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To examine this possibility, each gene was manually divided into two parts.
To test for this possibility, each gene was divided into 20 equal segments and the mean hydropathy of the amino acids calculated for each.
To test for this possibility, each taxon was successively removed from the dataset (N = 63 experiments) and subsequently a likelihood run (using RAxML) under the GTR + 3 model with 1000 rapid bootstrap replicates was conducted for each resulting dataset.
To investigate this possibility, each member of the immediately adjacent gene pairs was compared by BLAST analysis to its adjacent partner and to the other genes in the S. cerevisiae genome [ 31].
In order to rule out this possibility each human disease gene was classified according to the molecular function of its protein product as determined by Gene Ontology (GO) 'slim' terms [ 18], and the conservation score in mouse and KA/KS values between human and chimpanzee of dominant and recessive disease genes in each of the functional annotations were assessed (Table 4).
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To exclude this possibility, in each model we examined the CL Bundle's "cross-over" effects by assessing whether compliance with the CL Bundle was associated with lower rates of ventilator-associated pneumonia (VAP).
We therefore analysed this possibility for each of the SNPs.
To investigate this possibility, at each frequency we calculated the number of sources for which the effect was reliably expressed (by the bootstrap test) (Fig. 4 C).
To test for this possibility, for each exon end, we calculated the difference (Eenrich) between the observed ESE density (Eobs) and the expected ESE density (Eexpect), given the base composition of that exon end.
To explore this possibility, for each MTB we identified, we computed 7 non-expression features, including the number of mRNAs and miRNAs in it, the density of 1's in the MTB, in the same rows, columns or either but outside the MTB, and the MTB type.
To test this possibility, we correlated each significant predictor of low prevalence accuracy with false alarms.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com