Exact(49)
Such model was inferred from experimental data and the, InferGene inference methodology [ 15], which is used to obtain kinetic parameters from experimental steady-state data.
In Figure 2 we provide a graphical representation of the causal inference methodology.
In the following, we explain such obtained benefits within the framework of our proposed inference methodology.
The M-LaF model parameters are calibrated as posterior distribution using the Bayesian inference methodology.
Although already efficient, coarse-fine sensing approaches could further benefit from the correlation-based inference methodology proposed in this work.
One of the applications of the BRB is the Rule-base Inference Methodology using the Evidential Reasoning approach (RIMER).
Similar(11)
We review recent Bayesian network inference methodologies we developed to infer genetic and metabolic pathways associated to oncological drug chemoresistance.
Secondly, we propose to study statistical inference methodologies for bivariate (and, more generally, multivariate) BG distributions in (9) and (12).
The incorporation of new information from monitoring and/or testing will be performed by the application of Bayesian inference methodologies.
A general probabilistic inference procedure is proposed in this paper based on the Maximum relative Entropy (MrE) approach which generalizes both Bayesian and Maximum Entropy (MaxEnt) inference methodologies.
Here, we test one fundamental difference between stochastic mapping and maximum parsimony inference methodologies.
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