in mind, it could just as easily overcome high losses on any free space QKD link.

  10. How to implement decoy-state quantum key distribution for a satellite uplink with 50-dB channel loss

    Science.gov (United States)

    Meyer-Scott, Evan; Yan, Zhizhong; MacDonald, Allison; Bourgoin, Jean-Philippe; Hübel, Hannes; Jennewein, Thomas

    2011-12-01

    Quantum key distribution (QKD) takes advantage of fundamental properties of quantum physics to allow two distant parties to share a secret key; however, QKD is hampered by a distance limitation of a few hundred kilometers on Earth. The most immediate solution for global coverage is to use a satellite, which can receive separate QKD transmissions from two or more ground stations and act as a trusted node to link these ground stations. In this article we report on a system capable of performing QKD in the high loss regime expected in an uplink to a satellite using weak coherent pulses and decoy states. Such a scenario profits from the simplicity of its receiver payload, but has so far been considered to be infeasible due to very high transmission losses (40-50 dB). The high loss is overcome by implementing an innovative photon source and advanced timing analysis. Our system handles up to 57 dB photon loss in the infinite key limit, confirming the viability of the satellite uplink scenario. We emphasize that while this system was designed with a satellite uplink in mind, it could just as easily overcome high losses on any free space QKD link.

  11. Conserved Fever Pathways across Vertebrates: A Herpesvirus Expressed Decoy TNF-α Receptor Delays Behavioral Fever in Fish.

    Science.gov (United States)

    Rakus, Krzysztof; Ronsmans, Maygane; Forlenza, Maria; Boutier, Maxime; Piazzon, M Carla; Jazowiecka-Rakus, Joanna; Gatherer, Derek; Athanasiadis, Alekos; Farnir, Frédéric; Davison, Andrew J; Boudinot, Pierre; Michiels, Thomas; Wiegertjes, Geert F; Vanderplasschen, Alain

    2017-02-08

    Both endotherms and ectotherms (e.g., fish) increase their body temperature to limit pathogen infection. Ectotherms do so by moving to warmer places, hence the term "behavioral fever." We studied the manifestation of behavioral fever in the common carp infected by cyprinid herpesvirus 3, a native carp pathogen. Carp maintained at 24°C died from the infection, whereas those housed in multi-chamber tanks encompassing a 24°C-32°C gradient migrated transiently to the warmest compartment and survived as a consequence. Behavioral fever manifested only at advanced stages of infection. Consistent with this, expression of CyHV-3 ORF12, encoding a soluble decoy receptor for TNF-α, delayed the manifestation of behavioral fever and promoted CyHV-3 replication in the context of a temperature gradient. Injection of anti-TNF-α neutralizing antibodies suppressed behavioral fever, and decreased fish survival in response to infection. This study provides a unique example of how viruses have evolved to alter host behavior to increase fitness. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

  12. Adaptive linear rank tests for eQTL studies.

    Science.gov (United States)

    Szymczak, Silke; Scheinhardt, Markus O; Zeller, Tanja; Wild, Philipp S; Blankenberg, Stefan; Ziegler, Andreas

    2013-02-10

    Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. Copyright © 2012 John Wiley & Sons, Ltd.

  13. A p130Cas tyrosine phosphorylated substrate domain decoy disrupts v-Crk signaling

    Directory of Open Access Journals (Sweden)

    Hanafusa Hidesaburo

    2002-07-01

    Full Text Available Abstract Background The adaptor protein p130Cas (Cas has been shown to be involved in different cellular processes including cell adhesion, migration and transformation. This protein has a substrate domain with up to 15 tyrosines that are potential kinase substrates, able to serve as docking sites for proteins with SH2 or PTB domains. Cas interacts with focal adhesion plaques and is phosphorylated by the tyrosine kinases FAK and Src. A number of effector molecules have been shown to interact with Cas and play a role in its function, including c-crk and v-crk, two adaptor proteins involved in intracellular signaling. Cas function is dependent on tyrosine phosphorylation of its substrate domain, suggesting that tyrosine phosphorylation of Cas in part regulates its control of adhesion and migration. To determine whether the substrate domain alone when tyrosine phosphorylated could signal, we have constructed a chimeric Cas molecule that is phosphorylated independently of upstream signals. Results We found that a tyrosine phosphorylated Cas substrate domain acts as a dominant negative mutant by blocking Cas-mediated signaling events, including JNK activation by the oncogene v-crk in transient and stable lines and v-crk transformation. This block was the result of competition for binding partners as the chimera competed for binding to endogenous c-crk and exogenously expressed v-crk. Conclusion Our approach suggests a novel method to study adaptor proteins that require phosphorylation, and indicates that mere tyrosine phosphorylation of the substrate domain of Cas is not sufficient for its function.

  14. PageRank as a method to rank biomedical literature by importance.

    Science.gov (United States)

    Yates, Elliot J; Dixon, Louise C

    2015-01-01

    Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

  15. RANK/RANK-Ligand/OPG: Ein neuer Therapieansatz in der Osteoporosebehandlung

    Directory of Open Access Journals (Sweden)

    Preisinger E

    2007-01-01

    Full Text Available Die Erforschung der Kopplungsmechanismen zur Osteoklastogenese, Knochenresorption und Remodellierung eröffnete neue mögliche Therapieansätze in der Behandlung der Osteoporose. Eine Schlüsselrolle beim Knochenabbau spielt der RANK- ("receptor activator of nuclear factor (NF- κB"- Ligand (RANKL. Durch die Bindung von RANKL an den Rezeptor RANK wird die Knochenresorption eingeleitet. OPG (Osteoprotegerin sowie der für den klinischen Gebrauch entwickelte humane monoklonale Antikörper (IgG2 Denosumab blockieren die Bindung von RANK-Ligand an RANK und verhindern den Knochenabbau.

  16. Identify High-Quality Protein Structural Models by Enhanced K-Means.

    Science.gov (United States)

    Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

    2017-01-01

    Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

  17. Mining Functional Modules in Heterogeneous Biological Networks Using Multiplex PageRank Approach.

    Science.gov (United States)

    Li, Jun; Zhao, Patrick X

    2016-01-01

    Identification of functional modules/sub-networks in large-scale biological networks is one of the important research challenges in current bioinformatics and systems biology. Approaches have been developed to identify functional modules in single-class biological networks; however, methods for systematically and interactively mining multiple classes of heterogeneous biological networks are lacking. In this paper, we present a novel algorithm (called mPageRank) that utilizes the Multiplex PageRank approach to mine functional modules from two classes of biological networks. We demonstrate the capabilities of our approach by successfully mining functional biological modules through integrating expression-based gene-gene association networks and protein-protein interaction networks. We first compared the performance of our method with that of other methods using simulated data. We then applied our method to identify the cell division cycle related functional module and plant signaling defense-related functional module in the model plant Arabidopsis thaliana. Our results demonstrated that the mPageRank method is effective for mining sub-networks in both expression-based gene-gene association networks and protein-protein interaction networks, and has the potential to be adapted for the discovery of functional modules/sub-networks in other heterogeneous biological networks. The mPageRank executable program, source code, the datasets and results of the presented two case studies are publicly and freely available at http://plantgrn.noble.org/MPageRank/.

  18. Country-specific determinants of world university rankings

    OpenAIRE

    Pietrucha, Jacek

    2017-01-01

    This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42–71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: econom...

  19. Support vector regression scoring of receptor-ligand complexes for rank-ordering and virtual screening of chemical libraries.

    Science.gov (United States)

    Li, Liwei; Wang, Bo; Meroueh, Samy O

    2011-09-26

    The community structure-activity resource (CSAR) data sets are used to develop and test a support vector machine-based scoring function in regression mode (SVR). Two scoring functions (SVR-KB and SVR-EP) are derived with the objective of reproducing the trend of the experimental binding affinities provided within the two CSAR data sets. The features used to train SVR-KB are knowledge-based pairwise potentials, while SVR-EP is based on physicochemical properties. SVR-KB and SVR-EP were compared to seven other widely used scoring functions, including Glide, X-score, GoldScore, ChemScore, Vina, Dock, and PMF. Results showed that SVR-KB trained with features obtained from three-dimensional complexes of the PDBbind data set outperformed all other scoring functions, including best performing X-score, by nearly 0.1 using three correlation coefficients, namely Pearson, Spearman, and Kendall. It was interesting that higher performance in rank ordering did not translate into greater enrichment in virtual screening assessed using the 40 targets of the Directory of Useful Decoys (DUD). To remedy this situation, a variant of SVR-KB (SVR-KBD) was developed by following a target-specific tailoring strategy that we had previously employed to derive SVM-SP. SVR-KBD showed a much higher enrichment, outperforming all other scoring functions tested, and was comparable in performance to our previously derived scoring function SVM-SP.

  20. Global network centrality of university rankings

    Science.gov (United States)

    Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

    2017-10-01

    Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

  1. Diversity rankings among bacterial lineages in soil.

    Science.gov (United States)

    Youssef, Noha H; Elshahed, Mostafa S

    2009-03-01

    We used rarefaction curve analysis and diversity ordering-based approaches to rank the 11 most frequently encountered bacterial lineages in soil according to diversity in 5 previously reported 16S rRNA gene clone libraries derived from agricultural, undisturbed tall grass prairie and forest soils (n=26,140, 28 328, 31 818, 13 001 and 53 533). The Planctomycetes, Firmicutes and the delta-Proteobacteria were consistently ranked among the most diverse lineages in all data sets, whereas the Verrucomicrobia, Gemmatimonadetes and beta-Proteobacteria were consistently ranked among the least diverse. On the other hand, the rankings of alpha-Proteobacteria, Acidobacteria, Actinobacteria, Bacteroidetes and Chloroflexi varied widely in different soil clone libraries. In general, lineages exhibiting largest differences in diversity rankings also exhibited the largest difference in relative abundance in the data sets examined. Within these lineages, a positive correlation between relative abundance and diversity was observed within the Acidobacteria, Actinobacteria and Chloroflexi, and a negative diversity-abundance correlation was observed within the Bacteroidetes. The ecological and evolutionary implications of these results are discussed.

  2. Social class rank, essentialism, and punitive judgment.

    Science.gov (United States)

    Kraus, Michael W; Keltner, Dacher

    2013-08-01

    Recent evidence suggests that perceptions of social class rank influence a variety of social cognitive tendencies, from patterns of causal attribution to moral judgment. In the present studies we tested the hypotheses that upper-class rank individuals would be more likely to endorse essentialist lay theories of social class categories (i.e., that social class is founded in genetically based, biological differences) than would lower-class rank individuals and that these beliefs would decrease support for restorative justice--which seeks to rehabilitate offenders, rather than punish unlawful action. Across studies, higher social class rank was associated with increased essentialism of social class categories (Studies 1, 2, and 4) and decreased support for restorative justice (Study 4). Moreover, manipulated essentialist beliefs decreased preferences for restorative justice (Study 3), and the association between social class rank and class-based essentialist theories was explained by the tendency to endorse beliefs in a just world (Study 2). Implications for how class-based essentialist beliefs potentially constrain social opportunity and mobility are discussed.

  3. RANK und RANKL - Vom Knochen zum Mammakarzinom

    Directory of Open Access Journals (Sweden)

    Sigl V

    2012-01-01

    Full Text Available RANK („Receptor Activator of NF-κB“ und sein Ligand RANKL sind Schlüsselmoleküle im Knochenmetabolismus und spielen eine essenzielle Rolle in der Entstehung von pathologischen Knochenveränderungen. Die Deregulation des RANK/RANKL-Systems ist zum Beispiel ein Hauptgrund für das Auftreten von postmenopausaler Osteoporose bei Frauen. Eine weitere wesentliche Funktion von RANK und RANKL liegt in der Entwicklung von milchsekretierenden Drüsen während der Schwangerschaft. Dabei regulieren Sexualhormone, wie zum Beispiel Progesteron, die Expression von RANKL und induzieren dadurch die Proliferation von epithelialen Zellen der Brust. Seit Längerem war schon bekannt, dass RANK und RANKL in der Metastasenbildung von Brustkrebszellen im Knochengewebe beteiligt sind. Wir konnten nun das RANK/RANKLSystem auch als essenziellen Mechanismus in der Entstehung von hormonellem Brustkrebs identifizieren. In diesem Beitrag werden wir daher den neuesten Erkenntnissen besondere Aufmerksamkeit schenken und diese kritisch in Bezug auf Brustkrebsentwicklung betrachten.

  4. Low Rank Approximation Algorithms, Implementation, Applications

    CERN Document Server

    Markovsky, Ivan

    2012-01-01

    Matrix low-rank approximation is intimately related to data modelling; a problem that arises frequently in many different fields. Low Rank Approximation: Algorithms, Implementation, Applications is a comprehensive exposition of the theory, algorithms, and applications of structured low-rank approximation. Local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. A major part of the text is devoted to application of the theory. Applications described include: system and control theory: approximate realization, model reduction, output error, and errors-in-variables identification; signal processing: harmonic retrieval, sum-of-damped exponentials, finite impulse response modeling, and array processing; machine learning: multidimensional scaling and recommender system; computer vision: algebraic curve fitting and fundamental matrix estimation; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; ...

  5. Resolution of ranking hierarchies in directed networks

    Science.gov (United States)

    Barucca, Paolo; Lillo, Fabrizio

    2018-01-01

    Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

  6. Data envelopment analysis of randomized ranks

    Directory of Open Access Journals (Sweden)

    Sant'Anna Annibal P.

    2002-01-01

    Full Text Available Probabilities and odds, derived from vectors of ranks, are here compared as measures of efficiency of decision-making units (DMUs. These measures are computed with the goal of providing preliminary information before starting a Data Envelopment Analysis (DEA or the application of any other evaluation or composition of preferences methodology. Preferences, quality and productivity evaluations are usually measured with errors or subject to influence of other random disturbances. Reducing evaluations to ranks and treating the ranks as estimates of location parameters of random variables, we are able to compute the probability of each DMU being classified as the best according to the consumption of each input and the production of each output. Employing the probabilities of being the best as efficiency measures, we stretch distances between the most efficient units. We combine these partial probabilities in a global efficiency score determined in terms of proximity to the efficiency frontier.

  7. Ranking spreaders by decomposing complex networks

    International Nuclear Information System (INIS)

    Zeng, An; Zhang, Cheng-Jun

    2013-01-01

    Ranking the nodes' ability of spreading in networks is crucial for designing efficient strategies to hinder spreading in the case of diseases or accelerate spreading in the case of information dissemination. In the well-known k-shell method, nodes are ranked only according to the links between the remaining nodes (residual links) while the links connecting to the removed nodes (exhausted links) are entirely ignored. In this Letter, we propose a mixed degree decomposition (MDD) procedure in which both the residual degree and the exhausted degree are considered. By simulating the epidemic spreading process on real networks, we show that the MDD method can outperform the k-shell and degree methods in ranking spreaders.

  8. Calculation of accurate small angle X-ray scattering curves from coarse-grained protein models

    DEFF Research Database (Denmark)

    Stovgaard, Kasper; Andreetta, Christian; Ferkinghoff-Borg, Jesper

    2010-01-01

    , which is paramount for structure determination based on statistical inference. Results: We present a method for the efficient calculation of accurate SAXS curves based on the Debye formula and a set of scattering form factors for dummy atom representations of amino acids. Such a method avoids......DBN. This resulted in a significant improvement in the decoy recognition performance. In conclusion, the presented method shows great promise for use in statistical inference of protein structures from SAXS data....

  9. Sign rank versus Vapnik-Chervonenkis dimension

    Science.gov (United States)

    Alon, N.; Moran, Sh; Yehudayoff, A.

    2017-12-01

    This work studies the maximum possible sign rank of sign (N × N)-matrices with a given Vapnik-Chervonenkis dimension d. For d=1, this maximum is three. For d=2, this maximum is \\widetilde{\\Theta}(N1/2). For d >2, similar but slightly less accurate statements hold. The lower bounds improve on previous ones by Ben-David et al., and the upper bounds are novel. The lower bounds are obtained by probabilistic constructions, using a theorem of Warren in real algebraic topology. The upper bounds are obtained using a result of Welzl about spanning trees with low stabbing number, and using the moment curve. The upper bound technique is also used to: (i) provide estimates on the number of classes of a given Vapnik-Chervonenkis dimension, and the number of maximum classes of a given Vapnik-Chervonenkis dimension--answering a question of Frankl from 1989, and (ii) design an efficient algorithm that provides an O(N/log(N)) multiplicative approximation for the sign rank. We also observe a general connection between sign rank and spectral gaps which is based on Forster's argument. Consider the adjacency (N × N)-matrix of a Δ-regular graph with a second eigenvalue of absolute value λ and Δ ≤ N/2. We show that the sign rank of the signed version of this matrix is at least Δ/λ. We use this connection to prove the existence of a maximum class C\\subseteq\\{+/- 1\\}^N with Vapnik-Chervonenkis dimension 2 and sign rank \\widetilde{\\Theta}(N1/2). This answers a question of Ben-David et al. regarding the sign rank of large Vapnik-Chervonenkis classes. We also describe limitations of this approach, in the spirit of the Alon-Boppana theorem. We further describe connections to communication complexity, geometry, learning theory, and combinatorics. Bibliography: 69 titles.

  10. RankProdIt: A web-interactive Rank Products analysis tool

    Directory of Open Access Journals (Sweden)

    Laing Emma

    2010-08-01

    Full Text Available Abstract Background The first objective of a DNA microarray experiment is typically to generate a list of genes or probes that are found to be differentially expressed or represented (in the case of comparative genomic hybridizations and/or copy number variation between two conditions or strains. Rank Products analysis comprises a robust algorithm for deriving such lists from microarray experiments that comprise small numbers of replicates, for example, less than the number required for the commonly used t-test. Currently, users wishing to apply Rank Products analysis to their own microarray data sets have been restricted to the use of command line-based software which can limit its usage within the biological community. Findings Here we have developed a web interface to existing Rank Products analysis tools allowing users to quickly process their data in an intuitive and step-wise manner to obtain the respective Rank Product or Rank Sum, probability of false prediction and p-values in a downloadable file. Conclusions The online interactive Rank Products analysis tool RankProdIt, for analysis of any data set containing measurements for multiple replicated conditions, is available at: http://strep-microarray.sbs.surrey.ac.uk/RankProducts

  11. Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models

    NARCIS (Netherlands)

    Hallin, M.; van den Akker, R.; Werker, B.J.M.

    2012-01-01

    Abstract: This paper introduces rank-based tests for the cointegrating rank in an Error Correction Model with i.i.d. elliptical innovations. The tests are asymptotically distribution-free, and their validity does not depend on the actual distribution of the innovations. This result holds despite the

  12. When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

    KAUST Repository

    Wang, Jim Jing-Yan

    2017-06-28

    Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

  13. Learning to rank for information retrieval

    CERN Document Server

    Liu, Tie-Yan

    2011-01-01

    Due to the fast growth of the Web and the difficulties in finding desired information, efficient and effective information retrieval systems have become more important than ever, and the search engine has become an essential tool for many people. The ranker, a central component in every search engine, is responsible for the matching between processed queries and indexed documents. Because of its central role, great attention has been paid to the research and development of ranking technologies. In addition, ranking is also pivotal for many other information retrieval applications, such as coll

  14. Cointegration rank testing under conditional heteroskedasticity

    DEFF Research Database (Denmark)

    Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, Robert M.

    2010-01-01

    We analyze the properties of the conventional Gaussian-based cointegrating rank tests of Johansen (1996, Likelihood-Based Inference in Cointegrated Vector Autoregressive Models) in the case where the vector of series under test is driven by globally stationary, conditionally heteroskedastic......, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples under a variety of conditionally heteroskedastic innovation processes. An empirical application to the term structure of interest rates is given....

