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In order to predict the product distribution, we have proposed our own chain growth model and fitted parameters to experimental data from Yang et al. (2016).
The experimental results were analysed by means of a dynamic one-dimensional heterogeneous PFR model, and fitted by multiresponse nonlinear regression to provide estimates of the rate parameters.
Althaus presented a SEIR mathematical model and fitted the model to the reported data of infected cases and deaths for Ebola virus disease in Guinea, Sierra Leone and Liberia [17].
In addition, we simulated data under the 1PL, 2PL, and 3PL model and fitted the 1PL to all three data sets, the 2PL to the latter two, and the 3PL to the latter only.
The positional placement of geranylpyrophosphate and a single magnesium cation were extracted from the E. coli UbiA model and fitted into the model of UBIAD1.
We therefore modified this binomial model and fitted instead a beta-binomial distribution (seeSection 3) to account for the over-dispersion in read count ratio.
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It was formulated as a mathematical model, and fits the known experimental data.
Walters conceived of the model and fit it to the data.
Calculating the PI from the original model and fitting this single predictor to the validation data.
We added (10) as the association model and fit a Heagerty and Zeger's model with cutpoint-varied regression coefficients.
Biosensor data were collected, modeled and fitted by means of BIAevaluation 3.1 software (Biacore, Uppsala, Sweden).
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