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  • 1
    Electronic Resource
    Electronic Resource
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 4 (2008), S. 1 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: The commonly used two-sample tests of equal area-under-the-curve (AUC), where AUC is based on the linear trapezoidal rule, may have poor properties when observations are missing, even if they are missing completely at random (MCAR). We propose two tests: one that has good properties when data are MCAR and another that has good properties when the data are missing at random (MAR), provided that the pattern of missingness is monotonic. In addition, we discuss other non-parametric tests of hypotheses that are similar, but not identical, to the hypothesis of equal AUCs, but that often have better statistical properties than do AUC tests and may be more scientifically appropriate for many settings.
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  • 2
    Electronic Resource
    Electronic Resource
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 7.2008, 1, art2 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: The relationship between speciation times and the corresponding times of gene divergence is of interest in phylogenetic inference as a means of understanding the past evolutionary dynamics of populations and of estimating the timing of speciation events. It has long been recognized that gene divergence times might substantially pre-date speciation events. Although the distribution of the difference between these has previously been studied for the case of two populations, this distribution has not been explicitly computed for larger species phylogenies. Here we derive a simple method for computing this distribution for trees of arbitrary size. A two-stage procedure is proposed which (i) considers the probability distribution of the time from the speciation event at the root of the species tree to the gene coalescent time conditionally on the number of gene lineages available at the root; and (ii) calculates the probability mass function for the number of gene lineages at the root. This two-stage approach dramatically simplifies numerical analysis, because in the first step the conditional distribution does not depend on an underlying species tree, while in the second step the pattern of gene coalescence prior to the species tree root is irrelevant. In addition, the algorithm provides intuition concerning the properties of the distribution with respect to the various features of the underlying species tree. The methodology is complemented by developing probabilistic formulae and software, written in R. The method and software are tested on five-taxon species trees with varying levels of symmetry. The examples demonstrate that more symmetric species trees tend to have larger mean coalescent times and are more likely to have a unimodal gamma-like distribution with a long right tail, while asymmetric trees tend to have smaller mean coalescent times with an exponential-like distribution. In addition, species trees with longer branches generally have shorter mean coalescent times, with branches closest to the root of the tree being most influential.
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  • 3
    Electronic Resource
    Electronic Resource
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 7.2008, 1, art1 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Based on previous studies related to the yeast cell cycle, it is well known that the underlying cellular network in yeast consists of many interactions between genes that have periodic expression patterns during the cell division cycle. In this study, it is proposed that cell cycle-specific gene expression can be understood as a phenomenon of collective synchronization or, in other words, an ensemble of non-identical oscillating response signals from different systems. Therefore, we aimed to apply the theory of statistical multivariate phase synchronization to understand the cell's cyclic transcriptome as a phenomenon of collective synchronization. To this end, a novel algorithm called Self-Organizing Maps with statistical Phase Synchronization (SOMPS) is proposed and evaluated using yeast cell cycle-specific gene expression data. From the evaluation experiments, we draw the following conclusions: 1) It is possible to find groups of genes that have biological interactions with each other and significantly share gene ontology slim terms of biological processes using the theory of multivariate phase synchronization with cell cycle-specific gene expression signals; 2) Among all output clusters of SOMPS, a relatively large cluster with high periodicity with respect to its trained mean field can be considered a prominent cluster; 3) For each gene, it is possible to identify the degree of the strength of its biological interactions with other genes using the coupling strength of synchronization with its trained mean field; and 4) It is feasible to understand cell cycle-specific expression patterns as a phenomenon of collective synchronization.
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  • 4
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. -2--1 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
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  • 5
    Electronic Resource
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 37-47 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: In this work, two systems of mesoporous bioactive glasses (MBGs) with a series ofdifferent SiO2:CaO:P2O5 ratios were derived via a sol-gel method involving the usage of blockcopolymers Pluronic F127 and P123 as templates, respectively. A two-dimensional hexagonal(P6mm) mesoporous structure was obtained in the two systems with a SiO2:CaO:P2O5 ratio of80:16:4. With the decrease of the SiO2 content, the porous structure of MBGs became less regular,and the BET surface area and the pore volume were also decreased. Mesoporous bioactive glassesfrom the template F127 displayed a higher degree of bioactivity than those from the template P123,as a result of the existence of more defects on the walls of the mesopores
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  • 6
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 1-36 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: The paper reports about different kind of sutures, their suitability and performance. An ideal suture should possess many characteristics such as - easy to handle, bio-compatibility, minimal tissue reaction, resistance to bacterial growth, adequate tensile strength and elasticity, knot security, strength loss versus healing rate of tissues. Selection of suture is often very complex for satisfying host of physical, mechanical and biological properties, and fulfilling contradictory requirements in varied applications. The paper develops an understanding about the selection of suture depending on the varied requirement. Past research work pertaining to the development of suture as reported in this paper, provides insight about the suitability of different surgical sutures and possible direction of future research
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  • 7
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 49-56 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: A general model of transport of gases in an artificial epidermal layer (membrane) wasestablished. The model was developed based on Dusty Gas Model (DGM), solution diffusion andsurface diffusion. As a result, solutions of the model for different transport conditions were derived.In this investigation, parameters of oxygen and carbon dioxide gases through an artificial“epidermal” membrane of varying porosity were used to calculate semi-empirical solutions of thegeneral model. In other words, the solutions of the general model were analytically obtained fordifferent transport conditions, using experimentally obtained parameters of oxygen and carbondioxide gases through the artificial “epidermal” membrane of varying porosity. The obtainedsolutions of the general model were for the oxygen and carbon dioxide gases through the artificial“epidermal” membrane of the varying porosity
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  • 8
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 57-68 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: Hydroxyapatite-zirconia composites have received much attention during the last decadedue to their combination of the desirable mechanical properties of zirconia and the excellentbioactivity of hydroxyapatite (HA). However, thermal decomposition of the hydroxyapatite phase andreaction between the zirconia phase and the hydroxyapatite phase remain a major problem in thehydroxyapatite-zirconia composites. In this study, thermally stable and fluorine-substitutedhydroxyapatite (Ca10(PO4)6(OH)0.8F1.2; coded as HA06F) was prepared by a sol-gel method to replacethe hydroxyapatite. Yttria-stabilized zirconia (YTZP) was also prepared by a sol-gel method in orderto produce HA06F-YTZP composites with 5, 10, 15, 20, 40, and 60 wt% YTZP by simple andcost-effective pressureless sintering. Thermogravimetric analysis (TGA) and x-ray diffraction (XRD)of the HA06F-YTZP composites showed that the thermal stability of the HA06F matrices could bemaintained when the YTZP content did not exceed 20 wt% and for sintering temperatures less than1400 oC. Dilatometric analysis and microstructural observation revealed that the YTZP phase in theHA06F-YTZP composites retarded the densification of the composites if the zirconia content wasover 20 wt%. Electron scanning microscopy (SEM) and high resolution transmission electronmicroscopy (HR-TEM) of the HA06F-YTZP composites showed that the YTZP second phase had asize in the nanometer scale and the reaction between the HA06F phase and the zirconia phase wassuppressed. Mechanical properties including the Knoop hardness, the Young’s modulus, and thefracture toughness of the HA06F-YTZP composites increased with the YTZP content until theoptimal content of 20 wt%; higher YTZP contents led to low mechanical properties due to poordensification of the composites and the severe thermal decomposition of the HA06F phase. Theoptimal HA06F-20YTZP composite also showed desirable attachment and proliferation of osteoblastcells. Nevertheless, the study of the composite system indicated the limitations of the pressurelesssintering technique. To achieve the full potential of the composites for medium or low load bearingapplications, a pressure-assisted sintering technique would still be necessary
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  • 9
    Electronic Resource
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 99-107 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: The limitations of autogenic, allogenic and xenogenic grafting methods have led to the developmentof synthetic grafts as an alternative. The aim of this study was to manufacture highly porous andwell interconnected hydroxyapatite scaffolds and modify them with a poly(lactic-co-glycolic acid)(PLGA)-bioactive glass composite coating to achieve mechanical properties close to those ofnatural cancellous bones. In this study, hydroxyapatite scaffolds were prepared from a calciumphosphate cement (CPC) powder and cell culture using fibroblast cells was done to examine thecytotoxicity of the materials used for the scaffolds. The average pore size of the scaffolds was foundto be 650μm and the total porosity was about 80%. The hydroxyapatite scaffolds without thecoating had a mean compressive strength and a mean compressive modulus of 0.74 MPa and 20.46MPa, respectively, which were in contrast to those of the scaffolds coated with the PLGA-bioacitveglass composite material (1.36 MPa and 24.58 MPa, respectively). The fibroblast cells wereobserved to proliferate well on the PLGA-bioactive glass coated scaffolds. The cells had alsopenetrated into the scaffold to a depth of approximately 2mm. Thus the scaffolds fabricated in thisstudy exhibited a favourable porous structure and good cell response which are desirable for bonetissue engineering
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  • 10
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 69-79 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: Palmitic acid was added into drug-loaded poly(L-lactide) (PLLA) to modify the drugrelease profiles of the polymer. The acid was added in different concentrations and gradients acrossthe thickness of the polymer. Drug release was monitored using a UV spectrometer over a period of90 days. Degradation was studied using gel permeation chromatography and differential scanningcalorimetry (DSC) to follow the change in the molecular weight and glass transition temperaturerespectively. Addition of palmitic acid was found to accelerate the degradation of PLLA andresulted in an accelerated release of the drug as expected. Modification of release profiles bydesigning the acid gradient was also attempted. It was found that the total acid concentration is stillthe dominant factor over the gradient design in affecting the degradation and subsequently therelease profiles. Different drug concentrations also played a role in the different release profilesexhibited. Surprisingly the sample with lower drug concentration (2wt%) showed a much higherinitial burst than the 5wt% loaded samples. This was due to the induced nucleation of the polymerby the drug at low concentration resulting in higher crystallinity of the polymer and consequentlyoverall lower solubility of the drug
