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The proposed framework is based on a posterior sampling approach in which information obtained by low-resolution (MRI or X-ray) measurements is combined with prior models inferred from high-resolution microscopic data, typically 2D.
This analysis was based on a posterior distribution of phylogenetic trees inferred using the Bayesian Markov Chain Monte Carlo (MCMC) available in the BEAST package [78].
When the lrt was significant (using a 0.01 α threshold), the beb (Bayes empirical Bayes) method was used to identify residues that are likely to have evolved under positive selection [ 56], based on a posterior probability threshold of 0.95.
Next, we then performed a sparse ANOVA on the training data set (45,101 Affymetrix probes) to identify 4,276 genes that were significantly differentially expressed between the control and tumor-bearing mice (based on a posterior probability of ≥0.99).
We further estimated the critical amino acid residues responsible for the functional divergence by calculating the site-specific profile based on a posterior probability (Q k ) analysis of the non-TIR- and TIR-NBS-LRR subfamilies.
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Experimental results on some real data sets are also provided to show the effectiveness of this approach versus the classical cross entropy (based on a global posterior probability estimation).
Following the suggestions of Anderson and Thompson (2002), individual genetic assignment to classes was based on a minimum posterior probability threshold (T q) of 0.50.
Following the suggestions of Vaha and Primmer [ 34], individual genetic assignment to clusters was based on a minimum posterior probability threshold (Tq) of 0.90.
Cheung and Thall [ 25] present a method for monitoring survival probabilities based on an approximate posterior, and they apply stopping rules described in Thall and Simon [ 6] based on the approximate probabilities.
Aimed at the problem of nonlinear and time-varying noise characteristics in inertial and land-based integrated navigation system, a cubature Kalman filter algorithm based on maximum a posterior estimation and fading factor has been proposed, and the fuzzy control theory is used to make it better to track the time-varying noise characteristics.
Bayesian inference of phylogeny is based on a quantity called the posterior probability function of a tree, in the same way as maximum-likelihood inference is based on the likelihood function.
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