970 resultados para DATASETS


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An experiment to quantify intra- and interobserver error in anatomical measurements found that interobserver measurements can vary by over 14% of mean specimen length; disparity in measurement increases logarithmically with the number of contributors; instructions did not reduce variation or measurement disparity; scale of the specimen influenced the precision of measurement (relative error increasing with specimen size); different methods of taking a measurement yielded different results, although they did not differ in terms of precision, and topographical complexity of the elements being considered may potentially influence error (error increasing with complexity). These results highlight concerns about introduction of noise and potential bias that should be taken into account when compiling composite datasets and meta-analyses.

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Connectivity mapping is a recently developed technique for discovering the underlying connections between different biological states based on gene-expression similarities. The sscMap method has been shown to provide enhanced sensitivity in mapping meaningful connections leading to testable biological hypotheses and in identifying drug candidates with particular pharmacological and/or toxicological properties. Challenges remain, however, as to how to prioritise the large number of discovered connections in an unbiased manner such that the success rate of any following-up investigation can be maximised. We introduce a new concept, gene-signature perturbation, which aims to test whether an identified connection is stable enough against systematic minor changes (perturbation) to the gene-signature. We applied the perturbation method to three independent datasets obtained from the GEO database: acute myeloid leukemia (AML), cervical cancer, and breast cancer treated with letrozole. We demonstrate that the perturbation approach helps to identify meaningful biological connections which suggest the most relevant candidate drugs. In the case of AML, we found that the prevalent compounds were retinoic acids and PPAR activators. For cervical cancer, our results suggested that potential drugs are likely to involve the EGFR pathway; and with the breast cancer dataset, we identified candidates that are involved in prostaglandin inhibition. Thus the gene-signature perturbation approach added real values to the whole connectivity mapping process, allowing for increased specificity in the identification of possible therapeutic candidates.

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Background/Aims: The NOS3 gene is a biological and positional candidate for diabetic nephropathy. However, the relationship between NOS3 polymorphisms and renal disease is inconclusive. This study aimed to clarify the association of NOS3 variants with nephropathy in individuals with type 1 diabetes. Methods: We conducted a case-control study examining all common SNPs in the NOS3 gene by a tag SNP approach. Individuals with type 1 diabetes and persistent proteinuria (cases, n = 718) were compared with individuals with type 1 diabetes but no evidence of renal disease (controls, n = 749). Our replication collection comprised 1,105 individuals with type 1 diabetes recruited to a nephropathy case group and 862 control individuals with normal urinary albumin excretion rates. Meta-analysis was conducted for SNPs where more than three genotype datasets were available. Results: A novel association was identified in the discovery collection (rs1800783, p(genotype) = 0.006, p(allele) = 0.002, OR = 1.26, 95% CI: 1.08-1.47) and supported by independent replication using a tag SNP (rs4496877, pairwise r(2) = 0.96 with rs1800783) in the replication collection (p(genotype) = 0.002, p(allele) = 0.0006, OR = 1.27, 95% CI: 1.10-1.45). Conclusion: The A allele of rs1800783 is a significant risk factor for nephropathy in individuals with type 1 diabetes, and further comprehensive studies are warranted to confirm the definitive functional variant in the NOS3 gene. Copyright (C) 2010 S. Karger AG, Basel

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Schizophrenia is a common psychotic mental disorder that is believed to result from the effects of multiple genetic and environmental factors. In this study, we explored gene-gene interactions and main effects in both case-control (657 cases and 411 controls) and family-based (273 families, 1350 subjects) datasets of English or Irish ancestry. Fifty three markers in 8 genes were genotyped in the family sample and 44 markers in 7 genes were genotyped in the case-control sample. The Multifactor Dimensionality Reduction Pedigree Disequilibrium Test (MDR-PDT) was used to examine epistasis in the family dataset and a 3-locus model was identified (permuted p=0.003). The 3-locus model involved the IL3 (rs2069803), RGS4 (rs2661319), and DTNBP1 (rs21319539) genes. We used MDR to analyze the case-control dataset containing the same markers typed in the RGS4, IL3 and DTNBP1 genes and found evidence of a joint effect between IL3 (rs31400) and DTNBP1 (rs760761) (cross-validation consistency 4/5, balanced prediction accuracy=56.84%, p=0.019). While this is not a direct replication, the results obtained from both the family and case-control samples collectively suggest that IL3 and DTNBP1 are likely to interact and jointly contribute to increase risk for schizophrenia. We also observed a significant main effect in DTNBP1, which survived correction for multiple comparisons, and numerous nominally significant effects in several genes. (C) 2008 Elsevier B.V. All rights reserved.

