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Sample records for rank candidate protein-binding

  1. 14 CFR 1214.1104 - Evaluation and ranking of highly qualified candidates.

    Science.gov (United States)

    2010-01-01

    ... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Evaluation and ranking of highly qualified candidates. 1214.1104 Section 1214.1104 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION... ranking of highly qualified candidates. (a) A selection board consisting of discipline experts, and such...

  2. Meaning That Social Studies Teacher Candidates Give to Value Concept and Their Value Rankings

    Science.gov (United States)

    Aysegül, Tural

    2018-01-01

    This work determines the role that value education plays in shaping people's personal and social life. This research aims to put forward meaning that social studies teacher candidates give to value concept and its value ranking. To achieve this aim, the opinions of 12 social studies teacher candidates were obtained. During the data collection…

  3. Competitive protein binding assay

    International Nuclear Information System (INIS)

    Kaneko, Toshio; Oka, Hiroshi

    1975-01-01

    The measurement of cyclic GMP (cGMP) by competitive protein binding assay was described and discussed. The principle of binding assay was represented briefly. Procedures of our method by binding protein consisted of preparation of cGMP binding protein, selection of 3 H-cyclic GMP on market, and measurement procedures. In our method, binding protein was isolated from the chrysalis of silk worm. This method was discussed from the points of incubation medium, specificity of binding protein, the separation of bound cGMP from free cGMP, and treatment of tissue from which cGMP was extracted. cGMP existing in the tissue was only one tenth or one scores of cGMP, and in addition, cGMP competed with cGMP in binding with binding protein. Therefore, Murad's technique was applied to the isolation of cGMP. This method provided the measurement with sufficient accuracy; the contamination by cAMP was within several per cent. (Kanao, N.)

  4. Building blocks for automated elucidation of metabolites: natural product-likeness for candidate ranking.

    Science.gov (United States)

    Jayaseelan, Kalai Vanii; Steinbeck, Christoph

    2014-07-05

    In metabolomics experiments, spectral fingerprints of metabolites with no known structural identity are detected routinely. Computer-assisted structure elucidation (CASE) has been used to determine the structural identities of unknown compounds. It is generally accepted that a single 1D NMR spectrum or mass spectrum is usually not sufficient to establish the identity of a hitherto unknown compound. When a suite of spectra from 1D and 2D NMR experiments supplemented with a molecular formula are available, the successful elucidation of the chemical structure for candidates with up to 30 heavy atoms has been reported previously by one of the authors. In high-throughput metabolomics, usually 1D NMR or mass spectrometry experiments alone are conducted for rapid analysis of samples. This method subsequently requires that the spectral patterns are analyzed automatically to quickly identify known and unknown structures. In this study, we investigated whether additional existing knowledge, such as the fact that the unknown compound is a natural product, can be used to improve the ranking of the correct structure in the result list after the structure elucidation process. To identify unknowns using as little spectroscopic information as possible, we implemented an evolutionary algorithm-based CASE mechanism to elucidate candidates in a fully automated fashion, with input of the molecular formula and 13C NMR spectrum of the isolated compound. We also tested how filters like natural product-likeness, a measure that calculates the similarity of the compounds to known natural product space, might enhance the performance and quality of the structure elucidation. The evolutionary algorithm is implemented within the SENECA package for CASE reported previously, and is available for free download under artistic license at http://sourceforge.net/projects/seneca/. The natural product-likeness calculator is incorporated as a plugin within SENECA and is available as a GUI client and

  5. When is protein binding important?

    Science.gov (United States)

    Heuberger, Jules; Schmidt, Stephan; Derendorf, Hartmut

    2013-09-01

    The present paper is an ode to a classic citation by Benet and Hoener (2002. Clin Pharm Ther 71(3):115-121). The now classic paper had a huge impact on drug development and the way the issue of protein binding is perceived and interpreted. Although the authors very clearly pointed out the limitations and underlying assumptions for their delineations, these are too often overlooked and the classic paper's message is misinterpreted by broadening to cases that were not intended. Some members of the scientific community concluded from the paper that protein binding is not important. This was clearly not intended by the authors, as they finished their paper with a paragraph entitled: "When is protein binding important?" Misinterpretation of the underlying assumptions in the classic work can result in major pitfalls in drug development. Therefore, we revisit the topic of protein binding with the intention of clarifying when clinically relevant changes should be considered during drug development. Copyright © 2013 Wiley Periodicals, Inc.

  6. 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.

  7. Protein binding of psychotropic agents

    International Nuclear Information System (INIS)

    Hassan, H.A.

    1990-01-01

    Based upon fluorescence measurements, protein binding of some psychotropic agents (chlorpromazine, promethazine, and trifluoperazine) to human IgG and HSA was studied in aqueous cacodylate buffer, PH7. The interaction parameters determined from emission quenching of the proteins. The interaction parameters determined include the equilibrium constant (K), calculated from equations derived by Borazan and coworkers, the number of binding sites (n) available to the monomer molecules on a single protein molecule. The results revealed a high level of affinity, as reflected by high values of K, and the existence of specific binding sites, since a limited number of n values are obtained. 39 tabs.; 37 figs.; 83 refs

  8. 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.

  9. Protein Binding Capacity of Different Forages Tannin

    Science.gov (United States)

    Yusiati, L. M.; Kurniawati, A.; Hanim, C.; Anas, M. A.

    2018-02-01

    Eight forages of tannin sources(Leucaena leucocephala, Arachis hypogaea, Mimosa pudica, Morus alba L, Swietenia mahagoni, Manihot esculenta, Gliricidia sepium, and Bauhinia purpurea)were evaluated their tannin content and protein binding capacity. The protein binding capacity of tannin were determined using precipitation of bovine serum albumin (BSA). Swietenia mahagonihas higest total tannin level and condensed tannin (CT) compared with other forages (P<0.01). The Leucaena leucocephala has highest hydrolysable tannin (HT) level (P<0.01). The total and condensed tannin content of Swietenia mahagoni were 11.928±0.04 mg/100 mg and 9.241±0.02mg/100mg dry matter (DM) of leaves. The hydrolysable tannin content of Leucaena leucocephala was 5.338±0.03 mg/100 mg DM of leaves. Binding capacity was highest in Swietenia mahagoni and Leucaena leucocephala compared to the other forages (P<0.01). The optimum binding of BSA to tannin in Leucaena leucocephala and Swietenia mahagoniwere1.181±0.44 and 1.217±0.60mg/mg dry matter of leaves. The present study reports that Swietenia mahagoni has highest of tannin content and Leucaena leucocephala and Swietenia mahagoni capacity of protein binding.

  10. Characterization of plasma protein binding dissociation with online SPE-HPLC

    OpenAIRE

    Li, Ping; Fan, Yiran; Wang, Yunlong; Lu, Yaxin; Yin, Zheng

    2015-01-01

    A novel parameter of relative recovery (Rre) was defined and determined by online SPE-HPLC to characterize plasma protein binding (PPB) kinetics of highly plasma binding drugs. The proportional relationship of Rre with koff of PPB has been established with a new SPE model. A rapid, easy to use method could potentially be used to categorize PK properties of the drug candidates in the decision process of drug discovery and development.

  11. Informing the Human Plasma Protein Binding of ...

    Science.gov (United States)

    The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data is scarce for environmentally relevant chemicals. The presented work explores the merit of utilizing available pharmaceutical data to predict Fub for environmentally relevant chemicals via machine learning techniques. Quantitative structure-activity relationship (QSAR) models were constructed with k nearest neighbors (kNN), support vector machines (SVM), and random forest (RF) machine learning algorithms from a training set of 1045 pharmaceuticals. The models were then evaluated with independent test sets of pharmaceuticals (200 compounds) and environmentally relevant ToxCast chemicals (406 total, in two groups of 238 and 168 compounds). The selection of a minimal feature set of 10-15 2D molecular descriptors allowed for both informative feature interpretation and practical applicability domain assessment via a bounded box of descriptor ranges and principal component analysis. The diverse pharmaceutical and environmental chemical sets exhibit similarities in terms of chemical space (99-82% overlap), as well as comparable bias and variance in constructed learning curves. All the models exhibit significant predictability with mean absolute errors (MAE) in the range of 0.10-0.18 Fub. The models performed best for highly bound chemicals (MAE 0.07-0.12), neutrals (MAE 0

  12. Discrete persistent-chain model for protein binding on DNA.

    Science.gov (United States)

    Lam, Pui-Man; Zhen, Yi

    2011-04-01

    We describe and solve a discrete persistent-chain model of protein binding on DNA, involving an extra σ(i) at a site i of the DNA. This variable takes the value 1 or 0, depending on whether or not the site is occupied by a protein. In addition, if the site is occupied by a protein, there is an extra energy cost ɛ. For a small force, we obtain analytic expressions for the force-extension curve and the fraction of bound protein on the DNA. For higher forces, the model can be solved numerically to obtain force-extension curves and the average fraction of bound proteins as a function of applied force. Our model can be used to analyze experimental force-extension curves of protein binding on DNA, and hence deduce the number of bound proteins in the case of nonspecific binding. ©2011 American Physical Society

  13. Is a gene important for bone resorption a candidate for obesity? An association and linkage study on the RANK (receptor activator of nuclear factor-kappaB) gene in a large Caucasian sample.

    Science.gov (United States)

    Zhao, Lan-Juan; Guo, Yan-Fang; Xiong, Dong-Hai; Xiao, Peng; Recker, Robert R; Deng, Hong-Wen

    2006-11-01

    In light of findings that osteoporosis and obesity may share some common genetic determination and previous reports that RANK (receptor activator of nuclear factor-kappaB) is expressed in skeletal muscles which are important for energy metabolism, we hypothesize that RANK, a gene essential for osteoclastogenesis, is also important for obesity. In order to test the hypothesis with solid data we first performed a linkage analysis around the RANK gene in 4,102 Caucasian subjects from 434 pedigrees, then we genotyped 19 SNPs in or around the RANK gene. A family-based association test (FBAT) was performed with both a quantitative measure of obesity [fat mass, lean mass, body mass index (BMI), and percentage fat mass (PFM)] and a dichotomously defined obesity phenotype-OB (OB if BMI > or = 30 kg/m(2)). In the linkage analysis, an empirical P = 0.004 was achieved at the location of the RANK gene for BMI. Family-based association analysis revealed significant associations of eight SNPs with at least one obesity-related phenotype (P obesity phenotype. The P value is 0.126 for OB, 0.033 for fat mass, 0.021 for lean mass, 0.016 for BMI, and 0.006 for PFM. The haplotype data analyses provide further association evidence. In conclusion, for the first time, our results suggest that RANK is a novel candidate for determination of obesity.

  14. SCOWLP classification: Structural comparison and analysis of protein binding regions

    Directory of Open Access Journals (Sweden)

    Anders Gerd

    2008-01-01

    Full Text Available Abstract Background Detailed information about protein interactions is critical for our understanding of the principles governing protein recognition mechanisms. The structures of many proteins have been experimentally determined in complex with different ligands bound either in the same or different binding regions. Thus, the structural interactome requires the development of tools to classify protein binding regions. A proper classification may provide a general view of the regions that a protein uses to bind others and also facilitate a detailed comparative analysis of the interacting information for specific protein binding regions at atomic level. Such classification might be of potential use for deciphering protein interaction networks, understanding protein function, rational engineering and design. Description Protein binding regions (PBRs might be ideally described as well-defined separated regions that share no interacting residues one another. However, PBRs are often irregular, discontinuous and can share a wide range of interacting residues among them. The criteria to define an individual binding region can be often arbitrary and may differ from other binding regions within a protein family. Therefore, the rational behind protein interface classification should aim to fulfil the requirements of the analysis to be performed. We extract detailed interaction information of protein domains, peptides and interfacial solvent from the SCOWLP database and we classify the PBRs of each domain family. For this purpose, we define a similarity index based on the overlapping of interacting residues mapped in pair-wise structural alignments. We perform our classification with agglomerative hierarchical clustering using the complete-linkage method. Our classification is calculated at different similarity cut-offs to allow flexibility in the analysis of PBRs, feature especially interesting for those protein families with conflictive binding regions

  15. Multiple protonation equilibria in electrostatics of protein-protein binding.

    Science.gov (United States)

    Piłat, Zofia; Antosiewicz, Jan M

    2008-11-27

    All proteins contain groups capable of exchanging protons with their environment. We present here an approach, based on a rigorous thermodynamic cycle and the partition functions for energy levels characterizing protonation states of the associating proteins and their complex, to compute the electrostatic pH-dependent contribution to the free energy of protein-protein binding. The computed electrostatic binding free energies include the pH of the solution as the variable of state, mutual "polarization" of associating proteins reflected as changes in the distribution of their protonation states upon binding and fluctuations between available protonation states. The only fixed property of both proteins is the conformation; the structure of the monomers is kept in the same conformation as they have in the complex structure. As a reference, we use the electrostatic binding free energies obtained from the traditional Poisson-Boltzmann model, computed for a single macromolecular conformation fixed in a given protonation state, appropriate for given solution conditions. The new approach was tested for 12 protein-protein complexes. It is shown that explicit inclusion of protonation degrees of freedom might lead to a substantially different estimation of the electrostatic contribution to the binding free energy than that based on the traditional Poisson-Boltzmann model. This has important implications for the balancing of different contributions to the energetics of protein-protein binding and other related problems, for example, the choice of protein models for Brownian dynamics simulations of their association. Our procedure can be generalized to include conformational degrees of freedom by combining it with molecular dynamics simulations at constant pH. Unfortunately, in practice, a prohibitive factor is an enormous requirement for computer time and power. However, there may be some hope for solving this problem by combining existing constant pH molecular dynamics

  16. Differential plasma protein binding to metal oxide nanoparticles

    International Nuclear Information System (INIS)

    Deng, Zhou J; Mortimer, Gysell; Minchin, Rodney F; Schiller, Tara; Musumeci, Anthony; Martin, Darren

    2009-01-01

    Nanoparticles rapidly interact with the proteins present in biological fluids, such as blood. The proteins that are adsorbed onto the surface potentially dictate the biokinetics of the nanomaterials and their fate in vivo. Using nanoparticles with different sizes and surface characteristics, studies have reported the effects of physicochemical properties on the composition of adsorbed plasma proteins. However, to date, few studies have been conducted focusing on the nanoparticles that are commonly exposed to the general public, such as the metal oxides. Using previously established ultracentrifugation approaches, two-dimensional gel electrophoresis and mass spectrometry, the current study investigated the binding of human plasma proteins to commercially available titanium dioxide, silicon dioxide and zinc oxide nanoparticles. We found that, despite these particles having similar surface charges in buffer, they bound different plasma proteins. For TiO 2 , the shape of the nanoparticles was also an important determinant of protein binding. Agglomeration in water was observed for all of the nanoparticles and both TiO 2 and ZnO further agglomerated in biological media. This led to an increase in the amount and number of different proteins bound to these nanoparticles. Proteins with important biological functions were identified, including immunoglobulins, lipoproteins, acute-phase proteins and proteins involved in complement pathways and coagulation. These results provide important insights into which human plasma proteins bind to particular metal oxide nanoparticles. Because protein absorption to nanoparticles may determine their interaction with cells and tissues in vivo, understanding how and why plasma proteins are adsorbed to these particles may be important for understanding their biological responses.

  17. Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2018-01-01

    Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  18. 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

  19. The BRCT domain is a phospho-protein binding domain.

    Science.gov (United States)

    Yu, Xiaochun; Chini, Claudia Christiano Silva; He, Miao; Mer, Georges; Chen, Junjie

    2003-10-24

    The carboxyl-terminal domain (BRCT) of the Breast Cancer Gene 1 (BRCA1) protein is an evolutionarily conserved module that exists in a large number of proteins from prokaryotes to eukaryotes. Although most BRCT domain-containing proteins participate in DNA-damage checkpoint or DNA-repair pathways, or both, the function of the BRCT domain is not fully understood. We show that the BRCA1 BRCT domain directly interacts with phosphorylated BRCA1-Associated Carboxyl-terminal Helicase (BACH1). This specific interaction between BRCA1 and phosphorylated BACH1 is cell cycle regulated and is required for DNA damage-induced checkpoint control during the transition from G2 to M phase of the cell cycle. Further, we show that two other BRCT domains interact with their respective physiological partners in a phosphorylation-dependent manner. Thirteen additional BRCT domains also preferentially bind phospho-peptides rather than nonphosphorylated control peptides. These data imply that the BRCT domain is a phospho-protein binding domain involved in cell cycle control.

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

    Science.gov (United States)

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

    2016-01-01

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

  1. Interspecies In Vitro Evaluation of Stereoselective Protein Binding for 3,4-Methylenedioxymethamphetamine

    Directory of Open Access Journals (Sweden)

    Wan Raihana Wan Aasim

    2017-01-01

    Full Text Available Abuse of 3,4-methylenedioxymethamphetamine (MDMA is becoming more common worldwide. To date, there is no information available on stereoselectivity of MDMA protein binding in humans, rats, and mice. Since stereoselectivity plays an important role in MDMA’s pharmacokinetics and pharmacodynamics, in this study we investigated its stereoselectivity in protein binding. The stereoselective protein binding of rac-MDMA was investigated using two different concentrations (20 and 200 ng/mL in human plasma and mouse and rat sera using an ultrafiltration technique. No significant stereoselectivity in protein binding was observed in both human plasma and rat serum; however, a significant stereoselective binding (p<0.05 was observed in mouse serum. Since the protein binding of MDMA in mouse serum is considerably lower than in humans and rats, caution should be exercised when using mice for in vitro studies involving MDMA.

  2. Competitive protein binding analysis for thyroxine using Sephadex column (Tetralute)

    International Nuclear Information System (INIS)

    Miyai, Kiyoshi; Katayama, Yoshiaki; Sawazaki, Norio; Ishibashi, Kaichiro; Kawashima, Minoru.

    1975-01-01

    The method of competitive protein binding analysis of thyroxine (T 4 ) using Tetralute kit was evaluated. The net retention was decreased when the procedure of competition and separation was performed at a higher temperature but the final T 4 -I values were constant when the standard and test sera were treated identically. Coefficient of variation (C.V.) was 4% (within-assay) and 6% (between-assay) respectively. However, the T 4 -I values of pooled serum for quality control were slightly lower in earlier experiments in which correction factors (1.03--1.62 in 18 out of 21 assays) were necessary. T 4 -I values were determined by the Tetralute in 155 cases. They were as follows: 4.9+-0.8 μg/dl (euthyroid subjects), 6.4+-1.2 μg/dl (cord serum), 7.1+-1.1 μg/dl (pregnant women). 9.0+-3.6 μg/dl (trophoblastic disease), 13.3+-4.8 μg/dl (Graves' disease), 6.3+-1.6 μg/dl (Plummer's disease), 4 -I values determined by Tetralute and Res-O-Mat T 4 (r=0.96). Following oral administration of Telepaque the serum protein-bound iodine was markedly elevated, while the T 4 -I determined by Tetralute did not change. In vitro addition of diphenylhydantoin (500 μg/ml), salicylate (4 mg/ml) and phenobarbital (1 mg/ml) had no or little effect on T 4 determination by Tetralute. A high concentration of benzbromarone (0.1 mg/ml) caused a higher value of T 4 -I determined by Tetralute when added to a TBG solution but there was only a slight increase when it was added to serum. (auth.)

  3. ANALYSIS OF DRUG-PROTEIN BINDING BY ULTRAFAST AFFINITY CHROMATOGRAPHY USING IMMOBILIZED HUMAN SERUM ALBUMIN

    Science.gov (United States)

    Mallik, Rangan; Yoo, Michelle J.; Briscoe, Chad J.; Hage, David S.

    2010-01-01

    Human serum albumin (HSA) was explored for use as a stationary phase and ligand in affinity microcolumns for the ultrafast extraction of free drug fractions and the use of this information for the analysis of drug-protein binding. Warfarin, imipramine, and ibuprofen were used as model analytes in this study. It was found that greater than 95% extraction of all these drugs could be achieved in as little as 250 ms on HSA microcolumns. The retained drug fraction was then eluted from the same column under isocratic conditions, giving elution in less than 40 s when working at 4.5 mL/min. The chromatographic behavior of this system gave a good fit with that predicted by computer simulations based on a reversible, saturable model for the binding of an injected drug with immobilized HSA. The free fractions measured by this method were found to be comparable to those determined by ultrafiltration, and equilibrium constants estimated by this approach gave good agreement with literature values. Advantages of this method include its speed and the relatively low cost of microcolumns that contain HSA. The ability of HSA to bind many types of drugs also creates the possibility of using the same affinity microcolumn to study and measure the free fractions for a variety of pharmaceutical agents. These properties make this technique appealing for use in drug binding studies and in the high-throughput screening of new drug candidates. PMID:20227701

  4. The Leptospiral Antigen Lp49 is a Two-Domain Protein with Putative Protein Binding Function

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira Giuseppe,P.; Oliveira Neves, F.; Nascimento, A.; Gomes Guimaraes, B.

    2008-01-01

    Pathogenic Leptospira is the etiological agent of leptospirosis, a life-threatening disease that affects populations worldwide. Currently available vaccines have limited effectiveness and therapeutic interventions are complicated by the difficulty in making an early diagnosis of leptospirosis. The genome of Leptospira interrogans was recently sequenced and comparative genomic analysis contributed to the identification of surface antigens, potential candidates for development of new vaccines and serodiagnosis. Lp49 is a membrane-associated protein recognized by antibodies present in sera from early and convalescent phases of leptospirosis patients. Its crystal structure was determined by single-wavelength anomalous diffraction using selenomethionine-labelled crystals and refined at 2.0 Angstroms resolution. Lp49 is composed of two domains and belongs to the all-beta-proteins class. The N-terminal domain folds in an immunoglobulin-like beta-sandwich structure, whereas the C-terminal domain presents a seven-bladed beta-propeller fold. Structural analysis of Lp49 indicates putative protein-protein binding sites, suggesting a role in Leptospira-host interaction. This is the first crystal structure of a leptospiral antigen described to date.

  5. [Determination of plasma protein binding rate of arctiin and arctigenin with ultrafiltration].

    Science.gov (United States)

    Han, Xue-Ying; Wang, Wei; Tan, Ri-Qiu; Dou, De-Qiang

    2013-02-01

    To determine the plasma protein binding rate of arctiin and arctigenin. The ultrafiltration combined with HPLC was employed to determine the plasma protein binding rate of arctiin and arctigenin as well as rat plasma and healthy human plasma proteins. The plasma protein binding rate of arctiin with rat plasma at the concentrations of 64. 29, 32.14, 16.07 mg x L(-1) were (71.2 +/- 2.0)%, (73.4 +/- 0.61)%, (78.2 +/- 1.9)%, respectively; while the plasma protein binding rate of arctiin with healthy human plasma at the above concentrations were (64.8 +/- 3.1)%, (64.5 +/- 2.5)%, (77.5 +/- 1.7)%, respectively. The plasma protein binding rate of arctigenin with rat plasma at the concentrations of 77.42, 38.71, 19.36 mg x L(-1) were (96.7 +/- 0.41)%, (96.8 +/- 1.6)%, (97.3 +/- 0.46)%, respectively; while the plasma protein binding rate of arctigenin with normal human plasma at the above concentrations were (94.7 +/- 3.1)%, (96.8 +/- 1.6)%, (97.9 +/- 1.3)%, respectively. The binding rate of arctiin with rat plasma protein was moderate, which is slightly higher than the binding rate of arctiin with healthy human plasma protein. The plasma protein binding rates of arctigenin with both rat plasma and healthy human plasma are very high.

  6. Porcine circovirus type 2 ORF4 protein binds heavy chain ferritin

    Indian Academy of Sciences (India)

    Porcine circovirus type 2 ORF4 protein binds heavy chain ferritin. Qizhuang Lv Kangkang Guo Tao Wang ... Keywords. Cellular protein; FHC; ORF4 protein; porcine circovirus type 2 (PCV2); yeast two-hybrid ... Journal of Biosciences | News ...

  7. Standardization for cortisol determination in human blood by competitive protein-binding

    International Nuclear Information System (INIS)

    Okada, H.

    1978-01-01

    Standardization for determination of cortisol from human plasma (17-hydroxycorticosteroids) using competitive protein-binding method is presented. Activated carbon coated with dextrans is used for separation of the hormone-protein complexe and hormone labelled free [pt

  8. Preparation and characterization of magnetic polymer nanospheres with high protein binding capacity

    International Nuclear Information System (INIS)

    Liu Xianqiao; Guan Yueping; Liu Huizhou; Ma Zhiya; Yang Yu; Wu Xiaobing

    2005-01-01

    A novel magnetic support with high protein binding capacity was prepared by mini-emulsion polymerization. The magnetic poly(methacrylate-divinylbenzene) nanospheres prepared are 390 nm in diameter with narrow size distribution and star-like external morphology which leads to a large increase in specific surface area. Experimental results indicate that the maximum protein binding capacity is 316 mg bovine hemoglobin (BHb)/g support

  9. CORRELATION BETWEEN ANGIOTENSIN-CONVERTING ENZYME INHIBITORS LIPOPHILICITY AND PROTEIN BINDING DATA

    Directory of Open Access Journals (Sweden)

    Jasna Trbojević-Stanković

    2012-01-01

    Full Text Available Angiotensin-converting enzyme (ACE inhibitors represent a significant group of drugs primarily used in the treatment of hypertension and congestive heart failure. In this research, seven ACE inhibitors (enalapril, quinapril, fosinopril, lisinopril, cilazapril, ramipril, benazepril were studied to evaluate the relationship between their protein binding and calculated (logP values or ultra-high performance liquid chromatographytandem mass spectrometry (UHPLC-MS and reversed-phase thin-layer chromatography (RP-TLC lipophilicity data (ϕ0, CHI or C0 parameters, respectively. Their protein binding data varied from negligible (lisinopril to 99% (fosinopril, while calculated logPKOWWINvalues ranged from -0.94 (lisinopril to 6.61 (fosinopril. The good correlations were established between protein binding values and logPKOWWIN data (R2=0.7520 as well as between protein binding and chromatographic hydrophobicity data, ϕ0, CHI or C0parameters (R2 were 0.6160, 0.6242 and 0.6547, respectively. The possible application of hydrophobicity data in drugs protein binding evaluation can be of great importance in drug bioavailability.

