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A more complicated simulated environment was also constructed as shown in Fig. 7.
Similar(59)
In future work, larger systems should be simulated that have a greater number of dimensions (to reveal further non-trivial types of interaction) and involve more-complicated simulated models such as QCD.
Already, they have created an anatomical model of its branching airways, which includes a representation of how oxygen is exchanged for carbon dioxide.Modelling how lungs work is even more complicated than simulating the heart, because lungs also depend on the activity of adjacent structures, such as muscles and ribs.
> -wrap-foot> Real data are more complicated than the simulated data due to the uneven read coverage induced by the broad dynamic range of gene expression levels.
The XPS spectrum indicates that Si is distributed more in the outer carbon shell, and therefore, a more complicated structure model seems necessary to simulate the electric dipoles.
Although the team is keen to simulate more complicated systems, M. genitalium was chosen as its genome is small, being contained within a single chromosome, rather than for more aesthetic reasons: the bacterium is a sexually transmitted parasite.
Generic place and transition have been practically applied for modeling and simulating more complicated biological processes [ 7, 19, 20], e.g., activities of enzymes for a multi-modification protein.
When simulating more complicated systems, this can be approximated by a histogram of the distribution of species at T (from the initial ETL simulations, for instance) to get a reasonable idea of its shape.
However, when modeling biological pathways, it has been noticed that several useful extensions should be applied for modeling and simulating more complicated biopathway processes (e.g., activities of enzymes for a multi-modification protein) and other biological processes that are not normally treated in biological pathways (e.g., alternative splicing and frameshifting) [ 18].
Figure 3 (top) shows the detection power and type I error for standard imputation, haplotype analysis, AI, and single-SNP logistic regression for data simulated under a more complicated scenario (Scenario 4), a haplotype model in which disease was assumed to be caused by a haplotype effect defined by two underlying causal nongenotyped SNPs, rs7926004, and rs10500679.
Finally the new hybrid algorithm is successfully applied to simulate the more complicated Sydney swirling bluff-body flame 'SM1'SM1
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