Sentence examples for cause-effect network from inspiring English sources

Normally, traditional methods are used to identify and evaluate environmental impacts, such as matrices, cause-effect network diagrams or check lists.

2. A cause-effect network is reconstructed starting from these tables.

The cause-effect network (after graph pruning), used for prediction, is shown in Figure 1.

A cause-effect network connecting stimuli, inhibited and measured proteins, was reconstructed by a two step procedure: from single-stimulus/inhibitor data, a table was first built to code significant effects of stimuli and inhibitors on output proteins, which was then translated into links among nodes of the network according to very simple rules.

The task of the DREAM4 (Dialogue for Reverse Engineering Assessments and Methods) "Predictive signaling network modeling" challenge was to develop a method that, from single-stimulus/inhibitor data, reconstructs a cause-effect network to be used to predict the protein activity level in multi-stimulus/inhibitor experimental conditions.

In [16], fuzzy cause-effect networks are used to model the heuristic knowledge inference involved in the restoration plan, however, fuzzy method does not guarantee the optimal solution.

In this paper, we present a simple method able to reconstruct, from single-stimulus/inhibitor protein data, cause-effect networks representing signaling pathways and to predict protein levels during multi-stimulus/inhibitor perturbations.

First the "cause-and-effect" network model describing the mechanism and second, the gene expression dataset from a well-designed experiment.

Leveraging the "cause-and-effect" network models together with Network Perturbation Amplitude (NPA) algorithms ([ 29, 43]), the fold changes of gene expression were translated into differential network backbone value for each backbone node in the network.

This model is integrated with a Bayesian belief network characterizing the cause-effect relationships among factors influencing the repairman error probability during maintenance.

Networks offer another way of visualizing cause-effect relationships.