Search results for "statistical [Methods]"
showing 10 items of 1664 documents
Expectation or Sensorial Reality? An Empirical Investigation of the Biodynamic Calendar for Wine Drinkers.
2017
International audience; The study's aim was to investigate a central tenet of biodynamic philosophy as applied to wine tasting, namely that wines taste different in systematic ways on days determined by the lunar cycle. Nineteen New Zealand wine professionals tasted blind 12 Pinot noir wines at times determined within the biodynamic calendar for wine drinkers as being favourable (Fruit day) and unfavourable (Root day) for wine tasting. Tasters rated each wine four times, twice on a Fruit day and twice on a Root day, using 20 experimenter-provided descriptors. Wine descriptors spanned a range of varietal-relevant aroma, taste, and mouthfeel characteristics, and were selected with the aim of …
Uhlmann number in translational invariant systems
2019
We define the Uhlmann number as an extension of the Chern number, and we use this quantity to describe the topology of 2D translational invariant Fermionic systems at finite temperature. We consider two paradigmatic systems and we study the changes in their topology through the Uhlmann number. Through the linear response theory we linked two geometrical quantities of the system, the mean Uhlmann curvature and the Uhlmann number, to directly measurable physical quantities, i.e. the dynamical susceptibility and to the dynamical conductivity, respectively.
Retrieving infinite numbers of patterns in a spin-glass model of immune networks
2013
The similarity between neural and immune networks has been known for decades, but so far we did not understand the mechanism that allows the immune system, unlike associative neural networks, to recall and execute a large number of memorized defense strategies {\em in parallel}. The explanation turns out to lie in the network topology. Neurons interact typically with a large number of other neurons, whereas interactions among lymphocytes in immune networks are very specific, and described by graphs with finite connectivity. In this paper we use replica techniques to solve a statistical mechanical immune network model with `coordinator branches' (T-cells) and `effector branches' (B-cells), a…
Ecological network analysis reveals the inter-connection between soil biodiversity and ecosystem function as affected by land use across Europe
2016
Soil organisms are considered drivers of soil ecosystem services (primary productivity, nutrient cycling, carbon cycling, water regulation) associated with sustainable agricultural production. Soil biodiversity was highlighted in the soil thematic strategy as a key component of soil quality. The lack of quantitative standardised data at a large scale has resulted in poor understanding of how soil biodiversity could be incorporated into legislation for the protection of soil quality. In 2011, the EcoFINDERS (FP7) project sampled 76 sites across 11 European countries, covering five biogeographical zones (Alpine, Atlantic, Boreal, Continental and Mediterranean) and three land-uses (arable, gra…
Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies
2016
Mieth, Bettina et al.
Partitioned learning of deep Boltzmann machines for SNP data.
2016
Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…
The intrinsic combinatorial organization and information theoretic content of a sequence are correlated to the DNA encoded nucleosome organization of…
2015
Abstract Motivation: Thanks to research spanning nearly 30 years, two major models have emerged that account for nucleosome organization in chromatin: statistical and sequence specific. The first is based on elegant, easy to compute, closed-form mathematical formulas that make no assumptions of the physical and chemical properties of the underlying DNA sequence. Moreover, they need no training on the data for their computation. The latter is based on some sequence regularities but, as opposed to the statistical model, it lacks the same type of closed-form formulas that, in this case, should be based on the DNA sequence only. Results: We contribute to close this important methodological gap …
Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate
2016
Abstract Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p -values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.
Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications
2015
The bootstrap method has become a widely used tool applied in diverse areas where results based on asymptotic theory are scarce. It can be applied, for example, for assessing the variance of a statistic, a quantile of interest or for significance testing by resampling from the null hypothesis. Recently, some approaches have been proposed in the biometrical field where hypothesis testing or model selection is performed on a bootstrap sample as if it were the original sample. P-values computed from bootstrap samples have been used, for example, in the statistics and bioinformatics literature for ranking genes with respect to their differential expression, for estimating the variability of p-v…
Fasting regulates EGR1 and protects from glucose- and dexamethasone-dependent sensitization to chemotherapy
2017
Fasting reduces glucose levels and protects mice against chemotoxicity, yet drugs that promote hyperglycemia are widely used in cancer treatment. Here, we show that dexamethasone (Dexa) and rapamycin (Rapa), commonly administered to cancer patients, elevate glucose and sensitize cardiomyocytes and mice to the cancer drug doxorubicin (DXR). Such toxicity can be reversed by reducing circulating glucose levels by fasting or insulin. Furthermore, glucose injections alone reversed the fasting-dependent protection against DXR in mice, indicating that elevated glucose mediates, at least in part, the sensitizing effects of rapamycin and dexamethasone. In yeast, glucose activates protein kinase A (P…