Search results for " statistica"
showing 10 items of 2672 documents
Epigenetic Control of Phenotypic Plasticity in the Filamentous Fungus Neurospora crassa
2016
Abstract Phenotypic plasticity is the ability of a genotype to produce different phenotypes under different environmental or developmental conditions. Phenotypic plasticity is a ubiquitous feature of living organisms, and is typically based on variable patterns of gene expression. However, the mechanisms by which gene expression is influenced and regulated during plastic responses are poorly understood in most organisms. While modifications to DNA and histone proteins have been implicated as likely candidates for generating and regulating phenotypic plasticity, specific details of each modification and its mode of operation have remained largely unknown. In this study, we investigated how e…
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…
Stagewise pseudo-value regression for time-varying effects on the cumulative incidence
2015
In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event s…
L1-Penalized Censored Gaussian Graphical Model
2018
Graphical lasso is one of the most used estimators for inferring genetic networks. Despite its diffusion, there are several fields in applied research where the limits of detection of modern measurement technologies make the use of this estimator theoretically unfounded, even when the assumption of a multivariate Gaussian distribution is satisfied. Typical examples are data generated by polymerase chain reactions and flow cytometer. The combination of censoring and high-dimensionality make inference of the underlying genetic networks from these data very challenging. In this article, we propose an $\ell_1$-penalized Gaussian graphical model for censored data and derive two EM-like algorithm…
Model selection for factorial Gaussian graphical models with an application to dynamic regulatory networks.
2016
Abstract Factorial Gaussian graphical Models (fGGMs) have recently been proposed for inferring dynamic gene regulatory networks from genomic high-throughput data. In the search for true regulatory relationships amongst the vast space of possible networks, these models allow the imposition of certain restrictions on the dynamic nature of these relationships, such as Markov dependencies of low order – some entries of the precision matrix are a priori zeros – or equal dependency strengths across time lags – some entries of the precision matrix are assumed to be equal. The precision matrix is then estimated by l 1-penalized maximum likelihood, imposing a further constraint on the absolute value…
A heuristic, iterative algorithm for change-point detection in abrupt change models
2017
Change-point detection in abrupt change models is a very challenging research topic in many fields of both methodological and applied Statistics. Due to strong irregularities, discontinuity and non-smootheness, likelihood based procedures are awkward; for instance, usual optimization methods do not work, and grid search algorithms represent the most used approach for estimation. In this paper a heuristic, iterative algorithm for approximate maximum likelihood estimation is introduced for change-point detection in piecewise constant regression models. The algorithm is based on iterative fitting of simple linear models, and appears to extend easily to more general frameworks, such as models i…
Reference genome assessment from a population scale perspective: an accurate profile of variability and noise.
2017
Abstract Motivation Current plant and animal genomic studies are often based on newly assembled genomes that have not been properly consolidated. In this scenario, misassembled regions can easily lead to false-positive findings. Despite quality control scores are included within genotyping protocols, they are usually employed to evaluate individual sample quality rather than reference sequence reliability. We propose a statistical model that combines quality control scores across samples in order to detect incongruent patterns at every genomic region. Our model is inherently robust since common artifact signals are expected to be shared between independent samples over misassembled regions …
Evaluation of Immunofluorescence Antibody Test Used for the Diagnosis of Canine Leishmaniasis in the Mediterranean Basin: A Systematic Review and Met…
2015
With an expected sensitivity (Se) of 96% and specificity (Sp) of 98%, the immunofluorescence antibody test (IFAT) is frequently used as a reference test to validate new diagnostic methods and estimate the canine leihmaniasis (CanL) true prevalence in the Mediterranean basin. To review the diagnostic accuracy of IFAT to diagnose CanL in this area with reference to its Se and Sp and elucidate the potential causes of their variations, a systematic review was conducted (31 studies for the 26-year period). Three IFAT validation methods stood out: the classical contingency table method, methods based on statistical models and those based on experimental studies. A variation in the IFAT Se and Sp …