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  • 11
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 81-89 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: The aim of this study was to investigate the feasibility of utilizing selective laser sintering(SLS) to build 3D porous tissue engineering scaffolds from small quantities of poly(L-lactide)(PLLA). PLLA microspheres with suitable particle sizes for the SLS process were produced by theoil-in-water emulsion solvent evaporation technique. A miniature build platform was designed,fabricated and incorporated in an existing Sinterstation® 2000 system to enable small quantities ofpolymer powder to be used for the production of 3D porous scaffolds. Trial runs were first performedusing the DuraForm™ polyamide powder and interfacing problems between the miniature buildplatform and the existing machine were solved. Then 3D porous scaffolds were successfully builtfrom the PLLA microspheres using the modified SLS machine. This study paved the way for furthercomprehensive studies on selective laser sintering of tissue engineering scaffolds using expensivebiopolymers and their composites
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  • 12
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    s.l. ; Stafa-Zurich, Switzerland
    Journal of biomimetics, biomaterials, and tissue engineering Vol. 1 (July 2008), p. 91-97 
    ISSN: 1662-100X
    Source: Scientific.Net: Materials Science & Technology / Trans Tech Publications Archiv 1984-2008
    Topics: Biology , Technology
    Notes: NiTi shape memory alloys are a group of materials which have a lot of applicationsespecially in aerospace industries and medical equipments because of their excellent properties.Shape memory effect (SME), pseudo-elasticity (PE), high corrosion resistance and biocompatibilityis special properties of these alloys which lead to their extensive applications. The superior behaviorof NiTi alloy is due to thermoelastic martensitic phase transformation. In the present paper, two NiTishape memory alloys were prepared by non-consumable vacuum arc melting technique in copperwater cooled crucible. One of them had commercial elements and the other had high purity elements.Metallographic investigation, chemical analysis, XRD and DSC were carried out on two alloys.Metallographic observation and XRD shows that structure at ambient temperature consists ofaustenite phase besides Ti2Ni, Ni3Ti intermetallic compounds and martensite phase. Transformationinvestigation determines that the impurity such as iron in commercial alloy causes two stage phasetransformation B2→R→B19′
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  • 13
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    Electronic Resource
    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 3 (2007), S. 12 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Understanding the genetic underpinnings to complex diseases requires consideration of sophisticated analytical methods designed to uncover intricate associations across multiple predictor variables. At the same time, knowledge of whether single nucleotide polymorphisms within a gene are on the same (in cis) or on different (in trans) chromosomal copies, may provide crucial information about measures of disease progression. In association studies of unrelated individuals, allelic phase is generally unobservable, generating an additional analytical challenge. In this manuscript, we describe a novel approach that combines multiple imputation and random forests for this high-dimensional, unobservable data setting. An application to a cohort of HIV-1 infected individuals receiving anti-retroviral therapies is presented. A simulation study is also presented to characterize method performance.
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  • 14
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 3 (2007), S. 9 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Child growth is characterised by increases in height, and increases in maturational status. Functional data analysis provides a tool to separate these two sources of variation (registration) and differentiates between the variation in maturational tempo (temporal, or "phase" variation) and the variation in height (amplitude variation). We extended this concept by combining Principal Component Analysis (PCA) and the Maximum Likelihood Principle. Longitudinal data on height were obtained from two large growth studies from Lublin, Poland, and Zurich, Switzerland, with altogether 361 children. Variation in amplitude monotonically rises with age; variation in phase peaks during puberty. During mid-puberty, phase variation is large and explains up to 40 percent of total height variance in girls, and up to 50 percent in boys. Eight amplitude and 4 phase components appeared biologically significant. The largest amplitude component explained 91% of the amplitude variance and is characterised by an almost horizontal pattern. The largest phase component explained 66% (boys) and 63% (girls) of phase variance, rises throughout childhood and reaches up to 0.85 years in adolescent boys, and up to 0.75 years in adolescent girls. Phase components significantly correlated with the clinical signs of puberty. The combination of PCA and the Maximum Likelihood Principle provides a new, powerful and automatic tool for growth modelling that includes estimates of future growth, adult stature and developmental tempo. Preliminary results indicate that this approach can be used for automatised screening purposes.
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  • 15
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    The @international journal of biostatistics 3 (2007), S. 10 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Analyses of individual disease-exposure data within a population are useful when exposure of interest varies sufficiently within the population. When the within-population variance of exposure is limited, however, power of the individual-data analysis is reduced. In such situations, aggregated-data analyses of disease data across populations, with a sample of individual exposure data from each population, can be powerful in estimating the exposure effect if between-population variation of exposure is large. In this paper, we consider a new analytical framework that is a combination of the individual- and aggregated-data analyses, based on an estimating equation approach. The proposed analysis utilizes strengths from individual data and aggregated data in the estimation of the exposure effect of interest, depending on which of the exposure variations (within- versus between-population) dominates. Simulation studies under various different scenarios were performed to show the strengths of the proposed approach in the estimation of the exposure effects of interest.
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  • 16
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 5.2007, 1, art30 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Previous nonparametric statistical methods on constructing the test and null statistics require having at least 4 arrays under each condition. In this paper, we provide an improved method of constructing the test and null statistics which only requires 2 arrays under one condition if the number of arrays under the other condition is at least 3. The conventional testing method defines the rejection region by controlling the probability of Type I error. In this paper, we propose to determine the critical values (or the cut-off points) of the rejection region by directly controlling the false discovery rate. Simulations were carried out to compare the performance of our proposed method with several existing methods. Finally, our proposed method is applied to the rat data of Pan et al. (2003). It is seen from both simulations and the rat data that our method has lower false discovery rates than those from the significance analysis of microarray (SAM) method of Tusher et al. (2001) and the mixture model method (MMM) of Pan et al. (2003).
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  • 17
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 6.2007, 1, art19 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Microarrays are a tool for measuring the expression levels of a large number of genes simultaneously. In the microarray experiment, however, many undesirable systematic variations are observed. Correct identification and removal of these variations is essential to allow the comparison of expression levels across experiments. We describe the use of linear mixed models for the normalization of two-color spotted microarrays for various sources of variation including printtip variation. Normalization with linear mixed models provides a parametric model of which results compare favorably to intensity dependent normalization LOWESS methods. We illustrate the use of this technique on two datasets. The first dataset contains 24 arrays, each with approximately 600 genes, replicated 3 times per array. A second dataset, coming from the apo AI experiment, was used to further illustrate the methods. Finally, a simulation study was done to compare between methods.
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  • 18
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 6.2007, 1, art13 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: In genetic association studies, there is increasing interest in understanding the joint effects of genetic and nongenetic factors. For rare diseases, the case-control study is a practical design, and logistic regression is the standard method of inference. However, the power to detect statistical interaction is a concern, even with relatively large samples. Under independence of genetic and nongenetic covariates, improved precision of interaction estimators is possible, but logistic regression does not make use of this assumption and consequently is not statistically efficient. In recent work to improve efficiency, profile likelihood methods have been used to develop semi-parametric inference that incorporates the independence assumption. We describe an alternate derivation of these estimators for rare diseases that is based on classic arguments from case-control inference. These arguments lead to a simplification in the variance estimator. We also describe a strategy for relaxing the independence assumption. Under either independence or the proposed dependence model, inference for association parameters is conveniently obtained by fitting a conditional logistic regression. The statistical properties of the proposed methodology are investigated by simulation.
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  • 19
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Dose-response studies are commonly used in experiments in pharmaceutical research in order to investigate the dependence of the response on dose, i.e., a trend of the response level toxicity with respect to dose. In this paper we focus on dose-response experiments within a microarray setting in which several microarrays are available for a sequence of increasing dose levels. A gene is called differentially expressed if there is a monotonic trend (with respect to dose) in the gene expression. We review several testing procedures which can be used in order to test equality among the gene expression means against ordered alternatives with respect to dose, namely Williams' (Williams 1971 and 1972), Marcus' (Marcus 1976), global likelihood ratio test (Bartholomew 1961, Barlow et al. 1972, and Robertson et al. 1988), and M (Hu et al. 2005) statistics. Additionally we introduce a modification to the standard error of the M statistic. We compare the performance of these five test statistics. Moreover, we discuss the issue of one-sided versus two-sided testing procedures. False Discovery Rate (Benjamni and Hochberg 1995, Ge et al. 2003), and resampling-based Familywise Error Rate (Westfall and Young 1993) are used to handle the multiple testing issue. The methods above are applied to a data set with 4 doses (3 arrays per dose) and 16,998 genes. Results on the number of significant genes from each statistic are discussed. A simulation study is conducted to investigate the power of each statistic. A R library IsoGene implementing the methods is available from the first author.
