1,176 research outputs found

    Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome

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    Microbial communities carry out the majority of the biochemical activity on the planet, and they play integral roles in processes including metabolism and immune homeostasis in the human microbiome. Shotgun sequencing of such communities' metagenomes provides information complementary to organismal abundances from taxonomic markers, but the resulting data typically comprise short reads from hundreds of different organisms and are at best challenging to assemble comparably to single-organism genomes. Here, we describe an alternative approach to infer the functional and metabolic potential of a microbial community metagenome. We determined the gene families and pathways present or absent within a community, as well as their relative abundances, directly from short sequence reads. We validated this methodology using a collection of synthetic metagenomes, recovering the presence and abundance both of large pathways and of small functional modules with high accuracy. We subsequently applied this method, HUMAnN, to the microbial communities of 649 metagenomes drawn from seven primary body sites on 102 individuals as part of the Human Microbiome Project (HMP). This provided a means to compare functional diversity and organismal ecology in the human microbiome, and we determined a core of 24 ubiquitously present modules. Core pathways were often implemented by different enzyme families within different body sites, and 168 functional modules and 196 metabolic pathways varied in metagenomic abundance specifically to one or more niches within the microbiome. These included glycosaminoglycan degradation in the gut, as well as phosphate and amino acid transport linked to host phenotype (vaginal pH) in the posterior fornix. An implementation of our methodology is available at http://huttenhower.sph.harvard.edu/human​n. This provides a means to accurately and efficiently characterize microbial metabolic pathways and functional modules directly from high-throughput sequencing reads, enabling the determination of community roles in the HMP cohort and in future metagenomic studies.National Institutes of Health (U.S.) (U54HG004968

    Chromosome 9p21 SNPs associated with multiple disease phenotypes correlate with ANRIL expression

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    Author Summary Genetic variants on chromosome 9p21 have been associated with several important diseases including coronary artery disease, diabetes, and multiple cancers. Most of the risk variants in this region do not alter any protein sequence and are therefore likely to act by influencing the expression of nearby genes. We investigated whether chromosome 9p21 variants are correlated with expression of the three nearest genes ( CDKN2A , CDKN2B , and ANRIL ) which might mediate the association with disease. Using two different techniques to study effects on expression in blood from two separate populations of healthy volunteers, we show that variants associated with disease are all correlated with ANRIL expression, but associations with the other two genes are weaker and less consistent. Multiple genetic variants are independently associated with expression of all three genes. Although total expression levels of CDKN2A , CDKN2B , and ANRIL are positively correlated, individual genetic variants influence ANRIL and CDKN2B expression in opposite directions, suggesting a possible role of ANRIL in CDKN2B regulation. Our study suggests that modulation of ANRIL expression mediates susceptibility to several important human diseases

    Measurement of the Ratio of b Quark Production Cross Sections in Antiproton-Proton Collisions at 630 GeV and 1800 GeV

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    We report a measurement of the ratio of the bottom quark production cross section in antiproton-proton collisions at 630 GeV to 1800 GeV using bottom quarks with transverse momenta greater than 10.75 GeV identified through their semileptonic decays and long lifetimes. The measured ratio sigma(630)/sigma(1800) = 0.171 +/- .024 +/- .012 is in good agreement with next-to-leading order (NLO) quantum chromodynamics (QCD)

    Optimasi Portofolio Resiko Menggunakan Model Markowitz MVO Dikaitkan dengan Keterbatasan Manusia dalam Memprediksi Masa Depan dalam Perspektif Al-Qur`an

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    Risk portfolio on modern finance has become increasingly technical, requiring the use of sophisticated mathematical tools in both research and practice. Since companies cannot insure themselves completely against risk, as human incompetence in predicting the future precisely that written in Al-Quran surah Luqman verse 34, they have to manage it to yield an optimal portfolio. The objective here is to minimize the variance among all portfolios, or alternatively, to maximize expected return among all portfolios that has at least a certain expected return. Furthermore, this study focuses on optimizing risk portfolio so called Markowitz MVO (Mean-Variance Optimization). Some theoretical frameworks for analysis are arithmetic mean, geometric mean, variance, covariance, linear programming, and quadratic programming. Moreover, finding a minimum variance portfolio produces a convex quadratic programming, that is minimizing the objective function ðð¥with constraintsð ð 𥠥 ðandð´ð¥ = ð. The outcome of this research is the solution of optimal risk portofolio in some investments that could be finished smoothly using MATLAB R2007b software together with its graphic analysis

    Differential cross section measurements for the production of a W boson in association with jets in proton–proton collisions at √s = 7 TeV