  10. Dynamic SPR monitoring of yeast nuclear protein binding to a cis-regulatory element

    International Nuclear Information System (INIS)

    Mao, Grace; Brody, James P.

    2007-01-01

    Gene expression is controlled by protein complexes binding to short specific sequences of DNA, called cis-regulatory elements. Expression of most eukaryotic genes is controlled by dozens of these elements. Comprehensive identification and monitoring of these elements is a major goal of genomics. In pursuit of this goal, we are developing a surface plasmon resonance (SPR) based assay to identify and monitor cis-regulatory elements. To test whether we could reliably monitor protein binding to a regulatory element, we immobilized a 16 bp region of Saccharomyces cerevisiae chromosome 5 onto a gold surface. This 16 bp region of DNA is known to bind several proteins and thought to control expression of the gene RNR1, which varies through the cell cycle. We synchronized yeast cell cultures, and then sampled these cultures at a regular interval. These samples were processed to purify nuclear lysate, which was then exposed to the sensor. We found that nuclear protein binds this particular element of DNA at a significantly higher rate (as compared to unsynchronized cells) during G1 phase. Other time points show levels of DNA-nuclear protein binding similar to the unsynchronized control. We also measured the apparent association complex of the binding to be 0.014 s -1 . We conclude that (1) SPR-based assays can monitor DNA-nuclear protein binding and that (2) for this particular cis-regulatory element, maximum DNA-nuclear protein binding occurs during G1 phase

  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 Low Protein Binding Cationic Poly(2-oxazoline) as Non-Viral Vector

    KAUST Repository

    He, Zhijian; Miao, Lei; Jordan, Rainer; S-Manickam, Devika; Luxenhofer, Robert; Kabanov, Alexander V.

    2015-01-01

    (diameter ≈80 nm) and narrowly dispersed polyplexes (PDI <0.2), which are stable upon dilution in saline and against thermal challenge. These polyplexes exhibited low plasma protein binding and very low cytotoxicity in vitro compared to the polyplexes of p

  13. Assessment of algorithms for inferring positional weight matrix motifs of transcription factor binding sites using protein binding microarray data.

    Directory of Open Access Journals (Sweden)

    Yaron Orenstein

    Full Text Available The new technology of protein binding microarrays (PBMs allows simultaneous measurement of the binding intensities of a transcription factor to tens of thousands of synthetic double-stranded DNA probes, covering all possible 10-mers. A key computational challenge is inferring the binding motif from these data. We present a systematic comparison of four methods developed specifically for reconstructing a binding site motif represented as a positional weight matrix from PBM data. The reconstructed motifs were evaluated in terms of three criteria: concordance with reference motifs from the literature and ability to predict in vivo and in vitro bindings. The evaluation encompassed over 200 transcription factors and some 300 assays. The results show a tradeoff between how the methods perform according to the different criteria, and a dichotomy of method types. Algorithms that construct motifs with low information content predict PBM probe ranking more faithfully, while methods that produce highly informative motifs match reference motifs better. Interestingly, in predicting high-affinity binding, all methods give far poorer results for in vivo assays compared to in vitro assays.

  14. Thermodynamic Characterization of Hydration Sites from Integral Equation-Derived Free Energy Densities: Application to Protein Binding Sites and Ligand Series.

    Science.gov (United States)

    Güssregen, Stefan; Matter, Hans; Hessler, Gerhard; Lionta, Evanthia; Heil, Jochen; Kast, Stefan M

    2017-07-24

    Water molecules play an essential role for mediating interactions between ligands and protein binding sites. Displacement of specific water molecules can favorably modulate the free energy of binding of protein-ligand complexes. Here, the nature of water interactions in protein binding sites is investigated by 3D RISM (three-dimensional reference interaction site model) integral equation theory to understand and exploit local thermodynamic features of water molecules by ranking their possible displacement in structure-based design. Unlike molecular dynamics-based approaches, 3D RISM theory allows for fast and noise-free calculations using the same detailed level of solute-solvent interaction description. Here we correlate molecular water entities instead of mere site density maxima with local contributions to the solvation free energy using novel algorithms. Distinct water molecules and hydration sites are investigated in multiple protein-ligand X-ray structures, namely streptavidin, factor Xa, and factor VIIa, based on 3D RISM-derived free energy density fields. Our approach allows the semiquantitative assessment of whether a given structural water molecule can potentially be targeted for replacement in structure-based design. Finally, PLS-based regression models from free energy density fields used within a 3D-QSAR approach (CARMa - comparative analysis of 3D RISM Maps) are shown to be able to extract relevant information for the interpretation of structure-activity relationship (SAR) trends, as demonstrated for a series of serine protease inhibitors.

  15. Predicting protein-binding RNA nucleotides with consideration of binding partners.

    Science.gov (United States)

    Tuvshinjargal, Narankhuu; Lee, Wook; Park, Byungkyu; Han, Kyungsook

    2015-06-01

    In recent years several computational methods have been developed to predict RNA-binding sites in protein. Most of these methods do not consider interacting partners of a protein, so they predict the same RNA-binding sites for a given protein sequence even if the protein binds to different RNAs. Unlike the problem of predicting RNA-binding sites in protein, the problem of predicting protein-binding sites in RNA has received little attention mainly because it is much more difficult and shows a lower accuracy on average. In our previous study, we developed a method that predicts protein-binding nucleotides from an RNA sequence. In an effort to improve the prediction accuracy and usefulness of the previous method, we developed a new method that uses both RNA and protein sequence data. In this study, we identified effective features of RNA and protein molecules and developed a new support vector machine (SVM) model to predict protein-binding nucleotides from RNA and protein sequence data. The new model that used both protein and RNA sequence data achieved a sensitivity of 86.5%, a specificity of 86.2%, a positive predictive value (PPV) of 72.6%, a negative predictive value (NPV) of 93.8% and Matthews correlation coefficient (MCC) of 0.69 in a 10-fold cross validation; it achieved a sensitivity of 58.8%, a specificity of 87.4%, a PPV of 65.1%, a NPV of 84.2% and MCC of 0.48 in independent testing. For comparative purpose, we built another prediction model that used RNA sequence data alone and ran it on the same dataset. In a 10 fold-cross validation it achieved a sensitivity of 85.7%, a specificity of 80.5%, a PPV of 67.7%, a NPV of 92.2% and MCC of 0.63; in independent testing it achieved a sensitivity of 67.7%, a specificity of 78.8%, a PPV of 57.6%, a NPV of 85.2% and MCC of 0.45. In both cross-validations and independent testing, the new model that used both RNA and protein sequences showed a better performance than the model that used RNA sequence data alone in

  16. Effect of benzimidazol-derivatives on the DNA-protein binding formation after UV-radiation of chromatin

    International Nuclear Information System (INIS)

    Mil', E.M.; Binyukov, V.I.; Zhil'tsova, V.M.; Stolyarova, L.G.; Kuznetsov, Yu.V.

    1991-01-01

    Effect of benzimidazol-derivatives on the DNA-protein binding formation was studied after UV-radiation of chromatin. These derivatives were shown to protect chromatin from UV-induced DNA-protein binding formation. Structural analog contained two aminomethyl residuals sensibilized additional binding formation in chromatin. Results suggested, that benzimidazol interacted with DNA, while aminomethyl groups interacted with protein and sensibilized binding of DNA, whilt aminomethyl groups interacted with protein and sensibilized binding of DNA with histone H1

  17. 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

  18. Does protein binding modulate the effect of angiotensin II receptor antagonists?

    Directory of Open Access Journals (Sweden)

    Marc P Maillard

    2001-03-01

    Full Text Available IntroductionAngiotensin II AT 1-receptor antagonists are highly bound to plasma proteins (≥ 99%. With some antagonists, such as DuP-532, the protein binding was such that no efficacy of the drug could be demonstrated clinically. Whether protein binding interferes with the efficacy of other antagonists is not known. We have therefore investigated in vitro how plasma proteins may affect the antagonistic effect of different AT1-receptor antagonists.MethodsA radio-receptor binding assay was used to analyse the interaction between proteins and the ability of various angiotensin II (Ang II antagonists to block AT1-receptors. In addition, the Biacore technology, a new technique which enables the real-time monitoring of binding events between two molecules, was used to evaluate the dissociation rate constants of five AT1-receptor antagonists from human serum albumin.ResultsThe in vitro AT 1-antagonistic effects of different Ang II receptor antagonists were differentially affected by the presence of human plasma, with rightward shifts of the IC50 ranging from one to several orders of magnitude. The importance of the shift correlates with the dissociation rate constants of these drugs from albumin. Our experiments also show that the way that AT1-receptor antagonists bind to proteins differs from one compound to another. These results suggest that the interaction with plasma proteins appears to modulate the efficacy of some Ang II antagonists.ConclusionAlthough the high binding level of Ang II receptor antagonist to plasma proteins appears to be a feature common to this class of compounds, the kinetics and characteristics of this binding is of great importance. With some antagonists, protein binding interferes markedly with their efficacy to block AT1-receptors.

  19. Effects of protein binding on the biodistribution of PEGylated PLGA nanoparticles post oral administration

    CSIR Research Space (South Africa)

    Semete, B

    2012-03-01

    Full Text Available of 1% w/v of the polyvinyl alcohol80 (PVA, Mw: 13,000?23,000 partially hydrolysed (87?89%)), 0.3%81 weight/volume (w/v) of chitosan and 5% (w/v) lactose to stabilise82 the emulsion. The mixture was further emulsified for 5 min by83 homogenisation... potential as indicated in Table 1 was not significantly 149 affected by the presence or absence of poloxamer coating. Lactose 150 was included in the formulation as drying aid agent together with 151 Table 2 Protein binding values of various nanoparticle...

  20. Fragment-based quantum mechanical calculation of protein-protein binding affinities.

    Science.gov (United States)

    Wang, Yaqian; Liu, Jinfeng; Li, Jinjin; He, Xiao

    2018-04-29

    The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

  1. Effect of protein binding on unbound atazanavir and darunavir cerebrospinal fluid concentrations.

    Science.gov (United States)

    Delille, Cecile A; Pruett, Sarah T; Marconi, Vincent C; Lennox, Jeffrey L; Armstrong, Wendy S; Arrendale, Richard F; Sheth, Anandi N; Easley, Kirk A; Acosta, Edward P; Vunnava, Aswani; Ofotokun, Ighovwerha

    2014-09-01

    HIV-1 protease inhibitors (PIs) exhibit different protein binding affinities and achieve variable plasma and tissue concentrations. Degree of plasma protein binding may impact central nervous system penetration. This cross-sectional study assessed cerebrospinal fluid (CSF) unbound PI concentrations, HIV-1 RNA, and neopterin levels in subjects receiving either ritonavir-boosted darunavir (DRV), 95% plasma protein bound, or atazanavir (ATV), 86% bound. Unbound PI trough concentrations were measured using rapid equilibrium dialysis and liquid chromatography/tandem mass spectrometry. Plasma and CSF HIV-1 RNA and neopterin were measured by Ampliprep/COBAS® Taqman® 2.0 assay (Roche) and enzyme-linked immunosorbent assay (ALPCO), respectively. CSF/plasma unbound drug concentration ratio was higher for ATV, 0.09 [95% confidence interval (CI) 0.06-0.12] than DRV, 0.04 (95%CI 0.03-0.06). Unbound CSF concentrations were lower than protein adjusted wild-type inhibitory concentration-50 (IC50 ) in all ATV and 1 DRV-treated subjects (P < 0.001). CSF HIV-1 RNA was detected in 2/15 ATV and 4/15 DRV subjects (P = 0.65). CSF neopterin levels were low and similar between arms. ATV relative to DRV had higher CSF/plasma unbound drug ratio. Low CSF HIV-1 RNA and neopterin suggest that both regimens resulted in CSF virologic suppression and controlled inflammation. © 2014, The American College of Clinical Pharmacology.

  2. 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...

  3. 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).

  4. Pharmacokinetics of warfarin in rats: role of serum protein binding and tissue distribution

    International Nuclear Information System (INIS)

    Cheung, W.K.

    1985-01-01

    The purpose of this study was to explore the role of serum protein binding and tissue distribution in the non-linear pharmacokinetics of warfarin in rats. The first phase of the research was an attempt to elucidate the causes of intersubject differences in serum protein binding of warfarin in rats. It was found that the distribution of S-warfarin between blood and liver, kidneys, muscle, or fatty tissue was non-linear. Based on the tissue distribution data obtained, a physiologically-based pharmacokinetic model was developed to describe the time course of S-warfarin concentrations in the serum and tissues of rats. The proposed model was able to display the dose-dependent pharmacokinetics of warfarin in rats. Namely a lower clearance and a smaller apparent volume of distribution with increasing dose, which appear to be due to the presence of capacity-limited, high-affinity binding sites for warfarin in various tissues. To determine if the binding of warfarin to the high-affinity binding sites in the liver of rats is reversible, concentrations of S-warfarin in the liver and serum of rats were monitored for a very long time after an intravenous injection of a 1 mg/kg dose. In another study in rats, non-radioactive warfarin was found to be able to displace tissue-bound C 14 -warfarin which was administered about 200 hours before the i.v. injection of the non-radioactive warfarin, showing that the binding of warfarin to the high-affinity binding sites in the body is persistent and reversible

  5. A Low Protein Binding Cationic Poly(2-oxazoline) as Non-Viral Vector

    KAUST Repository

    He, Zhijian

    2015-04-02

    © 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim. Developing safe and efficient non-viral gene delivery systems remains a major challenge. We present a new cationic poly(2-oxazoline) (CPOx) block copolymer for gene therapy that was synthesized by sequential polymerization of non-ionic 2-methyl-2-oxazoline and a new 2-oxazoline monomer, 2-(N-methyl, N-Boc-amino)-methyl-2-oxazoline, followed by deprotection of the pendant secondary amine groups. Upon mixing with plasmid DNA (pDNA), CPOx forms small (diameter ≈80 nm) and narrowly dispersed polyplexes (PDI <0.2), which are stable upon dilution in saline and against thermal challenge. These polyplexes exhibited low plasma protein binding and very low cytotoxicity in vitro compared to the polyplexes of pDNA and poly(ethylene glycol)-b-poly(L-lysine) (PEG-b-PLL). CPOx/pDNA polyplexes at N/P = 5 bound considerably less plasma protein compared to polyplexes of PEG-b-PLL at the same N/P ratio. This is a unique aspect of the developed polyplexes emphasizing their potential for systemic delivery in vivo. The transfection efficiency of the polyplexes in B16 murine melanoma cells was low after 4 h, but increased significantly for 10 h exposure time, indicative of slow internalization of polyplexes. Addition of Pluronic P85 boosted the transfection using CPOx/pDNA polyplexes considerably. The low protein binding of CPOx/pDNA polyplexes is particularly interesting for the future development of targeted gene delivery.

  6. 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

  7. 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.

  8. Sequence-based prediction of protein-binding sites in DNA: comparative study of two SVM models.

    Science.gov (United States)

    Park, Byungkyu; Im, Jinyong; Tuvshinjargal, Narankhuu; Lee, Wook; Han, Kyungsook

    2014-11-01

    As many structures of protein-DNA complexes have been known in the past years, several computational methods have been developed to predict DNA-binding sites in proteins. However, its inverse problem (i.e., predicting protein-binding sites in DNA) has received much less attention. One of the reasons is that the differences between the interaction propensities of nucleotides are much smaller than those between amino acids. Another reason is that DNA exhibits less diverse sequence patterns than protein. Therefore, predicting protein-binding DNA nucleotides is much harder than predicting DNA-binding amino acids. We computed the interaction propensity (IP) of nucleotide triplets with amino acids using an extensive dataset of protein-DNA complexes, and developed two support vector machine (SVM) models that predict protein-binding nucleotides from sequence data alone. One SVM model predicts protein-binding nucleotides using DNA sequence data alone, and the other SVM model predicts protein-binding nucleotides using both DNA and protein sequences. In a 10-fold cross-validation with 1519 DNA sequences, the SVM model that uses DNA sequence data only predicted protein-binding nucleotides with an accuracy of 67.0%, an F-measure of 67.1%, and a Matthews correlation coefficient (MCC) of 0.340. With an independent dataset of 181 DNAs that were not used in training, it achieved an accuracy of 66.2%, an F-measure 66.3% and a MCC of 0.324. Another SVM model that uses both DNA and protein sequences achieved an accuracy of 69.6%, an F-measure of 69.6%, and a MCC of 0.383 in a 10-fold cross-validation with 1519 DNA sequences and 859 protein sequences. With an independent dataset of 181 DNAs and 143 proteins, it showed an accuracy of 67.3%, an F-measure of 66.5% and a MCC of 0.329. Both in cross-validation and independent testing, the second SVM model that used both DNA and protein sequence data showed better performance than the first model that used DNA sequence data. To the best of

  9. Learning a peptide-protein binding affinity predictor with kernel ridge regression

    Science.gov (United States)

    2013-01-01

    peptide-protein binding affinities. The proposed approach is flexible and can be applied to predict any quantitative biological activity. Moreover, generating reliable peptide-protein binding affinities will also improve system biology modelling of interaction pathways. Lastly, the method should be of value to a large segment of the research community with the potential to accelerate the discovery of peptide-based drugs and facilitate vaccine development. The proposed kernel is freely available at http://graal.ift.ulaval.ca/downloads/gs-kernel/. PMID:23497081

  10. Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

    KAUST Repository

    Wong, Ka-Chun; Peng, Chengbin; Li, Yue

    2016-01-01

    Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

  11. Protein binding of glufosinate and factors affecting it revealed by an equilibrium dialysis technique.

    Science.gov (United States)

    Hori, Y; Koyama, K; Fujisawa, M; Nakajima, M; Shimada, K; Hirose, Y; Kohda, Y; Akuzawa, H

    2001-09-01

    We investigated the protein binding of glufosinate ammonium (GLF) and several factors affecting this binding using human serum albumin (HSA) and human volunteer serum under various conditions. The mean ratios of the free GLF (RFr-GLF) to 4% HSA were examined in the sera of patients described elsewhere at GLF levels from 1 microg/mL to 500 microg/mL; the range was found to be only from 0.80 to 0.88. Neither the incubation temperature nor buffers containing different chloride ion concentrations had any effect on the RFr-GLF to HSA. Moreover, the addition of heparin, glycoprotein-alpha1-acid (AAG), and sodium azide had no effect on the RFr-GLF. However, pH of the isotonic phosphate buffer and the addition of palmitic or oleic acid were seen to have an effect. In this study, the mean RFr-GLF to healthy human serum was 0.99. This high value was evidenced that GLF was rapidly excreted through the renal route.

  12. Clinical applications of HPLC-competitive protein binding assay for serum 25-hydroxyvitamin D

    International Nuclear Information System (INIS)

    Yang Shouli

    1989-01-01

    This report describes the clinical applications of HPLC-competitive protein binding assay for serum 25(OH) Vit D in 156 cases. Serum 25(OH) Vit D of normal human was 33.1 +- 14.8 nmol/L (13.2 +- 5.9 ng/ml), while for various diseases are as follows: rickets, 18.0 +- 9.0 nmol/L (7.2 +- 3.6 ng/ml, n = 36, P 0.1); pneumonia of children, 33.8 +- 14.8 nmol/L (13.5 +- 5.9 ng/ml, n = 10, P > 0.5); cirrhosis, 13.8 +- 11.3 nmol/L (5.5 +- 4.5 ng/ml, n = 9, P 0.2); administration of anticonvulsant (1 to 15 years), 19.0 +- 6.5 nmol/L (7.6 +- 2.6 ng/ml, n = 19, P 6 months), 15.3 +- 5.0 nmol/L (6.1 +- 2.0 ng/ml, n = 6, P 0.5); pregnant women, 39.8 +- 16.5 nmol/L (15.9 +- 6.6 ng/ml, n = 7, P > 0.1). We found it is a useful reference value for most of the above diseased state especially for differentiation between rickets and hypervitaminosis

  13. GPU-Based Point Cloud Superpositioning for Structural Comparisons of Protein Binding Sites.

    Science.gov (United States)

    Leinweber, Matthias; Fober, Thomas; Freisleben, Bernd

    2018-01-01

    In this paper, we present a novel approach to solve the labeled point cloud superpositioning problem for performing structural comparisons of protein binding sites. The solution is based on a parallel evolution strategy that operates on large populations and runs on GPU hardware. The proposed evolution strategy reduces the likelihood of getting stuck in a local optimum of the multimodal real-valued optimization problem represented by labeled point cloud superpositioning. The performance of the GPU-based parallel evolution strategy is compared to a previously proposed CPU-based sequential approach for labeled point cloud superpositioning, indicating that the GPU-based parallel evolution strategy leads to qualitatively better results and significantly shorter runtimes, with speed improvements of up to a factor of 1,500 for large populations. Binary classification tests based on the ATP, NADH, and FAD protein subsets of CavBase, a database containing putative binding sites, show average classification rate improvements from about 92 percent (CPU) to 96 percent (GPU). Further experiments indicate that the proposed GPU-based labeled point cloud superpositioning approach can be superior to traditional protein comparison approaches based on sequence alignments.

  14. GenProBiS: web server for mapping of sequence variants to protein binding sites.

    Science.gov (United States)

    Konc, Janez; Skrlj, Blaz; Erzen, Nika; Kunej, Tanja; Janezic, Dusanka

    2017-07-03

    Discovery of potentially deleterious sequence variants is important and has wide implications for research and generation of new hypotheses in human and veterinary medicine, and drug discovery. The GenProBiS web server maps sequence variants to protein structures from the Protein Data Bank (PDB), and further to protein-protein, protein-nucleic acid, protein-compound, and protein-metal ion binding sites. The concept of a protein-compound binding site is understood in the broadest sense, which includes glycosylation and other post-translational modification sites. Binding sites were defined by local structural comparisons of whole protein structures using the Protein Binding Sites (ProBiS) algorithm and transposition of ligands from the similar binding sites found to the query protein using the ProBiS-ligands approach with new improvements introduced in GenProBiS. Binding site surfaces were generated as three-dimensional grids encompassing the space occupied by predicted ligands. The server allows intuitive visual exploration of comprehensively mapped variants, such as human somatic mis-sense mutations related to cancer and non-synonymous single nucleotide polymorphisms from 21 species, within the predicted binding sites regions for about 80 000 PDB protein structures using fast WebGL graphics. The GenProBiS web server is open and free to all users at http://genprobis.insilab.org. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Towards an easy access to Annexin-A5 protein binding block copolymer micelles

    International Nuclear Information System (INIS)

    Schmidt, Vanessa; Giacomelli, Cristiano; Brisson, Alain R.; Borsali, Redouane

    2008-01-01

    The formation of Annexin-A5 decorated (bio-functionalized) nanoparticles is of particular interest in micelle-mediated target drug delivery, in vivo magnetic resonance imaging, and controlled fabrication of biochips. This work describes an easy access to the synthesis and manipulation of block copolymer nano-objects exhibiting Annexin-A5 protein binding ability. Well-defined spherical micelles containing negatively charged phosphonic diacid groups - which are potential binding sites for Annexin-A5 proteins - at their hydrophilic periphery originate from the self-assembly of polystyrene-b-poly(2-phosphatethyl methacrylate-stat-2-hydroxyethyl methacrylate) (PS-b-P(PEMA-stat-HEMA)) amphiphilic macromolecules in aqueous media. PS-b-P(PEMA-stat-HEMA) can be prepared in a three-step phosphorylation/silylation/methanolysis procedure applied to PS-b-PHEMA precursors synthesized via Atom Transfer Radical Polymerization (ATRP). The herein discussed approach allows precise control over micellar dimensions and properties such as core radius (i.e., loading capacity), corona width, and density of phosphate groups at the micelle periphery

  16. Structural Modulation of Phosducin by Phosphorylation and 14-3-3 Protein Binding

    Science.gov (United States)

    Rezabkova, Lenka; Kacirova, Miroslava; Sulc, Miroslav; Herman, Petr; Vecer, Jaroslav; Stepanek, Miroslav; Obsilova, Veronika; Obsil, Tomas

    2012-01-01

    Phosducin (Pdc), a highly conserved phosphoprotein, plays an important role in the regulation of G protein signaling, transcriptional control, and modulation of blood pressure. Pdc is negatively regulated by phosphorylation followed by binding to the 14-3-3 protein, whose role is still unclear. To gain insight into the role of 14-3-3 in the regulation of Pdc function, we studied structural changes of Pdc induced by phosphorylation and 14-3-3 protein binding using time-resolved fluorescence spectroscopy. Our data show that the phosphorylation of the N-terminal domain of Pdc at Ser-54 and Ser-73 affects the structure of the whole Pdc molecule. Complex formation with 14-3-3 reduces the flexibility of both the N- and C-terminal domains of phosphorylated Pdc, as determined by time-resolved tryptophan and dansyl fluorescence. Therefore, our data suggest that phosphorylated Pdc undergoes a conformational change when binding to 14-3-3. These changes involve the Gtβγ binding surface within the N-terminal domain of Pdc, and thus could explain the inhibitory effect of 14-3-3 on Pdc function. PMID:23199924

  17. SPRYSEC effectors: a versatile protein-binding platform to disrupt plant innate immunity

    Directory of Open Access Journals (Sweden)

    Amalia Diaz-Granados

    2016-10-01

    Full Text Available Persistent infections by sedentary plant-parasitic nematodes are a major threat to important food crops all over the world. These round worms manipulate host plant cell morphology and physiology to establish sophisticated feeding structures. Key modifications to plant cells during their transition into feeding structures are largely attributed to the activity of effectors secreted by the nematodes. The SPRYSEC effectors were initially identified in the potato cyst nematodes Globodera rostochiensis and G. pallida, and are characterized by a single SPRY domain, a non-catalytic domain present in modular proteins with different functions. The SPRY domain is wide-spread among eukaryotes and thought to be involved in mediating protein-protein interactions. Thus far, the SPRY domain is only reported as a functional domain in effectors of plant-parasitic nematodes, but not of other plant pathogens. SPRYSEC effectors have been implicated in both suppression and activation of plant immunity, but other possible roles in nematode virulence remain undefined. Here, we review the latest reports on the structure, function, and sequence diversity of SPRYSEC effectors, which provide support for a model featuring these effectors as a versatile protein-binding platform for the nematodes to target a wide range of host proteins during parasitism.

