718 resultados para Bayesian method


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Tags or personal metadata for annotating web resources have been widely adopted in Web 2.0 sites. However, as tags are freely chosen by users, the vocabularies are diverse, ambiguous and sometimes only meaningful to individuals. Tag recommenders may assist users during tagging process. Its objective is to suggest relevant tags to use as well as to help consolidating vocabulary in the systems. In this paper we discuss our approach for providing personalized tag recommendation by making use of existing domain ontology generated from folksonomy. Specifically we evaluated the approach in sparse situation. The evaluation shows that the proposed ontology-based method has improved the accuracy of tag recommendation in this situation.

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Background Loss of heterozygosity (LOH) is an important marker for one of the 'two-hits' required for tumor suppressor gene inactivation. Traditional methods for mapping LOH regions require the comparison of both tumor and patient-matched normal DNA samples. However, for many archival samples, patient-matched normal DNA is not available leading to the under-utilization of this important resource in LOH studies. Here we describe a new method for LOH analysis that relies on the genome-wide comparison of heterozygosity of single nucleotide polymorphisms (SNPs) between cohorts of cases and un-matched healthy control samples. Regions of LOH are defined by consistent decreases in heterozygosity across a genetic region in the case cohort compared to the control cohort. Methods DNA was collected from 20 Follicular Lymphoma (FL) tumor samples, 20 Diffuse Large B-cell Lymphoma (DLBCL) tumor samples, neoplastic B-cells of 10 B-cell Chronic Lymphocytic Leukemia (B-CLL) patients and Buccal cell samples matched to 4 of these B-CLL patients. The cohort heterozygosity comparison method was developed and validated using LOH derived in a small cohort of B-CLL by traditional comparisons of tumor and normal DNA samples, and compared to the only alternative method for LOH analysis without patient matched controls. LOH candidate regions were then generated for enlarged cohorts of B-CLL, FL and DLBCL samples using our cohort heterozygosity comparison method in order to evaluate potential LOH candidate regions in these non-Hodgkin's lymphoma tumor subtypes. Results Using a small cohort of B-CLL samples with patient-matched normal DNA we have validated the utility of this method and shown that it displays more accuracy and sensitivity in detecting LOH candidate regions compared to the only alternative method, the Hidden Markov Model (HMM) method. Subsequently, using B-CLL, FL and DLBCL tumor samples we have utilised cohort heterozygosity comparisons to localise LOH candidate regions in these subtypes of non-Hodgkin's lymphoma. Detected LOH regions included both previously described regions of LOH as well as novel genomic candidate regions. Conclusions We have proven the efficacy of the use of cohort heterozygosity comparisons for genome-wide mapping of LOH and shown it to be in many ways superior to the HMM method. Additionally, the use of this method to analyse SNP microarray data from 3 common forms of non-Hodgkin's lymphoma yielded interesting tumor suppressor gene candidates, including the ETV3 gene that was highlighted in both B-CLL and FL.

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Keeping exotic plant pests out of our country relies on good border control or quarantine. However with increasing globalization and mobilization some things slip through. Then the back up systems become important. This can include an expensive form of surveillance that purposively targets particular pests. A much wider net is provided by general surveillance, which is assimilated into everyday activities, like farmers checking the health of their crops. In fact farmers and even home gardeners have provided a front line warning system for some pests (eg European wasp) that could otherwise have wreaked havoc. Mathematics is used to model how surveillance works in various situations. Within this virtual world we can play with various surveillance and management strategies to "see" how they would work, or how to make them work better. One of our greatest challenges is estimating some of the input parameters : because the pest hasn't been here before, it's hard to predict how well it might behave: establishing, spreading, and what types of symptoms it might express. So we rely on experts to help us with this. This talk will look at the mathematical, psychological and logical challenges of helping experts to quantify what they think. We show how the subjective Bayesian approach is useful for capturing expert uncertainty, ultimately providing a more complete picture of what they think... And what they don't!