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Background: Late Onset Alzheimer's disease (LOAD) is the leading cause of dementia. Recent large genome-wide association studies (GWAS) identified the first strongly supported LOAD susceptibility genes since the discovery of the involvement of APOE in the early 1990s. We have now exploited these GWAS datasets to uncover key LOAD pathophysiological processes. Methodology: We applied a recently developed tool for mining GWAS data for biologically meaningful information to a LOAD GWAS dataset. The principal findings were then tested in an independent GWAS dataset.

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We sought to identify new susceptibility loci for Alzheimer's disease through a staged association study (GERAD+) and by testing suggestive loci reported by the Alzheimer's Disease Genetic Consortium (ADGC) in a companion paper. We undertook a combined analysis of four genome-wide association datasets (stage 1) and identified ten newly associated variants with P = 1 × 10(-5). We tested these variants for association in an independent sample (stage 2). Three SNPs at two loci replicated and showed evidence for association in a further sample (stage 3). Meta-analyses of all data provided compelling evidence that ABCA7 (rs3764650, meta P = 4.5 × 10(-17); including ADGC data, meta P = 5.0 × 10(-21)) and the MS4A gene cluster (rs610932, meta P = 1.8 × 10(-14); including ADGC data, meta P = 1.2 × 10(-16)) are new Alzheimer's disease susceptibility loci. We also found independent evidence for association for three loci reported by the ADGC, which, when combined, showed genome-wide significance: CD2AP (GERAD+, P = 8.0 × 10(-4); including ADGC data, meta P = 8.6 × 10(-9)), CD33 (GERAD+, P = 2.2 × 10(-4); including ADGC data, meta P = 1.6 × 10(-9)) and EPHA1 (GERAD+, P = 3.4 × 10(-4); including ADGC data, meta P = 6.0 × 10(-10)).

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Segregation measures have been applied in the study of many societies, and traditionally such measures have been used to assess the degree of division between social and cultural groups across urban areas, wider regions, or perhaps national areas. The degree of segregation can vary substantially from place to place even within very small areas. In this paper the substantive concern is with religious/political segregation in Northern Ireland—particularly the proportion of Protestants (often taken as an indicator of those who wish to retain the union with Britain) to Catholics (often taken as an indicator of those who favour union with the Republic of Ireland). Traditionally, segregation is measured globally—that is, across all units in a given area. A recent trend in spatial data analysis generally, and in segregation analysis specifically, is to assess local features of spatial datasets. The rationale behind such approaches is that global methods may obscure important spatial variations in the property of interest, and thus prevent full use of the data. In this paper the utility of local measures of residential segregation is assessed with reference to the religious/political composition of Northern Ireland. The paper demonstrates marked spatial variations in the degree and nature of residential segregation across Northern Ireland. It is argued that local measures provide highly useful information in addition to that provided in maps of the raw variables and in standard global segregation measures.

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To improve the performance of classification using Support Vector Machines (SVMs) while reducing the model selection time, this paper introduces Differential Evolution, a heuristic method for model selection in two-class SVMs with a RBF kernel. The model selection method and related tuning algorithm are both presented. Experimental results from application to a selection of benchmark datasets for SVMs show that this method can produce an optimized classification in less time and with higher accuracy than a classical grid search. Comparison with a Particle Swarm Optimization (PSO) based alternative is also included.

