2,974 research outputs found

    Using Ontology Fingerprints to evaluate genome-wide association study results

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    We describe an approach to characterize genes or phenotypes via ontology fingerprints which are composed of Gene Ontology (GO) terms overrepresented among those PubMed abstracts linked to the genes or phenotypes. We then quantify the biological relevance between genes and phenotypes by comparing their ontology fingerprints to calculate a similarity score. We validated this approach by correctly identifying genes belong to their biological pathways with high accuracy, and applied this approach to evaluate GWA study by ranking genes associated with the lipid concentrations in plasma as well as to prioritize genes within linkage disequilibrium (LD) block. We found that the genes with highest scores were: ABCA1, LPL, and CETP for HDL; LDLR, APOE and APOB for LDL; and LPL, APOA1 and APOB for triglyceride. In addition, we identified some top ranked genes linking to lipid metabolism from the literature even in cases where such knowledge was not reflected in current annotation of these genes. These results demonstrate that ontology fingerprints can be used effectively to prioritize genes from GWA studies for experimental validation

    Maximum likelihood estimation by monte carlo simulation:Toward data-driven stochastic modeling

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    We propose a gradient-based simulated maximum likelihood estimation to estimate unknown parameters in a stochastic model without assuming that the likelihood function of the observations is available in closed form. A key element is to develop Monte Carlo-based estimators for the density and its derivatives for the output process, using only knowledge about the dynamics of the model. We present the theory of these estimators and demonstrate how our approach can handle various types of model structures. We also support our findings and illustrate the merits of our approach with numerical results

    Particle Migration of Quasi-Steady Flow in Concentrated Suspension for Powder Injection Molding

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    A hybrid FEM/FDM algorithm for particle migration of quasi-steady flow in concentrated suspension materials is proposed in this study. This hybrid FEM/FDM algorithm in which the planar variables, such as pressure field, are described in terms of finite element method, and gapwise variables of temperature, density concentration and time derivatives are expressed by finite difference method. The particle concentration inhomogeneities can be predicted, which is ignored by the existing injection molding simulation packages. Simulation results indicated that powder concentration variation could be significant in practical processing in PIM.Singapore-MIT Alliance (SMA

    Rapid and robust association mapping of expression quantitative trait loci

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    We applied a simple and efficient two-step method to analyze a family-based association study of gene expression quantitative trait loci (eQTL) in a mixed model framework. This two-step method produces very similar results to the full mixed model method, with our method being significantly faster than the full model. Using the Genetic Analysis Workshop 15 (GAW15) Problem 1 data, we demonstrated the value of data filtering for reducing the number of tests and controlling the number of false positives. Specifically, we showed that removing non-expressed genes by filtering on expression variability effectively reduced the number of tests by nearly 50%. Furthermore, we demonstrated that filtering on genotype counts substantially reduced spurious detection. Finally, we restricted our analysis to the markers and transcripts that were closely located. We found five times more signals in close proximity (cis-) to transcripts than in our genome-wide analysis. Our results suggest that careful pre-filtering and partitioning of data are crucial for controlling false positives and allowing detection of genuine effects in genetic analysis of gene expression

    Long-term evaluation of cantilevered versus fixed–fixed resin-bonded fixed partial dentures for missing maxillary incisors

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    © 2016 Elsevier LtdObjectives To evaluate the long-term longevity and patient-reported outcomes of two-unit cantilevered (CL2) and three-unit fixed–fixed (FF3) resin-bonded fixed partial dentures (RBFPDs) for the replacement of a maxillary permanent incisor. Materials and methods Twenty-eight subjects were randomly assigned to receive either a CL2 or FF3 RBFPD placed by one operator. Prosthesis longevity was determined by clinical examination and history. Success was defined as absence of complications requiring intervention and survival as retention of the original prosthesis in mouth. Subjects’ satisfaction was assessed using visual analogue scale (VAS) and oral health-related quality of life (OHRQoL) using Oral Health Impact Profile (OHIP-49). Outcomes were analysed with t-test/Mann–Whitney U test, chi-square and log-rank test at significance level α = 0.05. Results Twenty-two subjects were reviewed. Thirteen of fifteen CL2 and ten of fourteen FF3 RBFPDs were examined (79.3 percent response rate) with a mean service life of 216.5 ± 20.8 months. All CL2 RBFPDs survived with no complications while only 10 percent of FF3 experienced no complications and only 50 percent of them survived (both P = 0.000). CL2 had a significantly better success and survival rate than FF3 (P = 0.000 and P = 0.009, respectively). There was no significant difference in subjects’ satisfaction and OHRQoL apart from CL2 group subjects had a higher satisfaction in cleaning of the prosthesis (84.1 ± 13.6) than FF3 group (72.6 ± 11.7) (P = 0.05). Conclusions Two-unit cantilevered RBFPDs were observed to have a significantly better success and survival than the FF3 design for the replacement of a maxillary incisor. Good patient-reported outcomes have been found for RBFPDs in single-tooth replacement in aesthetic zone.postprin
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