  15. Ranking health between countries in international comparisons

    DEFF Research Database (Denmark)

    Brønnum-Hansen, Henrik

    2014-01-01

    Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions and docum......Cross-national comparisons and ranking of summary measures of population health sometimes give rise to inconsistent and diverging conclusions. In order to minimise confusion, international comparative studies ought to be based on well-harmonised data with common standards of definitions...

  16. Preference Learning and Ranking by Pairwise Comparison

    Science.gov (United States)

    Fürnkranz, Johannes; Hüllermeier, Eyke

    This chapter provides an overview of recent work on preference learning and ranking via pairwise classification. The learning by pairwise comparison (LPC) paradigm is the natural machine learning counterpart to the relational approach to preference modeling and decision making. From a machine learning point of view, LPC is especially appealing as it decomposes a possibly complex prediction problem into a certain number of learning problems of the simplest type, namely binary classification. We explain how to approach different preference learning problems, such as label and instance ranking, within the framework of LPC. We primarily focus on methodological aspects, but also address theoretical questions as well as algorithmic and complexity issues.

  17. Compressed Sensing with Rank Deficient Dictionaries

    DEFF Research Database (Denmark)

    Hansen, Thomas Lundgaard; Johansen, Daniel Højrup; Jørgensen, Peter Bjørn

    2012-01-01

    In compressed sensing it is generally assumed that the dictionary matrix constitutes a (possibly overcomplete) basis of the signal space. In this paper we consider dictionaries that do not span the signal space, i.e. rank deficient dictionaries. We show that in this case the signal-to-noise ratio...... (SNR) in the compressed samples can be increased by selecting the rows of the measurement matrix from the column space of the dictionary. As an example application of compressed sensing with a rank deficient dictionary, we present a case study of compressed sensing applied to the Coarse Acquisition (C...

  18. Ranking mutual funds using Sortino method

    Directory of Open Access Journals (Sweden)

    Khosro Faghani Makrani

    2014-04-01

    Full Text Available One of the primary concerns on most business activities is to determine an efficient method for ranking mutual funds. This paper performs an empirical investigation to rank 42 mutual funds listed on Tehran Stock Exchange using Sortino method over the period 2011-2012. The results of survey have been compared with market return and the results have confirmed that there were some positive and meaningful relationships between Sortino return and market return. In addition, there were some positive and meaningful relationship between two Sortino methods.

  19. Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

    Directory of Open Access Journals (Sweden)

    LI Lan-yin

    2017-04-01

    Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank,which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes,topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs,and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

  20. Tumor Necrosis Factor α Stimulates Osteoclast Differentiation by a Mechanism Independent of the Odf/Rankl–Rank Interaction

    Science.gov (United States)

    Kobayashi, Kanichiro; Takahashi, Naoyuki; Jimi, Eijiro; Udagawa, Nobuyuki; Takami, Masamichi; Kotake, Shigeru; Nakagawa, Nobuaki; Kinosaki, Masahiko; Yamaguchi, Kyoji; Shima, Nobuyuki; Yasuda, Hisataka; Morinaga, Tomonori; Higashio, Kanji; Martin, T. John; Suda, Tatsuo

    2000-01-01

    Osteoclast differentiation factor (ODF, also called RANKL/TRANCE/OPGL) stimulates the differentiation of osteoclast progenitors of the monocyte/macrophage lineage into osteoclasts in the presence of macrophage colony-stimulating factor (M-CSF, also called CSF-1). When mouse bone marrow cells were cultured with M-CSF, M-CSF–dependent bone marrow macrophages (M-BMMφ) appeared within 3 d. Tartrate-resistant acid phosphatase–positive osteoclasts were also formed when M-BMMφ were further cultured for 3 d with mouse tumor necrosis factor α (TNF-α) in the presence of M-CSF. Osteoclast formation induced by TNF-α was inhibited by the addition of respective antibodies against TNF receptor 1 (TNFR1) or TNFR2, but not by osteoclastogenesis inhibitory factor (OCIF, also called OPG, a decoy receptor of ODF/RANKL), nor the Fab fragment of anti–RANK (ODF/RANKL receptor) antibody. Experiments using M-BMMφ prepared from TNFR1- or TNFR2-deficient mice showed that both TNFR1- and TNFR2-induced signals were important for osteoclast formation induced by TNF-α. Osteoclasts induced by TNF-α formed resorption pits on dentine slices only in the presence of IL-1α. These results demonstrate that TNF-α stimulates osteoclast differentiation in the presence of M-CSF through a mechanism independent of the ODF/RANKL–RANK system. TNF-α together with IL-1α may play an important role in bone resorption of inflammatory bone diseases. PMID:10637272

  1. Are Toll-Like Receptors and Decoy Receptors Involved in the Immunopathogenesis of Systemic Lupus Erythematosus and Lupus-Like Syndromes?

    Directory of Open Access Journals (Sweden)

    Giuliana Guggino

    2012-01-01

    Full Text Available In this paper we focus our attention on the role of two families of receptors, Toll-like receptors (TLR and decoy receptors (DcR involved in the generation of systemic lupus erythematosus (SLE and lupus-like syndromes in human and mouse models. To date, these molecules were described in several autoimmune disorders such as rheumatoid arthritis, antiphospholipids syndrome, bowel inflammation, and SLE. Here, we summarize the findings of recent investigations on TLR and DcR and their role in the immunopathogenesis of the SLE.

  2. MAZ-binding G4-decoy with locked nucleic acid and twisted intercalating nucleic acid modifications suppresses KRAS in pancreatic cancer cells and delays tumor growth in mice

    DEFF Research Database (Denmark)

    Cogoi, Susanna; Zorzet, Sonia; Rapozzi, Valentina

    2013-01-01

    and stability, two polycyclic aromatic hydrocarbon units (TINA or AMANY) were inserted internally, to cap the quadruplex. The most active G4-decoy (2998), which had two para-TINAs, strongly suppressed KRAS expression in Panc-1 cells. It also repressed their metabolic activity (IC50 = 520 nM), and it inhibited...... cell growth and colony formation by activating apoptosis. We finally injected 2998 and control oligonucleotides 5153, 5154 (2 nmol/mouse) intratumorally in SCID mice bearing a Panc-1 xenograft. After three treatments, 2998 reduced tumor xenograft growth by 64% compared with control and increased...

  3. Subject Gateway Sites and Search Engine Ranking.

    Science.gov (United States)

    Thelwall, Mike

    2002-01-01

    Discusses subject gateway sites and commercial search engines for the Web and presents an explanation of Google's PageRank algorithm. The principle question addressed is the conditions under which a gateway site will increase the likelihood that a target page is found in search engines. (LRW)

  4. Rank reduction of correlation matrices by majorization

    NARCIS (Netherlands)

    R. Pietersz (Raoul); P.J.F. Groenen (Patrick)

    2004-01-01

    textabstractIn this paper a novel method is developed for the problem of finding a low-rank correlation matrix nearest to a given correlation matrix. The method is based on majorization and therefore it is globally convergent. The method is computationally efficient, is straightforward to implement,

  5. Ranking related entities: components and analyses

    NARCIS (Netherlands)

    Bron, M.; Balog, K.; de Rijke, M.

    2010-01-01

    Related entity finding is the task of returning a ranked list of homepages of relevant entities of a specified type that need to engage in a given relationship with a given source entity. We propose a framework for addressing this task and perform a detailed analysis of four core components;

  6. Ranking Very Many Typed Entities on Wikipedia

    NARCIS (Netherlands)

    Zaragoza, Hugo; Rode, H.; Mika, Peter; Atserias, Jordi; Ciaramita, Massimiliano; Attardi, Guiseppe

    2007-01-01

    We discuss the problem of ranking very many entities of different types. In particular we deal with a heterogeneous set of types, some being very generic and some very specific. We discuss two approaches for this problem: i) exploiting the entity containment graph and ii) using a Web search engine

  7. On the Dirac groups of rank n

    International Nuclear Information System (INIS)

    Ferreira, P.L.; Alcaras, J.A.C.

    1980-01-01

    The group theoretical properties of the Dirac groups of rank n are discussed together with the properties and construction of their IR's. The cases n even and n odd show distinct features. Furthermore, for n odd, the cases n=4K+1 and n=4K+3 exhibit some different properties too. (Author) [pt

  8. On rank 2 Seiberg-Witten equations

    International Nuclear Information System (INIS)

    Massamba, F.; Thompson, G.

    2004-02-01

    We introduce and study a set of rank 2 Seiberg-Witten equations. We show that the moduli space of solutions is a compact, orientational and smooth manifold. For minimal surfaces of general type we are able to determine the basic classes. (author)

  9. A tilting approach to ranking influence

    KAUST Repository

    Genton, Marc G.; Hall, Peter

    2014-01-01

    We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking

  10. Texture Repairing by Unified Low Rank Optimization

    Institute of Scientific and Technical Information of China (English)

    Xiao Liang; Xiang Ren; Zhengdong Zhang; Yi Ma

    2016-01-01

    In this paper, we show how to harness both low-rank and sparse structures in regular or near-regular textures for image completion. Our method is based on a unified formulation for both random and contiguous corruption. In addition to the low rank property of texture, the algorithm also uses the sparse assumption of the natural image: because the natural image is piecewise smooth, it is sparse in certain transformed domain (such as Fourier or wavelet transform). We combine low-rank and sparsity properties of the texture image together in the proposed algorithm. Our algorithm based on convex optimization can automatically and correctly repair the global structure of a corrupted texture, even without precise information about the regions to be completed. This algorithm integrates texture rectification and repairing into one optimization problem. Through extensive simulations, we show our method can complete and repair textures corrupted by errors with both random and contiguous supports better than existing low-rank matrix recovery methods. Our method demonstrates significant advantage over local patch based texture synthesis techniques in dealing with large corruption, non-uniform texture, and large perspective deformation.

  11. Semantic association ranking schemes for information retrieval ...

    Indian Academy of Sciences (India)

    retrieval applications using term association graph representation ... Department of Computer Science and Engineering, Government College of ... Introduction ... leads to poor precision, e.g., model, python, and chip. ...... The approaches proposed in this paper focuses on the query-centric re-ranking of search results.

  12. Efficient Rank Reduction of Correlation Matrices

    NARCIS (Netherlands)

    I. Grubisic (Igor); R. Pietersz (Raoul)

    2005-01-01

    textabstractGeometric optimisation algorithms are developed that efficiently find the nearest low-rank correlation matrix. We show, in numerical tests, that our methods compare favourably to the existing methods in the literature. The connection with the Lagrange multiplier method is established,

  13. Zero forcing parameters and minimum rank problems

    NARCIS (Netherlands)

    Barioli, F.; Barrett, W.; Fallat, S.M.; Hall, H.T.; Hogben, L.; Shader, B.L.; Driessche, van den P.; Holst, van der H.

    2010-01-01

    The zero forcing number Z(G), which is the minimum number of vertices in a zero forcing set of a graph G, is used to study the maximum nullity/minimum rank of the family of symmetric matrices described by G. It is shown that for a connected graph of order at least two, no vertex is in every zero

  14. A note on ranking assignments using reoptimization

    DEFF Research Database (Denmark)

    Pedersen, Christian Roed; Nielsen, L.R.; Andersen, K.A.

    2005-01-01

    We consider the problem of ranking assignments according to cost in the classical linear assignment problem. An algorithm partitioning the set of possible assignments, as suggested by Murty, is presented where, for each partition, the optimal assignment is calculated using a new reoptimization...

  15. Language Games: University Responses to Ranking Metrics

    Science.gov (United States)

    Heffernan, Troy A.; Heffernan, Amanda

    2018-01-01

    League tables of universities that measure performance in various ways are now commonplace, with numerous bodies providing their own rankings of how institutions throughout the world are seen to be performing on a range of metrics. This paper uses Lyotard's notion of language games to theorise that universities are regaining some power over being…

  16. Ranking Thinning Potential of Lodgepole Pine Stands

    OpenAIRE

    United States Department of Agriculture, Forest Service

    1987-01-01

    This paper presents models for predicting edge-response of dominant and codominant trees to clearing. Procedures are given for converting predictions to a thinning response index, for ranking stands for thinning priority. Data requirements, sampling suggestions, examples of application, and suggestions for management use are included to facilitate use as a field guide.

  17. Primate Innovation: Sex, Age and Social Rank

    NARCIS (Netherlands)

    Reader, S.M.; Laland, K.N.

    2001-01-01

    Analysis of an exhaustive survey of primate behavior collated from the published literature revealed significant variation in rates of innovation among individuals of different sex, age and social rank. We searched approximately 1,000 articles in four primatology journals, together with other

  18. Biomechanics Scholar Citations across Academic Ranks

    Directory of Open Access Journals (Sweden)

    Knudson Duane

    2015-11-01

    Full Text Available Study aim: citations to the publications of a scholar have been used as a measure of the quality or influence of their research record. A world-wide descriptive study of the citations to the publications of biomechanics scholars of various academic ranks was conducted.

  19. An algorithm for ranking assignments using reoptimization

    DEFF Research Database (Denmark)

    Pedersen, Christian Roed; Nielsen, Lars Relund; Andersen, Kim Allan

    2008-01-01

    We consider the problem of ranking assignments according to cost in the classical linear assignment problem. An algorithm partitioning the set of possible assignments, as suggested by Murty, is presented where, for each partition, the optimal assignment is calculated using a new reoptimization...... technique. Computational results for the new algorithm are presented...

  20. Ranking Workplace Competencies: Student and Graduate Perceptions.

    Science.gov (United States)

    Rainsbury, Elizabeth; Hodges, Dave; Burchell, Noel; Lay, Mark

    2002-01-01

    New Zealand business students and graduates made similar rankings of the five most important workplace competencies: computer literacy, customer service orientation, teamwork and cooperation, self-confidence, and willingness to learn. Graduates placed greater importance on most of the 24 competencies, resulting in a statistically significant…

  1. Comparing survival curves using rank tests

    NARCIS (Netherlands)

    Albers, Willem/Wim

    1990-01-01

    Survival times of patients can be compared using rank tests in various experimental setups, including the two-sample case and the case of paired data. Attention is focussed on two frequently occurring complications in medical applications: censoring and tail alternatives. A review is given of the

  2. A generalization of Friedman's rank statistic

    NARCIS (Netherlands)

    Kroon, de J.; Laan, van der P.

    1983-01-01

    In this paper a very natural generalization of the two·way analysis of variance rank statistic of FRIEDMAN is given. The general distribution-free test procedure based on this statistic for the effect of J treatments in a random block design can be applied in general two-way layouts without

  3. Probabilistic relation between In-Degree and PageRank

    NARCIS (Netherlands)

    Litvak, Nelli; Scheinhardt, Willem R.W.; Volkovich, Y.

    2008-01-01

    This paper presents a novel stochastic model that explains the relation between power laws of In-Degree and PageRank. PageRank is a popularity measure designed by Google to rank Web pages. We model the relation between PageRank and In-Degree through a stochastic equation, which is inspired by the

  4. Generalized reduced rank tests using the singular value decomposition

    NARCIS (Netherlands)

    Kleibergen, F.R.; Paap, R.

    2002-01-01

    We propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables for the LDU

  5. Nominal versus Attained Weights in Universitas 21 Ranking

    Science.gov (United States)

    Soh, Kaycheng

    2014-01-01

    Universitas 21 Ranking of National Higher Education Systems (U21 Ranking) is one of the three new ranking systems appearing in 2012. In contrast with the other systems, U21 Ranking uses countries as the unit of analysis. It has several features which lend it with greater trustworthiness, but it also shared some methodological issues with the other…

  6. The effect of new links on Google PageRank

    NARCIS (Netherlands)

    Avrachenkov, Konstatin; Litvak, Nelli

    2004-01-01

    PageRank is one of the principle criteria according to which Google ranks Web pages. PageRank can be interpreted as a frequency of visiting a Web page by a random surfer and thus it reflects the popularity of a Web page. We study the effect of newly created links on Google PageRank. We discuss to

  7. Generalized Reduced Rank Tests using the Singular Value Decomposition

    NARCIS (Netherlands)

    F.R. Kleibergen (Frank); R. Paap (Richard)

    2003-01-01

    textabstractWe propose a novel statistic to test the rank of a matrix. The rank statistic overcomes deficiencies of existing rank statistics, like: necessity of a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson (1951), sensitivity to the ordering of the variables

  8. VaRank: a simple and powerful tool for ranking genetic variants

    Directory of Open Access Journals (Sweden)

    Véronique Geoffroy

    2015-03-01

    Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

  9. Model of Decision Making through Consensus in Ranking Case

    Science.gov (United States)

    Tarigan, Gim; Darnius, Open

    2018-01-01

    The basic problem to determine ranking consensus is a problem to combine some rankings those are decided by two or more Decision Maker (DM) into ranking consensus. DM is frequently asked to present their preferences over a group of objects in terms of ranks, for example to determine a new project, new product, a candidate in a election, and so on. The problem in ranking can be classified into two major categories; namely, cardinal and ordinal rankings. The objective of the study is to obtin the ranking consensus by appying some algorithms and methods. The algorithms and methods used in this study were partial algorithm, optimal ranking consensus, BAK (Borde-Kendal)Model. A method proposed as an alternative in ranking conssensus is a Weighted Distance Forward-Backward (WDFB) method, which gave a little difference i ranking consensus result compare to the result oethe example solved by Cook, et.al (2005).

  10. Statistical Optimality in Multipartite Ranking and Ordinal Regression.

    Science.gov (United States)

    Uematsu, Kazuki; Lee, Yoonkyung

    2015-05-01

    Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

  11. Ranking descriptive analysis in the sensory characterization of strawberry flavored diet yogurt enriched with whey protein concentrate / Análise descritiva por ordenação na caracterização sensorial de iogurte diet sabor morango enriquecido com concentrado protéico do soro

    Directory of Open Access Journals (Sweden)

    Luis Antonio Minim

    2010-09-01

    Full Text Available This study evaluated the sensory characteristics of diet strawberry flavored yogurt enriched with whey protein concentrate (WPC. Three formulations containing 0,5%, 1% and 1.5% of WPC (F2, F3 and F4 in order of increasing concentration and a controlled formulation without the addition of WCP (F1 were developed and evaluated by Ranking Descriptive Analysis. Twenty selected and trained panelists evaluated the samples characterized by attributes: pink color, viscosity, characteristic aroma of strawberry yogurt, characteristic flavor of strawberry yogurt, sweet taste, sour taste and consistency. The formulations differed significantly (p Este estudo avaliou as características sensoriais de iogurte diet sabor morango enriquecidos com concentrado protéico de soro (CPS. Três formulações contendo 0,5%, 1% e 1,5% de CPS (F2, F3 e F4 em ordem crescente de concentração e uma formulação controle sem adição de CPS (F1 foram desenvolvidas e avaliadas por meio da Análise Descritiva por Ordenação. Vinte provadores selecionados e treinados avaliaram as amostras caracterizadas pelos atributos: cor rosa, viscosidade, aroma característico de iogurte de morango, sabor característico de iogurte de morango, gosto doce, gosto ácido e consistência. As formulações diferiram significativamente (p < 0.05 nos atributos gosto doce e consistência. As amostras F3 e F4 apresentaram maior consistência confirmando a eficiência do CPS no aumento da consistência.

  12. Differential invariants for higher-rank tensors. A progress report

    International Nuclear Information System (INIS)

    Tapial, V.

    2004-07-01

    We outline the construction of differential invariants for higher-rank tensors. In section 2 we outline the general method for the construction of differential invariants. A first result is that the simplest tensor differential invariant contains derivatives of the same order as the rank of the tensor. In section 3 we review the construction for the first-rank tensors (vectors) and second-rank tensors (metrics). In section 4 we outline the same construction for higher-rank tensors. (author)

  13. Beyond Low Rank: A Data-Adaptive Tensor Completion Method

    OpenAIRE

    Zhang, Lei; Wei, Wei; Shi, Qinfeng; Shen, Chunhua; Hengel, Anton van den; Zhang, Yanning

    2017-01-01

    Low rank tensor representation underpins much of recent progress in tensor completion. In real applications, however, this approach is confronted with two challenging problems, namely (1) tensor rank determination; (2) handling real tensor data which only approximately fulfils the low-rank requirement. To address these two issues, we develop a data-adaptive tensor completion model which explicitly represents both the low-rank and non-low-rank structures in a latent tensor. Representing the no...