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Patterns of residential segregation in Northern Ireland reflect historic sectarian conflict as well as current animosities. A number of indices of segregation are examined in this paper and their relative merits in capturing localised societal divisions are discussed.The implications of such divisions on health as mediated through conflict-related stress are then considered. Costed datasets of hospital, community and anxiety/depression prescribing data havebeen assembled and attributed to local geographies.The association between geographical variations in these costs and levels of segregation was modelled using regression analysis.It was found that the level of segregation does not help to explain variations in costed utilisation of acute and elderly services but does explain variations in the costs of prescribing for anxiety and depression with controls for socio-economic deprivation included. Results in this paper would indicate that strategies to promote good relations in Northern Ireland have positive implications for mental health.

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Purpose. Keratoconus is a progressive disorder of the cornea that can lead to severe visual impairment or blindness. Although several genomic regions have been linked to rare familial forms of keratoconus, no genes have yet been definitively identified for common forms of the disease. Methods. Two genome-wide association scans were undertaken in parallel. The first used pooled DNA from an Australian cohort, followed by typing of top-ranked single-nucleotide polymorphisms (SNPs) in individual DNA samples. The second was conducted in individually genotyped patients, and controls from the USA. Tag SNPs around the hepatocyte growth factor (HGF) gene were typed in three additional replication cohorts. Serum levels of HGF protein in normal individuals were assessed with ELISA and correlated with genotype. Results. The only SNP observed to be associated in both the pooled discovery and primary replication cohort was rs1014091, located upstream of the HGF gene. The nearby SNP rs3735520 was found to be associated in the individually typed discovery cohort (P = 6.1 × 10 ). Genotyping of tag SNPs around HGF revealed association at rs3735520 and rs17501108/rs1014091 in four of the five cohorts. Meta-analysis of all five datasets together yielded suggestive P values for rs3735520 (P = 9.9 × 10 ) and rs17501108 (P = 9.9 × 10 ). In addition, SNP rs3735520 was found to be associated with serum HGF level in normal individuals (P = 0.036). Conclusions. Taken together, these results implicate genetic variation at the HGF locus with keratoconus susceptibility. © 2011 The Association for Research in Vision and Ophthalmology, Inc.

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Polyphosphate is a ubiquitous linear homopolymer of phosphate residues linked by high-energy bonds similar to those found in ATP. It has been associated with many processes including pathogenicity, DNA uptake and multiple stress responses across all domains. Bacteria have also been shown to use polyphosphate as a way to store phosphate when transferred from phosphate-limited to phosphate-rich media - a process exploited in wastewater treatment and other environmental contaminant remediation. Despite this, there has, to date, been little research into the role of polyphosphate in the survival of marine bacterioplankton in oligotrophic environments. The three main proteins involved in polyphosphate metabolism, Ppk1, Ppk2 and Ppx are multi-domain and have differential inter-domain and inter-gene conservation, making unbiased analysis of relative abundance in metagenomic datasets difficult. This paper describes the development of a novel Isofunctional Homolog Annotation Tool (IHAT) to detect homologs of genes with a broad range of conservation without bias of traditional expect-value cutoffs. IHAT analysis of the Global Ocean Sampling (GOS) dataset revealed that genes associated with polyphosphate metabolism are more abundant in environments where available phosphate is limited, suggesting an important role for polyphosphate metabolism in marine oligotrophs.

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Background: The world's oceans are home to a diverse array of microbial life whose metabolic activity helps to drive the earth's biogeochemical cycles. Metagenomic analysis has revolutionized our access to these communities, providing a system-scale perspective of microbial community interactions. However, while metagenome sequencing can provide useful estimates of the relative change in abundance of specific genes and taxa between environments or over time, this does not investigate the relative changes in the production or consumption of different metabolites.
Results: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome. Our analysis of metagenomic data from a time-series study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance of measured environmental parameters as well as with observed seasonal changes in bacterial population structure.
Conclusions: The PRMT method was successfully applied to metagenomic data to explore the Western English Channel microbial metabalome to generate specific, biologically testable hypotheses. Generated hypotheses linked organic phosphate utilization to Gammaproteobactaria, Plantcomycetes, and Betaproteobacteria, chitin degradation to Actinomycetes, and potential small molecule biosynthesis pathways for Lentisphaerae, Chlamydiae, and Crenarchaeota. The PRMT method can be applied as a general tool for the analysis of additional metagenomic or transcriptomic datasets.

