ABC-SysBio-approximate Bayesian computation in Python with GPU support.

Motivation: The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions. Results: Here we present a Python package, ABC-SysBio, that implements parameter inference and model selection for dynamical systems in an approximate Bayesian computation (ABC) framework. ABC-SysBio combines three algorithms: ABC rejection sampler, ABC SMC for parameter inference and ABC SMC for model selection. It is designed to work with models written in Systems Biology Markup Language (SBML). Deterministic and stochastic models can be analyzed in ABC-SysBio

Estimating the Effect of Liver and Pancreas Volume and Fat Content on Risk of Diabetes: A Mendelian Randomization Study

Fat content and volume of liver and pancreas are associated with risk of diabetes in observational studies; whether these associations are causal is unknown. We conducted a Mendelian randomization (MR) study to examine causality of such associations. We used genetic variants associated (P < 5 × 10-8) with the exposures (liver and pancreas volume and fat content) using MRI scans of UK Biobank participants (n = 32,859). We obtained summary-level data for risk of type 1 (9,358 cases) and type 2 (55,005 cases) diabetes from the largest available genome-wide association studies. We performed inverse-variance weighted MR as main analysis and several sensitivity analyses to assess pleiotropy and to exclude variants with potential pleiotropic effects. Observationally, liver fat and volume were associated with type 2 diabetes (odds ratio per 1 SD higher exposure 2.16 [2.02, 2.31] and 2.11 [1.96, 2.27], respectively). Pancreatic fat was associated with type 2 diabetes (1.42 [1.34, 1.51]) but not type 1 diabetes, and pancreas volume was negatively associated with type 1 diabetes (0.42 [0.36, 0.48]) and type 2 diabetes (0.73 [0.68, 0.78]). MR analysis provided evidence only for a causal role of liver fat and pancreas volume in risk of type 2 diabetes (1.27 [1.08, 1.49] or 27% increased risk and 0.76 [0.62, 0.94] or 24% decreased risk per 1SD, respectively) and no causal associations with type 1 diabetes. Our findings assist in understanding the causal role of ectopic fat in the liver and pancreas and of organ volume in the pathophysiology of type 1 and 2 diabetes. [Abstract copyright: © 2022 by the American Diabetes Association.

Crystal surfaces with correlated disorder: Phase transitions between roughening and superroughening

A theory for surface transitions in the presence of a disordered pinning potential is presented. Arbitrary disorder correlations are treated in the framework of a dynamical functional renormalization group. The roughening transition, where surface roughness and mobility behave discontinuously, is shown to turn smoothly into the continuous superroughening transition, when the range of disorder correlations is decreased. Implications for random-field $XY$-models and vortex glasses are discussed.Comment: 13 pages with 2 figures, latex+revte

ABC-SysBio—approximate Bayesian computation in Python with GPU support

Motivation: The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions

Phase Diagram for Splay Glass Superconductivity

Localization of flux lines to splayed columnar pins is studied. A sine-Gordon type renormalization group study reveals the existence of a Splay glass phase and yields an analytic form for the transition temperature into the glass phase. As an independent test, the $I-V$ characteristics are determined via a Molecular Dynamics code. The glass transition temperature supports the RG results convincingly. The full phase diagram of the model is constructed.Comment: 14 pages, uuencoded compressed tar file with 3 postscript figure

Interacting Arrays of Steps and Lines in Random Media

The phase diagram of two interacting planar arrays of directed lines in random media is obtained by a renormalization group analysis. The results are discussed in the contexts of the roughening of reconstructed crystal surfaces, and the pinning of flux line arrays in layered superconductors. Among the findings are a glassy flat phase with disordered domain structures, a novel second-order phase transition with continuously varying critical exponents, and the generic disappearance of the glassy ``super-rough'' phases found previously for a single array.Comment: 4 pages, REVTEX 3.0, uses epsf,multicol, 3 .eps-figures, submitted to PR

Glassy Roughness of a Crystalline Surface Upon a Disordered Substrate

The discrete Gaussian model for the surface of a crystal deposited on a disordered substrate is studied by Monte Carlo simulations. A continuous transition is found from a phase with a thermally-induced roughness to a glassy one in which the roughness is driven by the disorder. The behavior of the height-height correlations is consistent with the one-step replica symmetry broken solution of the variational approximation. The results differ from the renormalization group predictions and from recent simulations of a 2D vortex-glass model which belongs to the same universality class.Comment: 12 pages (RevTeX) & 3 figures (PS) uuencode

Models of stress fluctuations in granular media

We investigate in detail two models describing how stresses propagate and fluctuate in granular media. The first one is a scalar model where only the vertical component of the stress tensor is considered. In the continuum limit, this model is equivalent to a diffusion equation (where the r\^ole of time is played by the vertical coordinate) plus a randomly varying convection term. We calculate the response and correlation function of this model, and discuss several properties, in particular related to the stress distribution function. We then turn to the tensorial model, where the basic starting point is a wave equation which, in the absence of disorder, leads to a ray-like propagation of stress. In the presence of disorder, the rays acquire a diffusive width and the angle of propagation is shifted. A striking feature is that the response function becomes negative, which suggests that the contact network is mechanically unstable to very weak perturbations. The stress correlation function reveals characteristic features related to the ray-like propagation, which are absent in the scalar description. Our analytical calculations are confirmed and extended by a numerical analysis of the stochastic wave equation.Comment: 32 pages, latex, 18 figures and 6 diagram

Large time off-equilibrium dynamics of a manifold in a random potential

We study the out of equilibrium dynamics of an elastic manifold in a random potential using mean-field theory. We find two asymptotic time regimes: (i) stationary dynamics, (ii) slow aging dynamics with violation of equilibrium theorems. We obtain an analytical solution valid for all large times with universal scalings of two-time quantities with space. A non-analytic scaling function crosses over to ultrametricity when the correlations become long-range. We propose procedures to test numerically or experimentally the extent to which this scenario holds for a given system.Comment: 12 page

Glassy transition in a disordered model for the RNA secondary structure

We numerically study a disordered model for the RNA secondary structure and we find that it undergoes a phase transition, with a breaking of the replica symmetry in the low temperature region (like in spin glasses). Our results are based on the exact evaluation of the partition function.Comment: 4 pages, 3 figure