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n was set as 4 because of the computational efficiency.
Because of the computational efficiency of the FIM method, all chemicals and health effects can be considered in a single analysis.
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For the purpose of the computational efficiency, there are many methods to improve the computational speed.
Because the computational efficiency is not obvious on this small test network, the parallel performance will not be discussed further.
We present an empirical application focused on Ciona savignyi, a tunicate with very high SNP heterozygosity (~0.05), because high diversity challenges the computational efficiency of most existing nonmodel pipelines while also potentially exacerbating paralog artifacts.
This combines the functionality of plugins with the computational efficiency of C++.
L and the number of combinations of degrees of sparsity will impact the computational efficiency.
The adoption of the combined parameter reduces the computational efficiency because two sets of LUTs need to be used and the results obtained separately with the two methods need to be compared.
The details of the absolute computational times are not important, but a comparison of the analysis times is informative (see below) because it allows us to empirically compare the computational efficiency of the different methods.
Given the number of genes in high-throughput datasets, the computational efficiency of any data analysis method is critically important.
Because of this computational efficiency, we were able to perform a large-scale analysis of sequence data from the Human Microbiome Project (HMP, Peterson et al., 2009) without using a computer cluster or special hardware.
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