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PharmID: Pharmacophore Identification Using Gibbs Sampling
Journal of Chemical Information and Modeling, 2006The binding of a small molecule to a protein is inherently a 3D matching problem. As crystal structures are not available for most drug targets, there is a need to be able to infer from bioassay data the key binding features of small molecules and their disposition in space, the pharmacophore.
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1993
Publisher Summary This chapter presents an elementary introduction to Gibbs sampling. Gibbs sampling gives a way to approximate posterior distributions in many Bayesian models. It gives a convenient way to approximate the posterior densities of univariate functions of the parameter.
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Publisher Summary This chapter presents an elementary introduction to Gibbs sampling. Gibbs sampling gives a way to approximate posterior distributions in many Bayesian models. It gives a convenient way to approximate the posterior densities of univariate functions of the parameter.
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Gibbs Sampling with Deterministic Dependencies
2011There is a growing interest in the logical representation of both probabilistic and deterministic dependencies. While Gibbs sampling is a widely-used method for estimating probabilities, it is known to give poor results in the presence of determinism. In this paper, we consider acyclic Horn logic, a small, but significant fragment of first-order logic ...
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Markov Chain Monte Carlo algorithms are indispensable in classical thermodynamic simulation, perhaps due to their mathematical simplicity, algorithmic efficiency, and physical origin. In particular, Glauber dynamics is a detailed-balanced continuous-time Markov chain that fixes the Gibbs distribution and also serves as a mathematically succinct model ...
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Convergence Diagnosis for Gibbs Sampling Output
2000Gibbs sampling is a technique to calculate a complex posterior distribution as steady state measure of a Markov chain. The fundamental problem of inference from Markov chain simulation is that there will always be areas of the target distribution that have not been covered by the finite chain.
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Protein domain hierarchy Gibbs sampling strategies
Statistical Applications in Genetics and Molecular Biology, 2014AbstractHierarchically-arranged multiple sequence alignment profiles are useful for modeling protein domains that have functionally diverged into evolutionarily-related subgroups. Currently such alignment hierarchies are largely constructed through manual curation, as for the NCBI Conserved Domain Database (CDD).
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1997
In this section we discuss the use of simulation techniques to estimate and forecast MS-VAR processes. A general feature of MS-VAR models is that they approximate non-linear processes as piecewise linear by restricting the processes to be linear in each regime.
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In this section we discuss the use of simulation techniques to estimate and forecast MS-VAR processes. A general feature of MS-VAR models is that they approximate non-linear processes as piecewise linear by restricting the processes to be linear in each regime.
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