Sentence examples for de model from inspiring English sources

The general concept of fitting and comparing a small number of competing models to a dataset (such as a non-DE model vs. a DE model) can be readily applied to identifying genes with interesting patterns, where these patterns are predefined using biological knowledge and are encapsulated in the model formulation.

If the RSAD of the DE model is much smaller than the RSAD of the non-DE model, based on a predefined threshold, a gene is deemed to be differentially expressed (see Figure 8A for an example).

The non-DE model only requires fitting one parameter — the median value of the data, while the DE model requires fitting k parameters where k is the number of distinct class labels.

For identifying DE genes, we propose to fit and compare the goodness-of-fit of two models, where one model specifies that the median expression values are the same across multiple classes (the non-DE model), and the second model specifies that the median expression values can differ across multiple classes (the DE model).

The present paper is devoted to the reconstruction of a dark energy (DE) model dubbed as 'modified holographic Ricci dark energy' (MHRDE) in FAC.

Jamil et al. [30] studied the interacting DE model in the framework of f(T) modified gravity theory for a particular choice of f(T).

This enables a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.

Adaptation of the homogenisation approach to the case of rector internals is then exposed: it is shown that in such case, confinement effects can de modelled by a suitable modification of classical fluid structure symmetric formulation.

The developed ANFIS-DE model predictions are compared with the ANFIS model as well as existing sediment transport equations.

In this case, the objective function defined as RMSE (Eq. 25) is the smallest and the antecedent and consequent parameters are assigned to the ANFIS-DE model.

The MFs were selected by trial and error between the objective function values of the ANFIS-DE model vs. the number of MFs.