960 resultados para projection package


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We present and validate BlastR, a method for efficiently and accurately searching non-coding RNAs. Our approach relies on the comparison of di-nucleotides using BlosumR, a new log-odd substitution matrix. In order to use BlosumR for comparison, we recoded RNA sequences into protein-like sequences. We then showed that BlosumR can be used along with the BlastP algorithm in order to search non-coding RNA sequences. Using Rfam as a gold standard, we benchmarked this approach and show BlastR to be more sensitive than BlastN. We also show that BlastR is both faster and more sensitive than BlastP used with a single nucleotide log-odd substitution matrix. BlastR, when used in combination with WU-BlastP, is about 5% more accurate than WU-BlastN and about 50 times slower. The approach shown here is equally effective when combined with the NCBI-Blast package. The software is an open source freeware available from www.tcoffee.org/blastr.html.

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SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

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The research examines general practitioners attitudes and how these effect the management of drug misusers within their practice. The methodology is quantitative in approach. The instrument used is a structured postal questionnaire. Participants include all general practitioners within the North East region of Ireland. Anonymity and confidentiality of all respondents are guaranteed. Data was collected over a six week period, under the following headings - attitudes and beliefs, factors influencing treatment, treatment options, training and demographics. Attitudes and beliefs towards drug users were measured using a five point Likert scale ranging from strongly agrees to strongly disagree. The data was analysed with the aid of a computer package, SPSS allowing descriptive statistics to be presented. Results indicate that the majority of respondents are male. There appears to be sympathy towards drug users and that treatment approaches should be holistic. However, there appears to be a major lack of confidence in treating and managing drug misusers. Patient, social and practice factors all influence the decision to the drug misuser. Treatment options are varied, ranging from methadone maintenance to referral for residential treatment. However, a number of respondents offer no treatment for drug misusers. General practitioners do not feel adequately trained in treating and/or managing this client group. Results indicate that improved communication, ongoing education and more research is needed in this area.This resource was contributed by The National Documentation Centre on Drug Use.

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Aquest projecte té per objectiu conèixer i manipular fitxers creats amb el paquet ofimàtic de software lliure OpenOffice. Aquests fitxers es guarden en format anomenat OASIS, format que pren com a base l'estàndard XML i l'adapta a les característiques específiques que s'han dissenyat pels documents OpenOffice.

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Conventional coronary magnetic resonance angiography (MRA) techniques display the coronary blood-pool along with the surrounding structures, including the myocardium, the ventricular and atrial blood-pool, and the great vessels. This representation of the coronary lumen is not directly analogous to the information provided by x-ray coronary angiography, in which the coronary lumen displayed by iodinated contrast agent is seen. Analogous "luminographic" data may be obtained using MR arterial spin tagging (projection coronary MRA) techniques. Such an approach was implemented using a 2D selective "pencil" excitation for aortic spin tagging in concert with a 3D interleaved segmented spiral imaging sequence with free-breathing, and real-time navigator technology. This technique allows for selective 3D visualization of the coronary lumen blood-pool, while signal from the surrounding structures is suppressed.

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Nonadherence to treatment is a common problem in the clinical management of hypercholesterolemic patients. This study was carried out with the aim of monitoring the daily compliance to a 6-month course of lipid-lowering therapy, using a microelectronic device, the Medication Event Monitoring System (MEMS), versus pill count. Forty men with primary hypercholesterolemia were prescribed fluvastatin 1 x 40 mg daily, provided in a MEMS package to record the date and time of each opening of the pillbox. Thirty-nine of 40 patients (98%) completed the study. Total cholesterol and LDL cholesterol levels decreased significantly (18% and 25%, p < 0.001) during the 6-month therapy period. A high mean rate of compliance was achieved by MEMS using the following three indexes--compliance to total prescribed dose (88.8% +/- 13.5%), compliance to prescribed days (82.4% +/- 19.5%), and compliance to prescribed time of day (81.86% +/- 19.5%)--and by pill count (93.4% +/- 9.5%). In addition, the MEMS provided some patterns of nonadherence to medication, undetectable by pill count alone, such as a drug holiday in 38% of cases, a drug omission for more than 7 consecutive days in 9% of cases, and, conversely, use of more than the one prescribed daily dose in 47% of cases. A significant correlation between the rate of compliance and the decrease in LDL cholesterol was observed only when the compliance was assessed by MEMS. The results indicate that MEMS is a useful tool for monitoring compliance in clinical practice and may possibly increase adherence to long-term lipid-lowering therapy.