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  • 20
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Liquid Chromatography - Mass Spectrometry (LC-MS) is a powerful method for sensitive detection and quantification of proteins and peptides in complex biological fluids like serum. LC-MS produces complex data sets, consisting of some hundreds of millions of data points per sample at a resolution of 0.1 amu in the m/z domain and 7000 data points in the time domain. However, the detection of the lower abundance proteins from this data is hampered by the presence of artefacts, such as high frequency noise and spikes. Moreover, not all of the tens of thousands of the chromatograms produced per sample are relevant for the pursuit of the biomarkers. Thus in analysing the LC-MS data, two critical pre-processing issues arise. Which of the thousands of the: 1. chromatograms per sample are relevant for the detection of the biomarkers?, and 2. signals per chromatogram are truly compound-related? Each of these issues involves assessing the significance (deviation from noise) of multiple observations and the issue of multiple comparisons arises. Current methods disregard the multiplicity and provide no concrete threshold for significance. However, with such procedures, the probability of one or more false-positives is high as the number of tests to be performed is large, and must be controlled. Realizing that the cut-offs for declaring a chromatogram (or a signal) to be compound-related can hugely influence which proteins are detected, it seems natural to define thresholds that are neither arbitrary nor subjective. We suggest the choice of thresholds guided by the critical aim of controlling the False Discovery Rate (FDR) in multiple hypotheses testing for significance over a large set of features produced per sample. This involves the use of the regression diagnostics to characterize the signals of a chromatogram (e.g. as outliers or influential) and to suggest suitable tests statistics for the multiple testing procedures (MTP) for discriminating noise and spikes from true signals. The role of the Generalized Linear Models (GLM) in this MTP is investigated. The method is applied to LC-MS datasets from trypsin-digested serum spiked with varying levels of horse heart cytochrome C (cytoc).
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  • 21
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 6.2007, 1, art25 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: When trying to learn a model for the prediction of an outcome given a set of covariates, a statistician has many estimation procedures in their toolbox. A few examples of these candidate learners are: least squares, least angle regression, random forests, and spline regression. Previous articles (van der Laan and Dudoit (2003); van der Laan et al. (2006); Sinisi et al. (2007)) theoretically validated the use of cross validation to select an optimal learner among many candidate learners. Motivated by this use of cross validation, we propose a new prediction method for creating a weighted combination of many candidate learners to build the super learner. This article proposes a fast algorithm for constructing a super learner in prediction which uses V-fold cross-validation to select weights to combine an initial set of candidate learners. In addition, this paper contains a practical demonstration of the adaptivity of this so called super learner to various true data generating distributions. This approach for construction of a super learner generalizes to any parameter which can be defined as a minimizer of a loss function.
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  • 22
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 6.2007, 1, art29 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: We investigate an important issue of a meta-algorithm for selecting variables in the framework of microarray data. This wrapper method starts from any classification algorithm and weights each variable (i.e. gene) relative to its efficiency for classification. An optimization procedure is then inferred which exhibits important genes for the studied biological process. Theory and application with the SVM classifier were presented in Gadat and Younes, 2007 and we extend this method with CART. The classification error rates are computed on three famous public databases (Leukemia, Colon and Prostate) and compared with those from other wrapper methods (RFE, lo norm SVM, Random Forests). This allows the assessment of the statistical relevance of the proposed algorithm. Furthermore, a biological interpretation with the Ingenuity Pathway Analysis software outputs clearly shows that the gene selections from the different wrapper methods raise very relevant biological information, compared to a classical filter gene selection with T-test.
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  • 23
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    Berkeley, Calif. : Berkeley Electronic Press (now: De Gruyter)
    Statistical applications in genetics and molecular biology 6.2007, 1, art20 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Microarray applications for the study of gene expression are becoming accessible for researchers in more and more systems. Applications from field or laboratory experiments are often complicated by the need to superimpose sample pairing for two-color arrays on experimental designs that may already be complex. For example, split-plot designs are commonly used in biological systems where experiments involve two types of treatments that are not readily applied at the same scale. We demonstrate how effects that are confounded with arrays can still be estimated when there is sufficient replication. To illustrate, we evaluate three methods of sample pairing superimposed on a split-plot design with two treatments, deriving the variance associated with parameter estimates for each. Design A has levels of the whole plot treatment paired on the same microarray within a level of the subplot treatment. Design B has crossed levels paired on the same microarray. Design C has levels of the treatment applied to subplots paired on the same microarray within a whole plot. Designs A and B have lower variance than design C for comparing the levels of the whole plot treatment. Designs B and C have lower variance for comparing the levels of the subplot treatment and design C has lower variance for comparing the levels of the subplot treatment within each level of the whole plot treatment. We provide SAS code for the analyses of variance discussed.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art4 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Although researchers use duplicate genotyped data to calculate an inconsistency rate, there is no power analysis to assess the value of the duplicate data. In this paper, we present a model in which the genotyping error rate is related to the inconsistency rate. We extend the g genotype by h phenotype chi-squared test to incorporate the duplicate genotyped data. When a subject is inconsistently genotyped (that is, has two observed genotypes), our procedure is to allocate 0.5 units to each of the two genotypes. We specify the multivariate analysis of variance (MANOVA) test comparing these extended counts. We provide freely available software for this test and also for a permutation test used on small samples. A simulation study shows that the asymptotic null distribution of the MANOVA test holds when the total number of subjects, N, is at least 300. We also document with a simulation study that the asymptotic distribution of this test under various alternative hypotheses is a satisfactory approximation to the simulated power. In all cases, the power of the MANOVA test using the duplicate genotyped data is greater than the power of the chi-squared test ignoring the duplicate data. Power increases ranged from 0.776% to 4.652% for 80% powered tests and 0.292% to 2.028% for 95% powered tests. Researchers now can compute the value of the duplicate genotyped data as part of the design of the study.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art8 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: A number of computational methods have been proposed for identifying transcription factor binding sites from a set of unaligned sequences that are thought to share the motif in question. We here introduce an algorithm, called cosmo, that allows this search to be supervised by specifying a set of constraints that the position weight matrix of the unknown motif must satisfy. Such constraints may be formulated, for example, on the basis of prior knowledge about the structure of the transcription factor in question. The algorithm is based on the same two-component multinomial mixture model used by MEME, with stronger reliance, however, on the likelihood principle instead of more ad-hoc criteria like the E-value. The intensity parameter in the ZOOPS and TCM models, for instance, is estimated based on a profile-likelihood approach, and the width of the unknown motif is selected based on BIC. These changes allow cosmo to outperform MEME even in the absence of any constraints, as evidenced by 2- to 3-fold greater sensitivity in some simulation studies. Additional improvements in performance can be achieved by selecting the model type (OOPS, ZOOPS, or TCM) data-adaptively or by supplying correctly specified constraints, especially if the motif appears only as a weak signal in the data. The algorithm can data-adaptively choose between working in a given constrained model or in the completely unconstrained model, guarding against the risk of supplying mis-specified constraints. Simulation studies suggest that this approach can offer 3 to 3.5 times greater sensitivity than MEME. The algorithm has been implemented in the form of a stand-alone C program as well as a web application that can be accessed at http://cosmoweb.berkeley.edu. An R package is available through Bioconductor (http://bioconductor.org).