  14. Validation of protein models by a neural network approach

    Directory of Open Access Journals (Sweden)

    Fantucci Piercarlo

    2008-01-01

    Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

  15. Expression profile of osteoprotegerin, RANK and RANKL genes in the femoral head of patients with avascular necrosis.

    Science.gov (United States)

    Samara, Stavroula; Dailiana, Zoe; Chassanidis, Christos; Koromila, Theodora; Papatheodorou, Loukia; Malizos, Konstantinos N; Kollia, Panagoula

    2014-02-01

    Femoral head avascular necrosis (AVN) is a recalcitrant disease of the hip that leads to joint destruction. Osteoprotegerin (OPG), Receptor Activator of Nuclear Factor kappa-B (RANK) and RANK ligand (RANKL) regulate the balance between osteoclasts-osteoblasts. The expression of these genes affects the maturation and function of osteoblasts-osteoclasts and bone remodeling. In this study, we investigated the molecular pathways leading to AVN by studying the expression profile of OPG, RANK and RANKL genes. Quantitative Real Time-PCR was performed for evaluation of OPG, RANK and RANKL expression. Analysis was based on parallel evaluation of mRNA and protein levels in normal/necrotic sites of 42 osteonecrotic femoral heads (FHs). OPG and RANKL protein levels were estimated by western blotting. The OPG mRNA levels were higher (insignificantly) in the necrotic than the normal site (p > 0.05). Although the expression of RANK and RANKL was significantly lower than OPG in both sites, RANK and RANKL mRNA levels were higher in the necrotic part than the normal (p < 0.05). Protein levels of OPG and RANKL showed no remarkable divergence. Our results indicate that differential expression mechanisms for OPG, RANK and RANKL that could play an important role in the progress of bone remodeling in the necrotic area, disturbing bone homeostasis. This finding may have an effect on the resulting bone destruction and the subsequent collapse of the hip joint. Copyright © 2013. Published by Elsevier Inc.

  16. When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

    KAUST Repository

    Wang, Jim Jing-Yan; Cui, Xuefeng; Yu, Ge; Guo, Lili; Gao, Xin

    2017-01-01

    Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays

  17. A novel nonsteroidal antifibrotic oligo decoy containing the TGF-beta element found in the COL1A1 gene which regulates murine schistosomiasis liver fibrosis.

    Science.gov (United States)

    Boros, D L; Singh, K P; Gerard, H C; Hudson, A P; White, S L; Cutroneo, K R

    2005-08-01

    Schistosomiasis mansoni disseminated worm eggs in mice and humans induce granulomatous inflammations and cumulative fibrosis causing morbidity and possibly mortality. In this study, intrahepatic and I.V. injections of a double-stranded oligodeoxynucleotide decoy containing the TGF-beta regulatory element found in the distal promoter of the COL1A1 gene into worm-infected mice suppressed TGF-beta1, COL1A1, tissue inhibitor of metalloproteinase-1, and decreased COL3A1 mRNAs to a lesser extent. Sequence comparisons within the mouse genome found homologous sequences within the COL3A1, TGF-beta1, and TIMP-1 5' flanking regions. Cold competition gel mobility shift assays using these homologous sequences with 5' and 3' flanking regions found in the natural COL1A1 gene showed competition. Competitive gel mobility assays in a separate experiment showed no competition using a 5-base mutated or scrambled sequence. Explanted liver granulomas from saline-injected mice incorporated 10.45 +/- 1.7% (3)H-proline into newly synthesized collagen, whereas decoy-treated mice showed no collagen synthesis. Compared with the saline control schistosomiasis mice phosphorothioate double-stranded oligodeoxynucleotide treatment decreased total liver collagen content (i.e. hydroxy-4-proline) by 34%. This novel molecular approach has the potential to be employed as a novel antifibrotic treatment modality. (c) 2005 Wiley-Liss, Inc.

  18. Fourth-rank gravity. A progress report

    International Nuclear Information System (INIS)

    Tapia, V.

    1992-04-01

    We consider the consequences of describing the metric properties of space-time through a quartic line element. The associated ''metric'' is a fourth-rank tensor. After developing some fundamentals for such geometry, we construct a field theory for the gravitational field. This theory coincides with General Relativity in the vacuum case. Departures from General Relativity are obtained only in the presence of matter. We develop a simple cosmological model which is not in contradiction with the observed value Ω approx. 0.2-0.3 for the energy density parameter. A further application concerns conformal field theory. We are able to prove that a conformal field theory possesses an infinite-dimensional symmetry group only if the dimension of space-time is equal to the rank of the metric. In this case we are able to construct an integrable conformal field theory in four dimensions. The model is renormalisable by power counting. (author). 9 refs

  19. Low-rank quadratic semidefinite programming

    KAUST Repository

    Yuan, Ganzhao

    2013-04-01

    Low rank matrix approximation is an attractive model in large scale machine learning problems, because it can not only reduce the memory and runtime complexity, but also provide a natural way to regularize parameters while preserving learning accuracy. In this paper, we address a special class of nonconvex quadratic matrix optimization problems, which require a low rank positive semidefinite solution. Despite their non-convexity, we exploit the structure of these problems to derive an efficient solver that converges to their local optima. Furthermore, we show that the proposed solution is capable of dramatically enhancing the efficiency and scalability of a variety of concrete problems, which are of significant interest to the machine learning community. These problems include the Top-k Eigenvalue problem, Distance learning and Kernel learning. Extensive experiments on UCI benchmarks have shown the effectiveness and efficiency of our proposed method. © 2012.

  20. Ranking oil sands bitumen recovery techniques

    Energy Technology Data Exchange (ETDEWEB)

    Lam, A.; Nobes, D.S.; Lipsett, M.G. [Alberta Univ., Edmonton, AB (Canada). Dept. of Mechanical Engineering

    2009-07-01

    The preference ranking organization method (PROMETHEE) was used to assess and rank 3 techniques for in situ bitumen recovery: (1) steam assisted gravity drainage; (2) vapour extraction (VAPEX); and (3) toe-to-heel air injection (THAI). The study used a business scenario where management-type indicators included potential production rates; estimated overall operating costs; energy consumption; facilities requirement; recovery efficiency; and energy loss. Amounts of carbon dioxide (CO{sub 2}) emissions were also considered, as well as the production depth, formation thickness, and API gravity of the produced bitumen. The study showed that THAI recovery methods had the most beneficial criteria weighting of the 3 processes, while SAGD was the least favourable choice. However, SAGD processes are the most widely used of the 3 processes, while THAI has only been demonstrated on a limited scale. It was concluded that the maturity of a technology should be weighted more heavily when using the PROMETHEE method. 8 refs., 2 tabs.

  1. Low-rank quadratic semidefinite programming

    KAUST Repository

    Yuan, Ganzhao; Zhang, Zhenjie; Ghanem, Bernard; Hao, Zhifeng

    2013-01-01

    Low rank matrix approximation is an attractive model in large scale machine learning problems, because it can not only reduce the memory and runtime complexity, but also provide a natural way to regularize parameters while preserving learning accuracy. In this paper, we address a special class of nonconvex quadratic matrix optimization problems, which require a low rank positive semidefinite solution. Despite their non-convexity, we exploit the structure of these problems to derive an efficient solver that converges to their local optima. Furthermore, we show that the proposed solution is capable of dramatically enhancing the efficiency and scalability of a variety of concrete problems, which are of significant interest to the machine learning community. These problems include the Top-k Eigenvalue problem, Distance learning and Kernel learning. Extensive experiments on UCI benchmarks have shown the effectiveness and efficiency of our proposed method. © 2012.

  2. Social Media Impact on Website Ranking

    OpenAIRE

    Vaghela, Dushyant

    2014-01-01

    Internet is fast becoming critically important to commerce, industry and individuals. Search Engine (SE) is the most vital component for communication network and also used for discover information for users or people. Search engine optimization (SEO) is the process that is mostly used to increasing traffic from free, organic or natural listings on search engines and also helps to increase website ranking. It includes techniques like link building, directory submission, classified submission ...

  3. On Locally Most Powerful Sequential Rank Tests

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2017-01-01

    Roč. 36, č. 1 (2017), s. 111-125 ISSN 0747-4946 R&D Projects: GA ČR GA17-07384S Grant - others:Nadační fond na podporu vědy(CZ) Neuron Institutional support: RVO:67985807 Keywords : nonparametric test s * sequential ranks * stopping variable Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 0.339, year: 2016

  4. Probabilistic real-time contingency ranking method

    International Nuclear Information System (INIS)

    Mijuskovic, N.A.; Stojnic, D.

    2000-01-01

    This paper describes a real-time contingency method based on a probabilistic index-expected energy not supplied. This way it is possible to take into account the stochastic nature of the electric power system equipment outages. This approach enables more comprehensive ranking of contingencies and it is possible to form reliability cost values that can form the basis for hourly spot price calculations. The electric power system of Serbia is used as an example for the method proposed. (author)

  5. Returns to Tenure: Time or Rank?

    DEFF Research Database (Denmark)

    Buhai, Ioan Sebastian

    -specific investment, efficiency-wages or adverse-selection models. However, rent extracting arguments as suggested by the theory of internal labor markets, indicate that the relative position of the worker in the seniority hierarchy of the firm, her 'seniority rank', may also explain part of the observed returns...... relative to their peer workers), as predicted by theories on unionized and insider-outsider markets....

  6. Efficient Low Rank Tensor Ring Completion

    OpenAIRE

    Wang, Wenqi; Aggarwal, Vaneet; Aeron, Shuchin

    2017-01-01

    Using the matrix product state (MPS) representation of the recently proposed tensor ring decompositions, in this paper we propose a tensor completion algorithm, which is an alternating minimization algorithm that alternates over the factors in the MPS representation. This development is motivated in part by the success of matrix completion algorithms that alternate over the (low-rank) factors. In this paper, we propose a spectral initialization for the tensor ring completion algorithm and ana...

  7. Citation ranking versus peer evaluation of senior faculty research performance

    DEFF Research Database (Denmark)

    Meho, Lokman I.; Sonnenwald, Diane H.

    2000-01-01

    The purpose of this study is to analyze the relationship between citation ranking and peer evaluation in assessing senior faculty research performance. Other studies typically derive their peer evaluation data directly from referees, often in the form of ranking. This study uses two additional...... indicator of research performance of senior faculty members? Citation data, book reviews, and peer ranking were compiled and examined for faculty members specializing in Kurdish studies. Analysis shows that normalized citation ranking and citation content analysis data yield identical ranking results....... Analysis also shows that normalized citation ranking and citation content analysis, book reviews, and peer ranking perform similarly (i.e., are highly correlated) for high-ranked and low-ranked senior scholars. Additional evaluation methods and measures that take into account the context and content...

  8. Association between Metabolic Syndrome and Job Rank.

    Science.gov (United States)

    Mehrdad, Ramin; Pouryaghoub, Gholamreza; Moradi, Mahboubeh

    2018-01-01

    The occupation of the people can influence the development of metabolic syndrome. To determine the association between metabolic syndrome and its determinants with the job rank in workers of a large car factory in Iran. 3989 male workers at a large car manufacturing company were invited to participate in this cross-sectional study. Demographic and anthropometric data of the participants, including age, height, weight, and abdominal circumference were measured. Blood samples were taken to measure lipid profile and blood glucose level. Metabolic syndrome was diagnosed in each participant based on ATPIII 2001 criteria. The workers were categorized based on their job rank into 3 groups of (1) office workers, (2) workers with physical exertion, and (3) workers with chemical exposure. The study characteristics, particularly the frequency of metabolic syndrome and its determinants were compared among the study groups. The prevalence of metabolic syndrome in our study was 7.7% (95% CI 6.9 to 8.5). HDL levels were significantly lower in those who had chemical exposure (p=0.045). Diastolic blood pressure was significantly higher in those who had mechanical exertion (p=0.026). The frequency of metabolic syndrome in the office workers, workers with physical exertion, and workers with chemical exposure was 7.3%, 7.9%, and 7.8%, respectively (p=0.836). Seemingly, there is no association between metabolic syndrome and job rank.

  9. Rank-dependant factorization of entanglement evolution

    International Nuclear Information System (INIS)

    Siomau, Michael

    2016-01-01

    Highlights: • In some cases the complex entanglement evolution can be factorized on simple terms. • We suggest factorization equations for multiqubit entanglement evolution. • The factorization is solely defined by the rank of the final state density matrices. • The factorization is independent on the local noisy channels and initial pure states. - Abstract: The description of the entanglement evolution of a complex quantum system can be significantly simplified due to the symmetries of the initial state and the quantum channels, which simultaneously affect parts of the system. Using concurrence as the entanglement measure, we study the entanglement evolution of few qubit systems, when each of the qubits is affected by a local unital channel independently on the others. We found that for low-rank density matrices of the final quantum state, such complex entanglement dynamics can be completely described by a combination of independent factors representing the evolution of entanglement of the initial state, when just one of the qubits is affected by a local channel. We suggest necessary conditions for the rank of the density matrices to represent the entanglement evolution through the factors. Our finding is supported with analytical examples and numerical simulations.

  10. Fourth-rank gravity and cosmology

    International Nuclear Information System (INIS)

    Marrakchi, A.L.; Tapia, V.

    1992-07-01

    We consider the consequences of describing the metric properties of space-time through a quartic line element. The associated ''metric'' is a fourth-rank tensor G μυλπ . In order to recover a Riemannian behaviour of the geometry it is necessary to have G μυλπ = g (μυ g λπ) . We construct a theory for the gravitational field based on the fourth-rank metric G μυλπ . In the absence of matter the fourth-rank metric becomes separable and the theory coincides with General Relativity. In the presence of matter we can maintain Riemmanianicity, but now gravitation couples, as compared to General Relativity, in a different way to matter. We develop a simple cosmological model based on a FRW metric with matter described by a perfect fluid. For the present time the field equations are compatible with k OBS = O and Ω OBS t CLAS approx. 10 20 t PLANCK approx. 10 -23 s. Our final and most important result is the fact that the entropy is an increasing function of time. When interpreted at the light of General Relativity the treatment is shown to be almost equivalent to that of the standard model of cosmology combined with the inflationary scenario. (author). 16 refs, 1 fig

  11. Ranking agility factors affecting hospitals in Iran

    Directory of Open Access Journals (Sweden)

    M. Abdi Talarposht

    2017-04-01

    Full Text Available Background: Agility is an effective response to the changing and unpredictable environment and using these changes as opportunities for organizational improvement. Objective: The aim of the present study was to rank the factors affecting agile supply chain of hospitals of Iran. Methods: This applied study was conducted by cross sectional-descriptive method at some point of 2015 for one year. The research population included managers, administrators, faculty members and experts were selected hospitals. A total of 260 people were selected as sample from the health centers. The construct validity of the questionnaire was approved by confirmatory factor analysis test and its reliability was approved by Cronbach's alpha (α=0.97. All data were analyzed by Kolmogorov-Smirnov, Chi-square and Friedman tests. Findings: The development of staff skills, the use of information technology, the integration of processes, appropriate planning, and customer satisfaction and product quality had a significant impact on the agility of public hospitals of Iran (P<0.001. New product introductions had earned the highest ranking and the development of staff skills earned the lowest ranking. Conclusion: The new product introduction, market responsiveness and sensitivity, reduce costs, and the integration of organizational processes, ratings better to have acquired agility hospitals in Iran. Therefore, planners and officials of hospitals have to, through the promotion quality and variety of services customer-oriented, providing a basis for investing in the hospital and etc to apply for agility supply chain public hospitals of Iran.

  12. Estimation of rank correlation for clustered data.

    Science.gov (United States)

    Rosner, Bernard; Glynn, Robert J

    2017-06-30

    It is well known that the sample correlation coefficient (R xy ) is the maximum likelihood estimator of the Pearson correlation (ρ xy ) for independent and identically distributed (i.i.d.) bivariate normal data. However, this is not true for ophthalmologic data where X (e.g., visual acuity) and Y (e.g., visual field) are available for each eye and there is positive intraclass correlation for both X and Y in fellow eyes. In this paper, we provide a regression-based approach for obtaining the maximum likelihood estimator of ρ xy for clustered data, which can be implemented using standard mixed effects model software. This method is also extended to allow for estimation of partial correlation by controlling both X and Y for a vector U_ of other covariates. In addition, these methods can be extended to allow for estimation of rank correlation for clustered data by (i) converting ranks of both X and Y to the probit scale, (ii) estimating the Pearson correlation between probit scores for X and Y, and (iii) using the relationship between Pearson and rank correlation for bivariate normally distributed data. The validity of the methods in finite-sized samples is supported by simulation studies. Finally, two examples from ophthalmology and analgesic abuse are used to illustrate the methods. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

  13. Ranking environmental liabilities at a petroleum refinery

    International Nuclear Information System (INIS)

    Lupo, M.

    1995-01-01

    A new computer model is available to allow the management of a petroleum refinery to prioritize environmental action and construct a holistic approach to remediation. A large refinery may have numerous solid waste management units regulated by the Resource Conservation and Recovery Act (RCRA), as well as process units that emit hazardous chemicals into the environment. These sources can impact several environmental media, potentially including the air, the soil, the groundwater, the unsaturated zone water, and surface water. The number of chemicals of concern may be large. The new model is able to rank the sources by considering the impact of each chemical in each medium from each source in terms of concentration, release rate, and a weighted index based on toxicity. In addition to environmental impact, the sources can be ranked in three other ways: (1) by cost to remediate, (2) by environmental risk reduction caused by the remediation in terms of the decreases in release rate, concentration, and weighted index, and (3) by cost-benefit, which is the environmental risk reduction for each source divided by the cost of the remedy. Ranking each unit in the refinery allows management to use its limited environmental resources in a pro-active strategic manner that produces long-term results, rather than in reactive, narrowly focused, costly, regulatory-driven campaigns that produce only short-term results

  14. Iris Template Protection Based on Local Ranking

    Directory of Open Access Journals (Sweden)

    Dongdong Zhao

    2018-01-01

    Full Text Available Biometrics have been widely studied in recent years, and they are increasingly employed in real-world applications. Meanwhile, a number of potential threats to the privacy of biometric data arise. Iris template protection demands that the privacy of iris data should be protected when performing iris recognition. According to the international standard ISO/IEC 24745, iris template protection should satisfy the irreversibility, revocability, and unlinkability. However, existing works about iris template protection demonstrate that it is difficult to satisfy the three privacy requirements simultaneously while supporting effective iris recognition. In this paper, we propose an iris template protection method based on local ranking. Specifically, the iris data are first XORed (Exclusive OR operation with an application-specific string; next, we divide the results into blocks and then partition the blocks into groups. The blocks in each group are ranked according to their decimal values, and original blocks are transformed to their rank values for storage. We also extend the basic method to support the shifting strategy and masking strategy, which are two important strategies for iris recognition. We demonstrate that the proposed method satisfies the irreversibility, revocability, and unlinkability. Experimental results on typical iris datasets (i.e., CASIA-IrisV3-Interval, CASIA-IrisV4-Lamp, UBIRIS-V1-S1, and MMU-V1 show that the proposed method could maintain the recognition performance while protecting the privacy of iris data.