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Nutrition is central to health and children's diets can be an important influence now and in the future. Stop, Look and Cook is a new recipe book for use by catering staff in all grant-aided nursery, primary and post-primary schools in Northern Ireland.�Recipes have been collected from school caterers across the region. These recipes have been checked to ensure that they are compliant with nutritional standards for school lunches and have been tested in schools for taste and suitability. In addition all the recipes have been analysed by the PHA using a nutritional software package, with a particular focus on fat, salt and sugar.�This recipe book provides approximately 280 recipes, giving schools more choice for menus. It also contains useful advice for dealing with food allergies and supplying alternative meals for pupils from other cultures.For more information on Stop, Look and Cook please contact the school meals catering manager at your local Education and Library Board.�

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El sistema desenvolupat és un 'paquet detector', que vol facilitar la tasca de detecció del d'un trànsit de xarxa fora del normal i aconseguir que els resultats puguin ser vistos amb facilitat des d'altres segments de la xarxa.

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This case report outlines research undertaken as the result of a document examination case in which two envelopes were involved. The combination of the circumstances of the case and the results of the examination allows a simple application of a logical approach to pre-assess the probability that an envelope (or a package) potentially recovered at a suspect's home comes from the same batch (same source) as questioned envelopes. This highlights that it is useful to examine envelopes.

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El Library and Learning Support Working Group (LLSWG) és una xarxa europea de professionals de biblioteca i de la informació i educadors dins de l'Associació Europea d'Universitats d'Ensenyament (EADTU). EADTU és l'organització que representa tant les universitats obertes i d'ensenyament a distància com els consorcis nacionals d'institucions d'ensenyament superior actius en els camps d'educació de distància i e-learning. El 2005 l'Associació Europea d'Universitats d'Ensenyament de Distància (EADTU) presentava a la Comissió Europea una proposta de projecte sobre Mobilitat Virtual anomenada E-MOVE. El projecte incloïa, entre d'altres, un paquet de treball referent a biblioteca i suport a l'aprenentatge al context de mobilitat virtual. Aquest fou desenvolupat pel LLSWG de l'EADTU.

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Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

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The multiscale finite volume (MsFV) method has been developed to efficiently solve large heterogeneous problems (elliptic or parabolic); it is usually employed for pressure equations and delivers conservative flux fields to be used in transport problems. The method essentially relies on the hypothesis that the (fine-scale) problem can be reasonably described by a set of local solutions coupled by a conservative global (coarse-scale) problem. In most cases, the boundary conditions assigned for the local problems are satisfactory and the approximate conservative fluxes provided by the method are accurate. In numerically challenging cases, however, a more accurate localization is required to obtain a good approximation of the fine-scale solution. In this paper we develop a procedure to iteratively improve the boundary conditions of the local problems. The algorithm relies on the data structure of the MsFV method and employs a Krylov-subspace projection method to obtain an unconditionally stable scheme and accelerate convergence. Two variants are considered: in the first, only the MsFV operator is used; in the second, the MsFV operator is combined in a two-step method with an operator derived from the problem solved to construct the conservative flux field. The resulting iterative MsFV algorithms allow arbitrary reduction of the solution error without compromising the construction of a conservative flux field, which is guaranteed at any iteration. Since it converges to the exact solution, the method can be regarded as a linear solver. In this context, the schemes proposed here can be viewed as preconditioned versions of the Generalized Minimal Residual method (GMRES), with a very peculiar characteristic that the residual on the coarse grid is zero at any iteration (thus conservative fluxes can be obtained).