  18. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

    2015-01-01

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  19. Epidural ropivacaine hydrochloride during labour: protein binding, placental transfer and neonatal outcome.

    LENUS (Irish Health Repository)

    Porter, J M

    2012-02-03

    This study was undertaken: (i) to quantify the effects of labour and epidural analgesia on plasma alpha1-acid glycoprotein concentration, (ii) to examine the effects of changes in plasma alpha1-acid glycoprotein concentration on plasma protein binding and placental transfer of ropivacaine, and (iii) to examine the association between umbilical venous ropivacaine concentration and neurobehavioural function in the neonate. Multiparous patients undergoing induction of labour received a continuous epidural infusion of 0.1% ropivacaine following an epidural bolus. A significant association was demonstrated between maternal plasma alpha1-acid glycoprotein concentration and 1\\/free fraction of ropivacaine 60 min after starting ropivacaine administration (r(2) = 0.77) but not at delivery. No significant correlation was demonstrable between maternal unbound ropivacaine concentration and either neonatal (cord) ropivacaine concentration or UV\\/MV (a measure of placental transfer). Thirty minutes after delivery, 9\\/10 neonates had neurological and adaptive capacity scores < 35, whereas only three infants had scores < 35 at 2 h. All scores exceeded 35 16 h after delivery. No association between mean (SD) umbilical venous ropivacaine concentration [0.09 (0.08) mg x l(-1)] and neurological and adaptive capacity scores was demonstrated.

  20. Recognition of anesthetic barbiturates by a protein binding site: a high resolution structural analysis.

    Directory of Open Access Journals (Sweden)

    Simon Oakley

    Full Text Available Barbiturates potentiate GABA actions at the GABA(A receptor and act as central nervous system depressants that can induce effects ranging from sedation to general anesthesia. No structural information has been available about how barbiturates are recognized by their protein targets. For this reason, we tested whether these drugs were able to bind specifically to horse spleen apoferritin, a model protein that has previously been shown to bind many anesthetic agents with affinities that are closely correlated with anesthetic potency. Thiopental, pentobarbital, and phenobarbital were all found to bind to apoferritin with affinities ranging from 10-500 µM, approximately matching the concentrations required to produce anesthetic and GABAergic responses. X-ray crystal structures were determined for the complexes of apoferritin with thiopental and pentobarbital at resolutions of 1.9 and 2.0 Å, respectively. These structures reveal that the barbiturates bind to a cavity in the apoferritin shell that also binds haloalkanes, halogenated ethers, and propofol. Unlike these other general anesthetics, however, which rely entirely upon van der Waals interactions and the hydrophobic effect for recognition, the barbiturates are recognized in the apoferritin site using a mixture of both polar and nonpolar interactions. These results suggest that any protein binding site that is able to recognize and respond to the chemically and structurally diverse set of compounds used as general anesthetics is likely to include a versatile mixture of both polar and hydrophobic elements.

  1. Evolving Transcription Factor Binding Site Models From Protein Binding Microarray Data

    KAUST Repository

    Wong, Ka-Chun

    2016-02-02

    Protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner. In this paper, we describe the PBM motif model building problem. We apply several evolutionary computation methods and compare their performance with the interior point method, demonstrating their performance advantages. In addition, given the PBM domain knowledge, we propose and describe a novel method called kmerGA which makes domain-specific assumptions to exploit PBM data properties to build more accurate models than the other models built. The effectiveness and robustness of kmerGA is supported by comprehensive performance benchmarking on more than 200 datasets, time complexity analysis, convergence analysis, parameter analysis, and case studies. To demonstrate its utility further, kmerGA is applied to two real world applications: 1) PBM rotation testing and 2) ChIP-Seq peak sequence prediction. The results support the biological relevance of the models learned by kmerGA, and thus its real world applicability.

  2. A Comparison Study for DNA Motif Modeling on Protein Binding Microarray

    KAUST Repository

    Wong, Ka-Chun

    2015-06-11

    Transcription Factor Binding Sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, Protein Binding Microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k=810). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build motif models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement using di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

  3. Cysteine-rich intestinal protein binds zinc during transmucosal zinc transport

    International Nuclear Information System (INIS)

    Hempe, J.M.; Cousins, R.J.

    1991-01-01

    The mechanism of zinc absorption has not been delineated, but kinetic studies show that both passive and carrier-mediated processes are involved. The authors have identified a low molecular mass zinc-binding protein in the soluble fraction of rat intestinal mucosa that could function as an intracellular zinc carrier. The protein was not detected in liver or pancreas, suggesting a role specific to the intestine. The protein binds zinc during transmucosal zinc transport and shows signs of saturation at higher luminal zinc concentrations, characteristics consistent with a role in carrier-mediated zinc absorption. Microsequence analysis of the protein purified by gel-filtration HPCL and SDS/PAGE showed complete identity within the first 41 N-terminal amino acids with the deduced protein sequence of cysteine-rich intestinal protein. These investigators showed that the gene for this protein is developmentally regulated in neonates during the suckling period, conserved in many vertebrate species, and predominantly expressed in the small intestine. Cysteine-rich intestinal protein contains a recently identified conserved sequence of histidine and cysteine residues, the LIM motif, which our results suggest confers metal-binding properties that are important for zinc transport and/or functions of this micronutrient

  4. 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.

  5. 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

  6. 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.

  7. 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…

  8. Coating of Dacron vascular grafts with an ionic polyurethane: a novel sealant with protein binding properties.

    Science.gov (United States)

    Phaneuf, M D; Dempsey, D J; Bide, M J; Quist, W C; LoGerfo, F W

    2001-03-01

    The purpose of this study was to develop a novel sealant that would seal prosthetic vascular graft interstices and be accessible for protein binding. Crimped knitted Dacron vascular grafts were cleaned (CNTRL) and hydrolyzed in boiling sodium hydroxide (HYD). These HYD grafts were sealed using an 11% solids solution of a polyether-based urethane with carboxylic acid groups (PEU-D) via a novel technique that employs both trans-wall and luminal perfusion. Carboxylic acid content, determined via methylene blue dye uptake, was 2.3- and 4.2-fold greater in PEU-D segments (1.0+/-0.27 nmol/mg) as compared to HYD and CNTRL segments, respectively. Water permeation through PEU-D graft (1.1+/-2 ml/cm2 min(-1)) was comparable to collagen-impregnated Dacron (9.8+/-10 ml/cm2 min(-1)). Non-specific 125I-albumin (125I-Alb) binding to PEU-D segments (18+/-3 ng/mg) was significantly lower than HYD and CNTRL segments. 125I-Alb linkage to PEU-D using the crosslinker EDC resulted in 5.7-fold greater binding (103+/-2 ng/mg) than non-specific PEU-D controls. However, covalent linkage of 125I-Alb to PEU-D was 4.9- and 5.9-fold less than CNTRL and HYD segments with EDC, respectively. Thus, ionic polyurethane can be applied to a pre-formed vascular graft, seal the interstices and create "anchor" sites for protein attachment.

  9. A method to eliminate the effect of protein binding on GFR

    International Nuclear Information System (INIS)

    Prabakaran, K.; Fernandes, V.; Nour, R.

    1998-01-01

    Full text: Plasma clearance of 99m Tc-DTPA is a standard method for GFR assessment. Protein binding (PB) of 99m Tc-DTPA is thought to affect the accuracy of the GFR measurement. Therefore, eliminating PB portion would improve the accuracy of this measurement. Methods to eliminate PB are usually complex, but a simple Amicon micropartition system has been proposed to eliminate the PB effect. This study is aimed to assess if this simple method effectively excluded the PB fraction and improved the accuracy of the GFR measurement. Therefore, eliminating PB portion would improve the accuracy of this measurement. Methods to eliminate PB are usually complex, but a simple Amicon micropartition system separates free 99m Tc-DTPA from the PB fraction after a 10 min centrifugation of patient plasma. The ultrafiltrate obtained is totally free of PB 99m Tc-DTPA. 20 consecutive patients had GFRs performed using the two sample method with blood drawn at 60 and 150 min. All samples had an Ultrafiltrate 99m Tc-DTPA and normal plasma 99m Tc-DTPA. The GFRs were calculated from both samples. The findings showed a mean PB of 6.5 + 3.9% and 13 + 5.0% at 60 min and 150 min respectively for our DTPA. The mean GFR from normal plasma 85.7 + 26.4 mL/min and from ultrafiltrate = 97.2 + 28.8 mL/min. Statistical analysis using Student''s ''t'' test shows that there is a significant difference between the values of GFR (P < 0.05). Our result confirms that the PB of DTPA is substantial and affects the GFR estimation significantly. The method of ultrafiltration eliminates the PB, and very simple to use. This method could be used on a routine basis and/or to assess the suitability of the DTPA used in various departments for GFR measurement

  10. Chemical Affinity between Tannin Size and Salivary Protein Binding Abilities: Implications for Wine Astringency.

    Science.gov (United States)

    Ma, Wen; Waffo-Teguo, Pierre; Jourdes, Michael; Li, Hua; Teissedre, Pierre-Louis

    2016-01-01

    Astringency perception, as an essential parameter for high-quality red wine, is principally elicited by condensed tannins in diversified chemical structures. Condensed tannins, which are also known as proanthocyanidins (PAs), belong to the flavonoid class of polyphenols and are incorporated by multiple flavan-3-ols units according to their degree of polymerization (DP). However, the influence of DP size of PAs on astringency perception remains unclear for decades. This controversy was mainly attributed to the lack of efficient strategies to isolate the PAs in non-galloylated forms and with individual degree size from grape/wine. In the present study, the astringency intensity of purified and identified grape oligomeric tannins (DP ranged from 1 to 5) was firstly explored. A novel non-solid phase strategy was used to rapidly exclude the galloylated PAs from the non-galloylated PAs and fractionate the latter according to their DP size. Then, a series of PAs with individual DP size and galloylation were purified by an approach of preparative hydrophilic interaction chromatography. Furthermore, purified compounds were identified by both normal phase HPLC-FLD and reverse phase UHPLC-ESI-Q-TOF. Finally, the contribution of the astringency perception of the individual purified tannins was examined with a salivary protein binding ability test. The results were observed by HPLC-FLD and quantified by changes in PA concentration remaining in the filtrate. In summary, a new approach without a solid stationary phase was developed to isolate PAs according to their DP size. And a positive relationship between the DP of PAs and salivary protein affinity was revealed.

  11. Chemical Affinity between Tannin Size and Salivary Protein Binding Abilities: Implications for Wine Astringency.

    Directory of Open Access Journals (Sweden)

    Wen Ma

    Full Text Available Astringency perception, as an essential parameter for high-quality red wine, is principally elicited by condensed tannins in diversified chemical structures. Condensed tannins, which are also known as proanthocyanidins (PAs, belong to the flavonoid class of polyphenols and are incorporated by multiple flavan-3-ols units according to their degree of polymerization (DP. However, the influence of DP size of PAs on astringency perception remains unclear for decades. This controversy was mainly attributed to the lack of efficient strategies to isolate the PAs in non-galloylated forms and with individual degree size from grape/wine. In the present study, the astringency intensity of purified and identified grape oligomeric tannins (DP ranged from 1 to 5 was firstly explored. A novel non-solid phase strategy was used to rapidly exclude the galloylated PAs from the non-galloylated PAs and fractionate the latter according to their DP size. Then, a series of PAs with individual DP size and galloylation were purified by an approach of preparative hydrophilic interaction chromatography. Furthermore, purified compounds were identified by both normal phase HPLC-FLD and reverse phase UHPLC-ESI-Q-TOF. Finally, the contribution of the astringency perception of the individual purified tannins was examined with a salivary protein binding ability test. The results were observed by HPLC-FLD and quantified by changes in PA concentration remaining in the filtrate. In summary, a new approach without a solid stationary phase was developed to isolate PAs according to their DP size. And a positive relationship between the DP of PAs and salivary protein affinity was revealed.

  12. Chemical Affinity between Tannin Size and Salivary Protein Binding Abilities: Implications for Wine Astringency

    Science.gov (United States)

    Ma, Wen; Waffo-Teguo, Pierre; Jourdes, Michael; Li, Hua

    2016-01-01

    Astringency perception, as an essential parameter for high-quality red wine, is principally elicited by condensed tannins in diversified chemical structures. Condensed tannins, which are also known as proanthocyanidins (PAs), belong to the flavonoid class of polyphenols and are incorporated by multiple flavan-3-ols units according to their degree of polymerization (DP). However, the influence of DP size of PAs on astringency perception remains unclear for decades. This controversy was mainly attributed to the lack of efficient strategies to isolate the PAs in non-galloylated forms and with individual degree size from grape/wine. In the present study, the astringency intensity of purified and identified grape oligomeric tannins (DP ranged from 1 to 5) was firstly explored. A novel non-solid phase strategy was used to rapidly exclude the galloylated PAs from the non-galloylated PAs and fractionate the latter according to their DP size. Then, a series of PAs with individual DP size and galloylation were purified by an approach of preparative hydrophilic interaction chromatography. Furthermore, purified compounds were identified by both normal phase HPLC-FLD and reverse phase UHPLC-ESI-Q-TOF. Finally, the contribution of the astringency perception of the individual purified tannins was examined with a salivary protein binding ability test. The results were observed by HPLC-FLD and quantified by changes in PA concentration remaining in the filtrate. In summary, a new approach without a solid stationary phase was developed to isolate PAs according to their DP size. And a positive relationship between the DP of PAs and salivary protein affinity was revealed. PMID:27518822

  13. Co-Occurring Atomic Contacts for the Characterization of Protein Binding Hot Spots

    Science.gov (United States)

    Liu, Qian; Ren, Jing; Song, Jiangning; Li, Jinyan

    2015-01-01

    A binding hot spot is a small area at a protein-protein interface that can make significant contribution to binding free energy. This work investigates the substantial contribution made by some special co-occurring atomic contacts at a binding hot spot. A co-occurring atomic contact is a pair of atomic contacts that are close to each other with no more than three covalent-bond steps. We found that two kinds of co-occurring atomic contacts can play an important part in the accurate prediction of binding hot spot residues. One is the co-occurrence of two nearby hydrogen bonds. For example, mutations of any residue in a hydrogen bond network consisting of multiple co-occurring hydrogen bonds could disrupt the interaction considerably. The other kind of co-occurring atomic contact is the co-occurrence of a hydrophobic carbon contact and a contact between a hydrophobic carbon atom and a π ring. In fact, this co-occurrence signifies the collective effect of hydrophobic contacts. We also found that the B-factor measurements of several specific groups of amino acids are useful for the prediction of hot spots. Taking the B-factor, individual atomic contacts and the co-occurring contacts as features, we developed a new prediction method and thoroughly assessed its performance via cross-validation and independent dataset test. The results show that our method achieves higher prediction performance than well-known methods such as Robetta, FoldX and Hotpoint. We conclude that these contact descriptors, in particular the novel co-occurring atomic contacts, can be used to facilitate accurate and interpretable characterization of protein binding hot spots. PMID:26675422

  14. Ultra-fast optical manipulation of single proteins binding to the actin cytoskeleton

    Science.gov (United States)

    Capitanio, Marco; Gardini, Lucia; Pavone, Francesco Saverio

    2014-02-01

    In the last decade, forces and mechanical stresses acting on biological systems are emerging as regulatory factors essential for cell life. Emerging evidences indicate that factors such as applied forces or the rigidity of the extracellular matrix (ECM) determine the shape and function of cells and organisms1. Classically, the regulation of biological systems is described through a series of biochemical signals and enzymatic reactions, which direct the processes and cell fate. However, mechanotransduction, i.e. the conversion of mechanical forces into biochemical and biomolecular signals, is at the basis of many biological processes fundamental for the development and differentiation of cells, for their correct function and for the development of pathologies. We recently developed an in vitro system that allows the investigation of force-dependence of the interaction of proteins binding the actin cytoskeleton, at the single molecule level. Our system displays a delay of only ~10 μs between formation of the molecular bond and application of the force and is capable of detecting interactions as short as 100 μs. Our assay allows direct measurements of load-dependence of lifetimes of single molecular bonds and conformational changes of single proteins and molecular motors. We demonstrate our technique on molecular motors, using myosin II from fast skeletal muscle and on protein-DNA interaction, specifically on Lactose repressor (LacI). The apparatus is stabilized to less than 1 nm with both passive and active stabilization, allowing resolving specific binding regions along the actin filament and DNA molecule. Our technique extends single-molecule force-clamp spectroscopy to molecular complexes that have been inaccessible up to now, opening new perspectives for the investigation of the effects of forces on biological processes.

  15. Functional and DNA-protein binding studies of WRKY transcription factors and their expression analysis in response to biotic and abiotic stress in wheat (Triticum aestivum L.).

    Science.gov (United States)

    Satapathy, Lopamudra; Kumar, Dhananjay; Kumar, Manish; Mukhopadhyay, Kunal

    2018-01-01

    WRKY, a plant-specific transcription factor family, plays vital roles in pathogen defense, abiotic stress, and phytohormone signalling. Little is known about the roles and function of WRKY transcription factors in response to rust diseases in wheat. In the present study, three TaWRKY genes encoding complete protein sequences were cloned. They belonged to class II and III WRKY based on the number of WRKY domains and the pattern of zinc finger structures. Twenty-two DNA-protein binding docking complexes predicted stable interactions of WRKY domain with W-box. Quantitative real-time-PCR using wheat near-isogenic lines with or without Lr28 gene revealed differential up- or down-regulation in response to biotic and abiotic stress treatments which could be responsible for their functional divergence in wheat. TaWRKY62 was found to be induced upon treatment with JA, MJ, and SA and reduced after ABA treatments. Maximum induction of six out of seven genes occurred at 48 h post inoculation due to pathogen inoculation. Hence, TaWRKY (49, 50 , 52 , 55 , 57, and 62 ) can be considered as potential candidate genes for further functional validation as well as for crop improvement programs for stress resistance. The results of the present study will enhance knowledge towards understanding the molecular basis of mode of action of WRKY transcription factor genes in wheat and their role during leaf rust pathogenesis in particular.

  16. IN SILICO EVALUATION OF ANGIOTENSIN II RECEPTOR ANTAGONIST’S PLASMA PROTEIN BINDING USING COMPUTED MOLECULAR DESCRIPTORS

    Directory of Open Access Journals (Sweden)

    Jadranka Odović

    2014-03-01

    Full Text Available The discovery of new pharmacologically active substances and drugs modeling led to necessity of predicting drugs properties and its ADME data. Angiotensin II receptor antagonists are a group of pharmaceuticals which modulate the renin-angiotensin-aldosterone system and today represent the most commonly prescribed anti-hypertensive drugs. The aim of this study was to compare different molecular properties of seven angiotensin II receptor antagonists / blockers (ARBs, (eprosartan, irbesartan, losartan, olmesartan, telmisartan, valsartan and their plasma protein binding (PPB data. Several ARBs molecular descriptors were calculated using software package Molinspiration Depiction Software as well as Virtual Computational Chemistry Laboratory (electronic descriptor – PSA, constitutional parameter – Mw, geometric descriptor – Vol, lipophilicity descriptors - logP values, aqueous solubility data – logS. The correlations between all collected descriptors and plasma protein binding data obtained from relevant literature were established. In the simple linear regression poor correlations were obtained in relationships between PPB data and all calculated molecular descriptors. In the next stage of the study multiple linear regression (MLR was used for correlation of PPB data with two different descriptors as independent variables. The best correlation (R2=0.70 with P<0.05 was established between PPB data and molecular weight with addition of volume values as independent variables. The possible application of computed molecular descriptors in drugs protein binding evaluation can be of great importance in drug research.

  17. Exploring Protein Binding of Uremic Toxins in Patients with Different Stages of Chronic Kidney Disease and during Hemodialysis

    Directory of Open Access Journals (Sweden)

    Olivier Deltombe

    2015-09-01

    Full Text Available As protein binding of uremic toxins is not well understood, neither in chronic kidney disease (CKD progression, nor during a hemodialysis (HD session, we studied protein binding in two cross-sectional studies. Ninety-five CKD 2 to 5 patients and ten stable hemodialysis patients were included. Blood samples were taken either during the routine ambulatory visit (CKD patients or from blood inlet and outlet line during dialysis (HD patients. Total (CT and free concentrations were determined of p-cresylglucuronide (pCG, hippuric acid (HA, indole-3-acetic acid (IAA, indoxyl sulfate (IS and p-cresylsulfate (pCS, and their percentage protein binding (%PB was calculated. In CKD patients, %PB/CT resulted in a positive correlation (all p < 0.001 with renal function for all five uremic toxins. In HD patients, %PB was increased after 120 min of dialysis for HA and at the dialysis end for the stronger (IAA and the highly-bound (IS and pCS solutes. During one passage through the dialyzer at 120 min, %PB was increased for HA (borderline, IAA, IS and pCS. These findings explain why protein-bound solutes are difficult to remove by dialysis: a combination of the fact that (i only the free fraction can pass the filter and (ii the equilibrium, as it was pre-dialysis, cannot be restored during the dialysis session, as it is continuously disturbed.

  18. 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.

  19. Equilibrium-phase MR angiography: Comparison of unspecific extracellular and protein-binding gadolinium-based contrast media with respect to image quality.

    Science.gov (United States)

    Erb-Eigner, Katharina; Taupitz, Matthias; Asbach, Patrick

    2016-01-01

    The purpose of this study was to compare contrast and image quality of whole-body equilibrium-phase high-spatial-resolution MR angiography using a non-protein-binding unspecific extracellular gadolinium-based contrast medium with that of two contrast media with different protein-binding properties. 45 patients were examined using either 15 mL of gadobutrol (non-protein-binding, n = 15), 32 mL of gadobenate dimeglumine (weakly protein binding, n = 15) or 11 mL gadofosveset trisodium (protein binding, n = 15) followed by equilibrium-phase high-spatial-resolution MR-angiography of four consecutive anatomic regions. The time elapsed between the contrast injection and the beginning of the equilibrium-phase image acquisition in the respective region was measured and was up to 21 min. Signal intensity was measured in two vessels per region and in muscle tissue. Relative contrast (RC) values were calculated. Vessel contrast, artifacts and image quality were rated by two radiologists in consensus on a five-point scale. Compared with gadobutrol, gadofosveset trisodium revealed significantly higher RC values only when acquired later than 15 min after bolus injection. Otherwise, no significant differences between the three contrast media were found regarding vascular contrast and image quality. Equilibrium-phase high-spatial-resolution MR-angiography using a weakly protein-binding or even non-protein-binding contrast medium is equivalent to using a stronger protein-binding contrast medium when image acquisition is within the first 15 min after contrast injection, and allows depiction of the vasculature with high contrast and image quality. The protein-binding contrast medium was superior for imaging only later than 15 min after contrast medium injection. Copyright © 2015 John Wiley & Sons, Ltd.

  20. Clinical applications of HPLC-competitive protein binding assay for serum 25-hydroxyvitamin D

    Energy Technology Data Exchange (ETDEWEB)

    Shouli, Yang [China-Japan Friendship Hospital, Beijing, BJ (China). Inst. of Clinical Medical Science; and others

    1989-08-01

    This report describes the clinical applications of HPLC-competitive protein binding assay for serum 25(OH) Vit D in 156 cases. Serum 25(OH) Vit D of normal human was 33.1 +- 14.8 nmol/L (13.2 +- 5.9 ng/ml), while for various diseases are as follows: rickets, 18.0 +- 9.0 nmol/L (7.2 +- 3.6 ng/ml, n = 36, P < 0.005); hypervitaminosis D, 116.8 +- 31.3 nmol/L (46.7 +- 12.3 ng/ml, n = 6, P < 0.001); renal diseases of children, 25.3 +- 7.3 nmol/L (10.1 +- 2.9 ng/ml, n = 9. P > 0.1); pneumonia of children, 33.8 +- 14.8 nmol/L (13.5 +- 5.9 ng/ml, n = 10, P > 0.5); cirrhosis, 13.8 +- 11.3 nmol/L (5.5 +- 4.5 ng/ml, n = 9, P < 0.001); vasculitis, 25.5 +- 15.3 nmol/L (10.2 +- 6.1 ng/ml, n = 5, P > 0.2); administration of anticonvulsant (1 to 15 years), 19.0 +- 6.5 nmol/L (7.6 +- 2.6 ng/ml, n = 19, P < 0.001); administration of glococorticoids (> 6 months), 15.3 +- 5.0 nmol/L (6.1 +- 2.0 ng/ml, n = 6, P < 0.005); hyperthyroidism, 34.0 +- 23.5 nmol/L (13.6 +- 9.4 ng/ml, n = 13, P > 0.5); pregnant women, 39.8 +- 16.5 nmol/L (15.9 +- 6.6 ng/ml, n = 7, P > 0.1). We found it is a useful reference value for most of the above diseased state especially for differentiation between rickets and hypervitaminosis.

  1. 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

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. Informing the Human Plasma Protein Binding of Environmental Chemicals by Machine Learning in the Pharmaceutical Space: Applicability Domain and Limits of Predictability

    Science.gov (United States)

    The free fraction of a xenobiotic in plasma (Fub) is an important determinant of chemical adsorption, distribution, metabolism, elimination, and toxicity, yet experimental plasma protein binding data is scarce for environmentally relevant chemicals. The presented work explores th...

