226 resultados para SEQUENCE VARIABILITY


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Experimental studies have found that when the state-of-the-art probabilistic linear discriminant analysis (PLDA) speaker verification systems are trained using out-domain data, it significantly affects speaker verification performance due to the mismatch between development data and evaluation data. To overcome this problem we propose a novel unsupervised inter dataset variability (IDV) compensation approach to compensate the dataset mismatch. IDV-compensated PLDA system achieves over 10% relative improvement in EER values over out-domain PLDA system by effectively compensating the mismatch between in-domain and out-domain data.

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Variability in the pollutant wash-off process is a concept which needs to be understood in-depth in order to better assess the outcomes of stormwater quality models, and thereby strengthen stormwater pollution mitigation strategies. Current knowledge about the wash-off process does not extend to a clear understanding of the influence of the initially available pollutant build-up on the variability of the pollutant wash-off load and composition. Consequently, pollutant wash-off process variability is poorly characterised in stormwater quality models, which can result in inaccurate stormwater quality predictions. Mathematical simulation of particulate wash-off from three urban road surfaces confirmed that the wash-off load of particle size fractions <150µm and >150µm after a storm event vary with the build-up of the respective particle size fractions available at the beginning of the storm event. Furthermore, pollutant load and composition associated with the initially available build-up of <150µm particles predominantly influence the variability in washed-off pollutant load and composition. The influence of the build-up of pollutants associated with >150µm particles on wash-off process variability is significant only for relatively shorter duration storm events.

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Objective: To follow-up previous studies highlighting a possible role for cytochrome P450, family 2, subfamily C, 19 (CYP2C19) in susceptibility to endometriosis by searching for additional variants in the CYP2C19 gene that may be associated with the disease. Design Case-control study. Setting Academic research. Subject(s) The cases comprised 2,271 women with surgically confirmed endometriosis; the controls comprised 939 women with self-report of no endometriosis and 1,770 unscreened population samples. Intervention(s) Sequencing of the CYP2C19 region and follow-up of 80 single nucleotide polymorphisms (SNPs) in two case-control samples. Main Outcome Measure(s) Allele frequency differences between cases and controls. Result(s) Sequencing of the CYP2C19 gene region resulted in the detection of a large number of known and novel SNPs. Genotyping of 80 polymorphic SNPs in 901 endometriosis cases and 939 controls resulted in study-wide significant association signals for SNPs in moderate or complete linkage disequilibrium with rs4244285, a functional SNP in exon 5 that abrogates CYP2C19 function through the creation of an alternative splice site. Evidence of association was also detected for another functional SNP in the CYP2C19 promoter, rs12248560, which was highlighted in our previous study. Conclusion(s) Functional variants in CYP2C19 may contribute to endometriosis susceptibility in both familial and sporadic cases. © 2014 by American Society for Reproductive Medicine.

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Genetic factors contribute to risk of many common diseases affecting reproduction and fertility. In recent years, methods for genome-wide association studies(GWAS) have revolutionized gene discovery forcommontraits and diseases. Results of GWAS are documented in the Catalog of Published Genome-Wide Association Studies at the National Human Genome Research Institute and report over 70 publications for 32 traits and diseases associated with reproduction. These include endometriosis, uterine fibroids, age at menarche and age at menopause. Results that pass appropriate stringent levels of significance are generally well replicated in independent studies. Examples of genetic variation affecting twinning rate, infertility, endometriosis and age at menarche demonstrate that the spectrum of disease-related variants for reproductive traits is similar to most other common diseases.GWAS 'hits' provide novel insights into biological pathways and the translational value of these studies lies in discovery of novel gene targets for biomarkers, drug development and greater understanding of environmental factors contributing to disease risk. Results also show that genetic data can help define sub-types of disease and co-morbidity with other traits and diseases. To date, many studies on reproductive traits have used relatively small samples. Future genetic marker studies in large samples with detailed phenotypic and clinical information will yield new insights into disease risk, disease classification and co-morbidity for many diseases associated with reproduction and infertility.