  15. ET-09DECOY OLIGONUCLEOTIDE DERIVED FROM MGMT ENHANCER HAS AN ANTINEOPLASTIC ACTIVITY IN-VITRO AND IN-VIVO

    Science.gov (United States)

    Canello, Tamar; Ovadia, Haim; Refael, Miri; Zrihan, Daniel; Siegal, Tali; Lavon, Iris

    2014-01-01

    INTRODUCTION: Silencing of O(6)-methylguanine-DNA-methyltransferase (MGMT) in tumors, correlates with a better therapeutic response and with increased survival. Our previous results demonstrated the pivotal role of NF-kappaB in MGMT expression, mediated mainly through binding of p65/NF-kappaB homodimers to the non-canonical NF-KappaB motif (MGMT-kappaB1) within MGMT enhancer. METHODS AND RESULTS: In an attempt to attenuate the transcription activity of MGMT in tumors we designed locked nucleic acids (LNA) modified decoy oligonucleotides corresponding to the specific sequence of MGMT-kappaB1 (MGMT-kB1-LODN). Following confirmation of the ability of MGMT-kB1-LODN to interfere with the binding of p65/NF-kappaB to MGMT enhancer, the potential of the MGMT-kB1-LODN to enhance cell killing was studied in vitro in two glioma cell lines (T98G and U87) and a melanoma cell line (A375P). All three cell lines manifested a significant enhanced cell killing effect following exposure to temozolomide (TMZ) when first transfected with MGMT-kb1-LODN, and also induced a significant cell killing when administered as monotherapy. These results were confirmed also in-vivo on A375P Melanoma xenografts. Intratumoral (Intralesional - IL) injection of MGMT-kB1-LODN with or without IP injection of TMZ induced significant tumor growth inhibition either as a monotherapy or in combination with TMZ. The long-term effect of MGMT-kB1-LODN monotherapy was evaluated using a repetitive IL injection every 4 to 5 days for 55 days with either MGMT-κB1 LODN or control ODN or vehicle. A significant difference (p < 0.01) in tumor volume was obtained by MGMT-κB1-LODN compared to both control groups. Moreover, two out of the seven mice treated with MGMT-κB1-LODN demonstrated tumor regression by day 55 and no tumor recurrence was observed five months later. CONCLUSION: The results of these experiments show that the MGMT-kB1-LODN has a substantial antineoplastic effect when used either in combination with

  16. Dynamic programming re-ranking for PPI interactor and pair extraction in full-text articles

    Science.gov (United States)

    2011-01-01

    Background Experimentally verified protein-protein interactions (PPIs) cannot be easily retrieved by researchers unless they are stored in PPI databases. The curation of such databases can be facilitated by employing text-mining systems to identify genes which play the interactor role in PPIs and to map these genes to unique database identifiers (interactor normalization task or INT) and then to return a list of interaction pairs for each article (interaction pair task or IPT). These two tasks are evaluated in terms of the area under curve of the interpolated precision/recall (AUC iP/R) score because the order of identifiers in the output list is important for ease of curation. Results Our INT system developed for the BioCreAtIvE II.5 INT challenge achieved a promising AUC iP/R of 43.5% by using a support vector machine (SVM)-based ranking procedure. Using our new re-ranking algorithm, we have been able to improve system performance (AUC iP/R) by 1.84%. Our experimental results also show that with the re-ranked INT results, our unsupervised IPT system can achieve a competitive AUC iP/R of 23.86%, which outperforms the best BC II.5 INT system by 1.64%. Compared to using only SVM ranked INT results, using re-ranked INT results boosts AUC iP/R by 7.84%. Statistical significance t-test results show that our INT/IPT system with re-ranking outperforms that without re-ranking by a statistically significant difference. Conclusions In this paper, we present a new re-ranking algorithm that considers co-occurrence among identifiers in an article to improve INT and IPT ranking results. Combining the re-ranked INT results with an unsupervised approach to find associations among interactors, the proposed method can boost the IPT performance. We also implement score computation using dynamic programming, which is faster and more efficient than traditional approaches. PMID:21342534

  17. Country-specific determinants of world university rankings.

    Science.gov (United States)

    Pietrucha, Jacek

    2018-01-01

    This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42-71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: economic potential of the country, research and development expenditure, long-term political stability (freedom from war, occupation, coups and major changes in the political system), and institutional variables, including government effectiveness.

  18. QUASAR--scoring and ranking of sequence-structure alignments.

    Science.gov (United States)

    Birzele, Fabian; Gewehr, Jan E; Zimmer, Ralf

    2005-12-15

    Sequence-structure alignments are a common means for protein structure prediction in the fields of fold recognition and homology modeling, and there is a broad variety of programs that provide such alignments based on sequence similarity, secondary structure or contact potentials. Nevertheless, finding the best sequence-structure alignment in a pool of alignments remains a difficult problem. QUASAR (quality of sequence-structure alignments ranking) provides a unifying framework for scoring sequence-structure alignments that aids finding well-performing combinations of well-known and custom-made scoring schemes. Those scoring functions can be benchmarked against widely accepted quality scores like MaxSub, TMScore, Touch and APDB, thus enabling users to test their own alignment scores against 'standard-of-truth' structure-based scores. Furthermore, individual score combinations can be optimized with respect to benchmark sets based on known structural relationships using QUASAR's in-built optimization routines.

  19. Ranking U-Sapiens 2010-2

    Directory of Open Access Journals (Sweden)

    Carlos-Roberto Peña-Barrera

    2011-08-01

    Full Text Available Los principales objetivos de esta investigación son los siguientes: (1 que la comunidad científica nacional e internacional y la sociedad en general co-nozcan los resultados del Ranking U-Sapiens Colombia 2010_2, el cual clasifica a cada institución de educación superior colombiana según puntaje, posición y cuartil; (2 destacar los movimientos más importantes al comparar los resultados del ranking 2010_1 con los del 2010_2; (3 publicar las respuestas de algunos actores de la academia nacional con respecto a la dinámica de la investigación en el país; (4 reconocer algunas instituciones, medios de comunicación e investigadores que se han interesado a modo de reflexión, referenciación o citación por esta investigación; y (5 dar a conocer el «Sello Ranking U-Sapiens Colombia» para las IES clasificadas. El alcance de este estudio en cuanto a actores abordó todas y cada una de las IES nacionales (aunque solo algunas lograran entrar al ranking y en cuanto a tiempo, un periodo referido al primer semestre de 2010 con respecto a: (1 los resultados 2010-1 de revistas indexadas en Publindex, (2 los programas de maestrías y doctorados activos durante 2010-1 según el Ministerio de Educación Nacional, y (3 los resultados de grupos de investigación clasificados para 2010 según Colciencias. El método empleado para esta investigación es el mismo que para el ranking 2010_1, salvo por una especificación aún más detallada en uno de los pasos del modelo (las variables α, β, γ; es completamente cuantitativo y los datos de las variables que fundamentan sus resultados provienen de Colciencias y el Ministerio de Educación Nacional; y en esta ocasión se darán a conocer los resultados por variable para 2010_1 y 2010_2. Los resultados más relevantes son estos: (1 entraron 8 IES al ranking y salieron 3; (2 las 3 primeras IES son públicas; (3 en total hay 6 instituciones universitarias en el ranking; (4 7 de las 10 primeras IES son

  20. Ranking the Online Documents Based on Relative Credibility Measures

    Directory of Open Access Journals (Sweden)

    Ahmad Dahlan

    2013-09-01

    Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

  1. Ranking the Online Documents Based on Relative Credibility Measures

    Directory of Open Access Journals (Sweden)

    Ahmad Dahlan

    2009-05-01

    Full Text Available Information searching is the most popular activity in Internet. Usually the search engine provides the search results ranked by the relevance. However, for a certain purpose that concerns with information credibility, particularly citing information for scientific works, another approach of ranking the search engine results is required. This paper presents a study on developing a new ranking method based on the credibility of information. The method is built up upon two well-known algorithms, PageRank and Citation Analysis. The result of the experiment that used Spearman Rank Correlation Coefficient to compare the proposed rank (generated by the method with the standard rank (generated manually by a group of experts showed that the average Spearman 0 < rS < critical value. It means that the correlation was proven but it was not significant. Hence the proposed rank does not satisfy the standard but the performance could be improved.

  2. Algebraic and computational aspects of real tensor ranks

    CERN Document Server

    Sakata, Toshio; Miyazaki, Mitsuhiro

    2016-01-01

    This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through...

  3. On Locally Most Powerful Sequential Rank Tests

    Czech Academy of Sciences Publication Activity Database

    Kalina, Jan

    2017-01-01

    Roč. 36, č. 1 (2017), s. 111-125 ISSN 0747-4946 R&D Projects: GA ČR GA17-07384S Grant - others:Nadační fond na podporu vědy(CZ) Neuron Institutional support: RVO:67985556 Keywords : nonparametric test s * sequential ranks * stopping variable Subject RIV: BA - General Mathematics OBOR OECD: Pure mathematics Impact factor: 0.339, year: 2016 http://library.utia.cas.cz/separaty/2017/SI/kalina-0474065.pdf

  4. Motion in fourth-rank gravity

    International Nuclear Information System (INIS)

    Tapia, V.

    1992-04-01

    Recently we have explored the consequences of describing the metric properties of our universe through a quartic line element. In this geometry the natural object is a fourth-rank metric, i.e., a tensor with four indices. Based on this geometry we constructed a simple field theory for the gravitational field. The field equations coincide with the Einstein field equations in the vacuum case. This fact, however, does not guarantee the observational equivalence of both theories since one must still verify that, as a consequence of the field equations, test particles move along geodesics. This letter is aimed at establishing this result. (author). 7 refs

  5. Classical impurities associated to high rank algebras

    Energy Technology Data Exchange (ETDEWEB)

    Doikou, Anastasia, E-mail: A.Doikou@hw.ac.uk [Department of Mathematics, Heriot–Watt University, EH14 4AS, Edinburgh (United Kingdom); Department of Computer Engineering and Informatics, University of Patras, Patras GR-26500 (Greece)

    2014-07-15

    Classical integrable impurities associated with high rank (gl{sub N}) algebras are investigated. A particular prototype, i.e. the vector non-linear Schrödinger (NLS) model, is chosen as an example. A systematic construction of local integrals of motion as well as the time components of the corresponding Lax pairs is presented based on the underlying classical algebra. Suitable gluing conditions compatible with integrability are also extracted. The defect contribution is also examined in the case where non-trivial integrable conditions are implemented. It turns out that the integrable boundaries may drastically alter the bulk behavior, and in particular the defect contribution.

  6. Low-rank driving in quantum systems

    International Nuclear Information System (INIS)

    Burkey, R.S.

    1989-01-01

    A new property of quantum systems called low-rank driving is introduced. Numerous simplifications in the solution of the time-dependent Schroedinger equation are pointed out for systems having this property. These simplifications are in the areas of finding eigenvalues, taking the Laplace transform, converting Schroedinger's equation to an integral form, discretizing the continuum, generalizing the Weisskopf-Wigner approximation, band-diagonalizing the Hamiltonian, finding new exact solutions to Schroedinger's equation, and so forth. The principal physical application considered is the phenomenon of coherent populations-trapping in continuum-continuum interactions

  7. Classical impurities associated to high rank algebras

    International Nuclear Information System (INIS)

    Doikou, Anastasia

    2014-01-01

    Classical integrable impurities associated with high rank (gl N ) algebras are investigated. A particular prototype, i.e. the vector non-linear Schrödinger (NLS) model, is chosen as an example. A systematic construction of local integrals of motion as well as the time components of the corresponding Lax pairs is presented based on the underlying classical algebra. Suitable gluing conditions compatible with integrability are also extracted. The defect contribution is also examined in the case where non-trivial integrable conditions are implemented. It turns out that the integrable boundaries may drastically alter the bulk behavior, and in particular the defect contribution

  8. Two Ranking Methods of Single Valued Triangular Neutrosophic Numbers to Rank and Evaluate Information Systems Quality

    Directory of Open Access Journals (Sweden)

    Samah Ibrahim Abdel Aal

    2018-03-01

    Full Text Available The concept of neutrosophic can provide a generalization of fuzzy set and intuitionistic fuzzy set that make it is the best fit in representing indeterminacy and uncertainty. Single Valued Triangular Numbers (SVTrN-numbers is a special case of neutrosophic set that can handle ill-known quantity very difficult problems. This work intended to introduce a framework with two types of ranking methods. The results indicated that each ranking method has its own advantage. In this perspective, the weighted value and ambiguity based method gives more attention to uncertainty in ranking and evaluating ISQ as well as it takes into account cut sets of SVTrN numbers that can reflect the information on Truth-membership-membership degree, false membership-membership degree and Indeterminacy-membership degree. The value index and ambiguity index method can reflect the decision maker's subjectivity attitude to the SVTrN- numbers.

  9. The BiPublishers ranking: Main results and methodological problems when constructing rankings of academic publishers

    Directory of Open Access Journals (Sweden)

    Torres-Salinas, Daniel

    2015-12-01

    Full Text Available We present the results of the Bibliometric Indicators for Publishers project (also known as BiPublishers. This project represents the first attempt to systematically develop bibliometric publisher rankings. The data for this project was derived from the Book Citation Index and the study time period was 2009-2013. We have developed 42 rankings: 4 by fields and 38 by disciplines. We display six indicators for publishers divided into three types: output, impact and publisher’s profile. The aim is to capture different characteristics of the research performance of publishers. 254 publishers were processed and classified according to publisher type: commercial publishers and university presses. We present the main publishers by field and then discuss the principal challenges presented when developing this type of tool. The BiPublishers ranking is an on-going project which aims to develop and explore new data sources and indicators to better capture and define the research impact of publishers.Presentamos los resultados del proyecto Bibliometric Indicators for Publishers (BiPublishers. Es el primer proyecto que desarrolla de manera sistemática rankings bibliométricos de editoriales. La fuente de datos empleada es el Book Citation Index y el periodo de análisis 2009-2013. Se presentan 42 rankings: 4 por áreas y 38 por disciplinas. Mostramos seis indicadores por editorial divididos según su tipología: producción, impacto y características editoriales. Se procesaron 254 editoriales y se clasificaron según el tipo: comerciales y universitarias. Se presentan las principales editoriales por áreas. Después, se discuten los principales retos a superar en el desarrollo de este tipo de herramientas. El ranking Bipublishers es un proyecto en desarrollo que persigue analizar y explorar nuevas fuentes de datos e indicadores para captar y definir el impacto de las editoriales académicas.

  10. Generalized PageRank on Directed Configuration Networks

    NARCIS (Netherlands)

    Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana

    2017-01-01

    Note: formula is not displayed correctly. This paper studies the distribution of a family of rankings, which includes Google’s PageRank, on a directed configuration model. In particular, it is shown that the distribution of the rank of a randomly chosen node in the graph converges in distribution to

  11. PageRank in scale-free random graphs

    NARCIS (Netherlands)

    Chen, Ningyuan; Litvak, Nelli; Olvera-Cravioto, Mariana; Bonata, Anthony; Chung, Fan; Pralat, Paweł

    2014-01-01

    We analyze the distribution of PageRank on a directed configuration model and show that as the size of the graph grows to infinity, the PageRank of a randomly chosen node can be closely approximated by the PageRank of the root node of an appropriately constructed tree. This tree approximation is in

  12. Ranking Quality in Higher Education: Guiding or Misleading?

    Science.gov (United States)

    Bergseth, Brita; Petocz, Peter; Abrandt Dahlgren, Madeleine

    2014-01-01

    The study examines two different models of measuring, assessing and ranking quality in higher education. Do different systems of quality assessment lead to equivalent conclusions about the quality of education? This comparative study is based on the rankings of 24 Swedish higher education institutions. Two ranking actors have independently…

  13. Revisiting the Relationship between Institutional Rank and Student Engagement

    Science.gov (United States)

    Zilvinskis, John; Louis Rocconi

    2018-01-01

    College rankings dominate the conversation regarding quality in postsecondary education. However, the criteria used to rank institutions often have nothing to do with the quality of education students receive. A decade ago, Pike (2004) demonstrated that institutional rank had little association with student involvement in educational activities.…

  14. Academic Ranking--From Its Genesis to Its International Expansion

    Science.gov (United States)

    Vieira, Rosilene C.; Lima, Manolita C.

    2015-01-01

    Given the visibility and popularity of rankings that encompass the measurement of quality of post-graduate courses, for instance, the MBA (Master of Business Administration) or graduate studies program (MSc and PhD) as do global academic rankings--Academic Ranking of World Universities-ARWU, Times Higher/Thomson Reuters World University Ranking…

  15. 7 CFR 1491.6 - Ranking considerations and proposal selection.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 10 2010-01-01 2010-01-01 false Ranking considerations and proposal selection. 1491.6... PROGRAM General Provisions § 1491.6 Ranking considerations and proposal selection. (a) Before the State.... The national ranking criteria will be established by the Chief and the State criteria will be...

  16. 46 CFR 282.11 - Ranking of flags.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 8 2010-10-01 2010-10-01 false Ranking of flags. 282.11 Section 282.11 Shipping... COMMERCE OF THE UNITED STATES Foreign-Flag Competition § 282.11 Ranking of flags. The operators under each... priority of costs which are representative of the flag. For liner cargo vessels, the ranking of operators...

  17. 10 CFR 455.131 - State ranking of grant applications.

    Science.gov (United States)

    2010-01-01

    ... 10 Energy 3 2010-01-01 2010-01-01 false State ranking of grant applications. 455.131 Section 455... State ranking of grant applications. (a) Except as provided by § 455.92 of this part, all eligible... audit or energy use evaluation pursuant to § 455.20(k). Each State shall develop separate rankings for...

  18. Control by Numbers: New Managerialism and Ranking in Higher Education

    Science.gov (United States)

    Lynch, Kathleen

    2015-01-01

    This paper analyses the role of rankings as an instrument of new managerialism. It shows how rankings are reconstituting the purpose of universities, the role of academics and the definition of what it is to be a student. The paper opens by examining the forces that have facilitated the emergence of the ranking industry and the ideologies…

  19. Paired comparisons analysis: an axiomatic approach to ranking methods

    NARCIS (Netherlands)

    Gonzalez-Diaz, J.; Hendrickx, Ruud; Lohmann, E.R.M.A.

    2014-01-01

    In this paper we present an axiomatic analysis of several ranking methods for general tournaments. We find that the ranking method obtained by applying maximum likelihood to the (Zermelo-)Bradley-Terry model, the most common method in statistics and psychology, is one of the ranking methods that

  20. Extracting Rankings for Spatial Keyword Queries from GPS Data

    DEFF Research Database (Denmark)

    Keles, Ilkcan; Jensen, Christian Søndergaard; Saltenis, Simonas

    2018-01-01

    Studies suggest that many search engine queries have local intent. We consider the evaluation of ranking functions important for such queries. The key challenge is to be able to determine the “best” ranking for a query, as this enables evaluation of the results of ranking functions. We propose...

  1. Tutorial: Calculating Percentile Rank and Percentile Norms Using SPSS

    Science.gov (United States)

    Baumgartner, Ted A.

    2009-01-01

    Practitioners can benefit from using norms, but they often have to develop their own percentile rank and percentile norms. This article is a tutorial on how to quickly and easily calculate percentile rank and percentile norms using SPSS, and this information is presented for a data set. Some issues in calculating percentile rank and percentile…

  2. Variation in rank abundance replicate samples and impact of clustering

    NARCIS (Netherlands)

    Neuteboom, J.H.; Struik, P.C.

    2005-01-01

    Calculating a single-sample rank abundance curve by using the negative-binomial distribution provides a way to investigate the variability within rank abundance replicate samples and yields a measure of the degree of heterogeneity of the sampled community. The calculation of the single-sample rank

  3. A Fast Algorithm for Generating Permutation Distribution of Ranks in ...

    African Journals Online (AJOL)

    ... function of the distribution of the ranks. This further gives insight into the permutation distribution of a rank statistics. The algorithm is implemented with the aid of the computer algebra system Mathematica. Key words: Combinatorics, generating function, permutation distribution, rank statistics, partitions, computer algebra.