  7. 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

  8. 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....

  9. 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....

  10. 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....

  11. Controlled Modulation of Serum Protein Binding and Biodistribution of Asymmetric Cyanine Dyes by Variation of the Number of Sulfonate Groups

    Directory of Open Access Journals (Sweden)

    Franziska M. Hamann

    2011-07-01

    Full Text Available To assess the suitability of asymmetric cyanine dyes for in vivo fluoro-optical molecular imaging, a comprehensive study on the influence of the number of negatively charged sulfonate groups governing the hydrophilicity of the DY-67x family of asymmetric cyanines was performed. Special attention was devoted to the plasma protein binding capacity and related pharmacokinetic properties. Four members of the DY-67x cyanine family composed of the same main chromophore, but substituted with a sequentially increasing number of sulfonate groups (n = 1−4; DY-675, DY-676, DY-677, DY-678, respectively, were incubated with plasma proteins dissolved in phosphate-buffered saline. Protein binding was assessed by absorption spectroscopy, gel electrophoresis, ultrafiltration, and dialysis. Distribution of dye in organs was studied by intraveneous injection of 62 nmol dye/kg body weight into mice (n = 12; up to 180 minutes postinjection using whole-body near-infrared fluorescence imaging. Spectroscopic studies, gel electrophoresis, and dialysis demonstrated reduced protein binding with increasing number of sulfonate groups. The bovine serum albumin binding constant of the most hydrophobic dye, DY-675, is 18 times higher than that of the most hydrophilic fluorophore, DY-678. In vivo biodistribution analysis underlined a considerable influence of dye hydrophilicity on biodistribution and excretion pathways, with the more hydrophobic dyes, DY-675 and DY-676, accumulating in the liver, followed by strong fluorescence signals in bile and gut owing to accumulation in feces and comparatively hydrophilic DY-678-COOH accumulating in the bladder. Our results demonstrate the possibility of selectively controlling dye-protein interactions and, thus, biodistribution and excretion pathways via proper choice of the fluorophore's substitution pattern. This underlines the importance of structure-property relationships for fluorescent labels. Moreover, our data could provide the

  12. DBAC: A simple prediction method for protein binding hot spots based on burial levels and deeply buried atomic contacts

    Science.gov (United States)

    2011-01-01

    Background A protein binding hot spot is a cluster of residues in the interface that are energetically important for the binding of the protein with its interaction partner. Identifying protein binding hot spots can give useful information to protein engineering and drug design, and can also deepen our understanding of protein-protein interaction. These residues are usually buried inside the interface with very low solvent accessible surface area (SASA). Thus SASA is widely used as an outstanding feature in hot spot prediction by many computational methods. However, SASA is not capable of distinguishing slightly buried residues, of which most are non hot spots, and deeply buried ones that are usually inside a hot spot. Results We propose a new descriptor called “burial level” for characterizing residues, atoms and atomic contacts. Specifically, burial level captures the depth the residues are buried. We identify different kinds of deeply buried atomic contacts (DBAC) at different burial levels that are directly broken in alanine substitution. We use their numbers as input for SVM to classify between hot spot or non hot spot residues. We achieve F measure of 0.6237 under the leave-one-out cross-validation on a data set containing 258 mutations. This performance is better than other computational methods. Conclusions Our results show that hot spot residues tend to be deeply buried in the interface, not just having a low SASA value. This indicates that a high burial level is not only a necessary but also a more sufficient condition than a low SASA for a residue to be a hot spot residue. We find that those deeply buried atoms become increasingly more important when their burial levels rise up. This work also confirms the contribution of deeply buried interfacial atomic contacts to the energy of protein binding hot spot. PMID:21689480

  13. Evaluation of metabolism, plasma protein binding and other biological parameters after administration of (−)-[18 F]Flubatine in humans

    International Nuclear Information System (INIS)

    Patt, Marianne; Becker, Georg A.; Grossmann, Udo; Habermann, Bernd; Schildan, Andreas; Wilke, Stephan; Deuther-Conrad, Winnie; Graef, Susanne; Fischer, Steffen; Smits, René; Hoepping, Alexander; Wagenknecht, Gudrun; Steinbach, Jörg; Gertz, Hermann-Josef; Hesse, Swen; Schönknecht, Peter

    2014-01-01

    Introduction: (−)-[ 18 F]Flubatine is a PET tracer with high affinity and selectivity for the nicotinic acetylcholine α 4 β 2 receptor subtype. A clinical trial assessing the availability of this subtype of nAChRs was performed. From a total participant number of 21 Alzheimer’s disease (AD) patients and 20 healthy controls (HCs), the following parameters were determined: plasma protein binding, metabolism and activity distribution between plasma and whole blood. Methods: Plasma protein binding and fraction of unchanged parent compound were assessed by ultracentrifugation and HPLC, respectively. The distribution of radioactivity (parent compound + metabolites) between plasma and whole blood was determined ex vivo at different time-points after injection by gamma counting after separation of whole blood by centrifugation into the cellular and non-cellular components. In additional experiments in vitro, tracer distribution between these blood components was assessed for up to 90 min. Results: A fraction of 15% ± 2% of (−)-[ 18 F]Flubatine was found to be bound to plasma proteins. Metabolic degradation of (−)-[ 18 F]Flubatine was very low, resulting in almost 90% unchanged parent compound at 90 min p.i. with no significant difference between AD and HC. The radioactivity distribution between plasma and whole blood changed in vivo only slightly over time from 0.82 ± 0.03 at 3 min p.i. to 0.87 ± 0.03 at 270 min p.i. indicating the contribution of only a small amount of metabolites. In vitro studies revealed that (−)-[ 18 F]Flubatine was instantaneously distributed between cellular and non-cellular blood parts. Discussion: (−)-[ 18 F]Flubatine exhibits very favourable characteristics for a PET radiotracer such as slow metabolic degradation and moderate plasma protein binding. Equilibrium of radioactivity distribution between plasma and whole blood is reached instantaneously and remains almost constant over time allowing both convenient sample handling and

  14. Calculation of relative free energies for ligand-protein binding, solvation, and conformational transitions using the GROMOS software.

    Science.gov (United States)

    Riniker, Sereina; Christ, Clara D; Hansen, Halvor S; Hünenberger, Philippe H; Oostenbrink, Chris; Steiner, Denise; van Gunsteren, Wilfred F

    2011-11-24

    The calculation of the relative free energies of ligand-protein binding, of solvation for different compounds, and of different conformational states of a polypeptide is of considerable interest in the design or selection of potential enzyme inhibitors. Since such processes in aqueous solution generally comprise energetic and entropic contributions from many molecular configurations, adequate sampling of the relevant parts of configurational space is required and can be achieved through molecular dynamics simulations. Various techniques to obtain converged ensemble averages and their implementation in the GROMOS software for biomolecular simulation are discussed, and examples of their application to biomolecules in aqueous solution are given. © 2011 American Chemical Society

  15. 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.

  16. 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…

  17. 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...

  18. Preparation of fluorescent tocopherols for use in protein binding and localization with the alpha-tocopherol transfer protein.

    Science.gov (United States)

    Nava, Phillip; Cecchini, Matt; Chirico, Sara; Gordon, Heather; Morley, Samantha; Manor, Danny; Atkinson, Jeffrey

    2006-06-01

    Sixteen fluorescent analogues of the lipid-soluble antioxidant vitamin alpha-tocopherol were prepared incorporating fluorophores at the terminus of omega-functionalized 2-n-alkyl-substituted chromanols (1a-d and 4a-d) that match the methylation pattern of alpha-tocopherol, the most biologically active form of vitamin E. The fluorophores used include 9-anthroyloxy (AO), 7-nitrobenz-2-oxa-1,3-diazole (NBD), N-methyl anthranilamide (NMA), and dansyl (DAN). The compounds were designed to function as fluorescent reporter ligands for protein-binding and lipid transfer assays. The fluorophores were chosen to maximize the fluorescence changes observed upon moving from an aqueous environment (low fluorescence intensity) to an hydrophobic environment such as a protein's binding site (high fluorescence intensity). Compounds 9d (anthroyloxy) and 10d (nitrobenzoxadiazole), having a C9-carbon chain between the chromanol and the fluorophore, were shown to bind specifically and reversibly to recombinant human tocopherol transfer protein (alpha-TTP) with dissociation constants of approximately 280 and 60 nM, respectively, as compared to 25 nM for the natural ligand 2R,4'R,8'R-alpha-tocopherol. Thus, compounds have been prepared that allow the investigation of the rate of alpha-TTP-mediated inter-membrane transfer of alpha-tocopherol and to investigate the mechanism of alpha-TTP function at membranes of different composition.

  19. Automated measurement of serum thyroxine with the ''AIRA II,'' as compared with competitive protein binding and radioimmunoassay

    International Nuclear Information System (INIS)

    Reese, M.G.; Johnson, L.V.R.

    1978-01-01

    Two conventional serum thyroxine assays, run in separate laboratories, one by competitive protein binding and one by radioimmunoassay, were used to evaluate the automated ARIA II (Becton Dickinson Immunodiagnostics) serum thyroxine assay. Competitive protein binding as compared to ARIA II with 111 clinical serum samples gave a slope of 1.04 and a correlation coefficient of 0.94. The radioimmunoassay comparison to ARIA II with 53 clinical serum samples gave a slope of 1.05 and a correlation coefficient of 0.92. The ARIA II inter-assay coefficient of variation for 10 replicates of low, medium, and high thyroxine serum samples was 6.2, 6.0, and 2.9%, respectively, with an inter-assay coefficient of variation among 15 different assays of 15.5, 10.1, and 7.9%. The automated ARIA II, with a 2.2-min cycle per sample, gives results that compare well with those by manual methodology

  20. Stability, protein binding and clearance studies of [99mTc]DTPA. Evaluation of a commercially available dry-kit

    DEFF Research Database (Denmark)

    Rehling, M

    1988-01-01

    [99mTc]DTPA has achieved widespread use for the measurement of glomerular filtration rate (GFR) with the single injection plasma clearance technique and for gamma-camera renography. However, the quality of the commercial preparations varies. The purpose of the present investigation was to study...... the quality of a commercial [99mTc]DTPA preparation (C.I.S., France) with reference to stability, protein binding and accuracy of the determined plasma clearance values as a measure of GFR. The stability of the preparations was studied by thin-layer chromatography, the in vitro protein binding by Sephadex.......7% and 1.1%, respectively. The plasma clearance of [99mTc]DTPA was on an average 3.7% higher than that of [51Cr]EDTA in 27 patients. It is concluded that the [99mTc]DTPA preparation is reliable for the measurement of GFR. The preparation is stable for at least six hours at room temperature...

  1. 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 ...

  2. Membrane proteins bind lipids selectively to modulate their structure and function.

    Science.gov (United States)

    Laganowsky, Arthur; Reading, Eamonn; Allison, Timothy M; Ulmschneider, Martin B; Degiacomi, Matteo T; Baldwin, Andrew J; Robinson, Carol V

    2014-06-05

    Previous studies have established that the folding, structure and function of membrane proteins are influenced by their lipid environments and that lipids can bind to specific sites, for example, in potassium channels. Fundamental questions remain however regarding the extent of membrane protein selectivity towards lipids. Here we report a mass spectrometry approach designed to determine the selectivity of lipid binding to membrane protein complexes. We investigate the mechanosensitive channel of large conductance (MscL) from Mycobacterium tuberculosis and aquaporin Z (AqpZ) and the ammonia channel (AmtB) from Escherichia coli, using ion mobility mass spectrometry (IM-MS), which reports gas-phase collision cross-sections. We demonstrate that folded conformations of membrane protein complexes can exist in the gas phase. By resolving lipid-bound states, we then rank bound lipids on the basis of their ability to resist gas phase unfolding and thereby stabilize membrane protein structure. Lipids bind non-selectively and with high avidity to MscL, all imparting comparable stability; however, the highest-ranking lipid is phosphatidylinositol phosphate, in line with its proposed functional role in mechanosensation. AqpZ is also stabilized by many lipids, with cardiolipin imparting the most significant resistance to unfolding. Subsequently, through functional assays we show that cardiolipin modulates AqpZ function. Similar experiments identify AmtB as being highly selective for phosphatidylglycerol, prompting us to obtain an X-ray structure in this lipid membrane-like environment. The 2.3 Å resolution structure, when compared with others obtained without lipid bound, reveals distinct conformational changes that re-position AmtB residues to interact with the lipid bilayer. Our results demonstrate that resistance to unfolding correlates with specific lipid-binding events, enabling a distinction to be made between lipids that merely bind from those that modulate membrane

  3. 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

  4. Cell Surface Properties of Lactococcus lactis Reveal Milk Protein Binding Specifically Evolved in Dairy Isolates

    Directory of Open Access Journals (Sweden)

    Mariya Tarazanova

    2017-09-01

    Full Text Available Surface properties of bacteria are determined by the molecular composition of the cell wall and they are important for interactions of cells with their environment. Well-known examples of bacterial interactions with surfaces are biofilm formation and the fermentation of solid materials like food and feed. Lactococcus lactis is broadly used for the fermentation of cheese and buttermilk and it is primarily isolated from either plant material or the dairy environment. In this study, we characterized surface hydrophobicity, charge, emulsification properties, and the attachment to milk proteins of 55 L. lactis strains in stationary and exponential growth phases. The attachment to milk protein was assessed through a newly developed flow cytometry-based protocol. Besides finding a high degree of biodiversity, phenotype-genotype matching allowed the identification of candidate genes involved in the modification of the cell surface. Overexpression and gene deletion analysis allowed to verify the predictions for three identified proteins that altered surface hydrophobicity and attachment of milk proteins. The data also showed that lactococci isolated from a dairy environment bind higher amounts of milk proteins when compared to plant isolates. It remains to be determined whether the alteration of surface properties also has potential to alter starter culture functionalities.

  5. Rapid and accurate prediction and scoring of water molecules in protein binding sites.

    Directory of Open Access Journals (Sweden)

    Gregory A Ross

    Full Text Available Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.

  6. Synthesis and characterization of novel 2, 2'-bipyrimidine fluorescent derivative for protein binding

    Directory of Open Access Journals (Sweden)

    Padalkar Vikas S

    2011-11-01

    Full Text Available Abstract Background Fluorescent dyes with biocompatible functional group and good fluorescence behavior are used as biosensor for monitoring different biological processes as well as detection of protein assay. All reported fluorophore used as sensors are having high selectivity and sensitivity but till there is more demand to synthesized new fluorophore which have improved fluorescence properties and good biocompatibility. Results Novel 4, 4'-(1, 1'-(5-(2-methoxyphenoxy-[2, 2'-bipyrimidine]-4, 6-diylbis(1H-pyrazol-3, 1-diyl dianiline fluorescent dye was synthesized by multistep synthesis from 2-phenylacetonitrile, 2-chloropyrimidine and 2-methoxyphenol. This dye has absorption at 379 nm with intense single emission at 497 nm having fairly good quantum yield (0.375 and Stokes shift. The intermediates and dye were characterized by FT-IR, 1H NMR, 13C NMR and Mass spectral analysis. The pyrazole bipyrimidine based fluorescent dye possessing two amino groups suitable for binding with protein is reported. Its utility as a biocompatible conjugate was explained by conjugation with bovine serum albumin. The method is based on direct fluorescence detection of fluorophore-labelled protein before and after conjugation. Purified fluorescent conjugate was subsequently analyzed by fluorimetry. The analysis showed that the tested conjugation reaction yielded fluorescent conjugates of the dye through carbodiimide chemistry. Conclusion In summery synthesized fluorophore pyrazole-bipyrimidine has very good interaction towards protein bovine serum albumin and it acts as good candidate for protein assay.

  7. Cell Surface Properties of Lactococcus lactis Reveal Milk Protein Binding Specifically Evolved in Dairy Isolates

    Science.gov (United States)

    Tarazanova, Mariya; Huppertz, Thom; Beerthuyzen, Marke; van Schalkwijk, Saskia; Janssen, Patrick; Wels, Michiel; Kok, Jan; Bachmann, Herwig

    2017-01-01

    Surface properties of bacteria are determined by the molecular composition of the cell wall and they are important for interactions of cells with their environment. Well-known examples of bacterial interactions with surfaces are biofilm formation and the fermentation of solid materials like food and feed. Lactococcus lactis is broadly used for the fermentation of cheese and buttermilk and it is primarily isolated from either plant material or the dairy environment. In this study, we characterized surface hydrophobicity, charge, emulsification properties, and the attachment to milk proteins of 55 L. lactis strains in stationary and exponential growth phases. The attachment to milk protein was assessed through a newly developed flow cytometry-based protocol. Besides finding a high degree of biodiversity, phenotype-genotype matching allowed the identification of candidate genes involved in the modification of the cell surface. Overexpression and gene deletion analysis allowed to verify the predictions for three identified proteins that altered surface hydrophobicity and attachment of milk proteins. The data also showed that lactococci isolated from a dairy environment bind higher amounts of milk proteins when compared to plant isolates. It remains to be determined whether the alteration of surface properties also has potential to alter starter culture functionalities. PMID:28936202

  8. Prediction of protein binding sites using physical and chemical descriptors and the support vector machine regression method

    International Nuclear Information System (INIS)

    Sun Zhong-Hua; Jiang Fan

    2010-01-01

    In this paper a new continuous variable called core-ratio is defined to describe the probability for a residue to be in a binding site, thereby replacing the previous binary description of the interface residue using 0 and 1. So we can use the support vector machine regression method to fit the core-ratio value and predict the protein binding sites. We also design a new group of physical and chemical descriptors to characterize the binding sites. The new descriptors are more effective, with an averaging procedure used. Our test shows that much better prediction results can be obtained by the support vector regression (SVR) method than by the support vector classification method. (rapid communication)

  9. Modifications of nano-titania surface for in vitro evaluations of hemolysis, cytotoxicity, and nonspecific protein binding

    Energy Technology Data Exchange (ETDEWEB)

    Datta, Aparna, E-mail: adatta.research@gmail.com [Jadavpur University, School of Materials Science and Nanotechnology (India); Dasgupta, Sayantan [NRS Medical College and Hospital, Department of Biochemistry (India); Mukherjee, Siddhartha [Jadavpur University, Department of Metallurgical and Material Engineering (India)

    2017-04-15

    In the past decade, a variety of drug carriers based on mesoporous silica nanoparticles has been extensively reported. However, their biocompatibility still remains debatable, which motivated us to explore the porous nanostructures of other metal oxides, for example titanium dioxide (TiO{sub 2}), as potential drug delivery vehicles. Herein, we report the in vitro hemolysis, cytotoxicity, and protein binding of TiO{sub 2} nanoparticles, synthesized by a sol–gel method. The surface of the TiO{sub 2} nanoparticles was modified with hydroxyl, amine, or thiol containing moieties to examine the influence of surface functional groups on the toxicity and protein binding aspects of the nanoparticles. Our study revealed the superior hemocompatibility of pristine, as well as functionalized TiO{sub 2} nanoparticles, compared to that of mesoporous silica, the present gold standard. Among the functional groups studied, aminosilane moieties on the TiO{sub 2} surface substantially reduced the degree of hemolysis (down to 5%). Further, cytotoxicity studies by MTT assay suggested that surface functional moieties play a crucial role in determining the biocompatibility of the nanoparticles. The presence of NH{sub 2}– functional groups on the TiO{sub 2} nanoparticle surface enhanced the cell viability by almost 28% as compared to its native counterpart (at 100 μg/ml), which was in agreement with the hemolysis assay. Finally, nonspecific protein adsorption on functionalized TiO{sub 2} surfaces was examined using human serum albumin and it was found that negatively charged surface moieties, like –OH and –SH, could mitigate protein adsorption to a significant extent.

  10. A Simple, Fast, Low Cost, HPLC/UV Validated Method for Determination of Flutamide: Application to Protein Binding Studies.

    Science.gov (United States)

    Esmaeilzadeh, Sara; Valizadeh, Hadi; Zakeri-Milani, Parvin

    2016-06-01

    The main goal of this study was development of a reverse phase high performance liquid chromatography (RP-HPLC) method for flutamide quantitation which is applicable to protein binding studies. Ultrafilteration method was used for protein binding study of flutamide. For sample analysis, flutamide was extracted by a simple and low cost extraction method using diethyl ether and then was determined by HPLC/UV. Acetanilide was used as an internal standard. The chromatographic system consisted of a reversed-phase C8 column with C8 pre-column, and the mobile phase of a mixture of 29% (v/v) methanol, 38% (v/v) acetonitrile and 33% (v/v) potassium dihydrogen phosphate buffer (50 mM) with pH adjusted to 3.2. Acetanilide and flutamide were eluted at 1.8 and 2.9 min, respectively. The linearity of method was confirmed in the range of 62.5-16000 ng/ml (r(2) > 0.99). The limit of quantification was shown to be 62.5 ng/ml. Precision and accuracy ranges found to be (0.2-1.4%, 90-105%) and (0.2-5.3 %, 86.7-98.5 %) respectively. Acetanilide and flutamide capacity factor values of 1.35 and 2.87, tailing factor values of 1.24 and 1.07 and resolution values of 1.8 and 3.22 were obtained in accordance with ICH guidelines. Based on the obtained results a rapid, precise, accurate, sensitive and cost-effective analysis procedure was proposed for quantitative determination of flutamide.

  11. Modifications of nano-titania surface for in vitro evaluations of hemolysis, cytotoxicity, and nonspecific protein binding

    Science.gov (United States)

    Datta, Aparna; Dasgupta, Sayantan; Mukherjee, Siddhartha

    2017-04-01

    In the past decade, a variety of drug carriers based on mesoporous silica nanoparticles has been extensively reported. However, their biocompatibility still remains debatable, which motivated us to explore the porous nanostructures of other metal oxides, for example titanium dioxide (TiO2), as potential drug delivery vehicles. Herein, we report the in vitro hemolysis, cytotoxicity, and protein binding of TiO2 nanoparticles, synthesized by a sol-gel method. The surface of the TiO2 nanoparticles was modified with hydroxyl, amine, or thiol containing moieties to examine the influence of surface functional groups on the toxicity and protein binding aspects of the nanoparticles. Our study revealed the superior hemocompatibility of pristine, as well as functionalized TiO2 nanoparticles, compared to that of mesoporous silica, the present gold standard. Among the functional groups studied, aminosilane moieties on the TiO2 surface substantially reduced the degree of hemolysis (down to 5%). Further, cytotoxicity studies by MTT assay suggested that surface functional moieties play a crucial role in determining the biocompatibility of the nanoparticles. The presence of NH2- functional groups on the TiO2 nanoparticle surface enhanced the cell viability by almost 28% as compared to its native counterpart (at 100 μg/ml), which was in agreement with the hemolysis assay. Finally, nonspecific protein adsorption on functionalized TiO2 surfaces was examined using human serum albumin and it was found that negatively charged surface moieties, like -OH and -SH, could mitigate protein adsorption to a significant extent.

  12. 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.

  13. 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

  14. 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...

  15. 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…

  16. 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...

  17. 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.

  18. 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.

  19. Negligible depletion solid-phase microextraction with radiolabeled analytes to study free concentrations and protein binding : an example with [3H]Estradiol

    NARCIS (Netherlands)

    Heringa, M.B.; Pastor, D.; Algra, J.; Vaes, W.H.J.; Hemmens, J.L.M.

    2002-01-01

    A new method is presented that enables sensitive measurement of free concentrations of radiolabeled ligands. Additionally, protein binding of radiochemicals in complex matrixes can be determined with this new technique that combines negligible depletion solid-phase microextraction (nd-SPME) with

  20. 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.

  1. 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).

  2. 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.

  3. 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.

  4. 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.

  5. A novel injection strategy of flurbiprofen axetil by inhibiting protein binding with 6-methoxy-2-naphthylacetic acid.

    Science.gov (United States)

    Ogata, Kenji; Takamura, Norito; Tokunaga, Jin; Ikeda, Tetsuya; Setoguchi, Nao; Tanda, Kazuhiro; Yamasaki, Tetsuo; Nishio, Toyotaka; Kawai, Keiichi

    2016-04-01

    Flurbiprofen axetil (FPA) is an injection product and a prodrug of a non-steroidal anti-inflammatory drug (NSAID). After injection, it is rapidly hydrolyzed to the active form, flurbiprofen (FP). Since frequent injections of FPA can lead to abnormal physiology, an administration strategy is necessary to ensure there is enhancement of the analgesic efficiency of FP after a single dose and to reduce the total number of doses. FP strongly binds to site II of albumin, and thus the free (unbound) FP concentration is low. This study focused on 6-methoxy-2-naphthylacetic acid (6-MNA), the active metabolite of nabumetone (a prodrug of NSAID). We performed ultrafiltration experiments and pharmacokinetics analysis in rats to investigate whether the inhibitory effect of 6-MNA on FP binding to albumin increased the free FP concentration in vitro and in vivo. Results indicated that 6-MNA inhibited the binding of FP to albumin competitively. When 6-MNA was injected in rats, there was a significant increase in the free FP concentration and the area under concentration-time curve (AUC) calculated from the free FP concentration, while there was a significant decrease in the total (bound + free) FP concentration and the AUC calculated from the total FP concentration. These findings indicate that 6-MNA inhibits the protein binding of FP in vivo. This suggests that the frequency of FPA injections can be reduced when administered with nabumetone, as there is increase in the free FP concentration associated with pharmacological effect.

  6. Incubation of 14C-trichloroethylene vapor with rat liver microsomes: uptake of radioactivity and covalent protein binding of metabolites

    International Nuclear Information System (INIS)

    Bolt, H.M.; Wolowski, L.; Buchter, A.; Bolt, W.; Gil, D.L.