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    Statistical applications in genetics and molecular biology 6.2007, 1, art15 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: There have been various attempts to reconstruct gene regulatory networks from microarray expression data in the past. However, owing to the limited amount of independent experimental conditions and noise inherent in the measurements, the results have been rather modest so far. For this reason it seems advisable to include biological prior knowledge, related, for instance, to transcription factor binding locations in promoter regions or partially known signalling pathways from the literature. In the present paper, we consider a Bayesian approach to systematically integrate expression data with multiple sources of prior knowledge. Each source is encoded via a separate energy function, from which a prior distribution over network structures in the form of a Gibbs distribution is constructed. The hyperparameters associated with the different sources of prior knowledge, which measure the influence of the respective prior relative to the data, are sampled from the posterior distribution with MCMC. We have evaluated the proposed scheme on the yeast cell cycle and the Raf signalling pathway. Our findings quantify to what extent the inclusion of independent prior knowledge improves the network reconstruction accuracy, and the values of the hyperparameters inferred with the proposed scheme were found to be close to optimal with respect to minimizing the reconstruction error.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art18 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: In a hidden Markov model, one "estimates" the state of the hidden Markov chain at t by computing via the forwards-backwards algorithm the conditional distribution of the state vector given the observed data. The covariance matrix of this conditional distribution measures the information lost by failure to observe directly the state of the hidden process. In the case where changes of state occur slowly relative to the speed at which information about the underlying state accumulates in the observed data, we compute approximately these covariances in terms of functionals of Brownian motion that arise in change-point analysis. Applications in gene mapping, where these covariances play a role in standardizing the score statistic and in evaluating the loss of noncentrality due to incomplete information, are discussed. Numerical examples illustrate the range of validity and limitations of our results.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art34 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Digital images obtained by the laser scanning of spotted microarrays often include saturated pixel values. These arise when the scan settings are sufficiently high and some pixels exceed the limit L=65535 and are instead set to L. Failure to adjust for this censoring leads to biased estimates of gene expression levels. To impute censored values, we propose a linear model based on the principal components of uncensored spots on the same array. This is computationally fast, flexible to adapt to distinctive spot shapes and profiles on different arrays, and is shown to be more effective than the polynomial-hyperbolic model in correcting for the bias. The application to biological data demonstrates the potential for enhancing the dynamic range of detection. Fortran90 subroutines implementing these methods are available at http://www.bioss.ac.uk/~chris.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art6 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: In this paper, we propose a novel method for sparse logistic regression with non-convex regularization Lp (p 〈1). Based on smooth approximation, we develop several fast algorithms for learning the classifier that is applicable to high dimensional dataset such as gene expression. To the best of our knowledge, these are the first algorithms to perform sparse logistic regression with an Lp and elastic net (Le) penalty. The regularization parameters are decided through maximizing the area under the ROC curve (AUC) of the test data. Experimental results on methylation and microarray data attest the accuracy, sparsity, and efficiency of the proposed algorithms. Biomarkers identified with our methods are compared with that in the literature. Our computational results show that Lp Logistic regression (p 〈1) outperforms the L1 logistic regression and SCAD SVM. Software is available upon request from the first author.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art10 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Quantitative Polymerase Chain Reaction (Q-PCR) aims at determining the initial quantity of specific nucleic acids from the observation of the number of amplified DNA molecules. The most widely used technology to monitor the number of DNA molecules as they replicate is based on fluorescence chemistry. Considering this measurement technique, the observation of DNA amplification by PCR contains intrinsically two kinds of variability. On the one hand, the number of replicated DNA molecules is random, and on the other hand, the measurement of the fluorescence emitted by the DNA molecules is collected with some random error. Relying on a stochastic model of these two types of variability, we aim at providing estimators of the parameters arising in the proposed model, and, more specifically, of the initial amount of molecules. The theory of branching processes is classically used to model the evolution of the number of DNA molecules at each replication cycle. The model is a binary splitting Galton-Watson branching process. Its unknown parameters are the initial number of DNA molecules and the reaction efficiency of PCR, which is defined as the probability of replication of a DNA molecule. The number of DNA molecules is indirectly observed through noisy fluorescence measurements resulting in a so-called Hidden Markov Model. We aim at inference of the parameters of the underlying branching process, and the parameters of the noise from the fluorescence measurements in a Bayesian framework. Using simulations and experimental data, we investigate the performance of the Bayesian estimators obtained by Markov Chain Monte Carlo methods.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art5 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Multi-color optical mapping is a new technique being developed to obtain detailed physical maps (indicating relative positions of various recognition sites) of DNA molecules. We consider a study design in which the data consist of noisy observations of multiple copies of a DNA molecule marked with colors at recognition sites. The primary goal is to estimate a physical map. A secondary goal is to estimate error rates associated with the experiment, which are potentially useful for analysis and refinement of the biochemical steps in the mapping procedure. We propose statistical models for various sources of error and use maximum likelihood estimation (MLE) to construct a physical map and estimate error rates. To overcome difficulties arising in the maximization process, a latent-variable Markov chain version of the model is proposed, and the EM algorithm is used for maximization. In addition, a simulated annealing procedure is applied to maximize the profile likelihood over the discrete space of sequences of colors. We apply the methods to simulated data on the bacteriophage lambda genome.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art17 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: We propose here a simple and robust approach for meta-analysis of molecular association studies. Making use of the binary structure of the data, and by treating the genotypes as independent variables in a logistic regression, we apply a simple and commonly used methodology that performs satisfactorily, being at the same time very flexible. We present simple tests for detecting heterogeneity and we describe a random effects extension of the method in order to allow for between studies heterogeneity. We derive also simple tests for assessing the most plausible genetic model of inheritance, and its between-studies heterogeneity as well as adjusting for covariates. The methodology introduced here is easily extended in cases with polytomous or continuous outcomes as well as in cases with more than two alleles. We apply the methodology in several published meta-analyses of genetic association studies with very encouraging results. The main advantages of the proposed methodology is its flexibility and the ease of use, while at the same time covers almost every aspect of a meta-analysis providing overall estimates without the need of multiple comparisons. We anticipate that this simple method would be used in the future in meta-analyses of genetic association studies. A STATA command performing all the available computations is available at http://bioinformatics.biol.uoa.gr/~pbagos/metagen/.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art21 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: The problem of finding periodically expressed genes from time course microarray experiments is at the center of numerous efforts to identify the molecular components of biological clocks. We present a new approach to this problem based on the cyclohedron test, which is a rank test inspired by recent advances in algebraic combinatorics. The test has the advantage of being robust to measurement errors, and can be used to ascertain the significance of top-ranked genes. We apply the test to recently published measurements of gene expression during mouse somitogenesis and find 32 genes that collectively are significant. Among these are previously identified periodic genes involved in the Notch/FGF and Wnt signaling pathways, as well as novel candidate genes that may play a role in regulating the segmentation clock. These results confirm that there are an abundance of exceptionally periodic genes expressed during somitogenesis. The emphasis of this paper is on the statistics and combinatorics that underlie the cyclohedron test and its implementation within a multiple testing framework.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art24 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: The objective of the present paper is to develop a truly functional Bayesian method specifically designed for time series microarray data. The method allows one to identify differentially expressed genes in a time-course microarray experiment, to rank them and to estimate their expression profiles. Each gene expression profile is modeled as an expansion over some orthonormal basis, where the coefficients and the number of basis functions are estimated from the data. The proposed procedure deals successfully with various technical difficulties that arise in typical microarray experiments such as a small number of observations, non-uniform sampling intervals and missing or replicated data. The procedure allows one to account for various types of errors and offers a good compromise between nonparametric techniques and techniques based on normality assumptions. In addition, all evaluations are performed using analytic expressions, so the entire procedure requires very small computational effort. The procedure is studied using both simulated and real data, and is compared with competitive recent approaches. Finally, the procedure is applied to a case study of a human breast cancer cell line stimulated with estrogen. We succeeded in finding new significant genes that were not marked in an earlier work on the same dataset.
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    The @international journal of biostatistics 3 (2007), S. 4 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: We consider random design nonparametric regression when the response variable is subject to right censoring. Following the work of Fan and Gijbels (1994), a common approach to this problem is to apply what has been termed a censoring unbiased transformation to the data to obtain surrogate responses, and then enter these surrogate responses with covariate data into standard smoothing algorithms. Existing censoring unbiased transformations generally depend on either the conditional survival function of the response of interest, or that of the censoring variable. We show that a mapping introduced in another statistical context is in fact a censoring unbiased transformation with a beneficial double robustness property, in that it can be used for nonparametric regression if either of these two conditional distributions are estimated accurately. Advantages of using this transformation for smoothing are illustrated in simulations and on the Stanford heart transplant data.
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    The @international journal of biostatistics 3 (2007), S. 13 
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    Topics: Biology , Mathematics , Medicine
    Notes: Mortality rate ratios and the associated proportional hazards models have been used to summarize the effect of Alzheimer's disease on longevity. However, the mortality rate ratios vary by age and therefore do not provide a simple parsimonious summary of the effect of the disease on lifespan. Instead, we propose a new parameter that is defined by an additive multistate model. The proposed multistate model accounts for different stages of disease progression. The underlying assumption of the model is that the effect of disease on mortality is to add a constant amount to death rates once the disease progresses from an early to late stage. We explored the properties of the proposed model; in particular the behavior of the mortality rate ratio and median survival that is induced by the model. We combined information from several data sources to estimate the parameter in our model. We found that the effect of Alzheimer's disease on longevity is to increase the absolute annual risk of death by about 8% once a person progressed to late stage disease. Most importantly, we find that this additive effect is the same regardless of the patients' age or gender. Thus, the proposed additive multi-state model provides a parsimonious and clinically interpretable description of the effects of Alzheimer's disease on mortality.
