Recognizing regulatory sequences in genomes is a continuing challenge, despite a wealth of available genomic data and a growing number of experimentally validated examples.
If a model 'fails to validate', for example it has adequate discrimination but poor calibration, we may wish to refine it.
The description of the problem, the methods, and the three experimentally validated examples is somewhat lengthy and redundant.
Maternal and paternal anxiety at all time points was measured using the anxiety items from the Crown Crisp experiential index (CCEI), a validated self-rating inventory (for example, see Crisp et al).; example items include 'worry a lot' and 'feeling strung up inside').
Figure 9 illustrates the general nature of how the ABM provides feedback to the GP-based ML system, essentially acting as a data generator until real data can be used to validate, for example, a wait-time forecasting function.
A numerical example validates the efficiency of the method.
A simulation example validates the theoretical results and the proposed approach.
The gaming industry is a perfect example, validating users from the moment they begin playing.
Details of the BAC analysis are given in the Materials and Methods section and a representative example validating a potential break-point in Chromosome 4 is illustrated in Figure 5.
Finally, the methodology is verified and validated through an example of a numerical test bed.
The results, validated using an example application of a modular transfer system, show that using the proposed method can significantly speed up the process of finding the appropriate module configuration based on reliable simulation models even for non-simulation-experts.