    1977-01-01

    Microsomal uptake irreversible protein binding of labelled trichloroehtylene was measured following incubation with rat liver microsomes in an all-glass vacuum system. If the cofactor for oxidative metabolism, NADPH, is not added, the gaseous trichloroethylene rapidly equilibrates with the microsomal suspension. Addition of NADPH results in a further uptake of 14 C-trichloroethylene from the gas phase, linearly with time, which is due to enzymic metabolism. This part of uptake is inhibited by some arylimidazoles and 1.2.3-benzothiadiazoles. The compounds of greatest inhibitory potency were 6-chloro-1.2.3-benzothiadiazole and 5.6-dimethyl-1.2.3-benzothiadiazole. Part of the metabolites of 14 C-trichloroethylene formed by rat liver microsomes were irreversibly bound to microsomal protein, amounting up to 1 nmol per mg microsomal protein per hour. Model experiments on uptake of 14 C-trichloroethylene from the gas phase by albumin solutions and liposomal suspensions (from lecithin) showed a rapid equilibration of trichloroethylene also with these systems. Comparison with previous analogous data on vinyl chloride revealed an about 10 times higher affinity of trichloroethylene to albumin and lipid, consistent with the behaviour of both compounds in the rat liver microsomal system. (orig.) [de

  7. 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.

  8. 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.

  9. Single daily dosing of antibiotics: importance of in vitro killing rate, serum half-life, and protein binding.

    Science.gov (United States)

    Potel, G; Chau, N P; Pangon, B; Fantin, B; Vallois, J M; Faurisson, F; Carbon, C

    1991-10-01

    The relative importance of pharmacokinetic and pharmacodynamic parameters for the feasibility of a single daily dose (SDD) of antibiotics remains to be established. Therefore, we studied the relationship between in vitro bacteriological parameters (MIC, MBC, and killing rate [KR], defined as the reduction in the inoculum within 3 h), pharmacokinetic parameters (t1/2 and protein binding [PB], and in vivo antibacterial effect of a single antibiotic dose in an experimental rabbit model of Escherichia coli endocarditis. Nine antibiotics were investigated: two aminoglycosides, two quinolones, and five beta-lactams. For each drug, the minimal effective dose (MED) (in milligrams per kilogram) was defined as the lowest dose able to achieve a significant difference (P less than 0.05) of CFU in the vegetations in comparison with controls 24 h after a single intravenous injection. Aminoglycosides and quinolones had the lowest MEDs, followed by beta-lactams. Univariate regression analysis showed that KR was the major determinant of MED. A stepwise regression analysis showed that t1/2 significantly improved the predictive value of KR, while PB, MIC, and MBC did not. The final equation was MED = 1,586-238 KR-297 t1/2 (r = 0.90, P = 0.01). We concluded that the pharmacodynamic parameters (especially the high KR) of aminoglycosides and quinolones explained their low MEDs and might allow SDD. In contrast, the low KR of beta-lactams emphasized the critical importance of a long t1/2, as for ceftriaxone, allowing the use of this beta-lactam alone in SDD.

  10. 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)

  11. Hantaan Virus Nucleocapsid Protein Binds to Importin alpha Proteins and Inhibits Tumor Necrosis Factor Alpha-Induced Activation of Nuclear Factor Kappa B

    Science.gov (United States)

    2008-11-19

    Microbiology . All Rights Reserved. Hantaan Virus Nucleocapsid Protein Binds to Importin Proteins and Inhibits Tumor Necrosis Factor Alpha-Induced...Division, U.S. Army Medical Research Institute of Infectious Diseases, Fort Detrick, Maryland 21702,1 and Department of Microbiology , Mount Sinai...34–36. 32. Prescott , J., C. Ye, G. Sen, and B. Hjelle. 2005. Induction of innate immune response genes by Sin Nombre hantavirus does not require

  12. Cytoplasmic protein binding to highly conserved sequences in the 3' untranslated region of mouse protamine 2 mRNA, a translationally regulated transcript of male germ cells

    International Nuclear Information System (INIS)

    Kwon, Y.K.; Hecht, N.B.

    1991-01-01

    The expression of the protamines, the predominant nuclear proteins of mammalian spermatozoa, is regulated translationally during male germ-cell development. The 3' untranslated region (UTR) of protamine 1 mRNA has been reported to control its time of translation. To understand the mechanisms controlling translation of the protamine mRNAs, we have sought to identify cis elements of the 3' UTR of protamine 2 mRNA that are recognized by cytoplasmic factors. From gel retardation assays, two sequence elements are shown to form specific RNA-protein complexes. Protein binding sites of the two complexes were determined by RNase T1 mapping, by blocking the putative binding sites with antisense oligonucleotides, and by competition assays. The sequences of these elements, located between nucleotides + 537 and + 572 in protamine 2 mRNA, are highly conserved among postmeiotic translationally regulated nuclear proteins of the mammalian testis. Two closely linked protein binding sites were detected. UV-crosslinking studies revealed that a protein of about 18 kDa binds to one of the conserved sequences. These data demonstrate specific protein binding to a highly conserved 3' UTR of translationally regulated testicular mRNA

  13. 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)

  14. Can Future Academic Surgeons be Identified in the Residency Ranking Process?

    Science.gov (United States)

    Beninato, Toni; Kleiman, David A; Zarnegar, Rasa; Fahey, Thomas J

    2016-01-01

    The goal of surgical residency training programs is to train competent surgeons. Academic surgical training programs also have as a mission training future academicians-surgical scientists, teachers, and leaders. However, selection of surgical residents is dependent on a relatively unscientific process. Here we sought to determine how well the residency selection process is able to identify future academicians in surgery. Rank lists from an academic surgical residency program from 1992 to 1997 were examined. All ranked candidates׳ career paths after residency were reviewed to determine whether they stayed in academics, were university affiliated, or in private practice. The study was performed at New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY. A total of 663 applicants for general surgery residency participated in this study. In total 6 rank lists were evaluated, which included 663 candidates. Overall 76% remained in a general surgery subspecialty. Of those who remained in general surgery, 49% were in private practice, 20% were university affiliated, and 31% had academic careers. Approximately 47% of candidates that were ranked in the top 20 had ≥20 publications, with decreasing percentages as rank number increased. There was a strong correlation between the candidates׳ rank position and pursuing an academic career (p career. The residency selection process can identify candidates likely to be future academicians. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  15. Does resident ranking during recruitment accurately predict subsequent performance as a surgical resident?

    Science.gov (United States)

    Fryer, Jonathan P; Corcoran, Noreen; George, Brian; Wang, Ed; Darosa, Debra

    2012-01-01

    While the primary goal of ranking applicants for surgical residency training positions is to identify the candidates who will subsequently perform best as surgical residents, the effectiveness of the ranking process has not been adequately studied. We evaluated our general surgery resident recruitment process between 2001 and 2011 inclusive, to determine if our recruitment ranking parameters effectively predicted subsequent resident performance. We identified 3 candidate ranking parameters (United States Medical Licensing Examination [USMLE] Step 1 score, unadjusted ranking score [URS], and final adjusted ranking [FAR]), and 4 resident performance parameters (American Board of Surgery In-Training Examination [ABSITE] score, PGY1 resident evaluation grade [REG], overall REG, and independent faculty rating ranking [IFRR]), and assessed whether the former were predictive of the latter. Analyses utilized Spearman correlation coefficient. We found that the URS, which is based on objective and criterion based parameters, was a better predictor of subsequent performance than the FAR, which is a modification of the URS based on subsequent determinations of the resident selection committee. USMLE score was a reliable predictor of ABSITE scores only. However, when we compared our worst residence performances with the performances of the other residents in this evaluation, the data did not produce convincing evidence that poor resident performances could be reliably predicted by any of the recruitment ranking parameters. Finally, stratifying candidates based on their rank range did not effectively define a ranking cut-off beyond which resident performance would drop off. Based on these findings, we recommend surgery programs may be better served by utilizing a more structured resident ranking process and that subsequent adjustments to the rank list generated by this process should be undertaken with caution. Copyright © 2012 Association of Program Directors in Surgery

  16. 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)

  17. 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

  18. 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.

  19. RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

    Science.gov (United States)

    Pan, Xiaoyong; Shen, Hong-Bin

    2017-02-28

    RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recognize the target RNAs and why they bind specific positions is still far from clear. Machine learning-based algorithms are widely acknowledged to be capable of speeding up this process. Although many automatic tools have been developed to predict the RNA-protein binding sites from the rapidly growing multi-resource data, e.g. sequence, structure, their domain specific features and formats have posed significant computational challenges. One of current difficulties is that the cross-source shared common knowledge is at a higher abstraction level beyond the observed data, resulting in a low efficiency of direct integration of observed data across domains. The other difficulty is how to interpret the prediction results. Existing approaches tend to terminate after outputting the potential discrete binding sites on the sequences, but how to assemble them into the meaningful binding motifs is a topic worth of further investigation. In viewing of these challenges, we propose a deep learning-based framework (iDeep) by using a novel hybrid convolutional neural network and deep belief network to predict the RBP interaction sites and motifs on RNAs. This new protocol is featured by transforming the original observed data into a high-level abstraction feature space using multiple layers of learning blocks, where the shared representations across different domains are integrated. To validate our iDeep method, we performed experiments on 31 large-scale CLIP-seq datasets, and our results show that by integrating multiple sources of data, the average AUC can be improved by 8% compared to the best single-source-based predictor; and through cross-domain knowledge integration at an abstraction level, it outperforms the state-of-the-art predictors by 6

  20. 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.

  1. 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.

  2. Citizen Candidates Under Uncertainty

    OpenAIRE

    Eguia, Jon X.

    2005-01-01

    In this paper we make two contributions to the growing literature on "citizen-candidate" models of representative democracy. First, we add uncertainty about the total vote count. We show that in a society with a large electorate, where the outcome of the election is uncertain and where winning candidates receive a large reward from holding office, there will be a two-candidate equilibrium and no equilibria with a single candidate. Second, we introduce a new concept of equilibrium, which we te...

  3. Validation of SmartRank: A likelihood ratio software for searching national DNA databases with complex DNA profiles.

    Science.gov (United States)

    Benschop, Corina C G; van de Merwe, Linda; de Jong, Jeroen; Vanvooren, Vanessa; Kempenaers, Morgane; Kees van der Beek, C P; Barni, Filippo; Reyes, Eusebio López; Moulin, Léa; Pene, Laurent; Haned, Hinda; Sijen, Titia

    2017-07-01

    Searching a national DNA database with complex and incomplete profiles usually yields very large numbers of possible matches that can present many candidate suspects to be further investigated by the forensic scientist and/or police. Current practice in most forensic laboratories consists of ordering these 'hits' based on the number of matching alleles with the searched profile. Thus, candidate profiles that share the same number of matching alleles are not differentiated and due to the lack of other ranking criteria for the candidate list it may be difficult to discern a true match from the false positives or notice that all candidates are in fact false positives. SmartRank was developed to put forward only relevant candidates and rank them accordingly. The SmartRank software computes a likelihood ratio (LR) for the searched profile and each profile in the DNA database and ranks database entries above a defined LR threshold according to the calculated LR. In this study, we examined for mixed DNA profiles of variable complexity whether the true donors are retrieved, what the number of false positives above an LR threshold is and the ranking position of the true donors. Using 343 mixed DNA profiles over 750 SmartRank searches were performed. In addition, the performance of SmartRank and CODIS were compared regarding DNA database searches and SmartRank was found complementary to CODIS. We also describe the applicable domain of SmartRank and provide guidelines. The SmartRank software is open-source and freely available. Using the best practice guidelines, SmartRank enables obtaining investigative leads in criminal cases lacking a suspect. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. 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.

  5. 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.

  6. 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...

  7. 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

  8. 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....

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

    Directory of Open Access Journals (Sweden)

    Aronow Bruce J

    2009-02-01

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

  10. Application of a UPLC–MS/MS method to the protein binding study of TM-2 in rat, human and beagle dog plasma

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2016-02-01

    Full Text Available TM-2 known as a potential antitumor drug is a novel semi-synthetic taxane derivative. As drug–protein interactions contribute to insights into pharmacokinetic and pharmacodynamic properties, we elucidated the binding of TM-2 to plasma protein. In this study, a simple, rapid and reliable method was developed and validated employing equilibrium dialysis for the separation of bound and unbound drugs and ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS for the quantitation. Protein binding reached equilibrium within 24 h of incubation at 37 °C. After liquid–liquid extraction with methyl tert-butyl ether, the samples were separated on Thermo Syncronis UPLC® C18 (2.1 mm×50 mm, 1.7 µm, and acquisition of mass spectrometric data was performed in multiple reaction monitoring (MRM mode via positive electrospray ionization. The assay was linear over the concentration rang of 5–2000 ng/mL. The intra- and inter-day precisions were 0.1%–14.8%, and the accuracy was from −6.4% to 7.0%. This assay has been successfully applied to a protein binding study of TM-2 in rat, human and beagle dog plasma. TM-2 showed high protein binding of 81.4%±6.5% (rat, 87.9%±3.6% (human and 79.4%±4.0% (beagle dog. The results revealed that there was an insignificant difference among the three species.

  11. Serum protein binding displacement: theoretical analysis using a hypothetical radiopharmaceutical and experimental analysis with 123I-N-isopropyl-p-iodoamphetamine

    International Nuclear Information System (INIS)

    Kawai, Keiichi; Nishii, Ryuichi; Shikano, Naoto; Makino, Nobuo; Kuga, Noriyuki; Yoshimoto, Mitsuyoshi; Jinnouchi, Seishi; Nagamachi, Shigeki; Tamura, Shozo; Takamura, Norito

    2009-01-01

    Introduction: The binding of radiopharmaceutical to serum proteins is thought to be an important factor that restricts its excretion and accumulation in tissue. We calculated the effect of inhibitors of serum protein binding using a hypothetical radiopharmaceutical. In vitro experiments and protein binding inhibitor-loaded monkey scintigraphy were then conducted using 123 I-N-isopropyl-p-iodoamphetamine (IMP) as the radiopharmaceutical. Methods: Free fraction ratios of radiopharmaceutical were calculated with one radiopharmaceutical, two serum proteins and two specific inhibitors in the steady state at various serum protein concentrations. In vitro protein binding inhibition studies using human, rat and monkey sera were performed with site-selective displacers of specific binding sites: 400 μM 6-methoxy-2-naphthylacetic acid (6MNA; a major nabumeton metabolite) as a serum albumin Site II inhibitor and 400 μM erythromycin (ETC) as an α 1 -acid glycoprotein (AGP) site inhibitor. Scintigraphy with or without 6MNA loading of monkeys was performed. Results: The theoretical findings roughly corresponded to the experimental results. Approximately 75% of IMP bound to serum albumin Site II and AGP in the species examined. The free fraction of IMP (25.0±0.6% for human, 22.8±0.4% for monkey, 23.7±0.3% for rat) increased with loading of specific protein binding inhibitors (6MNA: 28.0±0.3% for human, 24.5±0.7% for monkey, 24.3±0.2% for rat; ETC: 26.3±0.4% for human, 29.5±1.1% for monkey, 26.0±0.7% for rat) and was serum protein concentration dependant based on the results of calculations. Simultaneous administration of 6MNA and ETC produced a higher free fraction ratio of IMP (31.9±1.0% for human, 34.6±0.4% for monkey, 27.0±0.3% for rat) than summation of the single administrations of 6MNA and ETC (domino effect) in human, rat and monkey sera. Rapid cerebral accumulation was observed with 6MNA loading in monkey scintigraphy. Conclusions: 6MNA appears to change

  12. The T alpha 2 nuclear protein binding site from the human T cell receptor alpha enhancer functions as both a T cell-specific transcriptional activator and repressor

    OpenAIRE

    1990-01-01

    T cell-specific expression of the human T cell receptor alpha (TCR- alpha) gene is regulated by the interaction of variable region promoter elements with a transcriptional enhancer that is located 4.5 kb 3' of the TCR-alpha constant region (C alpha) gene segment. The minimal TCR- alpha enhancer is composed of two nuclear protein binding sites, T alpha 1 and T alpha 2, that are both required for the T cell-specific activity of the enhancer. The T alpha 1 binding site contains a consensus cAMP ...

  13. 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…

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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. ...

  19. 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.

  20. 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.

  1. 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...

  2. 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.

  3. Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants

    Science.gov (United States)

    Hüllermeier, Eyke; Fürnkranz, Johannes

    The term “preference learning” refers to the application of machine learning methods for inducing preference models from empirical data. In the recent literature, corresponding problems appear in various guises. After a brief overview of the field, this work focuses on a particular learning scenario called label ranking where the problem is to learn a mapping from instances to rankings over a finite number of labels. Our approach for learning such a ranking function, called ranking by pairwise comparison (RPC), first induces a binary preference relation from suitable training data, using a natural extension of pairwise classification. A ranking is then derived from this relation by means of a ranking procedure. This paper elaborates on a key advantage of such an approach, namely the fact that our learner can be adapted to different loss functions by using different ranking procedures on the same underlying order relations. In particular, the Spearman rank correlation is minimized by using a simple weighted voting procedure. Moreover, we discuss a loss function suitable for settings where candidate labels must be tested successively until a target label is found. In this context, we propose the idea of “empirical conditioning” of class probabilities. A related ranking procedure, called “ranking through iterated choice”, is investigated experimentally.

  4. 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.

  5. General correlation and partial correlation analysis in finding interactions: with Spearman rank correlation and proportion correlation as correlation measures

    OpenAIRE

    WenJun Zhang; Xin Li

    2015-01-01

    Between-taxon interactions can be detected by calculating the sampling data of taxon sample type. In present study, Spearman rank correlation and proportion correlation are chosen as the general correlation measures, and their partial correlations are calculated and compared. The results show that for Spearman rank correlation measure, in all predicted candidate direct interactions by partial correlation, about 16.77% (x, 0-45.4%) of them are not successfully detected by Spearman rank correla...

  6. Development and validation of a high-performance liquid chromatography method for the quantification of talazoparib in rat plasma: Application to plasma protein binding studies.

    Science.gov (United States)

    Hidau, Mahendra Kumar; Kolluru, Srikanth; Palakurthi, Srinath

    2018-02-01

    A sensitive and selective RP-HPLC method has been developed and validated for the quantification of a highly potent poly ADP ribose polymerase inhibitor talazoparib (TZP) in rat plasma. Chromatographic separation was performed with isocratic elution method. Absorbance for TZP was measured with a UV detector (SPD-20A UV-vis) at a λ max of 227 nm. Protein precipitation was used to extract the drug from plasma samples using methanol-acetonitrile (65:35) as the precipitating solvent. The method proved to be sensitive and reproducible over a 100-2000 ng/mL linearity range with a lower limit of quantification (LLQC) of 100 ng/mL. TZP recovery was found to be >85%. Following analytical method development and validation, it was successfully employed to determine the plasma protein binding of TZP. TZP has a high level of protein binding in rat plasma (95.76 ± 0.38%) as determined by dialysis method. Copyright © 2017 John Wiley & Sons, Ltd.

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

    KAUST Repository

    Zhang, Tianzhu

    2014-06-19

    Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against 14 state-of-the-art tracking methods on a set of 25 challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time.

  14. Low-rank sparse learning for robust visual tracking

    KAUST Repository

    Zhang, Tianzhu

    2012-01-01

    In this paper, we propose a new particle-filter based tracking algorithm that exploits the relationship between particles (candidate targets). By representing particles as sparse linear combinations of dictionary templates, this algorithm capitalizes on the inherent low-rank structure of particle representations that are learned jointly. As such, it casts the tracking problem as a low-rank matrix learning problem. This low-rank sparse tracker (LRST) has a number of attractive properties. (1) Since LRST adaptively updates dictionary templates, it can handle significant changes in appearance due to variations in illumination, pose, scale, etc. (2) The linear representation in LRST explicitly incorporates background templates in the dictionary and a sparse error term, which enables LRST to address the tracking drift problem and to be robust against occlusion respectively. (3) LRST is computationally attractive, since the low-rank learning problem can be efficiently solved as a sequence of closed form update operations, which yield a time complexity that is linear in the number of particles and the template size. We evaluate the performance of LRST by applying it to a set of challenging video sequences and comparing it to 6 popular tracking methods. Our experiments show that by representing particles jointly, LRST not only outperforms the state-of-the-art in tracking accuracy but also significantly improves the time complexity of methods that use a similar sparse linear representation model for particles [1]. © 2012 Springer-Verlag.

  15. 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.

  16. Preclinical pharmacokinetics, tissue distribution and plasma protein binding of sodium (±-5-bromo-2-(α-hydroxypentyl benzoate (BZP, an innovative potent anti-ischemic stroke agent

    Directory of Open Access Journals (Sweden)

    Xin Tian

    2016-08-01

    Full Text Available Sodium (±-5-bromo-2-(α-hydroxypentyl benzoate (BZP is a potential cardiovascular drug and exerts potent neuroprotective effect against transient and long-term ischemic stroke in rats. BZP could convert into 3-butyl-6-bromo-1(3H-isobenzofuranone (Br-NBP in vitro and in vivo. However, the pharmacokinetic profiles of BZP and Br-NBP still have not been evaluated. For the purpose of investigating the pharmacokinetic profiles, tissue distribution and plasma protein binding of BZP and Br-NBP, a rapid, sensitive and specific method based on liquid chromatography coupled to mass spectrometry (LC-MS/MS has been developed for determination of BZP and Br-NBP in biological samples. The results indicated that BZP and Br-NBP showed a short elimination half-life, and pharmacokinetic profile in rats (3, 6 and 12 mg/kg; i.v. and beagle dogs (1, 2 and 4 mg/kg; i.v.gtt were obtained after single dosing of BZP. After multiple dosing of BZP, there was no significant accumulation of BZP and Br-NBP in the plasma of rats and beagle dogs. Following i.v. single dose (6 mg/kg to rats, BZP and Br-NBP were distributed rapidly into all tissues examined, with the highest concentrations of BZP and Br-NBP in lung and kidney, respectively. The brain distribution of Br-NBP in middle cerebral artery occlusion (MCAO rats was more than in normal rats (P<0.05. The plasma protein binding degree of BZP at three concentrations (8000, 20000 and 80000 ng/mL from rat, beagle dog and human plasma were 98.1~98.7%, 88.9~92.7% and 74.8%~83.7% respectively. In conclusion, both BZP and Br-NBP showed short half-life, good dose-linear pharmacokinetic profile, wide tissue distribution and different degree protein binding to various species plasma. This was the first preclinical pharmacokinetic investigation of BZP and Br-NBP in both rats and beagle dogs, which provided vital guidance for further preclinical research and the subsequent clinical trials.

  17. 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.

  18. 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;…

  19. 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…

  20. Evaluations of in vitro metabolism, drug-drug interactions mediated by reversible and time-dependent inhibition of CYPs, and plasma protein binding of MMB4 DMS.

    Science.gov (United States)

    Hong, S Peter; Lusiak, Bozena D; Burback, Brian L; Johnson, Jerry D

    2013-01-01

    1,1'-Methylenebis[4-[(hydroxyimino)methyl]-pyridinium] (MMB4) dimethanesulfonate (DMS) is a bisquaternary pyridinium aldoxime that reactivates acetylcholinesterase inhibited by organophosphorus nerve agent. Drug metabolism and plasma protein binding for MMB4 DMS were examined using various techniques and a wide range of species. When (14)C-MMB4 DMS was incubated in liver microsomes, 4-pyridine aldoxime (4-PA) and an additional metabolite were detected in all species tested. Identity of the additional metabolite was postulated to be isonicotinic acid (INA) based on liquid chromatography with a tandem mass spectrometry analysis, which was confirmed by comparison with authentic INA. Formation of INA was dependent on species, with the highest level found in monkey liver microsomes. The MMB4 DMS exhibited reversible inhibition in a concentration-dependent manner toward cytochrome P450 1A2 (CYP1A2), CYP2C9, CYP2C19, CYP2D6, and CYP3A4 in human liver microsomes showing the highest inhibition for CYP2D6. Human recombinant CYPs were used to evaluate inhibitory curves more adequately and determine detailed kinetic constants for reversible inhibition and potential time-dependent inhibition (TDI). The MMB4 DMS exhibited reversible inhibition toward human-recombinant CYP2D6 with an inhibition constant (K i) value of 66.6 µmol/L. Based on the k inact/K I values, MMB4 DMS was found to exhibit the most potent TDI toward CYP2D6. The MMB4 DMS at 5 different concentrations was incubated in plasma for 5 hours using an equilibrium dialysis device. For all species tested, there were no concentration-dependent changes in plasma protein binding, ranging from 10% to 17%. These results suggest that MMB4 was not extensively bound to plasma protein, and there were no overt species-related differences in the extent of MMB4 bound to plasma protein.

  1. A Physiologically Based Pharmacokinetic Model to Predict the Pharmacokinetics of Highly Protein-Bound Drugs and Impact of Errors in Plasma Protein Binding

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2015-01-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data was often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding, and blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for terminal elimination half-life (t1/2, 100% of drugs), peak plasma concentration (Cmax, 100%), area under the plasma concentration-time curve (AUC0–t, 95.4%), clearance (CLh, 95.4%), mean retention time (MRT, 95.4%), and steady state volume (Vss, 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. PMID:26531057

  2. A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding.

    Science.gov (United States)

    Ye, Min; Nagar, Swati; Korzekwa, Ken

    2016-04-01

    Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t1/2 , 100% of drugs), peak plasma concentration (Cmax , 100%), area under the plasma concentration-time curve (AUC0-t , 95.4%), clearance (CLh , 95.4%), mean residence time (MRT, 95.4%) and steady state volume (Vss , 90.9%). The impact of fup errors on CLh and Vss prediction was evaluated. Errors in fup resulted in proportional errors in clearance prediction for low-clearance compounds, and in Vss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in fup did not propagate to errors in Vss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  3. Entrapment of alpha1-acid glycoprotein in high-performance affinity columns for drug-protein binding studies.