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Compositional data naturally arises from the scientific analysis of the chemicalcomposition of archaeological material such as ceramic and glass artefacts. Data of thistype can be explored using a variety of techniques, from standard multivariate methodssuch as principal components analysis and cluster analysis, to methods based upon theuse of log-ratios. The general aim is to identify groups of chemically similar artefactsthat could potentially be used to answer questions of provenance.This paper will demonstrate work in progress on the development of a documentedlibrary of methods, implemented using the statistical package R, for the analysis ofcompositional data. R is an open source package that makes available very powerfulstatistical facilities at no cost. We aim to show how, with the aid of statistical softwaresuch as R, traditional exploratory multivariate analysis can easily be used alongside, orin combination with, specialist techniques of compositional data analysis.The library has been developed from a core of basic R functionality, together withpurpose-written routines arising from our own research (for example that reported atCoDaWork'03). In addition, we have included other appropriate publicly availabletechniques and libraries that have been implemented in R by other authors. Availablefunctions range from standard multivariate techniques through to various approaches tolog-ratio analysis and zero replacement. We also discuss and demonstrate a smallselection of relatively new techniques that have hitherto been little-used inarchaeometric applications involving compositional data. The application of the libraryto the analysis of data arising in archaeometry will be demonstrated; results fromdifferent analyses will be compared; and the utility of the various methods discussed

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Background The 'database search problem', that is, the strengthening of a case - in terms of probative value - against an individual who is found as a result of a database search, has been approached during the last two decades with substantial mathematical analyses, accompanied by lively debate and centrally opposing conclusions. This represents a challenging obstacle in teaching but also hinders a balanced and coherent discussion of the topic within the wider scientific and legal community. This paper revisits and tracks the associated mathematical analyses in terms of Bayesian networks. Their derivation and discussion for capturing probabilistic arguments that explain the database search problem are outlined in detail. The resulting Bayesian networks offer a distinct view on the main debated issues, along with further clarity. Methods As a general framework for representing and analyzing formal arguments in probabilistic reasoning about uncertain target propositions (that is, whether or not a given individual is the source of a crime stain), this paper relies on graphical probability models, in particular, Bayesian networks. This graphical probability modeling approach is used to capture, within a single model, a series of key variables, such as the number of individuals in a database, the size of the population of potential crime stain sources, and the rarity of the corresponding analytical characteristics in a relevant population. Results This paper demonstrates the feasibility of deriving Bayesian network structures for analyzing, representing, and tracking the database search problem. The output of the proposed models can be shown to agree with existing but exclusively formulaic approaches. Conclusions The proposed Bayesian networks allow one to capture and analyze the currently most well-supported but reputedly counter-intuitive and difficult solution to the database search problem in a way that goes beyond the traditional, purely formulaic expressions. The method's graphical environment, along with its computational and probabilistic architectures, represents a rich package that offers analysts and discussants with additional modes of interaction, concise representation, and coherent communication.

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R from http://www.r-project.org/ is ‘GNU S’ – a language and environment for statistical computingand graphics. The environment in which many classical and modern statistical techniques havebeen implemented, but many are supplied as packages. There are 8 standard packages and many moreare available through the cran family of Internet sites http://cran.r-project.org .We started to develop a library of functions in R to support the analysis of mixtures and our goal isa MixeR package for compositional data analysis that provides support foroperations on compositions: perturbation and power multiplication, subcomposition with or withoutresiduals, centering of the data, computing Aitchison’s, Euclidean, Bhattacharyya distances,compositional Kullback-Leibler divergence etc.graphical presentation of compositions in ternary diagrams and tetrahedrons with additional features:barycenter, geometric mean of the data set, the percentiles lines, marking and coloring ofsubsets of the data set, theirs geometric means, notation of individual data in the set . . .dealing with zeros and missing values in compositional data sets with R procedures for simpleand multiplicative replacement strategy,the time series analysis of compositional data.We’ll present the current status of MixeR development and illustrate its use on selected data sets