  4. Rank hypocrisies the insult of the REF

    CERN Document Server

    Sayer, Derek

    2015-01-01

    "The REF is right out of Havel's and Kundera's Eastern Europe: a state-administered exercise to rank academic research like hotel chains dependent on the active collaboration of the UK professoriate. In crystalline text steeped in cold rage, Sayer takes aim at the REF's central claim, that it is a legitimate process of expert peer review. He critiques university and national-level REF processes against actual practices of scholarly review as found in academic journals, university presses, and North American tenure procedures. His analysis is damning. If the REF fails as scholarly review, how can academics and universities continue to participate? And how can government use its rankings as a basis for public policy?" - Tarak Barkawi, Reader in the Department of International Relations, London School of Economics "Many academics across the world have come to see the REF as an arrogant attempt to raise national research standards that has resulted in a variety of self-inflicted wounds to UK higher education. Der...

  5. Demographic Ranking of the Baltic Sea States

    Directory of Open Access Journals (Sweden)

    Sluka N.

    2014-06-01

    Full Text Available The relevance of the study lies in the acute need to modernise the tools for a more accurate and comparable reflection of the demographic reality of spatial objects of different scales. This article aims to test the methods of “demographic rankings” developed by Yermakov and Shmakov. The method is based on the principles of indirect standardisation of the major demographic coefficients relative to the age structure.The article describes the first attempt to apply the method to the analysis of birth and mortality rates in 1995 and 2010 for 140 countries against the global average, and for the Baltic Sea states against the European average. The grouping of countries and the analysis of changes over the given period confirmed a number of demographic development trends and the persistence of wide territorial disparities in major indicators. The authors identify opposite trends in ranking based on the standardised birth (country consolidation at the level of averaged values and mortality (polarisation rates. The features of demographic process development in the Baltic regions states are described against the global and European background. The study confirmed the validity of the demographic ranking method, which can be instrumental in solving not only scientific but also practical tasks, including those in the field of demographic and social policy.

  6. The opposing effects of isotropic and anisotropic attraction on association kinetics of proteins and colloids

    Science.gov (United States)

    Newton, Arthur C.; Kools, Ramses; Swenson, David W. H.; Bolhuis, Peter G.

    2017-10-01

    The association and dissociation of particles via specific anisotropic interactions is a fundamental process, both in biology (proteins) and in soft matter (colloidal patchy particles). The presence of alternative binding sites can lead to multiple productive states and also to non-productive "decoy" or intermediate states. Besides anisotropic interactions, particles can experience non-specific isotropic interactions. We employ single replica transition interface sampling to investigate how adding a non-productive binding site or a nonspecific isotropic interaction alters the dimerization kinetics of a generic patchy particle model. The addition of a decoy binding site reduces the association rate constant, independent of the site's position, while adding an isotropic interaction increases it due to an increased rebinding probability. Surprisingly, the association kinetics becomes non-monotonic for a tetramer complex formed by multivalent patchy particles. While seemingly identical to two-particle binding with a decoy state, the cooperativity of binding multiple particles leads to a kinetic optimum. Our results are relevant for the understanding and modeling of biochemical networks and self-assembly processes.

  7. Importance of the pharmacological profile of the bound ligand in enrichment on nuclear receptors: toward the use of experimentally validated decoy ligands.

    Science.gov (United States)

    Lagarde, Nathalie; Zagury, Jean-François; Montes, Matthieu

    2014-10-27

    The evaluation of virtual ligand screening methods is of major importance to ensure their reliability. Taking into account the agonist/antagonist pharmacological profile should improve the quality of the benchmarking data sets since ligand binding can induce conformational changes in the nuclear receptor structure and such changes may vary according to the agonist/antagonist ligand profile. We indeed found that splitting the agonist and antagonist ligands into two separate data sets for a given nuclear receptor target significantly enhances the quality of the evaluation. The pharmacological profile of the ligand bound in the binding site of the target structure was also found to be an additional critical parameter. We also illustrate that active compound data sets for a given pharmacological activity can be used as a set of experimentally validated decoy ligands for another pharmacological activity to ensure a reliable and challenging evaluation of virtual screening methods.

  8. Generalization Performance of Regularized Ranking With Multiscale Kernels.

    Science.gov (United States)

    Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

    2016-05-01

    The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

  9. Exact distributions of two-sample rank statistics and block rank statistics using computer algebra

    NARCIS (Netherlands)

    Wiel, van de M.A.

    1998-01-01

    We derive generating functions for various rank statistics and we use computer algebra to compute the exact null distribution of these statistics. We present various techniques for reducing time and memory space used by the computations. We use the results to write Mathematica notebooks for

  10. Low ranks make the difference : How achievement goals and ranking information affect cooperation intentions

    NARCIS (Netherlands)

    Poortvliet, P. Marijn; Janssen, Onne; Van Yperen, N.W.; Van de Vliert, E.

    This investigation tested the joint effect of achievement goals and ranking information on information exchange intentions with a commensurate exchange partner. Results showed that individuals with performance goals were less inclined to cooperate with an exchange partner when they had low or high

  11. Protein Frustratometer 2: a tool to localize energetic frustration in protein molecules, now with electrostatics.

    Science.gov (United States)

    Parra, R Gonzalo; Schafer, Nicholas P; Radusky, Leandro G; Tsai, Min-Yeh; Guzovsky, A Brenda; Wolynes, Peter G; Ferreiro, Diego U

    2016-07-08

    The protein frustratometer is an energy landscape theory-inspired algorithm that aims at localizing and quantifying the energetic frustration present in protein molecules. Frustration is a useful concept for analyzing proteins' biological behavior. It compares the energy distributions of the native state with respect to structural decoys. The network of minimally frustrated interactions encompasses the folding core of the molecule. Sites of high local frustration often correlate with functional regions such as binding sites and regions involved in allosteric transitions. We present here an upgraded version of a webserver that measures local frustration. The new implementation that allows the inclusion of electrostatic energy terms, important to the interactions with nucleic acids, is significantly faster than the previous version enabling the analysis of large macromolecular complexes within a user-friendly interface. The webserver is freely available at URL: http://frustratometer.qb.fcen.uba.ar. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  12. Inferring high-confidence human protein-protein interactions

    Directory of Open Access Journals (Sweden)

    Yu Xueping

    2012-05-01

    Full Text Available Abstract Background As numerous experimental factors drive the acquisition, identification, and interpretation of protein-protein interactions (PPIs, aggregated assemblies of human PPI data invariably contain experiment-dependent noise. Ascertaining the reliability of PPIs collected from these diverse studies and scoring them to infer high-confidence networks is a non-trivial task. Moreover, a large number of PPIs share the same number of reported occurrences, making it impossible to distinguish the reliability of these PPIs and rank-order them. For example, for the data analyzed here, we found that the majority (>83% of currently available human PPIs have been reported only once. Results In this work, we proposed an unsupervised statistical approach to score a set of diverse, experimentally identified PPIs from nine primary databases to create subsets of high-confidence human PPI networks. We evaluated this ranking method by comparing it with other methods and assessing their ability to retrieve protein associations from a number of diverse and independent reference sets. These reference sets contain known biological data that are either directly or indirectly linked to interactions between proteins. We quantified the average effect of using ranked protein interaction data to retrieve this information and showed that, when compared to randomly ranked interaction data sets, the proposed method created a larger enrichment (~134% than either ranking based on the hypergeometric test (~109% or occurrence ranking (~46%. Conclusions From our evaluations, it was clear that ranked interactions were always of value because higher-ranked PPIs had a higher likelihood of retrieving high-confidence experimental data. Reducing the noise inherent in aggregated experimental PPIs via our ranking scheme further increased the accuracy and enrichment of PPIs derived from a number of biologically relevant data sets. These results suggest that using our high

  13. RANKING RELATIONS USING ANALOGIES IN BIOLOGICAL AND INFORMATION NETWORKS1

    Science.gov (United States)

    Silva, Ricardo; Heller, Katherine; Ghahramani, Zoubin; Airoldi, Edoardo M.

    2013-01-01

    Analogical reasoning depends fundamentally on the ability to learn and generalize about relations between objects. We develop an approach to relational learning which, given a set of pairs of objects S = {A(1) : B(1), A(2) : B(2), …, A(N) : B(N)}, measures how well other pairs A : B fit in with the set S. Our work addresses the following question: is the relation between objects A and B analogous to those relations found in S? Such questions are particularly relevant in information retrieval, where an investigator might want to search for analogous pairs of objects that match the query set of interest. There are many ways in which objects can be related, making the task of measuring analogies very challenging. Our approach combines a similarity measure on function spaces with Bayesian analysis to produce a ranking. It requires data containing features of the objects of interest and a link matrix specifying which relationships exist; no further attributes of such relationships are necessary. We illustrate the potential of our method on text analysis and information networks. An application on discovering functional interactions between pairs of proteins is discussed in detail, where we show that our approach can work in practice even if a small set of protein pairs is provided. PMID:24587838

  14. Scoring predictive models using a reduced representation of proteins: model and energy definition.

    Science.gov (United States)

    Fogolari, Federico; Pieri, Lidia; Dovier, Agostino; Bortolussi, Luca; Giugliarelli, Gilberto; Corazza, Alessandra; Esposito, Gennaro; Viglino, Paolo

    2007-03-23

    Reduced representations of proteins have been playing a keyrole in the study of protein folding. Many such models are available, with different representation detail. Although the usefulness of many such models for structural bioinformatics applications has been demonstrated in recent years, there are few intermediate resolution models endowed with an energy model capable, for instance, of detecting native or native-like structures among decoy sets. The aim of the present work is to provide a discrete empirical potential for a reduced protein model termed here PC2CA, because it employs a PseudoCovalent structure with only 2 Centers of interactions per Amino acid, suitable for protein model quality assessment. All protein structures in the set top500H have been converted in reduced form. The distribution of pseudobonds, pseudoangle, pseudodihedrals and distances between centers of interactions have been converted into potentials of mean force. A suitable reference distribution has been defined for non-bonded interactions which takes into account excluded volume effects and protein finite size. The correlation between adjacent main chain pseudodihedrals has been converted in an additional energetic term which is able to account for cooperative effects in secondary structure elements. Local energy surface exploration is performed in order to increase the robustness of the energy function. The model and the energy definition proposed have been tested on all the multiple decoys' sets in the Decoys'R'us database. The energetic model is able to recognize, for almost all sets, native-like structures (RMSD less than 2.0 A). These results and those obtained in the blind CASP7 quality assessment experiment suggest that the model compares well with scoring potentials with finer granularity and could be useful for fast exploration of conformational space. Parameters are available at the url: http://www.dstb.uniud.it/~ffogolari/download/.

  15. A discriminatory function for prediction of protein-DNA interactions based on alpha shape modeling.

    Science.gov (United States)

    Zhou, Weiqiang; Yan, Hong

    2010-10-15

    Protein-DNA interaction has significant importance in many biological processes. However, the underlying principle of the molecular recognition process is still largely unknown. As more high-resolution 3D structures of protein-DNA complex are becoming available, the surface characteristics of the complex become an important research topic. In our work, we apply an alpha shape model to represent the surface structure of the protein-DNA complex and developed an interface-atom curvature-dependent conditional probability discriminatory function for the prediction of protein-DNA interaction. The interface-atom curvature-dependent formalism captures atomic interaction details better than the atomic distance-based method. The proposed method provides good performance in discriminating the native structures from the docking decoy sets, and outperforms the distance-dependent formalism in terms of the z-score. Computer experiment results show that the curvature-dependent formalism with the optimal parameters can achieve a native z-score of -8.17 in discriminating the native structure from the highest surface-complementarity scored decoy set and a native z-score of -7.38 in discriminating the native structure from the lowest RMSD decoy set. The interface-atom curvature-dependent formalism can also be used to predict apo version of DNA-binding proteins. These results suggest that the interface-atom curvature-dependent formalism has a good prediction capability for protein-DNA interactions. The code and data sets are available for download on http://www.hy8.com/bioinformatics.htm kenandzhou@hotmail.com.

  16. Drug-target interaction prediction: A Bayesian ranking approach.

    Science.gov (United States)

    Peska, Ladislav; Buza, Krisztian; Koller, Júlia

    2017-12-01

    In silico prediction of drug-target interactions (DTI) could provide valuable information and speed-up the process of drug repositioning - finding novel usage for existing drugs. In our work, we focus on machine learning algorithms supporting drug-centric repositioning approach, which aims to find novel usage for existing or abandoned drugs. We aim at proposing a per-drug ranking-based method, which reflects the needs of drug-centric repositioning research better than conventional drug-target prediction approaches. We propose Bayesian Ranking Prediction of Drug-Target Interactions (BRDTI). The method is based on Bayesian Personalized Ranking matrix factorization (BPR) which has been shown to be an excellent approach for various preference learning tasks, however, it has not been used for DTI prediction previously. In order to successfully deal with DTI challenges, we extended BPR by proposing: (i) the incorporation of target bias, (ii) a technique to handle new drugs and (iii) content alignment to take structural similarities of drugs and targets into account. Evaluation on five benchmark datasets shows that BRDTI outperforms several state-of-the-art approaches in terms of per-drug nDCG and AUC. BRDTI results w.r.t. nDCG are 0.929, 0.953, 0.948, 0.897 and 0.690 for G-Protein Coupled Receptors (GPCR), Ion Channels (IC), Nuclear Receptors (NR), Enzymes (E) and Kinase (K) datasets respectively. Additionally, BRDTI significantly outperformed other methods (BLM-NII, WNN-GIP, NetLapRLS and CMF) w.r.t. nDCG in 17 out of 20 cases. Furthermore, BRDTI was also shown to be able to predict novel drug-target interactions not contained in the original datasets. The average recall at top-10 predicted targets for each drug was 0.762, 0.560, 1.000 and 0.404 for GPCR, IC, NR, and E datasets respectively. Based on the evaluation, we can conclude that BRDTI is an appropriate choice for researchers looking for an in silico DTI prediction technique to be used in drug

  17. Inhibition of osteoclastogenesis by RNA interference targeting RANK

    Directory of Open Access Journals (Sweden)

    Ma Ruofan

    2012-08-01

    Full Text Available Abstract Background Osteoclasts and osteoblasts regulate bone resorption and formation to allow bone remodeling and homeostasis. The balance between bone resorption and formation is disturbed by abnormal recruitment of osteoclasts. Osteoclast differentiation is dependent on the receptor activator of nuclear factor NF-kappa B (RANK ligand (RANKL as well as the macrophage colony-stimulating factor (M-CSF. The RANKL/RANK system and RANK signaling induce osteoclast formation mediated by various cytokines. The RANK/RANKL pathway has been primarily implicated in metabolic, degenerative and neoplastic bone disorders or osteolysis. The central role of RANK/RANKL interaction in osteoclastogenesis makes RANK an attractive target for potential therapies in treatment of osteolysis. The purpose of this study was to assess the effect of inhibition of RANK expression in mouse bone marrow macrophages on osteoclast differentiation and bone resorption. Methods Three pairs of short hairpin RNAs (shRNA targeting RANK were designed and synthesized. The optimal shRNA was selected among three pairs of shRNAs by RANK expression analyzed by Western blot and Real-time PCR. We investigated suppression of osteoclastogenesis of mouse bone marrow macrophages (BMMs using the optimal shRNA by targeting RANK. Results Among the three shRANKs examined, shRANK-3 significantly suppressed [88.3%] the RANK expression (p Conclusions These findings suggest that retrovirus-mediated shRNA targeting RANK inhibits osteoclast differentiation and osteolysis. It may appear an attractive target for preventing osteolysis in humans with a potential clinical application.

  18. On the importance of the distance measures used to train and test knowledge-based potentials for proteins.

    Directory of Open Access Journals (Sweden)

    Martin Carlsen

    Full Text Available Knowledge-based potentials are energy functions derived from the analysis of databases of protein structures and sequences. They can be divided into two classes. Potentials from the first class are based on a direct conversion of the distributions of some geometric properties observed in native protein structures into energy values, while potentials from the second class are trained to mimic quantitatively the geometric differences between incorrectly folded models and native structures. In this paper, we focus on the relationship between energy and geometry when training the second class of knowledge-based potentials. We assume that the difference in energy between a decoy structure and the corresponding native structure is linearly related to the distance between the two structures. We trained two distance-based knowledge-based potentials accordingly, one based on all inter-residue distances (PPD, while the other had the set of all distances filtered to reflect consistency in an ensemble of decoys (PPE. We tested four types of metric to characterize the distance between the decoy and the native structure, two based on extrinsic geometry (RMSD and GTD-TS*, and two based on intrinsic geometry (Q* and MT. The corresponding eight potentials were tested on a large collection of decoy sets. We found that it is usually better to train a potential using an intrinsic distance measure. We also found that PPE outperforms PPD, emphasizing the benefits of capturing consistent information in an ensemble. The relevance of these results for the design of knowledge-based potentials is discussed.

  19. Are university rankings useful to improve research? A systematic review.

    Science.gov (United States)

    Vernon, Marlo M; Balas, E Andrew; Momani, Shaher

    2018-01-01

    Concerns about reproducibility and impact of research urge improvement initiatives. Current university ranking systems evaluate and compare universities on measures of academic and research performance. Although often useful for marketing purposes, the value of ranking systems when examining quality and outcomes is unclear. The purpose of this study was to evaluate usefulness of ranking systems and identify opportunities to support research quality and performance improvement. A systematic review of university ranking systems was conducted to investigate research performance and academic quality measures. Eligibility requirements included: inclusion of at least 100 doctoral granting institutions, be currently produced on an ongoing basis and include both global and US universities, publish rank calculation methodology in English and independently calculate ranks. Ranking systems must also include some measures of research outcomes. Indicators were abstracted and contrasted with basic quality improvement requirements. Exploration of aggregation methods, validity of research and academic quality indicators, and suitability for quality improvement within ranking systems were also conducted. A total of 24 ranking systems were identified and 13 eligible ranking systems were evaluated. Six of the 13 rankings are 100% focused on research performance. For those reporting weighting, 76% of the total ranks are attributed to research indicators, with 24% attributed to academic or teaching quality. Seven systems rely on reputation surveys and/or faculty and alumni awards. Rankings influence academic choice yet research performance measures are the most weighted indicators. There are no generally accepted academic quality indicators in ranking systems. No single ranking system provides a comprehensive evaluation of research and academic quality. Utilizing a combined approach of the Leiden, Thomson Reuters Most Innovative Universities, and the SCImago ranking systems may provide

  20. Asynchronous Gossip for Averaging and Spectral Ranking

    Science.gov (United States)

    Borkar, Vivek S.; Makhijani, Rahul; Sundaresan, Rajesh

    2014-08-01

    We consider two variants of the classical gossip algorithm. The first variant is a version of asynchronous stochastic approximation. We highlight a fundamental difficulty associated with the classical asynchronous gossip scheme, viz., that it may not converge to a desired average, and suggest an alternative scheme based on reinforcement learning that has guaranteed convergence to the desired average. We then discuss a potential application to a wireless network setting with simultaneous link activation constraints. The second variant is a gossip algorithm for distributed computation of the Perron-Frobenius eigenvector of a nonnegative matrix. While the first variant draws upon a reinforcement learning algorithm for an average cost controlled Markov decision problem, the second variant draws upon a reinforcement learning algorithm for risk-sensitive control. We then discuss potential applications of the second variant to ranking schemes, reputation networks, and principal component analysis.

  1. Fuzzy-set based contingency ranking

    International Nuclear Information System (INIS)

    Hsu, Y.Y.; Kuo, H.C.