    Science.gov (United States)

    Bi, Cong; Jackson, Abby; Vargas-Badilla, John; Li, Rong; Rada, Giana; Anguizola, Jeanethe; Pfaunmiller, Erika; Hage, David S

    2016-05-15

    A slurry-based method was developed for the entrapment of alpha1-acid glycoprotein (AGP) for use in high-performance affinity chromatography to study drug interactions with this serum protein. Entrapment was achieved based on the physical containment of AGP in hydrazide-activated porous silica supports and by using mildly oxidized glycogen as a capping agent. The conditions needed for this process were examined and optimized. When this type of AGP column was used in binding studies, the association equilibrium constant (Ka) measured by frontal analysis at pH 7.4 and 37°C for carbamazepine with AGP was found to be 1.0 (±0.5)×10(5)M(-1), which agreed with a previously reported value of 1.0 (±0.1)×10(5)M(-1). Binding studies based on zonal elution were conducted for several other drugs with such columns, giving equilibrium constants that were consistent with literature values. An entrapped AGP column was also used in combination with a column containing entrapped HSA in a screening assay format to compare the binding of various drugs to AGP and HSA. These results also agreed with previous data that have been reported in literature for both of these proteins. The same entrapment method could be extended to other proteins and to the investigation of additional types of drug-protein interactions. Potential applications include the rapid quantitative analysis of biological interactions and the high-throughput screening of drug candidates for their binding to a given protein. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. PEACE: pulsar evaluation algorithm for candidate extraction - a software package for post-analysis processing of pulsar survey candidates

    Science.gov (United States)

    Lee, K. J.; Stovall, K.; Jenet, F. A.; Martinez, J.; Dartez, L. P.; Mata, A.; Lunsford, G.; Cohen, S.; Biwer, C. M.; Rohr, M.; Flanigan, J.; Walker, A.; Banaszak, S.; Allen, B.; Barr, E. D.; Bhat, N. D. R.; Bogdanov, S.; Brazier, A.; Camilo, F.; Champion, D. J.; Chatterjee, S.; Cordes, J.; Crawford, F.; Deneva, J.; Desvignes, G.; Ferdman, R. D.; Freire, P.; Hessels, J. W. T.; Karuppusamy, R.; Kaspi, V. M.; Knispel, B.; Kramer, M.; Lazarus, P.; Lynch, R.; Lyne, A.; McLaughlin, M.; Ransom, S.; Scholz, P.; Siemens, X.; Spitler, L.; Stairs, I.; Tan, M.; van Leeuwen, J.; Zhu, W. W.

    2013-07-01

    Modern radio pulsar surveys produce a large volume of prospective candidates, the majority of which are polluted by human-created radio frequency interference or other forms of noise. Typically, large numbers of candidates need to be visually inspected in order to determine if they are real pulsars. This process can be labour intensive. In this paper, we introduce an algorithm called Pulsar Evaluation Algorithm for Candidate Extraction (PEACE) which improves the efficiency of identifying pulsar signals. The algorithm ranks the candidates based on a score function. Unlike popular machine-learning-based algorithms, no prior training data sets are required. This algorithm has been applied to data from several large-scale radio pulsar surveys. Using the human-based ranking results generated by students in the Arecibo Remote Command Center programme, the statistical performance of PEACE was evaluated. It was found that PEACE ranked 68 per cent of the student-identified pulsars within the top 0.17 per cent of sorted candidates, 95 per cent within the top 0.34 per cent and 100 per cent within the top 3.7 per cent. This clearly demonstrates that PEACE significantly increases the pulsar identification rate by a factor of about 50 to 1000. To date, PEACE has been directly responsible for the discovery of 47 new pulsars, 5 of which are millisecond pulsars that may be useful for pulsar timing based gravitational-wave detection projects.

  5. 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.

  6. 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...

  7. 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.

  8. Design of a fuzzy ranking system for admission processes in higher ...

    African Journals Online (AJOL)

    specific knowledge, as well as the knowledge and analytical skills of one or more human experts and reasons with ... In this paper we introduced fuzzy harming distance function into candidates ranking and implemented it with Java Netbean IDE 6.0.

  9. Developing an Open-Source Bibliometric Ranking Website Using Google Scholar Citation Profiles for Researchers in the Field of Biomedical Informatics.

    Science.gov (United States)

    Sittig, Dean F; McCoy, Allison B; Wright, Adam; Lin, Jimmy

    2015-01-01

    We developed the Biomedical Informatics Researchers ranking website (rank.informatics-review.com) to overcome many of the limitations of previous scientific productivity ranking strategies. The website is composed of four key components that work together to create an automatically updating ranking website: (1) list of biomedical informatics researchers, (2) Google Scholar scraper, (3) display page, and (4) updater. The site has been useful to other groups in evaluating researchers, such as tenure and promotions committees in interpreting the various citation statistics reported by candidates. Creation of the Biomedical Informatics Researchers ranking website highlights the vast differences in scholarly productivity among members of the biomedical informatics research community.

  10. 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.

  11. Novel Prostate Specific Antigen plastic antibody designed with charged binding sites for an improved protein binding and its application in a biosensor of potentiometric transduction

    International Nuclear Information System (INIS)

    Rebelo, Tânia S.C.R.; Santos, C.; Costa-Rodrigues, J.; Fernandes, M.H.; Noronha, João P.; Sales, M. Goreti F.

    2014-01-01

    Graphical abstract: EF13-201, Novel Prostate Specific Antigen plastic antibody designed with charged binding sites for an improved protein binding and its application in a biosensor of potentiometric transduction. - Abstract: This work shows that the synthesis of protein plastic antibodies tailored with selected charged monomers around the binding site enhances protein binding. These charged receptor sites are placed over a neutral polymeric matrix, thus inducing a suitable orientation the protein reception to its site. This is confirmed by preparing control materials with neutral monomers and also with non-imprinted template. This concept has been applied here to Prostate Specific Antigen (PSA), the protein of choice for screening prostate cancer throughout the population, with serum levels >10 ng/mL pointing out a high probability of associated cancer. Protein Imprinted Materials with charged binding sites (C/PIM) have been produced by surface imprinting over graphene layers to which the protein was first covalently attached. Vinylbenzyl(trimethylammonium chloride) and vinyl benzoate were introduced as charged monomers labelling the binding site and were allowed to self-organize around the protein. The subsequent polymerization was made by radical polymerization of vinylbenzene. Neutral PIM (N/PIM) prepared without oriented charges and non imprinted materials (NIM) obtained without template were used as controls. These materials were used to develop simple and inexpensive potentiometric sensor for PSA. They were included as ionophores in plasticized PVC membranes, and tested over electrodes of solid or liquid conductive contacts, made of conductive carbon over a syringe or of inner reference solution over micropipette tips. The electrodes with charged monomers showed a more stable and sensitive response, with an average slope of -44.2 mV/decade and a detection limit of 5.8 × 10 −11 mol/L (2 ng/mL). The corresponding non-imprinted sensors showed lower

  12. 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)

  13. 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...

  14. 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....

  15. 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....

  16. RANK rewires energy homeostasis in lung cancer cells and drives primary lung cancer.

    Science.gov (United States)

    Rao, Shuan; Sigl, Verena; Wimmer, Reiner Alois; Novatchkova, Maria; Jais, Alexander; Wagner, Gabriel; Handschuh, Stephan; Uribesalgo, Iris; Hagelkruys, Astrid; Kozieradzki, Ivona; Tortola, Luigi; Nitsch, Roberto; Cronin, Shane J; Orthofer, Michael; Branstetter, Daniel; Canon, Jude; Rossi, John; D'Arcangelo, Manolo; Botling, Johan; Micke, Patrick; Fleur, Linnea La; Edlund, Karolina; Bergqvist, Michael; Ekman, Simon; Lendl, Thomas; Popper, Helmut; Takayanagi, Hiroshi; Kenner, Lukas; Hirsch, Fred R; Dougall, William; Penninger, Josef M

    2017-10-15

    Lung cancer is the leading cause of cancer deaths. Besides smoking, epidemiological studies have linked female sex hormones to lung cancer in women; however, the underlying mechanisms remain unclear. Here we report that the receptor activator of nuclear factor-kB (RANK), the key regulator of osteoclastogenesis, is frequently expressed in primary lung tumors, an active RANK pathway correlates with decreased survival, and pharmacologic RANK inhibition reduces tumor growth in patient-derived lung cancer xenografts. Clonal genetic inactivation of KRas G12D in mouse lung epithelial cells markedly impairs the progression of KRas G12D -driven lung cancer, resulting in a significant survival advantage. Mechanistically, RANK rewires energy homeostasis in human and murine lung cancer cells and promotes expansion of lung cancer stem-like cells, which is blocked by inhibiting mitochondrial respiration. Our data also indicate survival differences in KRas G12D -driven lung cancer between male and female mice, and we show that female sex hormones can promote lung cancer progression via the RANK pathway. These data uncover a direct role for RANK in lung cancer and may explain why female sex hormones accelerate lung cancer development. Inhibition of RANK using the approved drug denosumab may be a therapeutic drug candidate for primary lung cancer. © 2017 Rao et al.; Published by Cold Spring Harbor Laboratory Press.

  17. Multi-dimensional Rankings, Program Termination, and Complexity Bounds of Flowchart Programs

    Science.gov (United States)

    Alias, Christophe; Darte, Alain; Feautrier, Paul; Gonnord, Laure

    Proving the termination of a flowchart program can be done by exhibiting a ranking function, i.e., a function from the program states to a well-founded set, which strictly decreases at each program step. A standard method to automatically generate such a function is to compute invariants for each program point and to search for a ranking in a restricted class of functions that can be handled with linear programming techniques. Previous algorithms based on affine rankings either are applicable only to simple loops (i.e., single-node flowcharts) and rely on enumeration, or are not complete in the sense that they are not guaranteed to find a ranking in the class of functions they consider, if one exists. Our first contribution is to propose an efficient algorithm to compute ranking functions: It can handle flowcharts of arbitrary structure, the class of candidate rankings it explores is larger, and our method, although greedy, is provably complete. Our second contribution is to show how to use the ranking functions we generate to get upper bounds for the computational complexity (number of transitions) of the source program. This estimate is a polynomial, which means that we can handle programs with more than linear complexity. We applied the method on a collection of test cases from the literature. We also show the links and differences with previous techniques based on the insertion of counters.

  18. Biofabrication of Zinc Oxide Nanoparticle from Ochradenus baccatus Leaves: Broad-Spectrum Antibiofilm Activity, Protein Binding Studies, and In Vivo Toxicity and Stress Studies

    Directory of Open Access Journals (Sweden)

    Nasser A. Al-Shabib

    2018-01-01

    Full Text Available Biofilms are complex aggregation of cells that are embedded in EPS matrix. These microcolonies are highly resistant to drugs and are associated with various diseases. Biofilms have greatly affected the food safety by causing severe losses due to food contamination and spoilage. Therefore, novel antibiofilm agents are needed. This study investigates the antibiofilm and protein binding activity of zinc nanoparticles (ZnNPs synthesized from leaf extract of Ochradenus baccatus. Standard physical techniques, including UV-visible spectroscopy Fourier transform infrared spectroscopy and X-ray diffraction and transmission electron microscopy, were used to characterize the synthesized OB-ZnNPs. Synthesized OB-ZnNPs demonstrated significant biofilm inhibition in human and food-borne pathogens (Chromobacterium violaceum, Escherichia coli, P. aeruginosa, Klebsiella pneumoniae, Serratia marcescens, and Listeria monocytogenes at subinhibitory concentrations. OB-ZnNPs significantly reduced the virulence factors like violacein, prodigiosin, and alginate and impaired swarming migration and EPS production. OB-ZnNPs demonstrated efficient binding with HSA protein and no change in their structure or stability was observed. In addition, in vivo toxicity evaluation confirmed that OB-ZnNPs possessed no serious toxic effect even at higher doses. Moreover, they were found to have excellent antioxidant properties that can be employed in the fields of food safety and medicine. Hence, it is envisaged that the OB-ZnNPs can be used as potential nanomaterials to combat drug resistant bacterial infections and prevent contamination/spoilage of food.

  19. In vitro membrane binding and protein binding (IAM MB/PB technology to estimate in vivo distribution: applications in early drug discovery

    Directory of Open Access Journals (Sweden)

    Klara Livia Valko

    2017-03-01

    Full Text Available The drug discovery process can be accelerated by chromatographic profiling of the analogs to model in vivo distribution and the major non-specific binding. A balanced potency and chromatographically determined membrane and protein binding (IAM MB/PB data enable selecting drug discovery compounds for further analysis that have the highest probability to show the desired in vivo distribution behavior for efficacy and reduced chance for toxicity. Although the basic principles of the technology have already appeared in numerous publications, the lack of standardized procedures limited its widespread applications especially in academia and small drug discovery biotech companies. In this paper, the standardized procedures are described that has been trademarked as Regis IAM MB/PB Technology®. Comparison between the Drug Efficiency Index (DEI=pIC50-logVdu+2 and generally used Ligand Lipophilicity Efficiency (LLE has been made, demonstrating the advantage of measured IAM and HSA binding over calculated log P. The power of the proposed chromatographic technology is demonstrated using the data of marketed drugs.

  20. Study on the interaction of plasma protein binding rate between edaravone and taurine in human plasma based on HPLC analysis coupled with ultrafiltration technique.

    Science.gov (United States)

    Tang, Dao-quan; Li, Yin-jie; Li, Zheng; Bian, Ting-ting; Chen, Kai; Zheng, Xiao-xiao; Yu, Yan-yan; Jiang, Shui-shi

    2015-08-01

    In this work, two high-performance liquid chromatography (HPLC) assays were developed and validated for the independent determination of edaravone and taurine using 3-methyl-1-p-tolyl-5-pyrazolone and L-glutamine as internal standards. In in vitro experiments, human plasma was separately spiked with a mixture of edaravone and taurine, edaravone or taurine alone. Plasma was precipitated with acetonitrile containing 0.1% formic acid. Ultrafiltration was employed to obtain the unbound ingredients of the two drugs. The factors that might influence the ultrafiltration effiency were elaborately optimized. Plasma supernatant and ultrafiltrate containing taurine were derivated with o-phthalaldehyde and ethanethiol in the presence of 40 mmol/L sodium borate buffer (pH 10.2) at room temperature within 1 min. Chromatographic separations were achieved on an InertSustain C18 column (250 × 4.6 mm, 5 µm). Isocratic 50 mmol/L ammonium acetate-acetonitrile and gradient 50 mmol/L sodium acetate (pH 5.3)-methanol were respectively selected as the mobile phase for the determination of edaravone and taurine. All of the validation data including linearity, extraction recovery, precision, accuracy and stability conformed to the requirements. Results showed that there were no significant alterations in the plasma protein binding rate of taurine and edaravone, implying that the proposed combination therapy was pharmacologically feasible. Copyright © 2014 John Wiley & Sons, Ltd.

  1. Regulation of CCL2 expression by an upstream TALE homeodomain protein-binding site that synergizes with the site created by the A-2578G SNP.

    Science.gov (United States)

    Page, Stephen H; Wright, Edward K; Gama, Lucio; Clements, Janice E

    2011-01-01

    CC Chemokine Ligand 2 (CCL2) is a potent chemoattractant produced by macrophages and activated astrocytes during periods of inflammation within the central nervous system. Increased CCL2 expression is correlated with disease progression and severity, as observed in pulmonary tuberculosis, HCV-related liver disease, and HIV-associated dementia. The CCL2 distal promoter contains an A/G polymorphism at position -2578 and the homozygous -2578 G/G genotype is associated with increased CCL2 production and inflammation. However, the mechanisms that contribute to the phenotypic differences in CCL2 expression are poorly understood. We previously demonstrated that the -2578 G polymorphism creates a TALE homeodomain protein binding site (TALE binding site) for PREP1/PBX2 transcription factors. In this study, we identified the presence of an additional TALE binding site 22 bp upstream of the site created by the -2578 G polymorphism and demonstrated the synergistic effects of the two sites on the activation of the CCL2 promoter. Using chromatin immunoprecipitation (ChIP) assays, we demonstrated increased binding of the TALE proteins PREP1 and PBX2 to the -2578 G allele, and binding of IRF1 to both the A and G alleles. The presence of TALE binding sites that form inverted repeats within the -2578 G allele results in increased transcriptional activation of the CCL2 distal promoter while the presence of only the upstream TALE binding site within the -2578 A allele exerts repression of promoter activity.

  2. DNA and protein binding, double-strand DNA cleavage and cytotoxicity of mixed ligand copper(II) complexes of the antibacterial drug nalidixic acid.

    Science.gov (United States)

    Loganathan, Rangasamy; Ganeshpandian, Mani; Bhuvanesh, Nattamai S P; Palaniandavar, Mallayan; Muruganantham, Amsaveni; Ghosh, Swapan K; Riyasdeen, Anvarbatcha; Akbarsha, Mohammad Abdulkader

    2017-09-01

    The water soluble mixed ligand complexes [Cu(nal)(diimine)(H 2 O)](ClO 4 ) 1-4, where H(nal) is nalidixic acid and diimine is 2,2'-bipyridine (1), 1,10-phenanthroline (2), 5,6-dimethyl-1,10-phenanthroline (3), and 3,4,7,8-tetramethyl-1,10-phenanthroline (4), have been isolated. The coordination geometry around Cu(II) in 1 and that in the Density Functional Theory optimized structures of 1-4 has been assessed as square pyramidal. The trend in DNA binding constants (K b ) determined using absorption spectral titration (K b : 1, 0.79±0.1base pair. In contrast, 3 and 4 are involved in intimate hydrophobic interaction with DNA through the methyl substituents on phen ring, which is supported by viscosity and protein binding studies. DNA docking studies imply that 4 is involved preferentially in DNA major groove binding while 1-3 in minor groove binding and that all the complexes, upon removing the axially coordinated water molecule, bind in the major groove. Interestingly, 3 and 4 display prominent double-strand DNA cleavage while 1 and 2 effect only single-strand DNA cleavage in the absence of an activator. The complexes 3 and 4 show cytotoxicity higher than 1 and 2 against human breast cancer cell lines (MCF-7). The complex 4 induces apoptotic mode of cell death in cancer cells. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Negligible effects of nonesterified fatty acids on serum thyroxine analysis by competitive protein-binding radioassay on Sephadex and by radioimmunoassay

    International Nuclear Information System (INIS)

    Alexander, N.M.; Nishimoto, M.

    1978-01-01

    Values for thyroxine by our competitive protein-binding assay on Sephadex (I) and by radioimmmunoassy (II) were identical for sera containing markedly increased concentrations of endogenous nonesterified fatty acids. Addition of as much as 5 mmol of long-chain saturated fatty acids per liter to normal serum had no significant effect on the thyroxine values by I; larger concentrations (10 mmol/liter) spuriously increased values by 20 to 30%. Added unsaturated fatty acids (1 mmol/liter) were without effect on procedure I, but spurious elevations in thyroxine appeared when concentrations were further increased up to 10 mmol/liter. The spurious effects by 2 to 5 mmol of added oleate and arachidonate (the most potent inhibitor of thyroxine binding to thyroxine-binding globulin) per liter could be reversed by washing the Sephadex columns with additional barbital buffer before binding with thyroxine-binding globulin (a step that is done on the gel). Three different II procedures were unaffected by as much as 5 mmol of added fatty acids per liter, but moderate spurious increases were noted with 10 mmol of oleate per liter. We conclude that method I is reliable for thyroxine analysis in nearly all sera from human subjects, because the concentrations of unsaturated fatty acids present either in vitro or in vivo are seldom large enough to interfere

  4. Dark matter candidates

    International Nuclear Information System (INIS)

    Turner, M.S.

    1989-01-01

    One of the simplest, yet most profound, questions we can ask about the Universe is, how much stuff is in it, and further what is that stuff composed of? Needless to say, the answer to this question has very important implications for the evolution of the Universe, determining both the ultimate fate and the course of structure formation. Remarkably, at this late date in the history of the Universe we still do not have a definitive answer to this simplest of questions---although we have some very intriguing clues. It is known with certainty that most of the material in the Universe is dark, and we have the strong suspicion that the dominant component of material in the Cosmos is not baryons, but rather is exotic relic elementary particles left over from the earliest, very hot epoch of the Universe. If true, the Dark Matter question is a most fundamental one facing both particle physics and cosmology. The leading particle dark matter candidates are: the axion, the neutralino, and a light neutrino species. All three candidates are accessible to experimental tests, and experiments are now in progress. In addition, there are several dark horse, long shot, candidates, including the superheavy magnetic monopole and soliton stars. 13 refs

  5. 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.

  6. 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.

  7. 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

  8. 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)

  9. 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

  10. 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...

  11. 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

  12. 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...

  13. 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

  14. 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…

  15. 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

  16. 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

  17. 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....

  18. 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…

  19. 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...

  20. 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

  1. 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…

  2. 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

  3. Functional validation of candidate genes detected by genomic feature models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

    2018-01-01

    Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated...

  4. 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.

  5. 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)

  6. 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)

  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, 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.

  8. 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}.

  9. 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.

  10. 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.

  11. Generating and evaluating a ranked candidate gene list for potential vertebrate heart field regulators

    Directory of Open Access Journals (Sweden)

    G. Musso

    2015-12-01

    Full Text Available The vertebrate heart develops from two distinct lineages of cardiomyocytes that arise from the first and second heart fields (FHF and SHF, respectively. The FHF forms the primitive heart tube, while adding cells from the SHF allows elongation at both poles of the tube. Initially seen as an exclusive characteristic of higher vertebrates, recent work has demonstrated the presence of a distinct FHF and SHF in lower vertebrates, including zebrafish. We found that key transcription factors that regulate septation and chamber formation in higher vertebrates, including Tbx5 and Pitx2, influence relative FHF and SHF contributions to the zebrafish heart tube. To identify molecular modulators of heart field migration, we used microarray-based expression profiling following inhibition of tbx5a and pitx2ab in embryonic zebrafish (Mosimann & Panakova, et al, 2015; GSE70750. Here, we describe in more detail the procedure used to process, prioritize, and analyze the expression data for functional enrichment.

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

    Science.gov (United States)

    Rust fungi are obligate biotrophic pathogens causing considerable damage on crop plants. P. graminis f. sp. tritici, the causal agent of wheat stem rust, and M. larici-populina, the poplar rust pathogen, have strong deleterious impact on wheat and poplar wood production, respectively. The recently r...

  13. 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

  14. 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.

  15. 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.

  16. 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.

  17. A Ranking Method for Neutral Pion and Eta Selection in Hadronic Events

    International Nuclear Information System (INIS)

    Bingoel, A.

    2004-01-01

    The selection of neutral pions and etas with a high purity while maintaining also a high efficiency can be important in the formation of statistically significant mass spectra in the reconstruction of short-lived particles such as the omega meson (ω→π + + π - + π 0 ). In this study a Ranking method has been optimized for data from the ALEPH Experiment, CERN. The results show that the Ranking method, when applied to high multiplicity events, yields significant improvements in the purity of selected pion candidates and facilitates the relaxation of standard cuts thereby avoiding some systematic uncertainties

  18. 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.

  19. 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.

  20. 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....

  1. 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

  2. Analysis of drug-protein binding using on-line immunoextraction and high-performance affinity microcolumns: Studies with normal and glycated human serum albumin.

    Science.gov (United States)

    Matsuda, Ryan; Jobe, Donald; Beyersdorf, Jared; Hage, David S

    2015-10-16

    A method combining on-line immunoextraction microcolumns with high-performance affinity chromatography (HPAC) was developed and tested for use in examining drug-protein interactions with normal or modified proteins. Normal human serum albumin (HSA) and glycated HSA were used as model proteins for this work. High-performance immunoextraction microcolumns with sizes of 1.0-2.0 cm × 2.1mm i.d. and containing anti-HSA polyclonal antibodies were developed and tested for their ability to bind normal HSA or glycated HSA. These microcolumns were able to extract up to 82-93% for either type of protein at 0.05-0.10 mL/min and had a binding capacity of 0.34-0.42 nmol HSA for a 1.0 cm × 2.1mm i.d. microcolumn. The immunoextraction microcolumns and their adsorbed proteins were tested for use in various approaches for drug binding studies. Frontal analysis was used with the adsorbed HSA/glycated HSA to measure the overall affinities of these proteins for the drugs warfarin and gliclazide, giving comparable values to those obtained previously using similar protein preparations that had been covalently immobilized within HPAC columns. Zonal elution competition studies with gliclazide were next performed to examine the specific interactions of this drug at Sudlow sites I and II of the adsorbed proteins. These results were also comparable to those noted in prior work with covalently immobilized samples of normal HSA or glycated HSA. These experiments indicated that drug-protein binding studies can be carried out by using on-line immunoextraction microcolumns with HPAC. The same method could be used in the future with clinical samples and other drugs or proteins of interest in pharmaceutical studies or biomedical research. Copyright © 2015 Elsevier B.V. All rights reserved.

  3. Urinary excretion and patterns of protein binding of iodipamide (Biligrafin forte). A comparison of the infusion technique with the single bolus injection in intravenous cholangiography

    Energy Technology Data Exchange (ETDEWEB)

    Husband, J; Saxton, H M [Guy' s Hospital, London (UK)

    1978-01-01

    It has been suggested that the bile ducts are seen better during intravenous cholangiography when the contrast medium is given by infusion rather than by injection in a single bolus. As an explanation, it has been proposed that a greater amount of contrast medium is bound to plasma proteins after infusion, resulting in a smaller quantity of contrast medium being excreted in the urine, so leaving a larger total for excretion by the liver. In this study, the urinary excretion of /sup 125/I labelled iodipamide methylglucamine (50% w/v Biligrafin forte) has been measured in 42 patients. The patients were divided into two groups. One group received a slow infusion of radioactive iodipamide over 45 minutes and the other an intravenous injection over five minutes. When a relatively high dose (0.6 mg/kg body weight) was used, no difference in urinary excretion was noted between these two groups; but with a lower dose (0.2 mg/kg body weight), slow infusion resulted in a reduced urinary excretion; however the total difference in contrast lost in the urine was too small to affect biliary concentration. The patterns of protein binding of iodipamide have been examined in 12 of these patients. The results showed that at the low dose a higher percentage of radioactive iodipamide was bound to protein in patients given contrast by infusion. There was clear evidence that the contrast binding capacity of plasma was limited so that with higher doses, much contrast remained unbound. At any given dose level, there was inverse correlation between the proportion of contrast bound to protein and the urinary excretion. The factors affecting contrast binding in individual subjects were not clear.

