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The biological responses described here and our analysis by modeling using reported values for the biophysical parameters [54] [61], (Supporting Text S1; Figs.
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The Excel optimization add-in, Solver, was used to calibrate the model using reported National Health and Nutrition Examination Survey NHANESS) prevalence data 1 as described below: Populations in a given health state (incident HCV, cured, F1, F2, etc).
Our micro-contact data contained detailed inter-participant contact patterns but lacked data about the threat of infection from non-participants, which we modeled using reported H1N1 incidence data for the same time and province as the contact data [ 8].
We controlled for ETS in models using report of living in a home with a smoker because data were missing less frequently.
Model validation using reported pheromone trap catches of male moths agreed with the simulated appearance dates of adults of the overwintered generation.
Model outputs were validated using reported UCG trial results.
We also compared the performance in terms of computing time for all the models we used, reported in column 3 of Table 3.
Calculating the "real" rate of foodborne illness requires development of models that use reported cases as a starting point to estimate underlying disease rates.
To explore the effects of several variables and their combined effects on survival, multivariate Cox's proportional hazards regression models were used (reported as Hazard Ratio (HR) with 95% confidence interval).
We confirmed the feasibility of our model using previously reported expression data on the MS2 coat protein.
We confirmed the validity of our model using previously reported expression data, and further confirmed our model experimentally using computationally designed synthetic RDS sequences ligated to luxR.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com