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Tag recommendation is a specific recommendation task for recommending metadata (tag) for a web resource (item) during user annotation process. In this context, sparsity problem refers to situation where tags need to be produced for items with few annotations or for user who tags few items. Most of the state of the art approaches in tag recommendation are rarely evaluated or perform poorly under this situation. This paper presents a combined method for mitigating sparsity problem in tag recommendation by mainly expanding and ranking candidate tags based on similar items’ tags and existing tag ontology. We evaluated the approach on two public social bookmarking datasets. The experiment results show better accuracy for recommendation in sparsity situation over several state of the art methods.

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Liuwei Dihuang Wan (LWD), a classic Chinese medicinal formulae, has been used to improve or restore declined functions related to aging and geriatric diseases, such as impaired mobility, vision, hearing, cognition and memory. It has attracted increasingly much attention as one of the most popular and valuable herbal medicines. However, the systematic analysis of the chemical constituents of LDW is difficult and thus has not been well established. In this paper, a rapid, sensitive and reliable ultra-performance liquid chromatography with electrospray ionization quadrupole time-of-flight high-definition mass spectrometry (UPLC-ESI-Q-TOF-MS) method with automated MetaboLynx analysis in positive and negative ion mode was established to characterize the chemical constituents of LDW. The analysis was performed on a Waters UPLCTM HSS T3 using a gradient elution system. MS/MS fragmentation behavior was proposed for aiding the structural identification of the components. Under the optimized conditions, a total of 50 peaks were tentatively characterized by comparing the retention time and MS data. It is concluded that a rapid and robust platform based on UPLC-ESI-Q-TOF-MS has been successfully developed for globally identifying multiple-constituents of traditional Chinese medicine prescriptions. This is the first report on systematic analysis of the chemical constituents of LDW. This article is protected by copyright. All rights reserved.

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This thesis developed and applied Bayesian models for the analysis of survival data. The gene expression was considered as explanatory variables within the Bayesian survival model which can be considered the new contribution in the analysis of such data. The censoring factor that is inherent of survival data has also been addressed in terms of its impact on the fitting of a finite mixture of Weibull distribution with and without covariates. To investigate this, simulation study were carried out under several censoring percentages. Censoring percentage as high as 80% is acceptable here as the work involved high dimensional data. Lastly the Bayesian model averaging approach was developed to incorporate model uncertainty in the prediction of survival.

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Soil-based emissions of nitrous oxide (N2O), a well-known greenhouse gas, have been associated with changes in soil water-filled pore space (WFPS) and soil temperature in many previous studies. However, it is acknowledged that the environment-N2O relationship is complex and still relatively poorly unknown. In this article, we employed a Bayesian model selection approach (Reversible jump Markov chain Monte Carlo) to develop a data-informed model of the relationship between daily N2O emissions and daily WFPS and soil temperature measurements between March 2007 and February 2009 from a soil under pasture in Queensland, Australia, taking seasonal factors and time-lagged effects into account. The model indicates a very strong relationship between a hybrid seasonal structure and daily N2O emission, with the latter substantially increased in summer. Given the other variables in the model, daily soil WFPS, lagged by a week, had a negative influence on daily N2O; there was evidence of a nonlinear positive relationship between daily soil WFPS and daily N2O emission; and daily soil temperature tended to have a linear positive relationship with daily N2O emission when daily soil temperature was above a threshold of approximately 19°C. We suggest that this flexible Bayesian modeling approach could facilitate greater understanding of the shape of the covariate-N2O flux relation and detection of effect thresholds in the natural temporal variation of environmental variables on N2O emission.

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The details of an application of the finite strip method to the elastic buckling analysis of thin-walled structures with various boundary conditions and subjected to single or combined loadings of longitudinal compression, transverse compression, bending and shear are presented. The presence of shear loading is accounted for by modifying the displacement functions which are commonly used in cases when shear is absent. A program based on the finite strip method was used to obtain the elastic buckling stress, buckling plot and buckling mode of thin-walled structures and some of these results are presented.