  4. [Lack of interest in general practice during the National Ranking Examination in 2005].

    Science.gov (United States)

    Lanson, Yves

    2006-03-01

    The second national ranking test took place in 2005 in the same conditions as the year before. Analysis of the results permits us to assess whether the objectives of this reform have been met so far. Data crossing of the results provided by the national testing center allowed us to rank: 1) the appeal of specializations for each geographic subdivision, 2) the candidates by medical school, and 3) the appeal of each subdivision by candidate rank. 66% of the students were classified high enough to be able to choose any specialization. Trends observed from the first examination, in 2004, were confirmed, with the clear desirability of medical specializations and a certain lack of interest in occupational medicine and public health. All the surgery posts were filled, even though the number of posts had increased enormously since the first examination. After adjustment for the number of posts available, the specializations in decreasing order of popularity were: medical, surgical, pediatrics, anesthesiology, gynecology-obstetrics, general medicine, psychiatry, and biology. Approximately 1000 posts in general medicine were not filled. The medical schools whose students ranked highest were Paris Pitié, Paris V, Paris West, Lyon North, Grenoble, and Aix-Marseille. Some medical schools did less well than previously: Marseille very slightly and Angers substantially. Strasbourg, Nancy Amiens and Bobigny were at the bottom of the list. The cities most desired for internships were Paris, Toulouse, Lyon, and Aix-Marseille, while Brest, Nancy, Limoges and the West Indies were ranked lowest, although each was chosen by highly ranked candidate. Two thirds of the students were ranked high enough to allow them a free choice of specializations. All the specializations except public health and occupational medicine had very highly ranked students. Medical specializations are the most desired, but surgery remains highly demanded, despite a substantial increase in the number of posts. All

  5. Optimized candidal biofilm microtiter assay

    NARCIS (Netherlands)

    Krom, Bastiaan P.; Cohen, Jesse B.; Feser, Gail E. McElhaney; Cihlar, Ronald L.

    Microtiter based candidal biofilm formation is commonly being used. Here we describe the analysis of factors influencing the development of candidal biofilms such as the coating with serum, growth medium and pH. The data reported here show that optimal candidal biofilm formation is obtained when

  6. 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.

  7. 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...

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. 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...

  13. 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

  14. 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.

  15. 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.

  16. 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).

  17. Characterizing Microseismicity at the Newberry Volcano Geothermal Site using PageRank

    Science.gov (United States)

    Aguiar, A. C.; Myers, S. C.

    2015-12-01

    The Newberry Volcano, within the Deschutes National Forest in Oregon, has been designated as a candidate site for the Department of Energy's Frontier Observatory for Research in Geothermal Energy (FORGE) program. This site was stimulated using high-pressure fluid injection during the fall of 2012, which generated several hundred microseismic events. Exploring the spatial and temporal development of microseismicity is key to understanding how subsurface stimulation modifies stress, fractures rock, and increases permeability. We analyze Newberry seismicity using both surface and borehole seismometers from the AltaRock and LLNL seismic networks. For our analysis we adapt PageRank, Google's initial search algorithm, to evaluate microseismicity during the 2012 stimulation. PageRank is a measure of connectivity, where higher ranking represents highly connected windows. In seismic applications connectivity is measured by the cross correlation of 2 time windows recorded on a common seismic station and channel. Aguiar and Beroza (2014) used PageRank based on cross correlation to detect low-frequency earthquakes, which are highly repetitive but difficult to detect. We expand on this application by using PageRank to define signal-correlation topology for micro-earthquakes, including the identification of signals that are connected to the largest number of other signals. We then use this information to create signal families and compare PageRank families to the spatial and temporal proximity of associated earthquakes. Studying signal PageRank will potentially allow us to efficiently group earthquakes with similar physical characteristics, such as focal mechanisms and stress drop. Our ultimate goal is to determine whether changes in the state of stress and/or changes in the generation of subsurface fracture networks can be detected using PageRank topology. This work performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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; ...

  6. 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

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. 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

  15. 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....

  16. 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...

  17. 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.

  18. 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...

  19. 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.

  20. 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.

  1. 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)

  2. 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,

  3. 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;

  4. 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

  5. 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

  6. 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)

  7. 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

  8. 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.

  9. 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.

  10. 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,

  11. 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

  12. 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...

  13. 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…

  14. 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.

  15. 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

  16. 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.

  17. 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...

  18. 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…

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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…

  4. 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

  5. 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

  6. 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/.

  7. 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.

  8. 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)

  9. 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...

  10. 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

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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 ...

  16. 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

  17. 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)

  18. 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....

  19. 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...

  20. Functional validation of candidate genes detected by genomic feature models

    DEFF Research Database (Denmark)

    Rohde, Palle Duun; Østergaard, Solveig; Kristensen, Torsten Nygaard

    2018-01-01

    to investigate locomotor activity, and applied genomic feature prediction models to identify gene ontology (GO) cate- gories predictive of this phenotype. Next, we applied the covariance association test to partition the genomic variance of the predictive GO terms to the genes within these terms. We...... then functionally assessed whether the identified candidate genes affected locomotor activity by reducing gene expression using RNA interference. In five of the seven candidate genes tested, reduced gene expression altered the phenotype. The ranking of genes within the predictive GO term was highly correlated......Understanding the genetic underpinnings of complex traits requires knowledge of the genetic variants that contribute to phenotypic variability. Reliable statistical approaches are needed to obtain such knowledge. In genome-wide association studies, variants are tested for association with trait...

  1. 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...

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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

  8. 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.

  9. 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.

  10. Identifying the Academic Rising Stars via Pairwise Citation Increment Ranking

    KAUST Repository

    Zhang, Chuxu

    2017-08-02

    Predicting the fast-rising young researchers (the Academic Rising Stars) in the future provides useful guidance to the research community, e.g., offering competitive candidates to university for young faculty hiring as they are expected to have success academic careers. In this work, given a set of young researchers who have published the first first-author paper recently, we solve the problem of how to effectively predict the top k% researchers who achieve the highest citation increment in Δt years. We explore a series of factors that can drive an author to be fast-rising and design a novel pairwise citation increment ranking (PCIR) method that leverages those factors to predict the academic rising stars. Experimental results on the large ArnetMiner dataset with over 1.7 million authors demonstrate the effectiveness of PCIR. Specifically, it outperforms all given benchmark methods, with over 8% average improvement. Further analysis demonstrates that temporal features are the best indicators for rising stars prediction, while venue features are less relevant.

  11. Screening and ranking Alberta oil pools for CO{sub 2} flooding and sequestration

    Energy Technology Data Exchange (ETDEWEB)

    Shaw, J.C. [Adams Pearson Associates Inc., Calgary, AB (Canada); Bachu, S. [Alberta Energy and Utilities Board, Calgary, AB (Canada)

    2001-06-01

    This paper presented the results of a technical screening program using Excel VBA to successfully screen and rank a very large number of oil pools for enhanced oil recovery using carbon dioxide (CO{sub 2}) flooding. A total of 6 ranking parameters were used, including API gravity of oil, residual oil saturation, ratio between reservoir pressure and minimum miscibility pressure, reservoir temperature, net pay thickness and porosity. The screening program provided a technical ranking of approximately 8,800 Alberta pools in less than 2 minutes. After compilation of the Alberta oil pools, it was determined that most of the deep carbonate oil pools are excellent candidates for CO{sub 2} miscible flooding. Other Devonian carbonate pools were also ranked as having high potential for the process. An environmental benefit of CO{sub 2} miscible flooding process is that carbon sequestration has the potential to reduce anthropogenic carbon dioxide emissions from reaching the atmosphere. Ongoing studies are currently addressing CO{sub 2} capture and transportation, making EOR technology viable for maintaining light oil production in western Canada. 11 refs., 7 tabs., 1 fig.

  12. 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

  13. 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.

  14. 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.

  15. 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...

  16. 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

  17. 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

  18. 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.

  19. 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

  20. 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

  1. 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.

  2. Determination of blood concentrations of main active compounds in Zi-Cao-Cheng-Qi decoction and their total plasma protein binding rates based on hollow fiber liquid phase microextraction coupled with high performance liquid chromatography.

    Science.gov (United States)

    Li, Miaomiao; Chen, Xuan; Hu, Shuang; Wang, Runqin; Peng, Xiaoli; Bai, Xiaohong

    2018-01-01

    Oil-in-salt hollow fiber liquid phase microextraction coupled with high performance liquid chromatography ultraviolet detection (HPLC-UV) was developed for determination of the blood concentrations of the main active compounds, hesperidin, honokiol, shikonin, magnolol, emodin and β,β'-dimethylacrylshikonin, after oral administration of Zi-Cao-Cheng-Qi decoction (ZCCQD) and their total plasma protein binding rates. In the procedure, a hollow fiber segment was immersed in organic solvent to fill the solvent in the fiber lumen and wall pore, and then the fiber was immersed into sodium chloride solution to cover a thin salt membrane on the fiber wall pore filling organic solvent. Various factors affecting the procedure, such as extraction solvent, sample phase pH, stirring rate, extraction time, NaCl concentration and fiber immersion time in the NaCl solution, were optimized. Under the optimum conditions, good linearities (r 2 ≥0.9905), low limits of detection (0.7-2.5ng/mL) or quantitation (1.2-12ng/mL), satisfactory precision (2.6%-12.8%) and accuracy (81.0%-114.2%) of this method, were observed. The results showed that, after oral administration of a 25g/kg dose, (1) the blood concentrations (at 0.5h) of hesperidin, honokiol, shikonin, magnolol, emodin and β,β'-dimethylacrylshikonin were 0.45, 0.40, 0.48, 0.74, 0.11 and 1.11μg/mL, respectively; (2) the total plasma protein binding rates of the six active compounds were 42.0% (hesperidin), 71.8% (honokiol), 64.6% (shikonin), 77.7% (magnolol), 75.3% (emodin) and 75.7% (β,β'-dimethylacrylshikonin), respectively. The proposed procedure coupled with HPLC shows obvious advantages, such as low solvent consumption, simple operation, high sensitivity and strong purifying and can be used for the determination of both the blood concentrations and total plasma protein binding rates of active compounds in traditional Chinese medicine. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. 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.

  4. 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

  5. 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

  6. 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…

  7. 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.…

  8. 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…

  9. 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...

  10. 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...

  11. 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...

  12. 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…

  13. 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

  14. 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...

  15. 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…

  16. 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

  17. 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.

  18. 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...

  19. 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.

  20. Solution Structure, Membrane Interactions, and Protein Binding Partners of the Tetraspanin Sm-TSP-2, a Vaccine Antigen from the Human Blood Fluke Schistosoma mansoni*

    Science.gov (United States)

    Jia, Xinying; Schulte, Leigh; Loukas, Alex; Pickering, Darren; Pearson, Mark; Mobli, Mehdi; Jones, Alun; Rosengren, Karl J.; Daly, Norelle L.; Gobert, Geoffrey N.; Jones, Malcolm K.; Craik, David J.; Mulvenna, Jason

    2014-01-01

    The tetraspanins (TSPs) are a family of integral membrane proteins that are ubiquitously expressed at the surface of eukaryotic cells. TSPs mediate a range of processes at the surface of the plasma membrane by providing a scaffold for the assembly of protein complexes known as tetraspanin-enriched microdomains (TEMs). We report here the structure of the surface-exposed EC2 domain from Sm-TSP-2, a TSP from Schistosoma mansoni and one of the better prospects for the development of a vaccine against schistosomiasis. This is the first solution structure of this domain, and our investigations of its interactions with lipid micelles provide a general model for interactions between TSPs, membranes, and other proteins. Using chemical cross-linking, eight potential protein constituents of Sm-TSP-2-mediated TEMs were also identified. These include proteins important for membrane maintenance and repair, providing further evidence for the functional role of Sm-TSP-2- and Sm-TSP-2-mediated TEMs. The identification of calpain, Sm29, and fructose-bisphosphate aldolase, themselves potential vaccine antigens, suggests that the Sm-TSP-2-mediated TEMs could be disrupted via multiple targets. The identification of further Sm-TSP-2-mediated TEM proteins increases the available candidates for multiplex vaccines and/or novel drugs targeting TEMs in the schistosome tegument. PMID:24429291

  1. Solution structure, membrane interactions, and protein binding partners of the tetraspanin Sm-TSP-2, a vaccine antigen from the human blood fluke Schistosoma mansoni.

    Science.gov (United States)

    Jia, Xinying; Schulte, Leigh; Loukas, Alex; Pickering, Darren; Pearson, Mark; Mobli, Mehdi; Jones, Alun; Rosengren, Karl J; Daly, Norelle L; Gobert, Geoffrey N; Jones, Malcolm K; Craik, David J; Mulvenna, Jason

    2014-03-07

    The tetraspanins (TSPs) are a family of integral membrane proteins that are ubiquitously expressed at the surface of eukaryotic cells. TSPs mediate a range of processes at the surface of the plasma membrane by providing a scaffold for the assembly of protein complexes known as tetraspanin-enriched microdomains (TEMs). We report here the structure of the surface-exposed EC2 domain from Sm-TSP-2, a TSP from Schistosoma mansoni and one of the better prospects for the development of a vaccine against schistosomiasis. This is the first solution structure of this domain, and our investigations of its interactions with lipid micelles provide a general model for interactions between TSPs, membranes, and other proteins. Using chemical cross-linking, eight potential protein constituents of Sm-TSP-2-mediated TEMs were also identified. These include proteins important for membrane maintenance and repair, providing further evidence for the functional role of Sm-TSP-2- and Sm-TSP-2-mediated TEMs. The identification of calpain, Sm29, and fructose-bisphosphate aldolase, themselves potential vaccine antigens, suggests that the Sm-TSP-2-mediated TEMs could be disrupted via multiple targets. The identification of further Sm-TSP-2-mediated TEM proteins increases the available candidates for multiplex vaccines and/or novel drugs targeting TEMs in the schistosome tegument.

  2. Teacher Candidate Selection and Evaluation.

    Science.gov (United States)

    Collins, Mary Lynn; And Others

    Summaries are presented of three papers presented at a summer workshop on Quality Assurance in Teacher Education conducted by the Association of Teacher Educators. The general topic covered by these presentations was teacher candidate selection and evaluation. Papers focused upon the following questions: (1) What entry level criteria should be…

  3. Candidate Prediction Models and Methods

    DEFF Research Database (Denmark)

    Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik

    2005-01-01

    This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines...... the possibilities w.r.t. different numerical weather predictions actually available to the project....

  4. Candidate cave entrances on Mars

    Science.gov (United States)

    Cushing, Glen E.

    2012-01-01

    This paper presents newly discovered candidate cave entrances into Martian near-surface lava tubes, volcano-tectonic fracture systems, and pit craters and describes their characteristics and exploration possibilities. These candidates are all collapse features that occur either intermittently along laterally continuous trench-like depressions or in the floors of sheer-walled atypical pit craters. As viewed from orbit, locations of most candidates are visibly consistent with known terrestrial features such as tube-fed lava flows, volcano-tectonic fractures, and pit craters, each of which forms by mechanisms that can produce caves. Although we cannot determine subsurface extents of the Martian features discussed here, some may continue unimpeded for many kilometers if terrestrial examples are indeed analogous. The features presented here were identified in images acquired by the Mars Odyssey's Thermal Emission Imaging System visible-wavelength camera, and by the Mars Reconnaissance Orbiter's Context Camera. Select candidates have since been targeted by the High-Resolution Imaging Science Experiment. Martian caves are promising potential sites for future human habitation and astrobiology investigations; understanding their characteristics is critical for long-term mission planning and for developing the necessary exploration technologies.

  5. 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

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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

  11. 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.

  12. 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

  13. 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...

  14. Candidate genes in panic disorder

    DEFF Research Database (Denmark)

    Howe, A. S.; Buttenschön, Henriette N; Bani-Fatemi, A.

    2016-01-01

    The utilization of molecular genetics approaches in examination of panic disorder (PD) has implicated several variants as potential susceptibility factors for panicogenesis. However, the identification of robust PD susceptibility genes has been complicated by phenotypic diversity, underpowered...... association studies and ancestry-specific effects. In the present study, we performed a succinct review of case-control association studies published prior to April 2015. Meta-analyses were performed for candidate gene variants examined in at least three studies using the Cochrane Mantel-Haenszel fixed......-effect model. Secondary analyses were also performed to assess the influences of sex, agoraphobia co-morbidity and ancestry-specific effects on panicogenesis. Meta-analyses were performed on 23 variants in 20 PD candidate genes. Significant associations after correction for multiple testing were observed...

  15. Identification of Inherited Retinal Disease-Associated Genetic Variants in 11 Candidate Genes.

    Science.gov (United States)

    Astuti, Galuh D N; van den Born, L Ingeborgh; Khan, M Imran; Hamel, Christian P; Bocquet, Béatrice; Manes, Gaël; Quinodoz, Mathieu; Ali, Manir; Toomes, Carmel; McKibbin, Martin; El-Asrag, Mohammed E; Haer-Wigman, Lonneke; Inglehearn, Chris F; Black, Graeme C M; Hoyng, Carel B; Cremers, Frans P M; Roosing, Susanne

    2018-01-10

    Inherited retinal diseases (IRDs) display an enormous genetic heterogeneity. Whole exome sequencing (WES) recently identified genes that were mutated in a small proportion of IRD cases. Consequently, finding a second case or family carrying pathogenic variants in the same candidate gene often is challenging. In this study, we searched for novel candidate IRD gene-associated variants in isolated IRD families, assessed their causality, and searched for novel genotype-phenotype correlations. Whole exome sequencing was performed in 11 probands affected with IRDs. Homozygosity mapping data was available for five cases. Variants with minor allele frequencies ≤ 0.5% in public databases were selected as candidate disease-causing variants. These variants were ranked based on their: (a) presence in a gene that was previously implicated in IRD; (b) minor allele frequency in the Exome Aggregation Consortium database (ExAC); (c) in silico pathogenicity assessment using the combined annotation dependent depletion (CADD) score; and (d) interaction of the corresponding protein with known IRD-associated proteins. Twelve unique variants were found in 11 different genes in 11 IRD probands. Novel autosomal recessive and dominant inheritance patterns were found for variants in Small Nuclear Ribonucleoprotein U5 Subunit 200 ( SNRNP200 ) and Zinc Finger Protein 513 ( ZNF513 ), respectively. Using our pathogenicity assessment, a variant in DEAH-Box Helicase 32 ( DHX32 ) was the top ranked novel candidate gene to be associated with IRDs, followed by eight medium and lower ranked candidate genes. The identification of candidate disease-associated sequence variants in 11 single families underscores the notion that the previously identified IRD-associated genes collectively carry > 90% of the defects implicated in IRDs. To identify multiple patients or families with variants in the same gene and thereby provide extra proof for pathogenicity, worldwide data sharing is needed.

  16. Identification of candidate genes for dyslexia susceptibility on chromosome 18.

    Directory of Open Access Journals (Sweden)

    Thomas S Scerri

    2010-10-01

    Full Text Available Six independent studies have identified linkage to chromosome 18 for developmental dyslexia or general reading ability. Until now, no candidate genes have been identified to explain this linkage. Here, we set out to identify the gene(s conferring susceptibility by a two stage strategy of linkage and association analysis.Linkage analysis: 264 UK families and 155 US families each containing at least one child diagnosed with dyslexia were genotyped with a dense set of microsatellite markers on chromosome 18. Association analysis: Using a discovery sample of 187 UK families, nearly 3000 SNPs were genotyped across the chromosome 18 dyslexia susceptibility candidate region. Following association analysis, the top ranking SNPs were then genotyped in the remaining samples. The linkage analysis revealed a broad signal that spans approximately 40 Mb from 18p11.2 to 18q12.2. Following the association analysis and subsequent replication attempts, we observed consistent association with the same SNPs in three genes; melanocortin 5 receptor (MC5R, dymeclin (DYM and neural precursor cell expressed, developmentally down-regulated 4-like (NEDD4L.Along with already published biological evidence, MC5R, DYM and NEDD4L make attractive candidates for dyslexia susceptibility genes. However, further replication and functional studies are still required.

  17. 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

  18. 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

  19. Pipeline for the Analysis of ChIP-seq Data and New Motif Ranking Procedure

    KAUST Repository

    Ashoor, Haitham

    2011-06-01

    This thesis presents a computational methodology for ab-initio identification of transcription factor binding sites based on ChIP-seq data. This method consists of three main steps, namely ChIP-seq data processing, motif discovery and models selection. A novel method for ranking the models of motifs identified in this process is proposed. This method combines multiple factors in order to rank the provided candidate motifs. It combines the model coverage of the ChIP-seq fragments that contain motifs from which that model is built, the suitable background data made up of shuffled ChIP-seq fragments, and the p-value that resulted from evaluating the model on actual and background data. Two ChIP-seq datasets retrieved from ENCODE project are used to evaluate and demonstrate the ability of the method to predict correct TFBSs with high precision. The first dataset relates to neuron-restrictive silencer factor, NRSF, while the second one corresponds to growth-associated binding protein, GABP. The pipeline system shows high precision prediction for both datasets, as in both cases the top ranked motif closely resembles the known motifs for the respective transcription factors.

  20. Novel Opportunistic Network Routing Based on Social Rank for Device-to-Device Communication

    Directory of Open Access Journals (Sweden)

    Tong Wang

    2017-01-01

    Full Text Available In recent years, there has been dramatic proliferation of research concerned with fifth-generation (5G mobile communication networks, among which device-to-device (D2D communication is one of the key technologies. Due to the intermittent connection of nodes, the D2D network topology may be disconnected frequently, which will lead to failure in transmission of large data files. In opportunistic networks, in case of encountering nodes which never meet before a flood message blindly to cause tremendous network overhead, a novel opportunistic network routing protocol based on social rank and intermeeting time (SRIT is proposed in this paper. An improved utility approach applied in utility replication based on encounter durations and intermeeting time is put forward to enhance the routing efficiency. Meanwhile, in order to select better candidate nodes in the network, a social graph among people is established when they socially relate to each other in social rank replication. The results under the scenario show an advantage of the proposed opportunistic network routing based on social rank and intermeeting time (SRIT over the compared algorithms in terms of delivery ratio, average delivery latency, and overhead ratio.

  1. Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

    Directory of Open Access Journals (Sweden)

    K. Somasundaram

    2015-01-01

    Full Text Available Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED and Optimally Adjusted Morphological Operator (OAMO effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

  2. Diagnosing and ranking retinopathy disease level using diabetic fundus image recuperation approach.

    Science.gov (United States)

    Somasundaram, K; Rajendran, P Alli

    2015-01-01

    Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

  3. 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.

  4. 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...

  5. 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.

  6. Unsupervised ensemble ranking of terms in electronic health record notes based on their importance to patients.

    Science.gov (United States)

    Chen, Jinying; Yu, Hong

    2017-04-01

    Allowing patients to access their own electronic health record (EHR) notes through online patient portals has the potential to improve patient-centered care. However, EHR notes contain abundant medical jargon that can be difficult for patients to comprehend. One way to help patients is to reduce information overload and help them focus on medical terms that matter most to them. Targeted education can then be developed to improve patient EHR comprehension and the quality of care. The aim of this work was to develop FIT (Finding Important Terms for patients), an unsupervised natural language processing (NLP) system that ranks medical terms in EHR notes based on their importance to patients. We built FIT on a new unsupervised ensemble ranking model derived from the biased random walk algorithm to combine heterogeneous information resources for ranking candidate terms from each EHR note. Specifically, FIT integrates four single views (rankers) for term importance: patient use of medical concepts, document-level term salience, word co-occurrence based term relatedness, and topic coherence. It also incorporates partial information of term importance as conveyed by terms' unfamiliarity levels and semantic types. We evaluated FIT on 90 expert-annotated EHR notes and used the four single-view rankers as baselines. In addition, we implemented three benchmark unsupervised ensemble ranking methods as strong baselines. FIT achieved 0.885 AUC-ROC for ranking candidate terms from EHR notes to identify important terms. When including term identification, the performance of FIT for identifying important terms from EHR notes was 0.813 AUC-ROC. Both performance scores significantly exceeded the corresponding scores from the four single rankers (P<0.001). FIT also outperformed the three ensemble rankers for most metrics. Its performance is relatively insensitive to its parameter. FIT can automatically identify EHR terms important to patients. It may help develop future interventions

  7. 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.

  8. 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

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. 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...

  2. 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

  3. 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.

  4. 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

  5. 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>).

  6. 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.

  7. 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

  8. 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

  9. 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.)

  10. 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.

  11. 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

  12. 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.

  13. 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...

  14. 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.

  15. 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.

  16. 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.

  17. Alternative dark matter candidates. Axions

    International Nuclear Information System (INIS)

    Ringwald, Andreas

    2017-01-01

    The axion is arguably one of the best motivated candidates for dark matter. For a decay constant >or similar 10 9 GeV, axions are dominantly produced non-thermally in the early universe and hence are ''cold'', their velocity dispersion being small enough to fit to large scale structure. Moreover, such a large decay constant ensures the stability at cosmological time scales and its behaviour as a collisionless fluid at cosmological length scales. Here, we review the state of the art of axion dark matter predictions and of experimental efforts to search for axion dark matter in laboratory experiments.

  18. Alternative dark matter candidates. Axions

    Energy Technology Data Exchange (ETDEWEB)

    Ringwald, Andreas

    2017-01-15

    The axion is arguably one of the best motivated candidates for dark matter. For a decay constant >or similar 10{sup 9} GeV, axions are dominantly produced non-thermally in the early universe and hence are ''cold'', their velocity dispersion being small enough to fit to large scale structure. Moreover, such a large decay constant ensures the stability at cosmological time scales and its behaviour as a collisionless fluid at cosmological length scales. Here, we review the state of the art of axion dark matter predictions and of experimental efforts to search for axion dark matter in laboratory experiments.

