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The less complex bimodal distribution, with equally weighted modes, was favored by the data using AIC; it is the basis for the bimodal results presented in Table 1.
We also checked the GTR + Gamma model for potential violations induced by the data using posterior predictive tests implemented in PhyloBayes 3.3 (Lartillot et al. 2009).
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Noise introduced by this manual tracing was accounted for by smoothing the data using a Gaussian filter.
A linear relation was obtained by fitting the data using Origin.
For the semantic web, such formalisation is typically performed by encoding the data using eXtensible Markup Language (XML).
The 50% inhibitory concentration (IC50) values were calculated by fitting the data using a nonlinear regression algorithm (GraphPad Software).
The kinetic rate constants were obtained by fitting the data using the Applied Photophysics SpectraKinetic Workstation v4.56-1 v4.56-1
We attempted to overcome this by analysing the data using different imputation methods for missing data.
The Ki values were determined by fitting the data using the EnzymeKinetics module in SigmaPlot.
This bias was largely corrected by standardizing the data using the Loess regression method.
PK parameters were determined by fitting the data using a one-compartmental model equation.
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