To determine if there were any existing data regarding these Salmonella mutations in animal models we performed an extensive literature search over "fluoroquinolone", "Typhimurium", "gyrA", and certain specific mutations of interest (over 400 studies met parts of these criteria).
In order to test the influence of ethnicity on the performance of the models, we performed the following two analyses: Upon building separate classification models for Kuwaiti natives and Asian expatriates (table 1 ), we find that the classification algorithms are not performing equally well for the two ethnicities.
To validate the models we performed three experiments.
In an effort to provide additional geophysical constraints on these models, we performed a local, regional, and teleseismic tomographic travel time inversion for the lithospheric and upper mantle velocity structure and earthquake locations beneath the Alboran region in an area of 800 x 800 km^2.
After localizing regions of interest (ROIs) in FFA and VWFA using general linear models, we performed spatial pattern analyses to examine both within- and cross-condition classification in these ROIs.
To validate and assess our models we performed tenfold cross-validation and nested cross-validation protocols.
For both models, we performed nondimensionalization to identify possible groupings of variables into classes corresponding to they timescales on which they evolve.
In order to validate accurately the statistical models we performed the nested cross-validation protocol as described by Ruschhaupt et al. [20].
Before constructing each of the statistical models, we performed a visual inspection of the predictor response relationship between the covariates of interest and the outcome variable using locally weighted scatter plot smoothing (lowess) [22].
Motivated by the aforementioned demands for AMIP-type experiments with high-resolution global models, we performed present (Kodama et al. 2015) and future (Satoh et al. 2015) climate simulations using the 14 km grid spacing NICAM.
To determine what order of magnitude effect a user's choice in n, k dataset will have on radiative transfer models, we performed a set of simple models on absorption cross-sections, total flux and spectral energy distribution.