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    The @international journal of biostatistics 3 (2007), S. 1 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Under the setting of a case-cohort design, covariate values are ascertained for a smaller subgroup of the original study cohort which typically is a representative sample from a population. Individuals with a specific event outcome are selected to the second stage study group as cases and an additional subsample is selected to act as a control group. We carry out analysis of such a design using conditional likelihood where the likelihood expression is conditioned on the ascertainment to the second stage study group. Such likelihood expression involves the probability of ascertainment which need to be expressed in terms of the model parameters. We present examples of conditional likelihoods for models for categorical response and time-to-event response. We show that the conditional likelihood inference leads to valid estimation of population parameters. Our application considers joint estimation of haplotype-event association parameters and population haplotype frequencies based on SNP genotype data collected under a case-cohort design.
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    The @international journal of biostatistics 3 (2007), S. 5 
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    Topics: Biology , Mathematics , Medicine
    Notes: As a generalization of the accelerated failure time models, we consider parametric models of lifetime Y, where the conditional mean E(Y|X;beta) can depend nonlinearly on the covariates X and some parameters beta. The error distribution can be heteroscedastic and dependent on X. With observed data subject to right censoring, we propose regression analysis for beta based on Kaplan-Meier estimates of the means over several regions of X. Consistency and asymptotic distributional properties of the estimators are established under general conditions. A resulting estimator of beta is shown to be the sum of two possibly dependent asymptotic normal quantities, based on which conservative confidence intervals and tests are derived. Simulation studies are conducted to investigate the performance of the proposed estimator and to compare it with Buckley-Jame's method. To illustrate the methodology, we study an example with kidney transplant data, where a nonlinear relationship called "mixtures-of-experts", proposed in the neural networks literature, is used to model the relationship between the survival time and the age of the patients.
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    The @international journal of biostatistics 3 (2007), S. 11 
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    Topics: Biology , Mathematics , Medicine
    Notes: We present a reformulation of the Benjamini-Hochberg method that is useful in 'large-scale' multiple testing problems based on discrete test statistics and derive its basic asymptotic (as the number of hypotheses tends to infinity) properties, subsuming earlier results. A set of gene expression data is used to illustrate the workings of the method in a multiple testing problem based on Kolmogorov-Smirnov and Mann-Whitney statistics.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art16 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Statistical analysis of microarray gene expression data has recently attracted a great deal of attention. One problem of interest is to relate genes to survival outcomes of patients with the purpose of building regression models for the prediction of future patients' survival based on their gene expression data. For this, several authors have discussed the use of the proportional hazards or Cox model after reducing the dimension of the gene expression data. This paper presents a new approach to conduct the Cox survival analysis of microarray gene expression data with the focus on models' predictive ability. The method modifies the correlation principal component regression (Sun, 1995) to handle the censoring problem of survival data. The results based on simulated data and a set of publicly available data on diffuse large B-cell lymphoma show that the proposed method works well in terms of models' robustness and predictive ability in comparison with some existing partial least squares approaches. Also, the new approach is simpler and easy to implement.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art11 
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    Topics: Biology
    Notes: Amplified Fragment Length Polymorphism (AFLP) markers are formed by selective amplification of DNA fragments from digested total genomic DNA. The technique is popular because it is a relatively inexpensive way to produce large numbers of reproducible genetic markers. In this paper, we describe a Bayesian approach to modeling AFLP marker evolution by nucleotide substitution and an MCMC approach to estimate phylogeny from AFLP marker data.We demonstrate the method on species in Carex section Ovales,a group of sedges common in North America.We compare the results of our analysis with a clustering method based on Nei and Li's restriction-site distance and a two-state Bayesian analysis using MrBayes.
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    The @international journal of biostatistics 3 (2007), S. 2 
    ISSN: 1557-4679
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology , Mathematics , Medicine
    Notes: Characterizing the genetic correlates to complex diseases requires consideration of a large number of potentially informative biological markers. In addition, attention to alignment of alleles within or across chromosomal pairs, commonly referred to as phase, may be essential for uncovering true biological associations. In the context of population based association studies, phase is generally unobservable. Preservation of type-1 error in a setting with multiple testing presents a further analytical challenge. This manuscript combines a likelihood-based approach to handling missing-ness in phase with a resampling method to adjust for multiple testing. Through simulations we demonstrate preservation of the family-wise error rate and reasonable power for detecting associations. The method is applied to a cohort of 626 HIV-1 infected individuals receiving highly active anti-retroviral therapies, to ascertain potential genetic contributions to abnormalities in lipid profiles. The haplotypic effects of 2 genes, hepatic lipase (HL) and endothelial lipase (EL), on high-density lipoprotein cholesterol (HDL-C) are tested.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art7 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Many alternative data-adaptive algorithms can be used to learn a predictor based on observed data. Examples of such learners include decision trees, neural networks, support vector regression, least angle regression, logic regression, and the Deletion/Substitution/Addition algorithm. The optimal learner for prediction will vary depending on the underlying data-generating distribution. In this article we introduce the "super learner", a prediction algorithm that applies any set of candidate learners and uses cross-validation to select between them. Theory shows that asymptotically the super learner performs essentially as well as or better than any of the candidate learners. In this article we present the theory behind the super learner, and illustrate its performance using simulations. We further apply the super learner to a data example, in which we predict the phenotypic antiretroviral susceptibility of HIV based on viral genotype. Specifically, we apply the super learner to predict susceptibility to a specific protease inhibitor, nelfinavir, using a set of database-derived non-polymorphic treatment-selected mutations.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art3 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: For testing multiple null hypotheses, the classical approach to dealing with the multiplicity problem is to restrict attention to procedures that control the familywise error rate (FWER), the probability of even one false rejection. In many applications, one might be willing to tolerate more than one false rejection provided the number of such cases is controlled, thereby increasing the ability of the procedure to detect false null hypotheses. This suggests replacing control of the FWER by controlling the probability of k or more false rejections, which is called the k-FWER. In Hommel and Hoffmann (1987) and Lehmann and Romano (2005a), single step and stepdown procedures are derived that control the k-FWER, without making any assumptions concerning the dependence structure of the p-values of the individual tests. However, if the p-values are mutually independent, one can improve the procedures. In fact, Sarkar (2005) provided such an improvement. However, we show other improvements are possible which appear to be generally much better, and are sometimes unimprovable. When k=1, the procedure reduces to the classical method of Sidak, and the stepdown procedure is unimprovable and strictly dominates that of Sarkar. Under a monotonicity condition, an unimprovable procedure is obtained. In the case k=2, the monotonicity condition is satisfied, and the condition can be checked numerically in general. We then develop a stepdown method that controls the false discovery proportion. Except for the case of k-FWER control with k=1, the gains are surprisingly dramatic, and theoretical and numerical evidence is given.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art9 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: High-dimensional case-control analysis is encountered in many different settings in genomics. In order to rank genes accordingly, many different scores have been proposed, ranging from ad hoc modifications of the ordinary t statistic to complicated hierarchical Bayesian models. Here, we introduce the "shrinkage t" statistic that is based on a novel and model-free shrinkage estimate of the variance vector across genes. This is derived in a quasi-empirical Bayes setting. The new rank score is fully automatic and requires no specification of parameters or distributions. It is computationally inexpensive and can be written analytically in closed form.Using a series of synthetic and three real expression data we studied the quality of gene rankings produced by the "shrinkage t" statistic. The new score consistently leads to highly accurate rankings for the complete range of investigated data sets and all considered scenarios for across-gene variance structures.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art12 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by systematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art14 
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    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: An objective of microarray data analysis is to identify gene expressions that are associated with a disease related outcome. For each gene, a test statistic is computed to determine if an association exists, and this statistic generates a marginal p-value. In an effort to pool this information across genes, a p-value density function is derived. The p-value density is modeled as a mixture of a uniform (0,1) density and a scaled ratio of normal densities derived from the asymptotic normality of the test statistic. The p-values are assumed to be weakly dependent and a quasi-likelihood is used to estimate the parameters in the mixture density. The quasi-likelihood and the weak dependence assumption enables estimation and asymptotic inference on the false discovery rate for a given rejection region, and its inverse, the p-value threshold parameter for a fixed false discovery rate. A false discovery rate analysis on a localized prostate cancer data set is used to illustrate the methodology. Simulations are performed to assess the performance of this methodology.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art32 
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    Topics: Biology
    Notes: Array Comparative Genomic Hybridization (aCGH) is an array-based technology which provides simultaneous spot assays of relative genetic abundance (RGA) levels at multiple sites across the genome. These spot assays are spatially correlated with respect to genomic location and, as a result, the univariate tests conducted using data generated from these spot assays are also spatially correlated. In the context of multiple hypothesis testing, this spatial correlation complicates the question of how best to define a `discovery' and consequently, how best to estimate the false discovery rate (FDR) corresponding to a given rejection region.One can quantify the number of discoveries as the total number of spots for which the spot-based univariate test statistic falls within a given rejection region. Under this spot-based method, separate but correlated discoveries are identified. We show via a simulation study that the method of Benjamini and Hochberg (1995) can provide a reasonable estimate of the spot-wise FDR, but these results require that the simulated spot assays are categorized as true or false discoveries in a particular way. However, laboratory researchers may actually be interested in estimating a `regional' FDR, rather than a `local' spot-wise FDR. We describe an example of such circumstances, and present a method for estimating the (chromosome) arm-wise False Discovery Rate. In this framework, one can quantify the number of discoveries as the total number of chromosome arms for which at least one spot-based test statistic falls into a given rejection region. Defining the discoveries in this way, both the biological and testing objectives coincide. We provide results from a series of simulations which involved the analysis of preferentially re-sampled spot assay values from a real aCGH dataset.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art30 