    1992-01-01

    In this paper, a new approach based on fuzzy set theory is developed for contingency ranking of Taiwan power system. To examine whether a power system can remain in a secure and reliable operating state under contingency conditions, those contingency cases that will result in loss-of-load, loss-of generation, or islanding are first identified. Then 1P-1Q iteration of fast decoupled load flow is preformed to estimate post-contingent quantities (line flows, bus voltages) for other contingency cases. Based on system operators' past experience, each post-contingent quantity is assigned a degree of severity according to the potential damage that could be imposed on the power system by the quantity, should the contingency occurs. An approach based on fuzzy set theory is developed to deal with the imprecision of linguistic terms

  2. Motif discovery in ranked lists of sequences

    DEFF Research Database (Denmark)

    Nielsen, Morten Muhlig; Tataru, Paula; Madsen, Tobias

    2016-01-01

    Motif analysis has long been an important method to characterize biological functionality and the current growth of sequencing-based genomics experiments further extends its potential. These diverse experiments often generate sequence lists ranked by some functional property. There is therefore...... advantage of the regular expression feature, including enrichments for combinations of different microRNA seed sites. The method is implemented and made publicly available as an R package and supports high parallelization on multi-core machinery....... a growing need for motif analysis methods that can exploit this coupled data structure and be tailored for specific biological questions. Here, we present an exploratory motif analysis tool, Regmex (REGular expression Motif EXplorer), which offers several methods to evaluate the correlation of motifs...

  3. Ranked retrieval of Computational Biology models.

    Science.gov (United States)

    Henkel, Ron; Endler, Lukas; Peters, Andre; Le Novère, Nicolas; Waltemath, Dagmar

    2010-08-11

    The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind. Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models. The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.

  4. An R package for analyzing and modeling ranking data.

    Science.gov (United States)

    Lee, Paul H; Yu, Philip L H

    2013-05-14

    In medical informatics, psychology, market research and many other fields, researchers often need to analyze and model ranking data. However, there is no statistical software that provides tools for the comprehensive analysis of ranking data. Here, we present pmr, an R package for analyzing and modeling ranking data with a bundle of tools. The pmr package enables descriptive statistics (mean rank, pairwise frequencies, and marginal matrix), Analytic Hierarchy Process models (with Saaty's and Koczkodaj's inconsistencies), probability models (Luce model, distance-based model, and rank-ordered logit model), and the visualization of ranking data with multidimensional preference analysis. Examples of the use of package pmr are given using a real ranking dataset from medical informatics, in which 566 Hong Kong physicians ranked the top five incentives (1: competitive pressures; 2: increased savings; 3: government regulation; 4: improved efficiency; 5: improved quality care; 6: patient demand; 7: financial incentives) to the computerization of clinical practice. The mean rank showed that item 4 is the most preferred item and item 3 is the least preferred item, and significance difference was found between physicians' preferences with respect to their monthly income. A multidimensional preference analysis identified two dimensions that explain 42% of the total variance. The first can be interpreted as the overall preference of the seven items (labeled as "internal/external"), and the second dimension can be interpreted as their overall variance of (labeled as "push/pull factors"). Various statistical models were fitted, and the best were found to be weighted distance-based models with Spearman's footrule distance. In this paper, we presented the R package pmr, the first package for analyzing and modeling ranking data. The package provides insight to users through descriptive statistics of ranking data. Users can also visualize ranking data by applying a thought

  5. Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

    Science.gov (United States)

    Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

    2017-08-18

    Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

  6. Using incomplete citation data for MEDLINE results ranking.

    Science.gov (United States)

    Herskovic, Jorge R; Bernstam, Elmer V

    2005-01-01

    Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

  7. Co-integration Rank Testing under Conditional Heteroskedasticity

    DEFF Research Database (Denmark)

    Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert

    null distributions of the rank statistics coincide with those derived by previous authors who assume either i.i.d. or (strict and covariance) stationary martingale difference innovations. We then propose wild bootstrap implementations of the co-integrating rank tests and demonstrate that the associated...... bootstrap rank statistics replicate the first-order asymptotic null distributions of the rank statistics. We show the same is also true of the corresponding rank tests based on the i.i.d. bootstrap of Swensen (2006). The wild bootstrap, however, has the important property that, unlike the i.i.d. bootstrap......, it preserves in the re-sampled data the pattern of heteroskedasticity present in the original shocks. Consistent with this, numerical evidence sug- gests that, relative to tests based on the asymptotic critical values or the i.i.d. bootstrap, the wild bootstrap rank tests perform very well in small samples un...

  8. Social Rank, Stress, Fitness, and Life Expectancy in Wild Rabbits

    Science.gov (United States)

    von Holst, Dietrich; Hutzelmeyer, Hans; Kaetzke, Paul; Khaschei, Martin; Schönheiter, Ronald

    Wild rabbits of the two sexes have separate linear rank orders, which are established and maintained by intensive fights. The social rank of individuals strongly influence their fitness: males and females that gain a high social rank, at least at the outset of their second breeding season, have a much higher lifetime fitness than subordinate individuals. This is because of two separate factors: a much higher fecundity and annual reproductive success and a 50% longer reproductive life span. These results are in contrast to the view in evolutionary biology that current reproduction can be increased only at the expense of future survival and/or fecundity. These concepts entail higher physiological costs in high-ranking mammals, which is not supported by our data: In wild rabbits the physiological costs of social positions are caused predominantly by differential psychosocial stress responses that are much lower in high-ranking than in low-ranking individuals.

  9. CLUB-MARTINI : Selecting favourable interactions amongst available candidates, a coarse-grained simulation approach to scoring docking decoys

    NARCIS (Netherlands)

    Hou, Qingzhen; Lensink, Marc F; Heringa, Jaap; Feenstra, K Anton

    2016-01-01

    Large-scale identification of native binding orientations is crucial for understanding the role of protein-protein interactions in their biological context. Measuring binding free energy is the method of choice to estimate binding strength and reveal the relevance of particular conformations in

  10. RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

    Directory of Open Access Journals (Sweden)

    Bouchra Sojod

    2017-05-01

    Full Text Available Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases.

  11. RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

    Science.gov (United States)

    Sojod, Bouchra; Chateau, Danielle; Mueller, Christopher G.; Babajko, Sylvie; Berdal, Ariane; Lézot, Frédéric; Castaneda, Beatriz

    2017-01-01

    Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg) and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases. PMID:28596739

  12. Discovering author impact: A PageRank perspective

    OpenAIRE

    Yan, Erjia; Ding, Ying

    2010-01-01

    This article provides an alternative perspective for measuring author impact by applying PageRank algorithm to a coauthorship network. A weighted PageRank algorithm considering citation and coauthorship network topology is proposed. We test this algorithm under different damping factors by evaluating author impact in the informetrics research community. In addition, we also compare this weighted PageRank with the h-index, citation, and program committee (PC) membership of the International So...

  13. Convolutional Codes with Maximum Column Sum Rank for Network Streaming

    OpenAIRE

    Mahmood, Rafid; Badr, Ahmed; Khisti, Ashish

    2015-01-01

    The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction invol...

  14. Ranking agricultural, environmental and natural resource economics journals: A note

    OpenAIRE

    Halkos, George; Tzeremes, Nickolaos

    2012-01-01

    This paper by applying Data Envelopment Analysis (DEA) ranks for the first time Economics journals in the field of Agricultural, Environmental and Natural Resource. Specifically, by using one composite input and one composite output the paper ranks 32 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with t...

  15. Is there a 'Mid-Rank Trap' for Universities'

    OpenAIRE

    Chang Da Wan

    2015-01-01

    The middle-income trap is an economic phenomenon to describe economies that have stagnated at the middle-income level and failed to progress into the high-income level. Inspired by this economic concept, this paper explores a hypothesis: is there a 'mid-rank trap' for universities in the exercise to rank universities globally' Using the rankings between 2004 and 2014 that were jointly and separately developed by Times Higher Education and Quacquarelli Symonds Company, this paper argues that t...

  16. Asympotic efficiency of signed - rank symmetry tests under skew alternatives.

    OpenAIRE

    Alessandra Durio; Yakov Nikitin

    2002-01-01

    The efficiency of some known tests for symmetry such as the sign test, the Wilcoxon signed-rank test or more general linear signed rank tests was studied mainly under the classical alternatives of location. However it is interesting to compare the efficiencies of these tests under asymmetric alternatives like the so-called skew alternative proposed in Azzalini (1985). We find and compare local Bahadur efficiencies of linear signed-rank statistics for skew alternatives and discuss also the con...

  17. Reduced Rank Adaptive Filtering in Impulsive Noise Environments

    KAUST Repository

    Soury, Hamza

    2014-01-06

    An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

  18. Reduced Rank Adaptive Filtering in Impulsive Noise Environments

    KAUST Repository

    Soury, Hamza; Abed-Meraim, Karim; Alouini, Mohamed-Slim

    2014-01-01

    An impulsive noise environment is used in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction. The minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each algorithm is discussed.

  19. A Citation-Based Ranking of Strategic Management Journals

    OpenAIRE

    Azar, Ofer H.; Brock, David M.

    2007-01-01

    Rankings of strategy journals are important for authors, readers, and promotion and tenure committees. We present several rankings, based either on the number of articles that cited the journal or the per-article impact. Our analyses cover various periods between 1991 and 2006, for most of which the Strategic Management Journal was in first place and Journal of Economics & Management Strategy (JEMS) second, although JEMS ranked first in certain instances. Long Range Planning and Technology An...

  20. Connectivity ranking of heterogeneous random conductivity models

    Science.gov (United States)

    Rizzo, C. B.; de Barros, F.

    2017-12-01

    To overcome the challenges associated with hydrogeological data scarcity, the hydraulic conductivity (K) field is often represented by a spatial random process. The state-of-the-art provides several methods to generate 2D or 3D random K-fields, such as the classic multi-Gaussian fields or non-Gaussian fields, training image-based fields and object-based fields. We provide a systematic comparison of these models based on their connectivity. We use the minimum hydraulic resistance as a connectivity measure, which it has been found to be strictly correlated with early time arrival of dissolved contaminants. A computationally efficient graph-based algorithm is employed, allowing a stochastic treatment of the minimum hydraulic resistance through a Monte-Carlo approach and therefore enabling the computation of its uncertainty. The results show the impact of geostatistical parameters on the connectivity for each group of random fields, being able to rank the fields according to their minimum hydraulic resistance.

  1. Multirelational Social Recommendations via Multigraph Ranking.

    Science.gov (United States)

    Mao, Mingsong; Lu, Jie; Zhang, Guangquan; Zhang, Jinlong

    2017-12-01

    Recommender systems aim to identify relevant items for particular users in large-scale online applications. The historical rating data of users is a valuable input resource for many recommendation models such as collaborative filtering (CF), but these models are known to suffer from the rating sparsity problem when the users or items under consideration have insufficient rating records. With the continued growth of online social networks, the increased user-to-user relationships are reported to be helpful and can alleviate the CF rating sparsity problem. Although researchers have developed a range of social network-based recommender systems, there is no unified model to handle multirelational social networks. To address this challenge, this paper represents different user relationships in a multigraph and develops a multigraph ranking model to identify and recommend the nearest neighbors of particular users in high-order environments. We conduct empirical experiments on two real-world datasets: 1) Epinions and 2) Last.fm, and the comprehensive comparison with other approaches demonstrates that our model improves recommendation performance in terms of both recommendation coverage and accuracy, especially when the rating data are sparse.

  2. Improving CBIR Systems Using Automated Ranking

    Directory of Open Access Journals (Sweden)

    B. D. Reljin

    2012-11-01

    Full Text Available The most common way of searching images on the Internet and in private collections is based on a similarity measuring of a series of text words that are assigned to each image with users query series. This method imposes strong constraints (the number of words to describe the image, the time necessary to thoroughly describe the subjective experience of images, the level of details in the picture, language barrier, etc., and is therefore very inefficient. Modern researches in this area are focused on the contentbased searching images (CBIR. In this way, all described disadvantages are overcome and the quality of searching results is improved. This paper presents a solution for CBIR systems where the search procedure is enhanced using sophisticated extraction and ranking of extracted images. The searching procedure is based on extraction and preprocessing of a large number of low level image features. Thus, when the user defines a query image, the proposed algorithm based on artificial intelligence, shows to the user a group of images which are most similar to a query image by content. The proposed algorithm is iterative, so the user can direct the searching procedure to an expected outcome and get a set of images that are more similar to the query one.

  3. Method ranks competing projects by priorities, risk

    International Nuclear Information System (INIS)

    Moeckel, D.R.

    1993-01-01

    A practical, objective guide for ranking projects based on risk-based priorities has been developed by Sun Pipe Line Co. The deliberately simple system guides decisions on how to allocate scarce company resources because all managers employ the same criteria in weighing potential risks to the company versus benefits. Managers at all levels are continuously having to comply with an ever growing amount of legislative and regulatory requirements while at the same time trying to run their businesses effectively. The system primarily is designed for use as a compliance oversight and tracking process to document, categorize, and follow-up on work concerning various issues or projects. That is, the system consists of an electronic database which is updated periodically, and is used by various levels of management to monitor progress of health, safety, environmental and compliance-related projects. Criteria used in determining a risk factor and assigning a priority also have been adapted and found useful for evaluating other types of projects. The process enables management to better define potential risks and/or loss of benefits that are being accepted when a project is rejected from an immediate work plan or budget. In times of financial austerity, it is extremely important that the right decisions are made at the right time

  4. A Note on the PageRank of Undirected Graphs

    OpenAIRE

    Grolmusz, Vince

    2012-01-01

    The PageRank is a widely used scoring function of networks in general and of the World Wide Web graph in particular. The PageRank is defined for directed graphs, but in some special cases applications for undirected graphs occur. In the literature it is widely noted that the PageRank for undirected graphs are proportional to the degrees of the vertices of the graph. We prove that statement for a particular personalization vector in the definition of the PageRank, and we also show that in gene...

  5. Multidimensional ranking the design and development of U-Multirank

    CERN Document Server

    Ziegele, Frank

    2012-01-01

    During the last decades ranking has become one of the most controversial issues in higher education and research. It is widely recognized now that, although some of the current rankings can be severely criticized, they seem to be here to stay. In addition, rankings appear to have a great impact on decision-makers at all levels of higher education and research systems worldwide, including in universities. Rankings reflect a growing international competition among universities for talent and resources; at the same time they reinforce competition by their very results. Yet major concerns remain a

  6. Rank diversity of languages: generic behavior in computational linguistics.

    Science.gov (United States)

    Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

    2015-01-01

    Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: "heads" consist of words which almost do not change their rank in time, "bodies" are words of general use, while "tails" are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied.

  7. Rank Diversity of Languages: Generic Behavior in Computational Linguistics

    Science.gov (United States)

    Cocho, Germinal; Flores, Jorge; Gershenson, Carlos; Pineda, Carlos; Sánchez, Sergio

    2015-01-01

    Statistical studies of languages have focused on the rank-frequency distribution of words. Instead, we introduce here a measure of how word ranks change in time and call this distribution rank diversity. We calculate this diversity for books published in six European languages since 1800, and find that it follows a universal lognormal distribution. Based on the mean and standard deviation associated with the lognormal distribution, we define three different word regimes of languages: “heads” consist of words which almost do not change their rank in time, “bodies” are words of general use, while “tails” are comprised by context-specific words and vary their rank considerably in time. The heads and bodies reflect the size of language cores identified by linguists for basic communication. We propose a Gaussian random walk model which reproduces the rank variation of words in time and thus the diversity. Rank diversity of words can be understood as the result of random variations in rank, where the size of the variation depends on the rank itself. We find that the core size is similar for all languages studied. PMID:25849150

  8. Tensor rank of the tripartite state |W>xn

    International Nuclear Information System (INIS)

    Yu Nengkun; Guo Cheng; Duan Runyao; Chitambar, Eric

    2010-01-01

    Tensor rank refers to the number of product states needed to express a given multipartite quantum state. Its nonadditivity as an entanglement measure has recently been observed. In this Brief Report, we estimate the tensor rank of multiple copies of the tripartite state |W>=(1/√(3))(|100>+|010>+|001>). Both an upper bound and a lower bound of this rank are derived. In particular, it is proven that the rank of |W> x 2 is 7, thus resolving a previously open problem. Some implications of this result are discussed in terms of transformation rates between |W> xn and multiple copies of the state |GHZ>=(1/√(2))(|000>+|111>).

  9. Quantum probability ranking principle for ligand-based virtual screening

    Science.gov (United States)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  10. Proceedings of the sixteenth biennial low-rank fuels symposium

    International Nuclear Information System (INIS)

    1991-01-01

    Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium

  11. Learning to rank for information retrieval and natural language processing

    CERN Document Server

    Li, Hang

    2014-01-01

    Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work.The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as tw

  12. Rank of quantized universal enveloping algebras and modular functions

    International Nuclear Information System (INIS)

    Majid, S.; Soibelman, Ya.S.

    1991-01-01

    We compute an intrinsic rank invariant for quasitriangular Hopf algebras in the case of general quantum groups U q (g). As a function of q the rank has remarkable number theoretic properties connected with modular covariance and Galois theory. A number of examples are treated in detail, including rank (U q (su(3)) and rank (U q (e 8 )). We briefly indicate a physical interpretation as relating Chern-Simons theory with the theory of a quantum particle confined to an alcove of g. (orig.)

  13. Extreme learning machine for ranking: generalization analysis and applications.

    Science.gov (United States)

    Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin

    2014-05-01

    The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

  14. Treatment plan ranking using physical and biological indices

    International Nuclear Information System (INIS)

    Ebert, M. A.; University of Western Asutralia, WA

    2001-01-01

    Full text: The ranking of dose distributions is of importance in several areas such as i) comparing rival treatment plans, ii) comparing iterations in an optimisation routine, and iii) dose-assessment of clinical trial data. This study aimed to investigate the influence of choice of objective function in ranking tumour dose distributions. A series of physical (mean, maximum, minimum, standard deviation of dose) dose-volume histogram (DVH) reduction indices and biologically-based (tumour-control probability - TCP; equivalent uniform dose -EUD) indices were used to rank a series of hypothetical DVHs, as well as DVHs obtained from a series of 18 prostate patients. The distribution in ranking and change in distribution with change in indice parameters were investigated. It is found that not only is the ranking of DVHs dependent on the actual model used to perform the DVH reduction, it is also found to depend on the inherent characteristics of each model (i.e., selected parameters). The adjacent figure shows an example where the 18 prostate patients are ranked (grey-scale from black to white) by EUD when an α value of 0.8 Gy -1 is used in the model. The change of ranking as α varies is evident. Conclusion: This study has shown that the characteristics of the model selected in plan optimisation or DVH ranking will have an impact on the ranking obtained. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

  15. Quantum probability ranking principle for ligand-based virtual screening.

    Science.gov (United States)

    Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

    2017-04-01

    Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

  16. Ranking accounting, banking and finance journals: A note

    OpenAIRE

    Halkos, George; Tzeremes, Nickolaos

    2012-01-01

    This paper by applying Data Envelopment Analysis (DEA) ranks Economics journals in the field of Accounting, Banking and Finance. By using one composite input and one composite output the paper ranks 57 journals. In addition for the first time three different quality ranking reports have been incorporated to the DEA modelling problem in order to classify the journals into four categories (‘A’ to ‘D’). The results reveal that the journals with the highest rankings in the field are Journal of Fi...

  17. Proceedings of the sixteenth biennial low-rank fuels symposium

    Energy Technology Data Exchange (ETDEWEB)

    1991-01-01

    Low-rank coals represent a major energy resource for the world. The Low-Rank Fuels Symposium, building on the traditions established by the Lignite Symposium, focuses on the key opportunities for this resource. This conference offers a forum for leaders from industry, government, and academia to gather to share current information on the opportunities represented by low-rank coals. In the United States and throughout the world, the utility industry is the primary user of low-rank coals. As such, current experiences and future opportunities for new technologies in this industry were the primary focuses of the symposium.