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One of the objectives of this study was to evaluate soil testing equipment based on its capability of measuring in-place stiffness or modulus values. As design criteria transition from empirical to mechanistic-empirical, soil test methods and equipment that measure properties such as stiffness and modulus and how they relate to Florida materials are needed. Requirements for the selected equipment are that they be portable, cost effective, reliable, a ccurate, and repeatable. A second objective is that the selected equipment measures soil properties without the use of nuclear materials.The current device used to measure soil compaction is the nuclear density gauge (NDG). Equipment evaluated in this research included lightweight deflectometers (LWD) from different manufacturers, a dynamic cone penetrometer (DCP), a GeoGauge, a Clegg impact soil tester (CIST), a Briaud compaction device (BCD), and a seismic pavement analyzer (SPA). Evaluations were conducted over ranges of measured densities and moistures.Testing (Phases I and II) was conducted in a test box and test pits. Phase III testing was conducted on materials found on five construction projects located in the Jacksonville, Florida, area. Phase I analyses determined that the GeoGauge had the lowest overall coefficient of variance (COV). In ascending order of COV were the accelerometer-type LWD, the geophone-type LWD, the DCP, the BCD, and the SPA which had the highest overall COV. As a result, the BCD and the SPA were excluded from Phase II testing.In Phase II, measurements obtained from the selected equipment were compared to the modulus values obtained by the static plate load test (PLT), the resilient modulus (MR) from laboratory testing, and the NDG measurements. To minimize soil and moisture content variability, the single spot testing sequence was developed. At each location, test results obtained from the portable equipment under evaluation were compared to the values from adjacent NDG, PLT, and laboratory MR measurements. Correlations were developed through statistical analysis. Target values were developed for various soils for verification on similar soils that were field tested in Phase III. The single spot testing sequence also was employed in Phase III, field testing performed on A-3 and A-2-4 embankments, limerock-stabilized subgrade, limerock base, and graded aggregate base found on Florida Department of Transportation construction projects. The Phase II and Phase III results provided potential trend information for future research—specifically, data collection for in-depth statistical analysis for correlations with the laboratory MR for specific soil types under specific moisture conditions. With the collection of enough data, stronger relationships could be expected between measurements from the portable equipment and the MR values. Based on the statistical analyses and the experience gained from extensive use of the equipment, the combination of the DCP and the LWD was selected for in-place soil testing for compaction control acceptance. Test methods and developmental specifications were written for the DCP and the LWD. The developmental specifications include target values for the compaction control of embankment, subgrade, and base materials.

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Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

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Process variability in pollutant build-up and wash-off generates inherent uncertainty that affects the outcomes of stormwater quality models. Poor characterisation of process variability constrains the accurate accounting of the uncertainty associated with pollutant processes. This acts as a significant limitation to effective decision making in relation to stormwater pollution mitigation. The study undertaken developed three theoretical scenarios based on research findings that variations in particle size fractions <150µm and >150µm during pollutant build-up and wash-off primarily determine the variability associated with these processes. These scenarios, which combine pollutant build-up and wash-off processes that takes place on a continuous timeline, are able to explain process variability under different field conditions. Given the variability characteristics of a specific build-up or wash-off event, the theoretical scenarios help to infer the variability characteristics of the associated pollutant process that follows. Mathematical formulation of the theoretical scenarios enables the incorporation of variability characteristics of pollutant build-up and wash-off processes in stormwater quality models. The research study outcomes will contribute to the quantitative assessment of uncertainty as an integral part of the interpretation of stormwater quality modelling outcomes.

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Variations in interannual rainfall totals can lead to large uncertainties in annual N2O emission budget estimates from short term field studies. The interannual variation in nitrous oxide (N2O) emissions from a subtropical pasture in Queensland, Australia, was examined using continuous measurements of automated chambers over 2 consecutive years. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than soil water content. Over 48% of the total N2O emitted was lost in just 16% of measurement days. Interannual variation in annual N2O estimates was high, with cumulative emissions increasing with decreasing rainfall. Cumulative emissions averaged 1826.7 ± 199.9 g N2O-N ha−1 yr−1 over the two year period, though emissions from 2008 (2148 ± 273 g N2O-N ha−1 yr−1) were 42% higher than 2007 (1504 ± 126 g N2O-N ha−1 yr−1). This increase in annual emissions coincided with almost half of the summer precipitation from 2007 to 2008. Emissions dynamics were chiefly driven by the distribution and size of rain events which varied on a seasonal and annual basis. Sampling frequency effects on cumulative N2O flux estimation were assessed using a jackknife technique to inform future manual sampling campaigns. Test subsets of the daily measured data were generated for the pasture and two adjacent land-uses (rainforest and lychee orchard) by selecting measured flux values at regular time intervals ranging from 1 to 30 days. Errors associated with weekly sampling were up to 34% of the sub-daily mean and were highly biased towards overestimation if strategically sampled following rain events. Sampling time of day also played a critical role. Morning sampling best represented the 24 hour mean in the pasture, whereas sampling at noon proved the most accurate in the shaded rainforest and lychee orchard.