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    Topics: Biology
    Notes: The investigation of microbial communities is an essential part of the study of the biosphere. Flexible molecular fingerprinting tools such as terminal-restriction fragment length polymorphism (T-RFLP) analysis are often applied in the studies to enable the characterization of the microbial population. However, such data have so far been primarily analyzed using conventional clustering methods. Here we introduce a Bayesian model-based method for the purpose of comparing microbial communities using T-RFLP data. Such datasets have in general several challenging features, e.g. sparseness, missing values and structurally zero-valued observations. These features are taken into account by developing a Bayesian latent class mixture model for the observations in our framework. To make inferences under the model we use a recent Markov chain Monte Carlo (MCMC) -based method for the Bayesian model selection. To assess the introduced method we analyze both simulated and real datasets. The simulations show that our approach compares preferably to standard statistical clustering tools, such as k-means, hierarchical clustering, and Autoclass. The developed tool is freely available as a software package T-BAPS at http://www.abo.fi/fak/mnf/mate/jc/software/t-baps.html.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art35 
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    Topics: Biology
    Notes: Maximum Likelihood (ML) is used as a standard method for estimating divergence times in phylogenetic trees. The method is consistent and hence the precision can be improved by analyzing longer sequences. In this paper we show that the precision can be improved also by including more taxa to the existing tree. It is a theoretical study, complemented with simulations, showing that the gain in precision is faster with increasing sequence length than with increasing number of taxa.We further compare the results of estimating divergence times using Maximum Likelihood with the much faster and less complex estimation method of Mean Path Length (MPL), which works with the evolution model of Jukes-Cantor (1969). It is shown that MPL is as good as ML in estimating divergence times of nodes that are located near the root in the tree, but ML is better in estimating the divergence times of nodes lower down.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art33 
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    Topics: Biology
    Notes: Characterizing genetic variability in the human pathogenic Plasmodium species, the group of parasites that cause Malaria, may have broad global health implications. Specifically, discerning the combinations of mutations that lead to viable parasites and the population level frequencies of these clonal sequences will allow for targeted vaccine development and individualized treatment choices. This presents an analytical challenge, however, since haplotypic phase (i.e. the alignment of bases on a single DNA strand) is generally unobservable in multiply infected individuals. This manuscript describes an expectation maximization (EM) approach to maximum likelihood estimation of haplotype frequencies in this missing data setting. The approach is applied to a cohort of N=341 malaria infected children in Uganda, Cameroon and Sudan to characterize regional differences. A simulation study is also presented to characterize method performance and assess sensitivity to distributional assumptions.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art28 
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    Topics: Biology
    Notes: Microarray studies often need to simultaneously examine thousands of genes to determine which are differentially expressed. One main challenge in those studies is to find suitable multiple testing procedures that provide accurate control of the error rates of interest and meanwhile are most powerful, that is, they return the longest list of truly interesting genes among competitors. Many multiple testing methods have been developed recently for microarray data analysis, especially resampling based methods, such as permutation methods, the null-centered and scaled bootstrap (NCSB) method, and the quantile-transformed-bootstrap-distribution (QTBD) method. Each of these methods has its own merits and limitations. Theoretically permutation methods can fail to provide accurate control of Type I errors when the so-called subset pivotality condition is violated. The NCSB method does not suffer from that limitation, but an impractical number of bootstrap samples are often needed to get proper control of Type I errors. The newly developed QTBD method has the virtues of providing accurate control of Type I errors under few restrictions. However, the relative practical performance of the above three types of multiple testing methods remains unresolved. This paper compares the above three resampling based methods according to the control of family wise error rates (FWER) through data simulations. Results show that among the three resampling based methods, the QTBD method provides relatively accurate and powerful control in more general circumstances.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art37 
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    Topics: Biology
    Notes: Most genetic diseases are complex, i.e. associated to combinations of SNPs rather than individual SNPs. In the last few years, this topic has often been addressed in terms of SNP-SNP interaction patterns given as expressions linked by logical operators. Methods for multiple testing in high-dimensional settings can be applied when many SNPs are considered simultaneously. However, another less well-known multiple testing problem arises within a fixed subset of SNPs when the logic expression is chosen optimally. In this article, we propose a general asymptotic approach for deriving the distribution of the maximally selected chi-square statistic in various situations. We show how this result can be used for testing logic expressions - in particular SNP-SNP interaction patterns - while controlling for multiple comparisons. Simulations show that our method provides multiple testing adjustments when the logic expression is chosen such as to maximize the statistic. Its benefit is demonstrated through an application to a real dataset from a large population-based study considering allergy and asthma in KORA. An implementation of our method is available from the Comprehensive R Archive Network (CRAN) as R package 'SNPmaxsel'.
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    The @international journal of biostatistics 3 (2007), S. 7 
    ISSN: 1557-4679
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    Topics: Biology , Mathematics , Medicine
    Notes: The objective of this work is to introduce a new method called the Survivorship Instantaneous Log-odds Ratios (SILOR); to illustrate the creation of SILOR from empirical bivariate survival functions; to also derive standard errors of estimation; to compare results with those derived from logistic regression. Hip fracture, AGE and BMI from the Third National Health and Nutritional Examination Survey (NHANES III) were used to calculate empirical survival functions for the adverse health outcome (AHO) and non-AHO. A stable copula was used to create a parametric bivariate survival function, that was fitted to the empirical bivariate survival function. The bivariate survival function had SILOR contours which are not constant. The proposed method has better advantages than logistic regression by following two reasons. The comparison deals with (i) the shapes of the survival surfaces, S(X1, X2), and (ii) the isobols of the log-odds ratios. When using logistic regression the survival surface is either a hyper plane or at most a conic section. Our approach preserves the shape of the survival surface in two dimensions, and the isobols are observed in every detail instead of being overly smoothed by a regression with no more than a second degree polynomial. The present method is straightforward, and it captures all but random variability of the data.
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    The @international journal of biostatistics 3 (2007), S. 3 
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    Topics: Biology , Mathematics , Medicine
    Notes: Marginal structural models (MSM) are an important class of models in causal inference. Given a longitudinal data structure observed on a sample of n independent and identically distributed experimental units, MSM model the counterfactual outcome distribution corresponding with a static treatment intervention, conditional on user-supplied baseline covariates. Identification of a static treatment regimen-specific outcome distribution based on observational data requires, beyond the standard sequential randomization assumption, the assumption that each experimental unit has positive probability of following the static treatment regimen. The latter assumption is called the experimental treatment assignment (ETA) assumption, and is parameter-specific. In many studies the ETA is violated because some of the static treatment interventions to be compared cannot be followed by all experimental units, due either to baseline characteristics or to the occurrence of certain events over time. For example, the development of adverse effects or contraindications can force a subject to stop an assigned treatment regimen.In this article we propose causal effect models for a user-supplied set of realistic individualized treatment rules. Realistic individualized treatment rules are defined as treatment rules which always map into the set of possible treatment options. Thus, causal effect models for realistic treatment rules do not rely on the ETA assumption and are fully identifiable from the data. Further, these models can be chosen to generalize marginal structural models for static treatment interventions. The estimating function methodology of Robins and Rotnitzky (1992) (analogue to its application in Murphy, et. al. (2001) for a single treatment rule) provides us with the corresponding locally efficient double robust inverse probability of treatment weighted estimator. In addition, we define causal effect models for "intention-to-treat" regimens. The proposed intention-to-treat interventions enforce a static intervention until the time point at which the next treatment does not belong to the set of possible treatment options, at which point the intervention is stopped. We provide locally efficient estimators of such intention-to-treat causal effects.
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    The @international journal of biostatistics 3 (2007), S. 6 
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    Topics: Biology , Mathematics , Medicine
    Notes: Consider a longitudinal observational or controlled study in which one collects chronological data over time on a random sample of subjects. The time-dependent process one observes on each subject contains time-dependent covariates, time-dependent treatment actions, and an outcome process or single final outcome of interest. A statically optimal individualized treatment rule (as introduced in van der Laan et. al. (2005), Petersen et. al. (2007)) is a treatment rule which at any point in time conditions on a user-supplied subset of the past, computes the future static treatment regimen that maximizes a (conditional) mean future outcome of interest, and applies the first treatment action of the latter regimen. In particular, Petersen et. al. (2007) clarified that, in order to be statically optimal, an individualized treatment rule should not depend on the observed treatment mechanism. Petersen et. al. (2007) further developed estimators of statically optimal individualized treatment rules based on a past capturing all confounding of past treatment history on outcome. In practice, however, one typically wishes to find individualized treatment rules responding to a user-supplied subset of the complete observed history, which may not be sufficient to capture all confounding. The current article provides an important advance on Petersen et. al. (2007) by developing locally efficient double robust estimators of statically optimal individualized treatment rules responding to such a user-supplied subset of the past. However, failure to capture all confounding comes at a price; the static optimality of the resulting rules becomes origin-specific. We explain origin-specific static optimality, and discuss the practical importance of the proposed methodology. We further present the results of a data analysis in which we estimate a statically optimal rule for switching antiretroviral therapy among patients infected with resistant HIV virus.