  18. Econophysics of a ranked demand and supply resource allocation problem

    Science.gov (United States)

    Priel, Avner; Tamir, Boaz

    2018-01-01

    We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

  19. Low-Rank Matrix Factorization With Adaptive Graph Regularizer.

    Science.gov (United States)

    Lu, Gui-Fu; Wang, Yong; Zou, Jian

    2016-05-01

    In this paper, we present a novel low-rank matrix factorization algorithm with adaptive graph regularizer (LMFAGR). We extend the recently proposed low-rank matrix with manifold regularization (MMF) method with an adaptive regularizer. Different from MMF, which constructs an affinity graph in advance, LMFAGR can simultaneously seek graph weight matrix and low-dimensional representations of data. That is, graph construction and low-rank matrix factorization are incorporated into a unified framework, which results in an automatically updated graph rather than a predefined one. The experimental results on some data sets demonstrate that the proposed algorithm outperforms the state-of-the-art low-rank matrix factorization methods.

  20. On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

    DEFF Research Database (Denmark)

    Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

    2011-01-01

    Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

  1. Forward projections of energy market competitiveness rankings

    International Nuclear Information System (INIS)

    2008-01-01

    By July 2007, the provisions of the second Internal Market Directives for Electricity and Gas had been implemented in the majority of EU Member States. These fundamental changes in market opening, ownership structures and network access conditions, together with the increasing maturity of liberalised trading and retail markets, can be expected to affect the behaviour of existing and potential market participants, consequently affecting the energy market competitiveness of alternative countries. While the UK was the most competitive of the EU and G7 energy markets in 2006, the dynamic effect of the liberalisation programme across Continental Europe may challenge that position in the future. This report assesses how competitiveness rankings may evolve in the future, identifying changes that could take place in the UK and the rest of the EU from 2007 to 201 1. It goes on to explore the potential risk that the competitiveness of the UK's energy markets will decline relative to those of other countries in the EU and G7, to the extent that the PSA target will not be met. A detailed analysis of the potential changes in the UK markets is undertaken, including the development of upside and downside scenarios showing the positive and negative effects of changes in market structure and behaviour on the UK's competitiveness score. Changes in market structures required for energy markets in both the 2006 comparator group and the rest of the EU to become as competitive as the UK are then assessed, along with the plausibility of these changes given the current and future market, legislative and regulatory environments

  2. Development and first application of an operating events ranking tool

    International Nuclear Information System (INIS)

    Šimić, Zdenko; Zerger, Benoit; Banov, Reni

    2015-01-01

    Highlights: • A method using analitycal hierarchy process for ranking operating events is developed and tested. • The method is applied for 5 years of U.S. NRC Licensee Event Reports (1453 events). • Uncertainty and sensitivity of the ranking results are evaluated. • Real events assessment shows potential of the method for operating experience feedback. - Abstract: The operating experience feedback is important for maintaining and improving safety and availability in nuclear power plants. Detailed investigation of all events is challenging since it requires excessive resources, especially in case of large event databases. This paper presents an event groups ranking method to complement the analysis of individual operating events. The basis for the method is the use of an internationally accepted events characterization scheme that allows different ways of events grouping and ranking. The ranking method itself consists of implementing the analytical hierarchy process (AHP) by means of a custom developed tool which allows events ranking based on ranking indexes pre-determined by expert judgment. Following the development phase, the tool was applied to analyze a complete set of 5 years of real nuclear power plants operating events (1453 events). The paper presents the potential of this ranking method to identify possible patterns throughout the event database and therefore to give additional insights into the events as well as to give quantitative input for the prioritization of further more detailed investigation of selected event groups

  3. University Rankings: How Well Do They Measure Library Service Quality?

    Science.gov (United States)

    Jackson, Brian

    2015-01-01

    University rankings play an increasingly large role in shaping the goals of academic institutions and departments, while removing universities themselves from the evaluation process. This study compares the library-related results of two university ranking publications with scores on the LibQUAL+™ survey to identify if library service quality--as…

  4. Jackknife Variance Estimator for Two Sample Linear Rank Statistics

    Science.gov (United States)

    1988-11-01

    Accesion For - - ,NTIS GPA&I "TIC TAB Unann c, nc .. [d Keywords: strong consistency; linear rank test’ influence function . i , at L By S- )Distribut...reverse if necessary and identify by block number) FIELD IGROUP SUB-GROUP Strong consistency; linear rank test; influence function . 19. ABSTRACT

  5. Monte Carlo methods of PageRank computation

    NARCIS (Netherlands)

    Litvak, Nelli

    2004-01-01

    We describe and analyze an on-line Monte Carlo method of PageRank computation. The PageRank is being estimated basing on results of a large number of short independent simulation runs initiated from each page that contains outgoing hyperlinks. The method does not require any storage of the hyperlink

  6. Positioning Open Access Journals in a LIS Journal Ranking

    Science.gov (United States)

    Xia, Jingfeng

    2012-01-01

    This research uses the h-index to rank the quality of library and information science journals between 2004 and 2008. Selected open access (OA) journals are included in the ranking to assess current OA development in support of scholarly communication. It is found that OA journals have gained momentum supporting high-quality research and…

  7. Feeding rank in the Derby eland: lessons for management ...

    African Journals Online (AJOL)

    High-ranking individuals in good condition limited access to supplementary feeding to their lower-ranking herdmates. Effective supplementary feeding should therefore be provided in excess amounts to enable younger and weaker individuals in need to benefit from it, despite their lower positions in the hierarchy. Keywords: ...

  8. Balancing exploration and exploitation in learning to rank online

    NARCIS (Netherlands)

    Hofmann, K.; Whiteson, S.; de Rijke, M.

    2011-01-01

    As retrieval systems become more complex, learning to rank approaches are being developed to automatically tune their parameters. Using online learning to rank approaches, retrieval systems can learn directly from implicit feedback, while they are running. In such an online setting, algorithms need

  9. Ranking production units according to marginal efficiency contribution

    DEFF Research Database (Denmark)

    Ghiyasi, Mojtaba; Hougaard, Jens Leth

    League tables associated with various forms of service activities from schools to hospitals illustrate the public need for ranking institutions by their productive performance. We present a new method for ranking production units which is based on each units marginal contribution to the technical...

  10. Trachomatous Scar Ranking: A Novel Outcome for Trachoma Studies.

    Science.gov (United States)

    Baldwin, Angela; Ryner, Alexander M; Tadesse, Zerihun; Shiferaw, Ayalew; Callahan, Kelly; Fry, Dionna M; Zhou, Zhaoxia; Lietman, Thomas M; Keenan, Jeremy D

    2017-06-01

    AbstractWe evaluated a new trachoma scarring ranking system with potential use in clinical research. The upper right tarsal conjunctivas of 427 individuals from Ethiopian villages with hyperendemic trachoma were photographed. An expert grader first assigned a scar grade to each photograph using the 1981 World Health Organization (WHO) grading system. Then, all photographs were ranked from least (rank = 1) to most scarring (rank = 427). Photographic grading found 79 (18.5%) conjunctivae without scarring (C0), 191 (44.7%) with minimal scarring (C1), 105 (24.6%) with moderate scarring (C2), and 52 (12.2%) with severe scarring (C3). The ranking method demonstrated good internal validity, exhibiting a monotonic increase in the median rank across the levels of the 1981 WHO grading system. Intrarater repeatability was better for the ranking method (intraclass correlation coefficient = 0.84, 95% CI = 0.74-0.94). Exhibiting better internal and external validity, this ranking method may be useful for evaluating the difference in scarring between groups of individuals.

  11. Optimal ranking regime analysis of TreeFlow dendrohydrological reconstructions

    Science.gov (United States)

    The Optimal Ranking Regime (ORR) method was used to identify 6-100 year time windows containing significant ranking sequences in 55 western U.S. streamflow reconstructions, and reconstructions of the level of the Great Salt Lake and San Francisco Bay salinity during 1500-2007. The method’s ability t...

  12. The Ranking Phenomenon and the Experience of Academics in Taiwan

    Science.gov (United States)

    Lo, William Yat Wai

    2014-01-01

    The primary aim of the paper is to examine how global university rankings have influenced the higher education sector in Taiwan from the perspective of academics. A qualitative case study method was used to examine how university ranking influenced the Taiwanese higher education at institutional and individual levels, respectively, thereby…

  13. Ranking Regime and the Future of Vernacular Scholarship

    Science.gov (United States)

    Ishikawa, Mayumi

    2014-01-01

    World university rankings and their global popularity present a number of far-reaching impacts for vernacular scholarship. This article employs a multidimensional approach to analyze the ranking regime's threat to local scholarship and knowledge construction through a study of Japanese research universities. First, local conditions that have led…

  14. The Distribution of the Sum of Signed Ranks

    Science.gov (United States)

    Albright, Brian

    2012-01-01

    We describe the calculation of the distribution of the sum of signed ranks and develop an exact recursive algorithm for the distribution as well as an approximation of the distribution using the normal. The results have applications to the non-parametric Wilcoxon signed-rank test.

  15. Ranking Exponential Trapezoidal Fuzzy Numbers by Median Value

    Directory of Open Access Journals (Sweden)

    S. Rezvani

    2013-12-01

    Full Text Available In this paper, we want represented a method for ranking of two exponential trapezoidal fuzzy numbers. A median value is proposed for the ranking of exponential trapezoidal fuzzy numbers. For the validation the results of the proposed approach are compared with different existing approaches.

  16. Rank dependent expected utility models of tax evasion.

    OpenAIRE

    Erling Eide

    2001-01-01

    In this paper the rank-dependent expected utility theory is substituted for the expected utility theory in models of tax evasion. It is demonstrated that the comparative statics results of the expected utility, portfolio choice model of tax evasion carry over to the more general rank dependent expected utility model.

  17. Prototyping a Distributed Information Retrieval System That Uses Statistical Ranking.

    Science.gov (United States)

    Harman, Donna; And Others

    1991-01-01

    Built using a distributed architecture, this prototype distributed information retrieval system uses statistical ranking techniques to provide better service to the end user. Distributed architecture was shown to be a feasible alternative to centralized or CD-ROM information retrieval, and user testing of the ranking methodology showed both…

  18. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse; Petta, A.; Serra, L.; Vangone, A.; Scarano, V.; Cavallo, Luigi; Oliva, R.

    2014-01-01

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  19. CONSRANK: a server for the analysis, comparison and ranking of docking models based on inter-residue contacts

    KAUST Repository

    Chermak, Edrisse

    2014-12-21

    Summary: Herein, we present CONSRANK, a web tool for analyzing, comparing and ranking protein–protein and protein–nucleic acid docking models, based on the conservation of inter-residue contacts and its visualization in 2D and 3D interactive contact maps.

  20. UTV Expansion Pack: Special-Purpose Rank-Revealing Algorithms

    DEFF Research Database (Denmark)

    Fierro, Ricardo D.; Hansen, Per Christian

    2005-01-01

    This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank-r...... values of a sparse or structured matrix. These new algorithms have applications in signal processing, optimization and LSI information retrieval.......This collection of Matlab 7.0 software supplements and complements the package UTV Tools from 1999, and includes implementations of special-purpose rank-revealing algorithms developed since the publication of the original package. We provide algorithms for computing and modifying symmetric rank......-revealing VSV decompositions, we expand the algorithms for the ULLV decomposition of a matrix pair to handle interference-type problems with a rank-deficient covariance matrix, and we provide a robust and reliable Lanczos algorithm which - despite its simplicity - is able to capture all the dominant singular...

  1. Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

    Science.gov (United States)

    Gerner, Nadine V; Cailleaud, Kevin; Bassères, Anne; Liess, Matthias; Beketov, Mikhail A

    2017-11-01

    Hydrocarbons have an utmost economical importance but may also cause substantial ecological impacts due to accidents or inadequate transportation and use. Currently, freshwater biomonitoring methods lack an indicator that can unequivocally reflect the impacts caused by hydrocarbons while being independent from effects of other stressors. The aim of the present study was to develop a sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants, which can be used in hydrocarbon-specific bioindicators. We employed the Relative Sensitivity method and developed the sensitivity ranking S hydrocarbons based on literature ecotoxicological data supplemented with rapid and mesocosm test results. A first validation of the sensitivity ranking based on an earlier field study has been conducted and revealed the S hydrocarbons ranking to be promising for application in sensitivity based indicators. Thus, the first results indicate that the ranking can serve as the core component of future hydrocarbon-specific and sensitivity trait based bioindicators.

  2. A model-based approach to operational event groups ranking

    Energy Technology Data Exchange (ETDEWEB)

    Simic, Zdenko [European Commission Joint Research Centre, Petten (Netherlands). Inst. for Energy and Transport; Maqua, Michael [Gesellschaft fuer Anlagen- und Reaktorsicherheit mbH (GRS), Koeln (Germany); Wattrelos, Didier [Institut de Radioprotection et de Surete Nucleaire (IRSN), Fontenay-aux-Roses (France)

    2014-04-15

    The operational experience (OE) feedback provides improvements in all industrial activities. Identification of the most important and valuable groups of events within accumulated experience is important in order to focus on a detailed investigation of events. The paper describes the new ranking method and compares it with three others. Methods have been described and applied to OE events utilised by nuclear power plants in France and Germany for twenty years. The results show that different ranking methods only roughly agree on which of the event groups are the most important ones. In the new ranking method the analytical hierarchy process is applied in order to assure consistent and comprehensive weighting determination for ranking indexes. The proposed method allows a transparent and flexible event groups ranking and identification of the most important OE for further more detailed investigation in order to complete the feedback. (orig.)

  3. A Case-Based Reasoning Method with Rank Aggregation

    Science.gov (United States)

    Sun, Jinhua; Du, Jiao; Hu, Jian

    2018-03-01

    In order to improve the accuracy of case-based reasoning (CBR), this paper addresses a new CBR framework with the basic principle of rank aggregation. First, the ranking methods are put forward in each attribute subspace of case. The ordering relation between cases on each attribute is got between cases. Then, a sorting matrix is got. Second, the similar case retrieval process from ranking matrix is transformed into a rank aggregation optimal problem, which uses the Kemeny optimal. On the basis, a rank aggregation case-based reasoning algorithm, named RA-CBR, is designed. The experiment result on UCI data sets shows that case retrieval accuracy of RA-CBR algorithm is higher than euclidean distance CBR and mahalanobis distance CBR testing.So we can get the conclusion that RA-CBR method can increase the performance and efficiency of CBR.

  4. Feasibility study of component risk ranking for plant maintenance

    International Nuclear Information System (INIS)

    Ushijima, Koji; Yonebayashi, Kenji; Narumiya, Yoshiyuki; Sakata, Kaoru; Kumano, Tetsuji

    1999-01-01

    Nuclear power is the base load electricity source in Japan, and reduction of operation and maintenance cost maintaining or improving plant safety is one of the major issues. Recently, Risk Informed Management (RIM) is focused as a solution. In this paper, the outline regarding feasibility study of component risk ranking for plant maintenance for a typical Japanese PWR plant is described. A feasibility study of component risk raking for plant maintenance optimization is performed on check valves and motor-operated valves. Risk ranking is performed in two steps using probabilistic analysis (quantitative method) for risk ranking of components, and deterministic examination (qualitative method) for component review. In this study, plant components are ranked from the viewpoint of plant safety / reliability, and the applicability for maintenance is assessed. As a result, distribution of maintenance resources using risk ranking is considered effective. (author)

  5. CNN-based ranking for biomedical entity normalization.

    Science.gov (United States)

    Li, Haodi; Chen, Qingcai; Tang, Buzhou; Wang, Xiaolong; Xu, Hua; Wang, Baohua; Huang, Dong

    2017-10-03

    Most state-of-the-art biomedical entity normalization systems, such as rule-based systems, merely rely on morphological information of entity mentions, but rarely consider their semantic information. In this paper, we introduce a novel convolutional neural network (CNN) architecture that regards biomedical entity normalization as a ranking problem and benefits from semantic information of biomedical entities. The CNN-based ranking method first generates candidates using handcrafted rules, and then ranks the candidates according to their semantic information modeled by CNN as well as their morphological information. Experiments on two benchmark datasets for biomedical entity normalization show that our proposed CNN-based ranking method outperforms traditional rule-based method with state-of-the-art performance. We propose a CNN architecture that regards biomedical entity normalization as a ranking problem. Comparison results show that semantic information is beneficial to biomedical entity normalization and can be well combined with morphological information in our CNN architecture for further improvement.

  6. Risk-informed ranking of engineering projects

    International Nuclear Information System (INIS)

    Jyrkama, M.; Pandey, M.

    2011-01-01

    Refurbishment planning requires prudent investment decisions with respect to the various systems and components at the station. These decisions are influenced by many factors, including engineering, safety, regulatory, economic, and political constraints. From an engineering perspective, the concept of cost-benefit analysis is a common way to allocate capital among various projects. Naturally, the 'best' or optimal project should have the lowest cost and the highest benefit. In the context of risk-informed decision making (RIDM), a process that has been widely embraced by the global nuclear community, the costs and benefits must further be 'weighted' by probabilities to estimate the underlying risk associated with the various planning alternatives. The main purpose of this study is to illustrate how risk and reliability information can be integrated into the refurbishment planning process to facilitate more objective and transparent investment decisions. The methodology is based on the concept of generation risk assessment (GRA) which provides a systematic approach for balancing investment costs with the reduction in overall financial risk. In addition to reliability predictions, the model provides estimates for the level of risk reduction associated with each system/project and also the break-even point for investment. This information is vital for project ranking, and helps to address the key question of whether capital investment should be made in the most risk critical systems, or in systems that reduce the overall risk the most. The application of the proposed methodology requires only basic information regarding the current reliability of each engineering system, which should be readily available from plant records and routine condition assessments. Because the methodology can be readily implemented in a Microsoft Excel spreadsheet, all plausible (e.g., bounding) planning scenarios, with or without investment, can also be generated quickly and easily, while

  7. Development and application of a free energy force field for all atom protein folding

    International Nuclear Information System (INIS)

    Verma, A.

    2007-11-01

    Proteins are the workhorses of all cellular life. They constitute the building blocks and the machinery of all cells and typically function in specific three-dimensional conformations into which each protein folds. Currently over one million protein sequences are known, compared to about 40,000 structures deposited in the Protein Data Bank (the world-wide database of protein structures). Reliable theoretical methods for protein structure prediction could help to reduce the gap between sequence and structural databases and elucidate the biological information in structurally unresolved sequences. In this thesis we explore an approach for protein structure prediction and folding that is based on the Anfinsen's hypothesis that most proteins in their native state are in thermodynamic equilibrium with their environment. We have developed a free energy forcefield (PFF02) that locates the native conformation of many proteins from all structural classes at the global minimum of the free-energy model. We have validated the forcefield against a large decoy set (Rosetta). The average root mean square deviation (RMSD) for the lowest energy structure for the 32 proteins of the decoy set was only 2.14 Aa from the experimental conformation. We have successfully implemented and used stochastic optimization methods, such as the basin hopping technique and evolutionary algorithms for all atom protein structure prediction. The evolutionary algorithm performs exceptionally well on large supercomputational architectures, such as BlueGene and MareNostrum. Using the PFF02 forcefield, we were able to fold 13 proteins (12-56 amino acids), which include helix, sheet and mixed secondary structure. On average the predicted structure of these proteins deviated from their experimental conformation by only 2.89 Aa RMSD. (orig.)