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The human genome project was a grand scientific enterprise which attracted both hyperbole and ridicule alike. The project was lauded as “the moon shot of the life sciences”, the “holy grail of man”, “the code of codes”, and “the book of life”. Such rhetoric has also received scorn. President George Bush senior managed to deflate the pretensions of the project with the accidental slip that it was the “human gnome initiative”. In The Sequence, Kevin Davies seeks to go beyond such metaphors, and provide a candid and honest account of the race of the human genome project. The author is indebted to the authoritative book The Gene Wars, which considered the early struggles over the human genome project. Robert Cook-Deegan observes that there was initially much debate over whether there should be a Human Genome Project at all: The debate became one of “big” science versus “small” science. The reliance on systematic technology development and goal-directed gene-mapping efforts presaged a new style for biology, one that elicited excitement from those attracted to whiz-bang technologies but drew gasps of revulsion from those who aspired to cultivate biology on a more modest scale and with decentralized organisation. The battle was, among other things, over whose vision would control the budget and which scientific aesthetic would prevail.

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It's akin to the old Spanish, English and Portuguese explorers. They would take their boats until they found some edge of land, then they would go up and plant the flag of their king or queen. They didn't know what they'd discovered; how big it is, where it goes to - but they would claim it anyway. David Korn of the Association of American Medical Colleges This article analyses recent litigation over patent law and expressed sequence tags (ESTs). In the case of In re Fisher, the United States Court of Appeals for the Federal Circuit engaged in judicial consideration of the revised utility guidelines of the United States Patent and Trademark Office (USPTO). In this matter, the agricultural biotechnology company Monsanto sought to patent ESTs in maize plants. A patent examiner and the Board of Patent Appeals and Interferences had doubted whether the patent application was useful. Monsanto appealed against the rulings of the USPTO. A number of amicus curiae intervened in the matter in support of the USPTO - including Genentech, Affymetrix, Dow AgroSciences, Eli Lilly, the National Academy of Sciences, and the Association of American Medical Colleges. The majority of the Court of Appeals for the Federal Circuit supported the position of the USPTO, and rejected the patent application on the grounds of utility. The split decision highlighted institutional tensions over the appropriate thresholds for patent criteria - such as novelty, non-obviousness, and utility. The litigation raised larger questions about the definition of research tools, the incremental nature of scientific progress, and the role of patent law in innovation policy. The decision of In re Fisher will have significant ramifications for gene patents, in the wake of the human genome project. Arguably, the USPTO utility guidelines need to be reinforced by a tougher application of the standards of novelty and non-obviousness in respect of gene patents.

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This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

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Idiomarina sp. strain 28-8 is an aerobic, Gram-negative, flagellar bacterium isolated from the bodies of ark shells (Scapharca broughtonii) collected from underwater sediments in Gangjin Bay, South Korea. Here, we present the draft genome sequence of Idiomarina sp. 28-8 (2,971,606 bp, with a G+C content of 46.9%), containing 2,795 putative coding sequences.

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The native Asian oyster, Crassostrea ariakensis is one of the most common and important Crassostrea species that occur naturally along the coast of East Asia. Molecular species diagnosis is a prerequisite for population genetic analysis of wild oyster populations because oyster species cannot be discriminated reliably using external morphological characters alone due to character ambiguity. To date there have been few phylogeographic studies of natural edible oyster populations in East Asia, in particular this is true of the common species in Korea C. ariakensis. We therefore assessed the levels and patterns of molecular genetic variation in East Asian wild populations of C. ariakensis from Korea, Japan, and China using DNA sequence analysis of five concatenated mtDNA regions namely; 16S rRNA, cytochrome oxidase I, cytochrome oxidase II, cytochrome oxidase III, and cytochrome b. Two divergent C. ariakensis clades were identified between southern China and remaining sites from the northern region. In addition, hierarchical AMOVA and pairwise UST analyses showed that genetic diversity was discontinuous among wild populations of C. ariakensis in East Asia. Biogeographical and historical sea level changes are discussed as potential factors that may have influenced the genetic heterogeneity of wild C. ariakensis stocks across this region.

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Single nucleotide polymorphisms (SNPs) are widely acknowledged as the marker of choice for many genetic and genomic applications because they show co-dominant inheritance, are highly abundant across genomes and are suitable for high-throughput genotyping. Here we evaluated the applicability of SNP markers developed from Crassostrea gigas and C. virginica expressed sequence tags (ESTs) in closely related Crassostrea and Ostrea species. A total of 213 putative interspecific level SNPs were identified from re-sequencing data in six amplicons, yielding on average of one interspecific level SNP per seven bp. High polymorphism levels were observed and the high success rate of transferability show that genic EST-derived SNP markers provide an efficient method for rapid marker development and SNP discovery in closely related oyster species. The six EST-SNP markers identified here will provide useful molecular tools for addressing questions in molecular ecology and evolution studies including for stock analysis (pedigree monitoring) in related oyster taxa.

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Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10-6). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority. © 2013 Lin et al.