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    The @international journal of biostatistics 3 (2007), S. 8 
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    Topics: Biology , Mathematics , Medicine
    Notes: In individuals infected with human immunodeficiency virus (HIV), distributions of quantitative HIV RNA measurements may be highly left-censored due to values falling below assay detection limits (DL). It is of the interest to find the relationship between plasma and semen viral loads. To address this type of problem, we developed an empirical goodness-of-fit test to check the Clayton model assumption for bivariate truncated data. We also used truncated tau to estimate the dependence parameter in the Clayton model for this type of data. It turns out that the proposed methodology works for both truncated and fixed left censored bivariate data. The proposed test procedure is demonstrated using an HIV data set, and statistical inference is drawn based on corresponding test result.
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    The @international journal of biostatistics 3 (2007), S. 14 
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    Topics: Biology , Mathematics , Medicine
    Notes: Observational studies of prescription medications and other medical interventions based on administrative data are increasingly used to inform regulatory and clinical decision making. The validity of such studies is often questioned, however, because the available data may not contain measurements of important prognostic variables that guide treatment decisions. Recently, approaches to this problem have been proposed that use instrumental variables (IV) defined at the level of an individual health care provider or aggregation of providers. Implicitly, these approaches attempt to estimate causal effects by using differences in medical practice patterns as a quasi-experiment. Although preference-based IV methods may usefully complement standard statistical approaches, they make assumptions that are unfamiliar to most biomedical researchers and therefore the validity of such an analysis can be hard to evaluate. Here, we describe a simple framework based on a single unobserved dichotomous variable that can be used to explore how violations of IV assumptions and treatment effect heterogeneity may bias the standard IV estimator with respect to the average treatment effect in the population. This framework suggests various ways to anticipate the likely direction of bias using both empirical data and commonly available subject matter knowledge, such as whether medications or medical procedures tend to be overused, underused, or often misused. This approach is described in the context of a study comparing the gastrointestinal bleeding risk attributable to different non-steroidal anti-inflammatory drugs.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art1 
    ISSN: 1544-6115
    Source: Berkeley Electronic Press Academic Journals
    Topics: Biology
    Notes: Differentiating strains of a pathogen is often central to investigating its epidemiological aspects. The genetic similarity of a group of strains can be assessed by calculating a matrix of dissimilarities from their DNA fingerprinting profiles. The mean dissimilarity for each strain across other strains within the group is then used as an observation in a statistical analysis. These observations are not independent of each other, and so standard analysis techniques such as the t-test are inappropriate, because they underestimate the variance of the group means, and hence overstate the statistical significance of any differences. By examining the correlation between elements of the dissimilarity matrix, it is shown that the variance is underestimated by a factor of between about 2 and 4.Permutation tests are proposed as a way of addressing the problem of dependence, and are applied to a study of fluconazole resistance in Candida albicans.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art2 
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    Topics: Biology
    Notes: This paper discusses characteristics of dye biases in microarray data that the conventional normalization methods do not handle, and proposes a new normalization method involving a mixture of splines model. We also develop a test for between-group comparisons of each gene that is designed to be used with our proposed method.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art22 
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    Topics: Biology
    Notes: We propose an approximate distribution for the gapped local score of a two sequence comparison. Our method stands on combining an adapted scoring scheme that includes the gaps and an approximate distribution of the ungapped local score of two independent sequences of i.i.d. random variables. The new scoring scheme is defined on h-tuples of the sequences, using the gapped global score. The influence of h and the accuracy of the p-value are numerically studied and compared with obtained p-value of BLAST. The numerical experiments emphasize that our approximate p-values outperform the BLAST ones, particularly for both simulated and real short sequences.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art27 
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    Topics: Biology
    Notes: Multiple testing procedures are commonly used in gene expression studies for the detection of differential expression, where typically thousands of genes are measured over at least two experimental conditions. Given the need for powerful testing procedures, and the attendant danger of false positives in multiple testing, the False Discovery Rate (FDR) controlling procedure of Benjamini and Hochberg (1995) has become a popular tool. When simultaneously testing hypotheses, suppose that R rejections are made, of which Fp are false positives. The Benjamini and Hochberg procedure ensures that the expectation of Fp/R is bounded above by some pre-specified proportion. In practice, the procedure is applied to a single experiment. In this paper we investigate the across-experiment variability of the proportion Fp/R as a function of three experimental parameters. The operational characteristics of the procedure when applied to dependent hypotheses are also considered.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art31 
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    Topics: Biology
    Notes: We describe a general model for pairwise microsatellite allele matching probabilities. The model can be used for analysis of population substructure, and is particularly focused on relating genetic correlation to measurable covariates. The approach is intended for cases when the existence of subpopulations is uncertain and a priori assignment of samples to hypothesized subpopulations is difficult. Such a situation arises, for example, with western Arctic bowhead whales, where genetic samples are available only from a possibly mixed migratory assemblage. We estimate genetic structure associated with spatial, temporal, or other variables that may confound the detection of population structure. In the bowhead case, the model permits detection of genetic patterns associated with a temporally pulsed multi-population assemblage in the annual migration. Hypothesis tests for population substructure and for covariate effects can be carried out using permutation methods. Simulated and real examples illustrate the effectiveness and reliability of the approach and enable comparisons with other familiar approaches. Analysis of the bowhead data finds no evidence for two temporally pulsed subpopulations using the best available data, although a significant pattern found by other researchers using preliminary data is also confirmed here. Code in the R language is available from www.stat.colostate.edu/~geof/gammmp.html.
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    Statistical applications in genetics and molecular biology 6.2007, 1, art36 
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    Topics: Biology
    Notes: We present a Bayesian hierarchical model for detecting differentially expressed genes using a mixture prior on the parameters representing differential effects. We formulate an easily interpretable 3-component mixture to classify genes as over-expressed, under-expressed and non-differentially expressed, and model gene variances as exchangeable to allow for variability between genes. We show how the proportion of differentially expressed genes, and the mixture parameters, can be estimated in a fully Bayesian way, extending previous approaches where this proportion was fixed and empirically estimated. Good estimates of the false discovery rates are also obtained.Different parametric families for the mixture components can lead to quite different classifications of genes for a given data set. Using Affymetrix data from a knock out and wildtype mice experiment, we show how predictive model checks can be used to guide the choice between possible mixture priors. These checks show that extending the mixture model to allow extra variability around zero instead of the usual point mass null fits the data better. A software package for R is available.
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    Nature medicine 13 (2007), S. 1-1 
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Medicine
    Notes: [Auszug] In the future, Nature Medicine will be famous to 15 ...
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    Notes: [Auszug] TH17 lymphocytes appear to be essential in the pathogenesis of numerous inflammatory diseases. We demonstrate here the expression of IL-17 and IL-22 receptors on blood-brain barrier endothelial cells (BBB-ECs) in multiple sclerosis lesions, and show that IL-17 and IL-22 disrupt BBB tight junctions ...
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    Nature medicine 13 (2007), S. 13-13 
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    Notes: [Auszug] To the editor: The recent article by Kerkelä et al. reported clinical findings of congestive heart failure (CHF) in ten patients, and preclinical studies showing that imatinib-treated mice can develop left ventricular contractile dysfunction and cellular abnormalities suggestive of a toxic ...
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    Nature medicine 13 (2007), S. 14-14 
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    Notes: [Auszug] To the editor: We read with interest the article of Kerkelä et al. discussing the potential cardiotoxicity of imatinib mesylate in animal models and detailing ten patients, nine from our institution, who developed congestive heart failure (CHF) on imatinib therapy. This report has generated ...
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    Nature medicine 13 (2007), S. 17-18 
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    Notes: [Auszug] To the Editor: Binding between C-reactive protein (CRP) and human leptin in vitro, and inhibition by CRP of the effects of human leptin in mice in vivo, have recently been reported by Chen et al.. In their in vitro studies the authors showed that after exposure of leptin-coupled agarose beads to ...
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    Nature medicine 13 (2007), S. 649-649 
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    Notes: [Auszug] The issue of aging academics in times of budgetary constraints has stirred vigorous debate. Many older professors continue to be productive researchers and inspiring teachers with plenty of wind in their sails. However, some say the abundance of older professors is clogging an already narrow ...
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    Nature medicine 13 (2007), S. 652-652 
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    Notes: [Auszug] Did you wear a thick, blue plastic bracelet with the words “I decline the Northfield PolyHeme study” splashed across it in bold black writing during the years 2004 to 2006?... If not, and had you been in a serious accident during that time, you could have been unwittingly enrolled in a ...
