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In this work, pathway topologies are inferred by using Bayesian networks with probabilistic Boolean threshold functions.
These estimates are inferred by using observed HIV prevalence data to fit a mathematical model, called the UNAIDS Estimation and Projection Package (EPP) [ 2– 5], which incorporates assumptions on survival times with HIV and the scale-up of antiretroviral therapy (ART).
In this novel network, false positive interactions are theoretically further reduced by cutting the inter-GO connections and weighting the interactions using co-expression values, as opposed to other networks which are inferred by using only the co-expression levels [ 9] or solely literature curated networks obtained from different contexts [ 10].
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For each gene, phylogenetic trees were inferred by using maximum-likelihood and Bayesian inference methods.
The rheological structures of the lowlands (North Pole) and highlands (Solis Planum) were inferred by using the temperature profiles of each region, as calculated above.
The evolutionary history was inferred by using the Maximum Likelihood method with the default options of MEGA5, based on the Tamura-Nei model and 1000 bootstrap replications.
The phylogenetic tree was inferred by using the Neighbour-Joining method with the Maximum Composite Likelihood model in MEGA4 program with bootstrap values based on 1000 replications.
The parameters of the MRF model are learned from the training data and then the most likely color distribution for each pixel in the given color-depleted image is inferred by using belief propagation (BP).
Phylogenetic trees were inferred by using maximum-likelihood (ML) and Bayesian methods.
In other methods this position can only be inferred by using additional secondary structure information to reduce alignment errors.
Phylogenetic relationships were inferred by using PAUP version 4b10 (15 ).
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