  19. AZU-1: A Candidate Breast Tumor Suppressor and Biomarker for Tumor Progression

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Huei-Mei; Schmeichel, Karen L; Mian, I. Saira; Lelie`vre, Sophie; Petersen, Ole W; Bissell, Mina J

    2000-02-04

    To identify genes misregulated in the final stages of breast carcinogenesis, we performed differential display to compare the gene expression patterns of the human tumorigenic mammary epithelial cells, HMT-3522-T4-2, with those of their immediate premalignant progenitors, HMT-3522-S2. We identified a novel gene, called anti-zuai-1 (AZU-1), that was abundantly expressed in non- and premalignant cells and tissues but was appreciably reduced in breast tumor cell types and in primary tumors. The AZU-1 gene encodes an acidic 571-amino-acid protein containing at least two structurally distinct domains with potential protein-binding functions: an N-terminal serine and proline-rich domain with a predicted immunoglobulin-like fold and a C-terminal coiled-coil domain. In HMT-3522 cells, the bulk of AZU-1 protein resided in a detergent-extractable cytoplasmic pool and was present at much lower levels in tumorigenic T4-2 cells than in their nonmalignant counterparts. Reversion of the tumorigenic phenotype of T4-2 cells, by means described previously, was accompanied by the up-regulation of AZU-1. In addition, reexpression of AZU-1 in T4-2 cells, using viral vectors, was sufficient to reduce their malignant phenotype substantially, both in culture and in vivo. These results indicate that AZU-1 is a candidate breast tumor suppressor that may exert its effects by promoting correct tissue morphogenesis.

  20. Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

    DEFF Research Database (Denmark)

    Shungin, Dmitry; Deng, Wei Q; Varga, Tibor V

    2017-01-01

    Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between...... variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman's ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv...... and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman's ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial BMI had...

  1. 11 CFR 100.154 - Candidate debates.

    Science.gov (United States)

    2010-01-01

    ... 11 Federal Elections 1 2010-01-01 2010-01-01 false Candidate debates. 100.154 Section 100.154 Federal Elections FEDERAL ELECTION COMMISSION GENERAL SCOPE AND DEFINITIONS (2 U.S.C. 431) Exceptions to Expenditures § 100.154 Candidate debates. Funds used to defray costs incurred in staging candidate debates in...

  2. 11 CFR 100.92 - Candidate debates.

    Science.gov (United States)

    2010-01-01

    ... 11 Federal Elections 1 2010-01-01 2010-01-01 false Candidate debates. 100.92 Section 100.92 Federal Elections FEDERAL ELECTION COMMISSION GENERAL SCOPE AND DEFINITIONS (2 U.S.C. 431) Exceptions to Contributions § 100.92 Candidate debates. Funds provided to defray costs incurred in staging candidate debates...

  3. 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

  4. 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

  5. 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…

  6. 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

  7. 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

  8. 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…

  9. 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: ...

  10. 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

  11. 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...

  12. 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.

  13. 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...

  14. 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…

  15. 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…

  16. 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.

  17. 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.

  18. 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.

  19. 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…

  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. [Obesity studies in candidate genes].

    Science.gov (United States)

    Ochoa, María del Carmen; Martí, Amelia; Martínez, J Alfredo

    2004-04-17

    There are more than 430 chromosomic regions with gene variants involved in body weight regulation and obesity development. Polymorphisms in genes related to energy expenditure--uncoupling proteins (UCPs), related to adipogenesis and insulin resistance--hormone-sensitive lipase (HLS), peroxisome proliferator-activated receptor gamma (PPAR gamma), beta adrenergic receptors (ADRB2,3), and alfa tumor necrosis factor (TNF-alpha), and related to food intake--ghrelin (GHRL)--appear to be associated with obesity phenotypes. Obesity risk depends on two factors: a) genetic variants in candidate genes, and b) biographical exposure to environmental risk factors. It is necessary to perform new studies, with appropriate control groups and designs, in order to reach relevant conclusions with regard to gene/environmental (diet, lifestyle) interactions.

  6. Competitive Protein-binding assay-based Enzyme-immunoassay Method, Compared to High-pressure Liquid Chromatography, Has a Very Lower Diagnostic Value to Detect Vitamin D Deficiency in 9–12 Years Children

    Science.gov (United States)

    Zahedi Rad, Maliheh; Neyestani, Tirang Reza; Nikooyeh, Bahareh; Shariatzadeh, Nastaran; Kalayi, Ali; Khalaji, Niloufar; Gharavi, Azam

    2015-01-01

    Background: The most reliable indicator of Vitamin D status is circulating concentration of 25-hydroxycalciferol (25(OH) D) routinely determined by enzyme-immunoassays (EIA) methods. This study was performed to compare commonly used competitive protein-binding assays (CPBA)-based EIA with the gold standard, high-pressure liquid chromatography (HPLC). Methods: Concentrations of 25(OH) D in sera from 257 randomly selected school children aged 9–11 years were determined by two methods of CPBA and HPLC. Results: Mean 25(OH) D concentration was 22 ± 18.8 and 21.9 ± 15.6 nmol/L by CPBA and HPLC, respectively. However, mean 25(OH) D concentrations of the two methods became different after excluding undetectable samples (25.1 ± 18.9 vs. 29 ± 14.5 nmol/L, respectively; P = 0.04). Based on predefined Vitamin D deficiency as 25(OH) D < 12.5 nmol/L, CPBA sensitivity and specificity were 44.2% and 60.6%, respectively, compared to HPLC. In receiver operating characteristic curve analysis, the best cut-offs for CPBA was 5.8 nmol/L, which gave 82% sensitivity, but specificity was 17%. Conclusions: Though CPBA may be used as a screening tool, more reliable methods are needed for diagnostic purposes. PMID:26330983

  7. Competitive Protein-binding assay-based Enzyme-immunoassay Method, Compared to High-pressure Liquid Chromatography, Has a Very Lower Diagnostic Value to Detect Vitamin D Deficiency in 9-12 Years Children.

    Science.gov (United States)

    Zahedi Rad, Maliheh; Neyestani, Tirang Reza; Nikooyeh, Bahareh; Shariatzadeh, Nastaran; Kalayi, Ali; Khalaji, Niloufar; Gharavi, Azam

    2015-01-01

    The most reliable indicator of Vitamin D status is circulating concentration of 25-hydroxycalciferol (25(OH) D) routinely determined by enzyme-immunoassays (EIA) methods. This study was performed to compare commonly used competitive protein-binding assays (CPBA)-based EIA with the gold standard, high-pressure liquid chromatography (HPLC). Concentrations of 25(OH) D in sera from 257 randomly selected school children aged 9-11 years were determined by two methods of CPBA and HPLC. Mean 25(OH) D concentration was 22 ± 18.8 and 21.9 ± 15.6 nmol/L by CPBA and HPLC, respectively. However, mean 25(OH) D concentrations of the two methods became different after excluding undetectable samples (25.1 ± 18.9 vs. 29 ± 14.5 nmol/L, respectively; P = 0.04). Based on predefined Vitamin D deficiency as 25(OH) D < 12.5 nmol/L, CPBA sensitivity and specificity were 44.2% and 60.6%, respectively, compared to HPLC. In receiver operating characteristic curve analysis, the best cut-offs for CPBA was 5.8 nmol/L, which gave 82% sensitivity, but specificity was 17%. Though CPBA may be used as a screening tool, more reliable methods are needed for diagnostic purposes.

  8. A Heterogeneous Nuclear Ribonucleoprotein A/B-Related Protein Binds to Single-Stranded DNA near the 5′ End or within the Genome of Feline Parvovirus and Can Modify Virus Replication

    Science.gov (United States)

    Wang, Dai; Parrish, Colin R.

    1999-01-01

    Phage display of cDNA clones prepared from feline cells was used to identify host cell proteins that bound to DNA-containing feline panleukopenia virus (FPV) capsids but not to empty capsids. One gene found in several clones encoded a heterogeneous nuclear ribonucleoprotein (hnRNP)-related protein (DBP40) that was very similar in sequence to the A/B-type hnRNP proteins. DBP40 bound specifically to oligonucleotides representing a sequence near the 5′ end of the genome which is exposed on the outside of the full capsid but did not bind most other terminal sequences. Adding purified DBP40 to an in vitro fill-in reaction using viral DNA as a template inhibited the production of the second strand after nucleotide (nt) 289 but prior to nt 469. DBP40 bound to various regions of the viral genome, including a region between nt 295 and 330 of the viral genome which has been associated with transcriptional attenuation of the parvovirus minute virus of mice, which is mediated by a stem-loop structure of the DNA and cellular proteins. Overexpression of the protein in feline cells from a plasmid vector made them largely resistant to FPV infection. Mutagenesis of the protein binding site within the 5′ end viral genome did not affect replication of the virus. PMID:10438866

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. ANALYSIS OF BUDGET DEFICIT IN THE CANDIDATE COUNTRIES FOR EU MEMBERSHIP

    Directory of Open Access Journals (Sweden)

    Danijela Despotović

    2017-11-01

    Full Text Available The problems of deficit and debt are the traditional drivers of the recession in the past. Due to the high impact of the budget deficit to increase in indebtedness and deterioration of a macroeconomic performance, the European Union in Maastricht Treaty and later in the Pact of Stability and Growth strictly defined fiscal criteria which the member states should adhere to. Fiscal criteria are particularly important when it comes to candidate countries for EU membership. The aim of this paper is that, through theoretical and empirical basis perform a comparative analysis of the budget deficit in EU countries and candidates for membership in the EU, to rank the 34 countries according to the criteria of public finances and to show the causality between the candidate countries for membership of the EU and EU member states.

  14. Speeding disease gene discovery by sequence based candidate prioritization

    Directory of Open Access Journals (Sweden)

    Porteous David J

    2005-03-01

    Full Text Available Abstract Background Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning. Results We examined a variety of sequence-based features and found that for many of them there are significant differences between the sets of genes known to be involved in human hereditary disease and those not known to be involved in disease. We have created an automatic classifier called PROSPECTR based on those features using the alternating decision tree algorithm which ranks genes in the order of likelihood of involvement in disease. On average, PROSPECTR enriches lists for disease genes two-fold 77% of the time, five-fold 37% of the time and twenty-fold 11% of the time. Conclusion PROSPECTR is a simple and effective way to identify genes involved in Mendelian and oligogenic disorders. It performs markedly better than the single existing sequence-based classifier on novel data. PROSPECTR could save investigators looking at large regions of interest time and effort by prioritizing positional candidate genes for mutation detection and case-control association studies.

  15. 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

  16. 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

  17. 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.

  18. 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

  19. Quantifying drug-protein binding in vivo

    International Nuclear Information System (INIS)

    Buchholz, B; Bench, G; Keating III, G; Palmblad, M; Vogel, J; Grant, P G; Hillegonds, D

    2004-01-01

    Accelerator mass spectrometry (AMS) provides precise quantitation of isotope labeled compounds that are bound to biological macromolecules such as DNA or proteins. The sensitivity is high enough to allow for sub-pharmacological (''micro-'') dosing to determine macromolecular targets without inducing toxicities or altering the system under study, whether it is healthy or diseased. We demonstrated an application of AMS in quantifying the physiologic effects of one dosed chemical compound upon the binding level of another compound in vivo at sub-toxic doses [4].We are using tissues left from this study to develop protocols for quantifying specific binding to isolated and identified proteins. We also developed a new technique to quantify nanogram to milligram amounts of isolated protein at precisions that are comparable to those for quantifying the bound compound by AMS

  20. Polymeric competitive protein binding adsorbents for radioassay

    International Nuclear Information System (INIS)

    Adams, R.J.

    1976-01-01

    Serum protein comprising specific binding proteins such as antibodies, B 12 intrinsic factor, thyroxin binding globulin and the like may be copolymerized with globulin constituents of serum by the action of ethylchloroformate to form readily packed insoluble precipitates which, following purification as by washing, are eminently suited for employment as competitive binding protein absorbents in radioassay procedures. 10 claims, no drawings

  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. BEEF CATTLE MUSCULARITY CANDIDATE GENES

    Directory of Open Access Journals (Sweden)

    Irida Novianti

    2010-04-01

    Full Text Available Muscularity is a potential indicator for the selection of more productive cattle. Mapping quantitative trait loci (QTL for traits related to muscularity is useful to identify the genomic regions where the genes affecting muscularity reside. QTL analysis from a Limousin-Jersey double backcross herd was conducted using QTL Express software with cohort and breed as the fixed effects. Nine QTL suggested to have an association with muscularity were identified on cattle chromosomes BTA 1, 2, 3, 4, 5, 8, 12, 14 and 17. The myostatin gene is located at the centromeric end of chromosome 2 and not surprisingly, the Limousin myostatin F94L variant accounted for the QTL on BTA2. However, when the myostatin F94L genotype was included as an additional fixed effect, the QTL on BTA17 was also no longer significant. This result suggests that there may be gene(s that have epistatic effects with myostatin located on cattle chromosome 17. Based on the position of the QTL in base pairs, all the genes that reside in the region were determined using the Ensembl data base (www.ensembl.org. There were two potential candidate genes residing within these QTL regions were selected. They were Smad nuclear interacting protein 1 (SNIP1 and similar to follistatin-like 5 (FSTL5. (JIIPB 2010 Vol 20 No 1: 1-10

  10. Importance measures in risk-informed decision making: Ranking, optimisation and configuration control

    Energy Technology Data Exchange (ETDEWEB)

    Vaurio, Jussi K., E-mail: jussi.vaurio@pp1.inet.fi [Prometh Solutions, Hiihtaejaenkuja 3K, 06100 Porvoo (Finland)

    2011-11-15

    This paper describes roles, extensions and applications of importance measures of components and configurations for making risk-informed decisions relevant to system operations, maintenance and safety. Basic importance measures and their relationships are described for independent and mutually exclusive events and for groups of events associated with common cause failures. The roles of importances are described mainly in two groups of activities: (a) ranking safety significance of systems, structures, components and human actions for preventive safety assurance activities, and (b) making decisions about permissible permanent and temporary configurations and allowed configuration times for regulation, technical specifications and for on-line risk monitoring. Criticality importance and sums of criticalities turn out to be appropriate measures for ranking and optimization. Several advantages are pointed out and consistent ranking of pipe segments for in-service inspection is provided as an example. Risk increase factor and its generalization risk gain are most appropriately used to assess corrective priorities and acceptability of a situation when components are already failed or when planning to take one or more components out of service for maintenance. Precise definitions are introduced for multi-failure configurations and it is shown how they can be assessed under uncertainties, in particular when common cause failures or success states may be involved. A general weighted average method is compared to other candidate methods in benchmark cases. It is the preferable method for prediction when a momentary configuration is known or only partially known. Potential applications and optimization of allowed outage times are described. The results show how to generalize and apply various importance measures to ranking and optimization and how to manage configurations in uncertain multi-failure situations. - Highlights: > Rigorous methods developed for using importances

  11. Importance measures in risk-informed decision making: Ranking, optimisation and configuration control

    International Nuclear Information System (INIS)

    Vaurio, Jussi K.

    2011-01-01

    This paper describes roles, extensions and applications of importance measures of components and configurations for making risk-informed decisions relevant to system operations, maintenance and safety. Basic importance measures and their relationships are described for independent and mutually exclusive events and for groups of events associated with common cause failures. The roles of importances are described mainly in two groups of activities: (a) ranking safety significance of systems, structures, components and human actions for preventive safety assurance activities, and (b) making decisions about permissible permanent and temporary configurations and allowed configuration times for regulation, technical specifications and for on-line risk monitoring. Criticality importance and sums of criticalities turn out to be appropriate measures for ranking and optimization. Several advantages are pointed out and consistent ranking of pipe segments for in-service inspection is provided as an example. Risk increase factor and its generalization risk gain are most appropriately used to assess corrective priorities and acceptability of a situation when components are already failed or when planning to take one or more components out of service for maintenance. Precise definitions are introduced for multi-failure configurations and it is shown how they can be assessed under uncertainties, in particular when common cause failures or success states may be involved. A general weighted average method is compared to other candidate methods in benchmark cases. It is the preferable method for prediction when a momentary configuration is known or only partially known. Potential applications and optimization of allowed outage times are described. The results show how to generalize and apply various importance measures to ranking and optimization and how to manage configurations in uncertain multi-failure situations. - Highlights: → Rigorous methods developed for using importances

  12. Output ordering and prioritisation system (OOPS): ranking biosynthetic gene clusters to enhance bioactive metabolite discovery.

    Science.gov (United States)

    Peña, Alejandro; Del Carratore, Francesco; Cummings, Matthew; Takano, Eriko; Breitling, Rainer

    2017-12-18

    The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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...

  18. 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.

  19. 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)

  20. 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.....

  1. 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.

  2. 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

  3. 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.

  4. On the classification of complex vector bundles of stable rank

    Indian Academy of Sciences (India)

    , the tuples of cohomology classes on a compact, complex manifold, corresponding to the Chern classes of a complex vector bundle of stable rank. This classification becomes more effective on generalized flag manifolds, where the Lie ...

  5. Ranking and evaluating the factors affecting the success of ...

    African Journals Online (AJOL)

    Ranking and evaluating the factors affecting the success of management team in construction projects. ... Journal of Fundamental and Applied Sciences. Journal Home ... The project management team is one of these important factors.

  6. A network-based dynamical ranking system for competitive sports

    Science.gov (United States)

    Motegi, Shun; Masuda, Naoki

    2012-12-01

    From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts.

  7. INTEL: Intel based systems move up in supercomputing ranks

    CERN Multimedia

    2002-01-01

    "The TOP500 supercomputer rankings released today at the Supercomputing 2002 conference show a dramatic increase in the number of Intel-based systems being deployed in high-performance computing (HPC) or supercomputing areas" (1/2 page).

  8. Hyper-local, directions-based ranking of places

    DEFF Research Database (Denmark)

    Venetis, Petros; Gonzalez, Hector; Jensen, Christian S.

    2011-01-01

    they are numerous and contain precise locations. Specifically, the paper proposes a framework that takes a user location and a collection of near-by places as arguments, producing a ranking of the places. The framework enables a range of aspects of directions queries to be exploited for the ranking of places......, including the frequency with which places have been referred to in directions queries. Next, the paper proposes an algorithm and accompanying data structures capable of ranking places in response to hyper-local web queries. Finally, an empirical study with very large directions query logs offers insight...... into the potential of directions queries for the ranking of places and suggests that the proposed algorithm is suitable for use in real web search engines....

  9. Superfund Hazard Ranking System Training Course: Table of Contents

    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

  10. Some relations between rank, chromatic number and energy of graphs

    International Nuclear Information System (INIS)

    Akbari, S.; Ghorbani, E.; Zare, S.

    2006-08-01

    The energy of a graph G is defined as the sum of the absolute values of all eigenvalues of G and denoted by E(G). Let G be a graph and rank(G) be the rank of the adjacency matrix of G. In this paper we characterize all the graphs with E(G) = rank(G). Among other results we show that apart from a few families of graphs, E(G) ≥ 2max(χ(G), n - χ(G--bar)), where G-bar and χ(G) are the complement and the chromatic number of G, respectively. Moreover some new lower bounds for E(G) in terms of rank(G) are given. (author)

  11. The importance of research in university's webometric ranking ...

    African Journals Online (AJOL)

    Results: Websites are the most efficient and cheapest way for boosting all the three ... Web indicators are used for ranking purposes; they are not based on number of visits or ... All academic staff should be involved in quality research activities.

  12. Personalized Profile Based Search Interface With Ranked and Clustered Display

    National Research Council Canada - National Science Library

    Kumar, Sachin; Oztekin, B. U; Ertoz, Levent; Singhal, Saurabh; Han, Euihong; Kumar, Vipin

    2001-01-01

    We have developed an experimental meta-search engine, which takes the snippets from traditional search engines and presents them to the user either in the form of clusters, indices or re-ranked list...

  13. RUSSIAN UNIVERSITIES IN THE LOOP OF THE WORLD EDUCATION RANKINGS

    Directory of Open Access Journals (Sweden)

    Inozemtseva Ekaterina Sergeevna

    2013-02-01

    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.

  14. an investigation into n investigation into index ranking technique

    African Journals Online (AJOL)

    eobe

    probability theory, namely, the Monte C. Simulation ... The study shows that the utility of the ranking technique may be limited by em. Therefore ... in decision making under fuzzy. The use of ... thereby making decision making impossible or.

  15. Intergenerational Educational Rank Mobility in 20th Century United States

    DEFF Research Database (Denmark)

    Karlson, Kristian Bernt

    2015-01-01

    in the overall schooling distribution both over time and among population groups defined by race and gender.METHODS & DATA: To analyze educational rank mobility, I use quantile transition matrices known from studies on intergenerational income mobility. However, because schooling distributions are quite lumpy......, particularly around 12 and 16 years of schooling, percentile ranks of interest may not always be defined among parents or offspring (e.g., the lower or upper quartile may not be given by the data). To deal with this issue, I use a cohort-adjustment that deflates the schooling distribution in proportion...... performance of historically disadvantaged groups. To reconcile these diverging trends, I propose examining educational mobility in terms of percentile ranks in the respective schooling distributions of parents and offspring. Using a novel estimator of educational rank, I compare patterns of mobility...

  16. PageRank, HITS and a unified framework for link analysis

    Energy Technology Data Exchange (ETDEWEB)

    Ding, Chris; He, Xiaofeng; Husbands, Parry; Zha, Hongyuan; Simon, Horst

    2001-10-01

    Two popular webpage ranking algorithms are HITS and PageRank. HITS emphasizes mutual reinforcement between authority and hub webpages, while PageRank emphasizes hyperlink weight normalization and web surfing based on random walk models. We systematically generalize/combine these concepts into a unified framework. The ranking framework contains a large algorithm space; HITS and PageRank are two extreme ends in this space. We study several normalized ranking algorithms which are intermediate between HITS and PageRank, and obtain closed-form solutions. We show that, to first order approximation, all ranking algorithms in this framework, including PageRank and HITS, lead to same ranking which is highly correlated with ranking by indegree. These results support the notion that in web resource ranking indegree and outdegree are of fundamental importance. Rankings of webgraphs of different sizes and queries are presented to illustrate our analysis.

  17. Learning to rank figures within a biomedical article.

    Directory of Open Access Journals (Sweden)

    Feifan Liu

    Full Text Available Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1 First Author, (2 Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3 Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or

  18. Ranking benchmarks of top 100 players in men's professional tennis.

    Science.gov (United States)

    Reid, Machar; Morris, Craig

    2013-01-01

    In men's professional tennis, players aspire to hold the top ranking position. On the way to the top spot, reaching the top 100 can be seen as a significant career milestone. National Federations undertake extensive efforts to assist their players to reach the top 100. However, objective data considering reasonable ranking yardsticks for top 100 success in men's professional tennis are lacking. Therefore, it is difficult for National Federations and those involved in player development to give empirical programming advice to young players. By taking a closer look at the ranking history of professional male tennis players, this article tries to provide those involved in player development a more objective basis for decision-making. The 100 names, countries, birthdates and ranking histories of the top 100 players listed in the Association of Tennis Professionals (ATP) at 31 December 2009 were recorded from websites in the public domain. Descriptive statistics were reported for the ranking milestones of interest. Results confirmed the merits of the International Tennis Federation's junior tour with 91% of the top 100 professionals earning a junior ranking, the mean peak of which was 94.1, s=148.9. On average, top 100 professionals achieved their best junior rankings and earned their first ATP point at similar ages, suggesting that players compete on both the junior and professional tours during their transition. Once professionally ranked, players took an average 4.5, s=2.1 years to reach the ATP top 100 at the mean age of 21.5, s=2.6 years, which contrasts with the mean current age of the top 100 of 26.8, s=3.2. The best professional rankings of players born in 1982 or earlier were positively related to the ages at which players earned their first ATP point and then entered the top 100, suggesting that the ages associated with these ranking milestones may have some forecasting potential. Future work should focus on the change in top 100 demographics over time as well

  19. Automatic figure ranking and user interfacing for intelligent figure search.

    Directory of Open Access Journals (Sweden)

    Hong Yu

    2010-10-01

    Full Text Available Figures are important experimental results that are typically reported in full-text bioscience articles. Bioscience researchers need to access figures to validate research facts and to formulate or to test novel research hypotheses. On the other hand, the sheer volume of bioscience literature has made it difficult to access figures. Therefore, we are developing an intelligent figure search engine (http://figuresearch.askhermes.org. Existing research in figure search treats each figure equally, but we introduce a novel concept of "figure ranking": figures appearing in a full-text biomedical article can be ranked by their contribution to the knowledge discovery.We empirically validated the hypothesis of figure ranking with over 100 bioscience researchers, and then developed unsupervised natural language processing (NLP approaches to automatically rank figures. Evaluating on a collection of 202 full-text articles in which authors have ranked the figures based on importance, our best system achieved a weighted error rate of 0.2, which is significantly better than several other baseline systems we explored. We further explored a user interfacing application in which we built novel user interfaces (UIs incorporating figure ranking, allowing bioscience researchers to efficiently access important figures. Our evaluation results show that 92% of the bioscience researchers prefer as the top two choices the user interfaces in which the most important figures are enlarged. With our automatic figure ranking NLP system, bioscience researchers preferred the UIs in which the most important figures were predicted by our NLP system than the UIs in which the most important figures were randomly assigned. In addition, our results show that there was no statistical difference in bioscience researchers' preference in the UIs generated by automatic figure ranking and UIs by human ranking annotation.The evaluation results conclude that automatic figure ranking and user

  20. Learning to rank figures within a biomedical article.

    Science.gov (United States)

    Liu, Feifan; Yu, Hong

    2014-01-01

    Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1) First Author, (2) Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3) Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or out