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    Nature medicine 13 (2007), S. 651-651 
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    Notes: [Auszug] In the fight against malaria, long-lasting insecticidal bed nets—made from polyester or plastic and treated with insecticides—are a favorite tool. Because they can be washed and reused for years, donors such as the Roll Back Malaria Partnership push for their use.... But the nets are ...
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    Nature medicine 13 (2007), S. 653-653 
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    Notes: [Auszug] British doctors have begun collecting samples for Britain's first storehouse of infectious diseases, two years after the launch of the UK's ambitious BioBank project.... Following nearly a year of discussion over ethical approval, Guy’s & St Thomas’ hospital in London has a £45 million ...
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    Notes: [Auszug] Interstitial loss of all or part of the long arm of chromosome 5, or del(5q), is a frequent clonal chromosomal abnormality in human myelodysplastic syndrome (MDS, a preleukemic disorder) and acute myeloid leukemia (AML), and is thought to contribute to the pathogenesis of these diseases by deleting ...
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    Notes: [Auszug] Abdominal pain is common in the general population and, in patients with irritable bowel syndrome, is attributed to visceral hypersensitivity. We found that oral administration of specific Lactobacillus strains induced the expression of μ-opioid and cannabinoid receptors in intestinal epithelial ...
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    Nature medicine 13 (2007), S. 3-3 
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    Notes: [Auszug] Here's how doctors decide which mental or neurological disorder their troubled patients suffer from: they ask questions like, “Are you hearing voices?” and “Do you feel like people are out to get you?”... Not all that different from how they used to do it about 100 years ...
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    Nature medicine 13 (2007), S. 28-30 
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    Topics: Biology , Medicine
    Notes: [Auszug] Findings by Obeid et al. in this issue highlight a way to potentially enhance the ability of the immune system to kill tumor cells. The authors suggest that how cells die during chemotherapy is critical; one set of chemotherapeutic agents in particular, anthracyclins, seem to foster a favorable ...
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  • 78
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    Notes: [Auszug] Nur77 (NR4A1) and Nor-1 (NR4A3) are highly homologous orphan nuclear receptors that regulate the transcription of overlapping target genes. The transcriptional activity of both proteins is regulated in a ligand-independent manner by cell- and stimulus-specific gene induction and protein ...
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  • 79
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    Notes: [Auszug] Exotoxins of Staphylococcus aureus belong to a family of bacterial proteins that act as superantigens by activating a large subset of the T-cell population, causing massive release of inflammatory cytokines. This cascade can ultimately result in toxic shock syndrome and death. Therapeutics ...
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  • 80
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    Notes: [Auszug] T-helper type 17 cells (TH17) are implicated in rodent models of immune-mediated diseases. Here we report their involvement in human uveitis and scleritis, and validate our findings in experimental autoimmune uveoretinitis (EAU), a model of uveitis. TH17 cells were present in human peripheral blood ...
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  • 81
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    Notes: [Auszug] The metabolism of vitamin A and the diverse effects of its metabolites are tightly controlled by distinct retinoid-generating enzymes, retinoid-binding proteins and retinoid-activated nuclear receptors. Retinoic acid regulates differentiation and metabolism by activating the retinoic acid receptor ...
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  • 82
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    Nature medicine 13 (2007), S. 517-517 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] Soldier's son, wife develop rare case of eczema ...
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  • 83
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    Nature medicine 13 (2007), S. 522-523 
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    Source: Nature Archives 1869 - 2009
    Topics: Biology , Medicine
    Notes: [Auszug] In the ongoing battle between bacteria and antibiotics, strains of Staphylococcus aureus are emerging the winners, reports Douglas ...
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  • 84
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    Nature medicine 13 (2007), S. 524-524 
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Medicine
    Notes: [Auszug] How good is the new prostate cancer ...
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  • 85
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    Nature medicine 13 (2007), S. 520-521 
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Medicine
    Notes: [Auszug] 19 Mar A group of nine prominent American scientific institutions call for an increase in funding for the US National Institutes of Health, warning that stagnant budgets outpaced by inflation threaten the progress of biomedical research.... 19 Mar Mosquitoes modified to carry a gene that ...
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  • 86
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    Nature medicine 13 (2007), S. 527-528 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] To the editor: Adult T-cell leukemia/lymphoma (ATLL) is a fatal T-cell neoplasm caused by infection with human T-cell leukemia virus type I (HTLV-I). Hasegawa et al. have described transgenic mice that express HTLV-I Tax viral regulatory protein/oncoprotein in thymocytes. These mice developed ...
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  • 87
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    Nature medicine 13 (2007), S. 534-536 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] Until recently, only 5–10% of autism cases were traceable to an underlying genetic cause. Two studies now change this. Jacquemont et al. and Sebat et al. suggest that this number is actually 10–20%, and it may grow to 30–40% with further research. The advance is based primarily on ...
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  • 88
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    Nature medicine 13 (2007), S. 538-539 
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] This year marks the twentieth anniversary of the discovery of the dystrophin gene, which is mutated in the devastating X-linked recessive muscle disease Duchenne muscular dystrophy (DMD). During DMD, heart and skeletal muscles break down, so that the affected boys are typically wheelchair-bound by ...
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  • 89
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    Nature medicine 13 (2007), S. 536-538 
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] The key immunological regulator osteopontin was first identified as a structural protein in bone that formed a bridge (Latin pons) between the bone's mineral matrix and the bone cells inside it. Later, expression of osteopontin by activated T cells and dendritic cells was found to be an essential ...
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  • 90
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    Nature medicine 13 (2007), S. 539-541 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] Heart failure is a common and lethal condition, yet why the heart muscle fails remains a mystery. Alterations in myocardial metabolism, defects in calcium handling, alterations in myosin isoforms, cytoskeletal abnormalities and excessive cardiac myocyte apoptosis have all been implicated as causal ...
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  • 91
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    Nature medicine 13 (2007), S. 541-541 
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    Source: Nature Archives 1869 - 2009
    Topics: Biology , Medicine
    Notes: [Auszug] How microRNAs (miRNAs) influence heart development and disease is a topic of growing interest. miRNAs regulate gene expression post-transcriptionally, typically by binding to mRNAs and inhibiting their translation. Three recent papers show that miRNAs are essential for heart development and ...
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  • 92
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    Nature medicine 13 (2007), S. 542-542 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] Gender matters How infertility-causing mutations are inherited is a tough puzzle. A dominant mutation with sex-specific phenotypes provides a clue (PLoS, doi:10.1371/journal.pbio.0050105). In screening mice for infertility, Laura Bannister et al. isolated a male sterile allele of ...
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  • 93
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] Human embryonic stem cells (hESCs) are a promising source for cell therapy in degenerative diseases. A key step in establishing the medical potential of hESCs is the development of techniques for the conversion of hESCs into tissue-restricted precursors suitable for transplantation. We recently ...
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  • 94
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] The superficial bladder epithelium is a powerful barrier to urine and also serves as a regulator of bladder volume, which is achieved by apical exocytosis of specialized fusiform vesicles during distension of the bladder. We report that type 1 fimbriated uropathogenic Escherichia coli (UPEC) ...
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  • 95
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] During physical exercise, increases in motor neuron activity stimulate the expression of muscle-specific genes through the myocyte enhancer factor 2 (MEF2) family of transcription factors. Elevations in intracellular calcium increase MEF2 activity via the phosphorylation-dependent inactivation of ...
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  • 96
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    Nature medicine 13 (2007), S. 392-393 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] When Gardasil, the first vaccine against human papilloma virus (HPV), was approved in June 2006 by the US Food and Drug Administration, it was widely hailed as a godsend for women.... Clinical trials involving more than 20,000 women showed the vaccine to be safe and effective. But the vaccine's ...
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  • 97
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    Nature medicine 13 (2007), S. 393-393 
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    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] The average doctor's office these days looks much like a pharmaceutical sales convention: patients wipe their noses with Lipitor tissues and sign forms with Boniva pens attached to Lunesta clipboards. The ubiquity of these drug ads—and the sales representatives that place them—is ...
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  • 98
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] Cbl-associated protein (Cap) is a member of a phosphatidylinositol 3-kinase–independent pathway for insulin-stimulated translocation of the glucose transporter GLUT4. Despite this positive role of Cap in glucose uptake, here we show that deletion of the gene encoding Cap (official gene name: ...
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  • 99
    ISSN: 1546-170X
    Source: Nature Archives 1869 - 2009
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    Notes: [Auszug] The germinal matrix of premature infants is selectively vulnerable to hemorrhage within the first 48 h of life. To assess the role of vascular immaturity in germinal matrix hemorrhage (GMH), we evaluated germinal matrix angiogenesis in human fetuses and premature infants, as well as in premature ...
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  • 100
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    Nature medicine 13 (2007), S. 234-235 
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    Notes: [Auszug] 22 Jan Hoping to raise flagging employee morale, the US Centers for Disease Control and Prevention will hire a full-time ombudsman, agency director Julie Gerberding announces. 24 Jan The first draft of the human 'metabolome' describes more than 2,500 metabolites found in the body, of which fewer ...
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