  8. VisualRank: applying PageRank to large-scale image search.

    Science.gov (United States)

    Jing, Yushi; Baluja, Shumeet

    2008-11-01

    Because of the relative ease in understanding and processing text, commercial image-search systems often rely on techniques that are largely indistinguishable from text-search. Recently, academic studies have demonstrated the effectiveness of employing image-based features to provide alternative or additional signals. However, it remains uncertain whether such techniques will generalize to a large number of popular web queries, and whether the potential improvement to search quality warrants the additional computational cost. In this work, we cast the image-ranking problem into the task of identifying "authority" nodes on an inferred visual similarity graph and propose VisualRank to analyze the visual link structures among images. The images found to be "authorities" are chosen as those that answer the image-queries well. To understand the performance of such an approach in a real system, we conducted a series of large-scale experiments based on the task of retrieving images for 2000 of the most popular products queries. Our experimental results show significant improvement, in terms of user satisfaction and relevancy, in comparison to the most recent Google Image Search results. Maintaining modest computational cost is vital to ensuring that this procedure can be used in practice; we describe the techniques required to make this system practical for large scale deployment in commercial search engines.

  9. The structure of completely positive matrices according to their CP-rank and CP-plus-rank

    NARCIS (Netherlands)

    Dickinson, Peter James Clair; Bomze, Immanuel M.; Still, Georg J.

    2015-01-01

    We study the topological properties of the cp-rank operator $\\mathrm{cp}(A)$ and the related cp-plus-rank operator $\\mathrm{cp}^+(A)$ (which is introduced in this paper) in the set $\\mathcal{S}^n$ of symmetric $n\\times n$-matrices. For the set of completely positive matrices, $\\mathcal{CP}^n$, we

  10. Journal Rankings by Health Management Faculty Members: Are There Differences by Rank, Leadership Status, or Area of Expertise?

    Science.gov (United States)

    Menachemi, Nir; Hogan, Tory H; DelliFraine, Jami L

    2015-01-01

    Health administration (HA) faculty members publish in a variety of journals, including journals focused on management, economics, policy, and information technology. HA faculty members are evaluated on the basis of the quality and quantity of their journal publications. However, it is unclear how perceptions of these journals vary by subdiscipline, department leadership role, or faculty rank. It is also not clear how perceptions of journals may have changed over the past decade since the last evaluation of journal rankings in the field was published. The purpose of the current study is to examine how respondents rank journals in the field of HA, as well as the variation in perception by academic rank, department leadership status, and area of expertise. Data were drawn from a survey of HA faculty members at U.S. universities, which was completed in 2012. Different journal ranking patterns were noted for faculty members of different subdisciplines. The health management-oriented journals (Health Care Management Review and Journal of Healthcare Management) were ranked higher than in previous research, suggesting that journal ranking perceptions may have changed over the intervening decade. Few differences in perceptions were noted by academic rank, but we found that department chairs were more likely than others to select Health Affairs in their top three most prestigious journals (β = 0.768; p journal prestige varied between a department chair and untenured faculty in different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

  11. A resource for benchmarking the usefulness of protein structure models.

    KAUST Repository

    Carbajo, Daniel

    2012-08-02

    BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

  12. A resource for benchmarking the usefulness of protein structure models.

    Science.gov (United States)

    Carbajo, Daniel; Tramontano, Anna

    2012-08-02

    Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by non-academics: No.

  13. A resource for benchmarking the usefulness of protein structure models.

    KAUST Repository

    Carbajo, Daniel; Tramontano, Anna

    2012-01-01

    BACKGROUND: Increasingly, biologists and biochemists use computational tools to design experiments to probe the function of proteins and/or to engineer them for a variety of different purposes. The most effective strategies rely on the knowledge of the three-dimensional structure of the protein of interest. However it is often the case that an experimental structure is not available and that models of different quality are used instead. On the other hand, the relationship between the quality of a model and its appropriate use is not easy to derive in general, and so far it has been analyzed in detail only for specific application. RESULTS: This paper describes a database and related software tools that allow testing of a given structure based method on models of a protein representing different levels of accuracy. The comparison of the results of a computational experiment on the experimental structure and on a set of its decoy models will allow developers and users to assess which is the specific threshold of accuracy required to perform the task effectively. CONCLUSIONS: The ModelDB server automatically builds decoy models of different accuracy for a given protein of known structure and provides a set of useful tools for their analysis. Pre-computed data for a non-redundant set of deposited protein structures are available for analysis and download in the ModelDB database. IMPLEMENTATION, AVAILABILITY AND REQUIREMENTS: Project name: A resource for benchmarking the usefulness of protein structure models. Project home page: http://bl210.caspur.it/MODEL-DB/MODEL-DB_web/MODindex.php.Operating system(s): Platform independent. Programming language: Perl-BioPerl (program); mySQL, Perl DBI and DBD modules (database); php, JavaScript, Jmol scripting (web server). Other requirements: Java Runtime Environment v1.4 or later, Perl, BioPerl, CPAN modules, HHsearch, Modeller, LGA, NCBI Blast package, DSSP, Speedfill (Surfnet) and PSAIA. License: Free. Any restrictions to use by

  14. Designing coarse grained-and atom based-potentials for protein-protein docking

    Directory of Open Access Journals (Sweden)

    Tobi Dror

    2010-11-01

    Full Text Available Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP technique, we developed two types of potentials: (i Side chain-based and (ii Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys, based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked structure, a potential energy lower than those of any of the non-native (misdocked structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. Conclusions Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.

  15. Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles

    Science.gov (United States)

    Eom, Young-Ho; Shepelyansky, Dima L.

    2013-01-01

    How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013 PMID:24098338

  16. Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

    Directory of Open Access Journals (Sweden)

    Young-Ho Eom

    Full Text Available How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013.

  17. SRS: Site ranking system for hazardous chemical and radioactive waste

    International Nuclear Information System (INIS)

    Rechard, R.P.; Chu, M.S.Y.; Brown, S.L.

    1988-05-01

    This report describes the rationale and presents instructions for a site ranking system (SRS). SRS ranks hazardous chemical and radioactive waste sites by scoring important and readily available factors that influence risk to human health. Using SRS, sites can be ranked for purposes of detailed site investigations. SRS evaluates the relative risk as a combination of potentially exposed population, chemical toxicity, and potential exposure of release from a waste site; hence, SRS uses the same concepts found in a detailed assessment of health risk. Basing SRS on the concepts of risk assessment tends to reduce the distortion of results found in other ranking schemes. More importantly, a clear logic helps ensure the successful application of the ranking procedure and increases its versatility when modifications are necessary for unique situations. Although one can rank sites using a detailed risk assessment, it is potentially costly because of data and resources required. SRS is an efficient approach to provide an order-of-magnitude ranking, requiring only readily available data (often only descriptive) and hand calculations. Worksheets are included to make the system easier to understand and use. 88 refs., 19 figs., 58 tabs

  18. Network-based ranking methods for prediction of novel disease associated microRNAs.

    Science.gov (United States)

    Le, Duc-Hau

    2015-10-01

    Many studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a "disease module" principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the "disease module" principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction. We constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm. Analyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In

  19. PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

    Science.gov (United States)

    Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

    2015-06-01

    Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

  20. Taking advantage of local structure descriptors to analyze interresidue contacts in protein structures and protein complexes.

    Science.gov (United States)

    Martin, Juliette; Regad, Leslie; Etchebest, Catherine; Camproux, Anne-Claude

    2008-11-15

    Interresidue protein contacts in proteins structures and at protein-protein interface are classically described by the amino acid types of interacting residues and the local structural context of the contact, if any, is described using secondary structures. In this study, we present an alternate analysis of interresidue contact using local structures defined by the structural alphabet introduced by Camproux et al. This structural alphabet allows to describe a 3D structure as a sequence of prototype fragments called structural letters, of 27 different types. Each residue can then be assigned to a particular local structure, even in loop regions. The analysis of interresidue contacts within protein structures defined using Voronoï tessellations reveals that pairwise contact specificity is greater in terms of structural letters than amino acids. Using a simple heuristic based on specificity score comparison, we find that 74% of the long-range contacts within protein structures are better described using structural letters than amino acid types. The investigation is extended to a set of protein-protein complexes, showing that the similar global rules apply as for intraprotein contacts, with 64% of the interprotein contacts best described by local structures. We then present an evaluation of pairing functions integrating structural letters to decoy scoring and show that some complexes could benefit from the use of structural letter-based pairing functions.

  1. Tensor rank is not multiplicative under the tensor product

    OpenAIRE

    Christandl, Matthias; Jensen, Asger Kjærulff; Zuiddam, Jeroen

    2017-01-01

    The tensor rank of a tensor t is the smallest number r such that t can be decomposed as a sum of r simple tensors. Let s be a k-tensor and let t be an l-tensor. The tensor product of s and t is a (k + l)-tensor. Tensor rank is sub-multiplicative under the tensor product. We revisit the connection between restrictions and degenerations. A result of our study is that tensor rank is not in general multiplicative under the tensor product. This answers a question of Draisma and Saptharishi. Specif...

  2. Consequence ranking of radionuclides in Hanford tank waste

    International Nuclear Information System (INIS)

    Schmittroth, F.A.; De Lorenzo, T.H.

    1995-09-01

    Radionuclides in the Hanford tank waste are ranked relative to their consequences for the Low-Level Tank Waste program. The ranking identifies key radionuclides where further study is merited. In addition to potential consequences for intrude and drinking-water scenarios supporting low-level waste activities, a ranking based on shielding criteria is provided. The radionuclide production inventories are based on a new and independent ORIGEN2 calculation representing the operation of all Hanford single-pass reactors and the N Reactor

  3. Google's pagerank and beyond the science of search engine rankings

    CERN Document Server

    Langville, Amy N

    2006-01-01

    Why doesn't your home page appear on the first page of search results, even when you query your own name? How do other Web pages always appear at the top? What creates these powerful rankings? And how? The first book ever about the science of Web page rankings, Google's PageRank and Beyond supplies the answers to these and other questions and more. The book serves two very different audiences: the curious science reader and the technical computational reader. The chapters build in mathematical sophistication, so that the first five are accessible to the general academic reader. While other cha

  4. Who's #1? The Science of Rating and Ranking

    CERN Document Server

    Langville, Amy N

    2012-01-01

    A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathemat

  5. An Efficient PageRank Approach for Urban Traffic Optimization

    Directory of Open Access Journals (Sweden)

    Florin Pop

    2012-01-01

    to determine optimal decisions for each traffic light, based on the solution given by Larry Page for page ranking in Web environment (Page et al. (1999. Our approach is similar with work presented by Sheng-Chung et al. (2009 and Yousef et al. (2010. We consider that the traffic lights are controlled by servers and a score for each road is computed based on efficient PageRank approach and is used in cost function to determine optimal decisions. We demonstrate that the cumulative contribution of each car in the traffic respects the main constrain of PageRank approach, preserving all the properties of matrix consider in our model.

  6. The THE-QS World University Rankings, 2004 – 2009

    Directory of Open Access Journals (Sweden)

    Richard Holmes

    2010-06-01

    Full Text Available This paper reviews the origin, development and demise of the Times Higher Education Supplement (now Times Higher Education – QS Quacquarelli Symonds (QS World University Rankings between 2004 and 2009. It describes the structure and methodology of the rankings, their public impact and various criticisms that have been made. It also analyses changes that were introduced between 2005 and 2009 and concludes by noting the development of two distinct ranking systems by the magazine Times Higher Education (THE and by its former partner, the consulting company Quacquarelli Symonds.

  7. Reduced rank adaptive filtering in impulsive noise environments

    KAUST Repository

    Soury, Hamza

    2014-11-01

    An impulsive noise environment is considered in this paper. A new aspect of signal truncation is deployed to reduce the harmful effect of the impulsive noise to the signal. A full rank direct solution is derived followed by an iterative solution. The reduced rank adaptive filter is presented in this environment by using two methods for rank reduction, while the minimized objective function is defined using the Lp norm. The results are presented and the efficiency of each method is discussed. © 2014 IEEE.

  8. A cautionary note on the rank product statistic.

    Science.gov (United States)

    Koziol, James A

    2016-06-01

    The rank product method introduced by Breitling R et al. [2004, FEBS Letters 573, 83-92] has rapidly generated popularity in practical settings, in particular, detecting differential expression of genes in microarray experiments. The purpose of this note is to point out a particular property of the rank product method, namely, its differential sensitivity to over- and underexpression. It turns out that overexpression is less likely to be detected than underexpression with the rank product statistic. We have conducted both empirical and exact power studies that demonstrate this phenomenon, and summarize these findings in this note. © 2016 Federation of European Biochemical Societies.

  9. MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

    Science.gov (United States)

    Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

    2012-09-11

    An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

  10. An Adaptive Reordered Method for Computing PageRank

    Directory of Open Access Journals (Sweden)

    Yi-Ming Bu

    2013-01-01

    Full Text Available We propose an adaptive reordered method to deal with the PageRank problem. It has been shown that one can reorder the hyperlink matrix of PageRank problem to calculate a reduced system and get the full PageRank vector through forward substitutions. This method can provide a speedup for calculating the PageRank vector. We observe that in the existing reordered method, the cost of the recursively reordering procedure could offset the computational reduction brought by minimizing the dimension of linear system. With this observation, we introduce an adaptive reordered method to accelerate the total calculation, in which we terminate the reordering procedure appropriately instead of reordering to the end. Numerical experiments show the effectiveness of this adaptive reordered method.

  11. Ranking stability and super-stable nodes in complex networks.

    Science.gov (United States)

    Ghoshal, Gourab; Barabási, Albert-László

    2011-07-19

    Pagerank, a network-based diffusion algorithm, has emerged as the leading method to rank web content, ecological species and even scientists. Despite its wide use, it remains unknown how the structure of the network on which it operates affects its performance. Here we show that for random networks the ranking provided by pagerank is sensitive to perturbations in the network topology, making it unreliable for incomplete or noisy systems. In contrast, in scale-free networks we predict analytically the emergence of super-stable nodes whose ranking is exceptionally stable to perturbations. We calculate the dependence of the number of super-stable nodes on network characteristics and demonstrate their presence in real networks, in agreement with the analytical predictions. These results not only deepen our understanding of the interplay between network topology and dynamical processes but also have implications in all areas where ranking has a role, from science to marketing.

  12. Diffusion of scientific credits and the ranking of scientists

    Science.gov (United States)

    Radicchi, Filippo; Fortunato, Santo; Markines, Benjamin; Vespignani, Alessandro

    2009-11-01

    Recently, the abundance of digital data is enabling the implementation of graph-based ranking algorithms that provide system level analysis for ranking publications and authors. Here, we take advantage of the entire Physical Review publication archive (1893-2006) to construct authors’ networks where weighted edges, as measured from opportunely normalized citation counts, define a proxy for the mechanism of scientific credit transfer. On this network, we define a ranking method based on a diffusion algorithm that mimics the spreading of scientific credits on the network. We compare the results obtained with our algorithm with those obtained by local measures such as the citation count and provide a statistical analysis of the assignment of major career awards in the area of physics. A website where the algorithm is made available to perform customized rank analysis can be found at the address http://www.physauthorsrank.org.

  13. Reduced-Rank Adaptive Filtering Using Krylov Subspace

    Directory of Open Access Journals (Sweden)

    Sergueï Burykh

    2003-01-01

    Full Text Available A unified view of several recently introduced reduced-rank adaptive filters is presented. As all considered methods use Krylov subspace for rank reduction, the approach taken in this work is inspired from Krylov subspace methods for iterative solutions of linear systems. The alternative interpretation so obtained is used to study the properties of each considered technique and to relate one reduced-rank method to another as well as to algorithms used in computational linear algebra. Practical issues are discussed and low-complexity versions are also included in our study. It is believed that the insight developed in this paper can be further used to improve existing reduced-rank methods according to known results in the domain of Krylov subspace methods.

  14. Hearing Office Dispositions Per ALJ Per Day Rate Ranking Report

    Data.gov (United States)

    Social Security Administration — A ranking of ODAR hearing offices by the average number of hearings dispositions per ALJ per day. The average shown will be a combined average for all ALJs working...

  15. Toward optimal feature selection using ranking methods and classification algorithms

    Directory of Open Access Journals (Sweden)

    Novaković Jasmina

    2011-01-01

    Full Text Available We presented a comparison between several feature ranking methods used on two real datasets. We considered six ranking methods that can be divided into two broad categories: statistical and entropy-based. Four supervised learning algorithms are adopted to build models, namely, IB1, Naive Bayes, C4.5 decision tree and the RBF network. We showed that the selection of ranking methods could be important for classification accuracy. In our experiments, ranking methods with different supervised learning algorithms give quite different results for balanced accuracy. Our cases confirm that, in order to be sure that a subset of features giving the highest accuracy has been selected, the use of many different indices is recommended.

  16. Weighted Discriminative Dictionary Learning based on Low-rank Representation

    International Nuclear Information System (INIS)

    Chang, Heyou; Zheng, Hao

    2017-01-01

    Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods. (paper)

  17. Ranking and Mapping the Contributions by Overseas Chinese Strategy Scholars

    DEFF Research Database (Denmark)

    Li, Weiwen; Li, Peter Ping; Shu, Cheng

    2015-01-01

    The authors comment on an article by H. Jiao and colleagues regarding development of a ranking of overseas Chines strategy scholars in terms of their contributions to the strategy research. Topics include selection of 24 business journals ranked by the University of Texas at Dallas for their rese......The authors comment on an article by H. Jiao and colleagues regarding development of a ranking of overseas Chines strategy scholars in terms of their contributions to the strategy research. Topics include selection of 24 business journals ranked by the University of Texas at Dallas...... for their research; identifying authors who had published articles in periodicals such as "Management and Organization Review;" and development of a coding protocol and discussing coding procedure.....

  18. Ranking online quality and reputation via the user activity

    Science.gov (United States)

    Liu, Xiao-Lu; Guo, Qiang; Hou, Lei; Cheng, Can; Liu, Jian-Guo

    2015-10-01

    How to design an accurate algorithm for ranking the object quality and user reputation is of importance for online rating systems. In this paper we present an improved iterative algorithm for online ranking object quality and user reputation in terms of the user degree (IRUA), where the user's reputation is measured by his/her rating vector, the corresponding objects' quality vector and the user degree. The experimental results for the empirical networks show that the AUC values of the IRUA algorithm can reach 0.9065 and 0.8705 in Movielens and Netflix data sets, respectively, which is better than the results generated by the traditional iterative ranking methods. Meanwhile, the results for the synthetic networks indicate that user degree should be considered in real rating systems due to users' rating behaviors. Moreover, we find that enhancing or reducing the influences of the large-degree users could produce more accurate reputation ranking lists.

  19. RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

    Directory of Open Access Journals (Sweden)

    Екатерина Сергеевна Иноземцева

    2013-04-01

    Full Text Available Purpose: a research on different sociological and economic aspects of world education rankings (THE, ARWU, QS, evaluation of their role and impact on the world education market’s main consumers (i.e. students and academic staff as a subject to discussion in terms of the customers’ preferences and choice motivators.  Methodology: general scientific research tools were applied throughout the research: analysis, synthesis, deduction.Results: world ranking approach and methodology was assessed, defined and systemized, a unique general ranking of the countries was developed and performed (based on the researched body – the US ranked #1, Russia #30, expert recommendations for Russian universities have been developed and concluded.Practical implications: the main statements could be used within learning courses on the internationalization of higher education and applied in sociological and economic research dedicated to macroeconomic problems and issues analysis.DOI: http://dx.doi.org/10.12731/2218-7405-2013-2-18

  20. Universality in the tail of musical note rank distribution

    Science.gov (United States)

    Beltrán del Río, M.; Cocho, G.; Naumis, G. G.

    2008-09-01

    Although power laws have been used to fit rank distributions in many different contexts, they usually fail at the tails. Languages as sequences of symbols have been a popular subject for ranking distributions, and for this purpose, music can be treated as such. Here we show that more than 1800 musical compositions are very well fitted by the first kind two parameter beta distribution, which arises in the ranking of multiplicative stochastic processes. The parameters a and b are obtained for classical, jazz and rock music, revealing interesting features. Specially, we have obtained a clear trend in the values of the parameters for major and minor tonal modes. Finally, we discuss the distribution of notes for each octave and its connection with the ranking of the notes.