Sentence examples for modelling using simulated from inspiring English sources

We have investigated the potential of combined PET-MRI kinetic modelling using simulated FDG data.

We evaluate the model using simulated and empirical backtests and analyze the impact of the insurance guarantees on the portfolio performance.

Davies et al. 2003 [32] built homology models of DRB1*0301, DRB1*0401, and DRB1*1101 using a DRB1*0101 template structure and docked peptides into these MHC models using simulated annealing optimization with the AMBER force field in explicit water.

We evaluated the performance of this model using simulated metagenomes and demonstrate its applicability on three recent metagenomic datasets.

In Figure 2, we show the theoretical behavior of this model using simulated data with varying base qualities.

We explore the behaviour of the models using simulated data sets, and illustrate their application to two real data sets of plant traits.

We compare these models using simulated data sets of allele-specific read counts under a null scenario in which there is bias (B≠0.5) and no allelic imbalance (R = 1) and simulated data sets with both bias and allelic imbalance (R≠1).

The objective of this paper was to develop three models that would permit multi-trait genomic selection by combining scarcely recorded traits with genetically correlated indicator traits, and to compare their performance to single-trait models, using simulated datasets.

In order to determine whether the mean LAP scores varied by each of the simulated patient scenarios, Generalised Estimating Equations (GEEs) were used to fit a linear model using simulated patient scenario as the single independent variable (Table  1).

To provide insights into the decision rule criterion (in terms of BF threshold) to declare SNPs as subjected to selection, we subsequently investigated the power and the robustness of the model using simulated data (see Methods).

We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data.