PHAISTOS: A framework for Markov chain Monte Carlo simulation and inference of protein structure

Gyration Radius and Energy Study at Different Temperatures for Acetylcholine Receptor Protein in Gas Phase by Monte Carlo, Molecular and Langevin Dynamics Simulations

The determination of gyration radius is a strong research for configuration of a Macromolecule. Italso reflects molecular compactness shape. In this work, to characterize the behavior of theprotein, we observe quantities such as the radius of gyration and the average energy. We studiedthe changes of these factors as a function of temperature for Acetylcholine receptor protein in gasphase with n...

BayesX - Software for Bayesian Inference based on Markov Chain Monte Carlo simulation techniques

Parallel GPGPU Evaluation of Small Angle X-ray Scattering Profiles in a Markov Chain Monte Carlo Framework Antonov,

Inference of protein structure from experimental data is of crucial interest in science, medicine and biotechnology. Low-resolution methods, such as small angle X-ray scattering (SAXS), play a major role in investigating important biological questions regarding the structure of proteins in solution. To infer protein structure from SAXS data, it is necessary to calculate the expected experimenta...

Efficient Bayesian Inference for Multivariate Probit Models with Sparse Inverse Correlation Matrices

We propose a Bayesian approach for inference in the multivariate probit model, taking into account the association structure between binary observations. We model the association through the correlation matrix of the latent Gaussian variables. Conditional independence is imposed by setting some off-diagonal elements of the inverse correlation matrix to zero and this sparsity structure is modele...

New Approaches in 3D Geomechanical Earth Modeling

In this paper two new approaches for building 3D Geomechanical Earth Model (GEM) were introduced. The first method is a hybrid of geostatistical estimators, Bayesian inference, Markov chain and Monte Carlo, which is called Model Based Geostatistics (MBG). It has utilized to achieve more accurate geomechanical model and condition the model and parameters of variogram. The second approach is the ...