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Moreover, it is shown in Table 1 (P(1)+(2)) that the correlation between p35 and p36 can be remedied by fitting two data sets together.
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This bimodal distribution allows us to derive a cutoff to separate cases into high and low expression groups by fitting two normal distributions to the data.
This method has been used to create a closed surface by adaptively fitting two adjacent patches to synthetic range data and a complex open surface by fitting four patches to experimentally measured range data.
A preliminary three-source analysis was performed by fitting eight log-linear models to the data arranged in a 2 contingency table, according to the presence or absence of each case in each source.
Cell survival data were analysed by fitting three four-parameter logistic curves to the three separate treatments (TNF alone, AZD9773 41 ng/ml+TNF and AZD9773 1200 ng/ml+TNFα) versus the TNF concentration on each plate.
As shown in Figure 4B, the correlation between p35 and p36 is remedied by fitting to two data sets together and, moreover, the parameters tend to approach their true values (i.e. 0.1, 1.0 and 2.0, see Table 1).
The authors try to help us resolve this ambiguity by fitting their data with two decision rules and selecting the better fit of the two (current-minus-average) as a benchmark of sorts.
We can get the value of β by fitting historical data of two years.
By fitting the data to two likelihood models in PAML, M1a and M2a, we have a test of whether positive selection, as defined by ω >1, has acted on a gene.
The theophylline transport mechanism was studied by fitting experimental data to five different model equations and calculating the corresponding parameters.
The vitamin B3 transport mechanism was studied by fitting experimental data to five different model equations and calculating the corresponding parameters.
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