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A new simple test method using small scale models has been developed for testing profiled steel cladding systems under wind uplift/suction forces. This simple method should replace the large scale test method using two-span claddings used at present. It can be used for roof or wall cladding systems fastened with screw fasteners at crests or valleys.

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A high performance liquid chromatographic method for the simultaneous analysis of two flavonoids (iso-vitexin and vitexin), and three indole alkaloids (harmane, harmine, and harmol) was developed. This method was then utilised to quantitate levels of these five constituents in methanolic extracts of Australian Passiflora incarnata. HPLC analysis was performed using a Waters™ Novapak C18 (150 × 4 mm, 4 μm) column, with a gradient solvent system of methanol-water-acetic acid. Detection was achieved by PDA UV (254 nm) and fluorescence (excitation 254 nm, emission 414 nm), utilising the external standard method to obtain quantification.

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Endotoxins can significantly affect the air quality in school environments. However, there is currently no reliable method for the measurement of endotoxins and there is a lack of reference values for endotoxin concentrations to aid in the interpretation of measurement results in school settings. We benchmarked the “baseline” range of endotoxin concentration in indoor air, together with endotoxin load in floor dust, and evaluated the correlation between endotoxin levels in indoor air and settled dust, as well as the effects of temperature and humidity on these levels in subtropical school settings. Bayesian hierarchical modeling indicated that the concentration in indoor air and the load in floor dust were generally (<95th percentile) < 13 EU/m3 and < 24,570 EU/m2, respectively. Exceeding these levels would indicate abnormal sources of endotoxins in the school environment, and the need for further investigation. Metaregression indicated no relationship between endotoxin concentration and load, which points to the necessity for measuring endotoxin levels in both the air and settled dust. Temperature increases were associated with lower concentrations in indoor air and higher loads in floor dust. Higher levels of humidity may be associated with lower airborne endotoxin concentrations.

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A high performance liquid chromatographic method for the simultaneous determination of five organochlorine pesticides (aldrin, p,p’-DDT, dieldrin, endrin, and heptachlor) was developed. The method was used to determine the levels of these pesticides in medicinal plant samples. Analysis was carried out using a Merck LiChrospher 100 RP C18 (5 μm) column with a gradient solvent system of acetonitrile-water and PDA UV detection (224 nm). Quantification was carried out by the external standard method. The limit of detection for the utilized method was below the local legal limits (ANZFA) for similar plant materials for all 5 pesticides excepting endrin. Medicinal plant extracts were further analyzed by conventional GC-ECD and GC-NPD means using SPE and GPC cleanup as required.

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An improved method for the assay of human platelet pyruvate dehydrogenase is described. By generating the substrate [1-14C]pyruvate in situ from [1-14C]lactate plus l-lactate dehydrogenase, the rate of spontaneous decarboxylation is dramatically reduced, allowing far greater sensitivity in the assay of low activities of pyruvate dehydrogenase. In addition, no special precautions are required for the storage and use of [1-14C]lactate, in contrast to those for [1-14C] pyruvate. These factors allow a 5–10-fold increase in sensitivity compared with current methods. The pyruvate dehydrogenase activity of normal subjects as determined by the [1-14C]lactate system was 215 ± 55 pmol · min−1 · mg−1 protein (n = 18). The advantages of this assay system are discussed.

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A novel method was developed for studying the genetic relatedness of Pseudomonas aeruginosa isolates from clinical and environmental sources. This bacterium is ubiquitous in the natural environment and is an important pathogen known to infect Cystic Fibrosis (CF) patients. The transmission route of strains has not yet been defined; current theories include acquisition from an environmental source or through patient-to-patient spread. A highly discriminatory, bioinformatics based, DNA typing method was developed to investigate the relatedness of clinical and environmental isolates. This study found a similarity between the environmental and several CF clonal strains and also highlighted occurrence of environmental P. aeruginosa strains in CF infections.

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We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed meth-od outperforms state-of-the-art text clustering approaches.