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While RNA interference (RNAi) has been deployed to facilitate gene function studies in diverse helminths, parasitic nematodes appear variably susceptible. To test if this is due to inter-species differences in RNAi effector complements, we performed a primary sequence similarity survey for orthologs of 77 Caenorhabditis elegans RNAi pathway proteins in 13 nematode species for which genomic or transcriptomic datasets were available, with all outputs subjected to domain-structure verification. Our dataset spanned transcriptomes of Ancylostoma caninum and Oesophagostomum dentatum, and genomes of Trichinella spiralis, Ascaris suum, Brugia malayi, Haemonchus contortus, Meloidogyne hapla, Meloidogyne incognita and Pristionchus pacificus, as well as the Caenorhabditis species C. brenneri, C. briggsae, C. japonica and C. remanei, and revealed that: (i) Most of the C. elegans proteins responsible for uptake and spread of exogenously applied double stranded (ds)RNA are absent from parasitic species, including RNAi-competent plant-nematodes; (ii) The Argonautes (AGOs) responsible for gene expression regulation in C. elegans are broadly conserved, unlike those recruited during the induction of RNAi by exogenous dsRNA; (iii) Secondary Argonautes (SAGOs) are poorly conserved, and the nuclear AGO NRDE-3 was not identified in any parasite; (iv) All five Caenorhabditis spp. possess an expanded RNAi effector repertoire relative to the parasitic nematodes, consistent with the propensity for gene loss in nematode parasites; (v) In spite of the quantitative differences in RNAi effector complements across nematode species, all displayed qualitatively similar coverage of functional protein groups. In summary, we could not identify RNAi effector deficiencies that associate with reduced susceptibility in parasitic nematodes. Indeed, similarities in the RNAi effector complements of RNAi refractory and competent nematode parasites support the broad applicability of this research genetic tool in nematodes.

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It is very common to analyse the factors associated with the onset and continuation of civil wars entirely separately, as if there were likely to be no similarity between them. This is an overstatement of the theoretical position, which has established only that they may be different (i.e. less than perfectly correlated). The hypothesis that the explanatory variables are the same is not theoretically excludable and is empirically testable, both for individual variables and for combinations of them. Starting from this approach yields a rather different picture of the factors associated with the continuation of civil wars, because the relatively small sample size means that confidence intervals on individual coefficients are wide in this case. It is shown here that country size, mountainous terrain and (in most datasets) ethnic diversity seem significant for the continuation of civil wars, starting from the null hypothesis that variables affect onset and continuation probabilities identically, rather than entirely independently. One variable that affects onset and continuation significantly differently is anocracy, which we find to matter only for onset. Civil war is more likely if it occurred two years previously, as well as one year previously, which indicates that wars are more likely to restart after only one year of peace, and also more likely to stop in their first year. The combined model strengthens the result that ethnic diversity matters (it is consistently significant across datasets, whereas it is not when onset is analysed separately), although in the UCD/PRIO dataset it is significant only for onset. By contrast, if continuation is analysed independently, virtually nothing is significant except a pre-1991 dummy and a dummy for civil war two years previously.

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Automated examination timetabling has been addressed by a wide variety of methodologies and techniques over the last ten years or so. Many of the methods in this broad range of approaches have been evaluated on a collection of benchmark instances provided at the University of Toronto in 1996. Whilst the existence of these datasets has provided an invaluable resource for research into examination timetabling, the instances have significant limitations in terms of their relevance to real-world examination timetabling in modern universities. This paper presents a detailed model which draws upon experiences of implementing examination timetabling systems in universities in Europe, Australasia and America. This model represents the problem that was presented in the 2nd International Timetabling Competition (ITC2007). In presenting this detailed new model, this paper describes the examination timetabling track introduced as part of the competition. In addition to the model, the datasets used in the competition are also based on current real-world instances introduced by EventMAP Limited. It is hoped that the interest generated as part of the competition will lead to the development, investigation and application of a host of novel and exciting techniques to address this important real-world search domain. Moreover, the motivating goal of this paper is to close the currently existing gap between theory and practice in examination timetabling by presenting the research community with a rigorous model which represents the complexity of the real-world situation. In this paper we describe the model and its motivations, followed by a full formal definition.