Sentence examples for by a probabilistic graphical from inspiring English sources

The main algorithmic idea of ProbHap is a new dynamic programming algorithm that exactly optimizes a likelihood function specified by a probabilistic graphical model and which generalizes a popular objective called the minimum error correction.

Without loss of generality, a gene network can be represented by a probabilistic graphical model, such as a Markov random field (MRF) if the gene states are taken as discrete (Segal et al., 2003), or a Gaussian graphical model (GGM) if the gene states are set to the continuous measurements of the microarray signal (Dobra et al., 2004), or a Bayesian network (Friedman et al., 2000).

In EDAs, modeling is achieved by building a probabilistic graphical model that represents a condensed representation of the features shared by the selected solutions.

This was done by designing a probabilistic graphical model which introduced a new dense layer of variables, and taking into account the predicted intensity of the signal in probes that are at ends of nucleosomes.

Results: We present a novel protein threading method, CNFpred, which achieves much more accurate sequence template alignment by employing a probabilistic graphical model called a Conditional Neural Field (CNF), which aligns one protein sequence to its remote template using a non-linear scoring function.

The motion estimates are computed in a sound probabilistic framework by performing inference on a probabilistic graphical model.

The advances behind P robH ap are made possible by framing the phasing problem within a probabilistic graphical models framework.

Here, we presented PMNs, a probabilistic graphical method that learns transcriptional networks by combining phenotypic effects (changes in gene expression) with their underlying physical mechanism (protein protein and protein DNA interactions).

In this work, a probabilistic graphical model based approach is employed to learn the dependence by running a number of conditional independence tests using observation data.

A Bayesian network is a probabilistic graphical model that combines the advantage of CF and CBF.

A probabilistic graphical model approach to uncertainty quantification for flows in random porous media is introduced.