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The four-stage parameter estimation method was vital to the success of the analysis.
We discuss in the following sections the benefits of the experimental design, factors that influenced the success of the analysis activity, and how our results will guide development of new strategies to increase learning in our large classrooms.
Although we are aware that the intensive sampling described here may not always be feasible, we would like to note that including field epidemiological information to guide the computational algorithms used to infer relationships among populations was key to the success of the analysis and should become a common practice when attempting to reconstruct the invasion history of an exotic organism.
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The technology has been used with success for the analysis of transcriptomes of several plant species including Cajanus cajan [ 20], Arabidopsis thaliana [ 21, 22], Medicago truncatula [ 23], Zea mays [ 24], Hordeum vulgare [ 25], Lycopersicum esculentum [ 26], Camellia sinenis [ 27], and Cicer arietinum [ 28].
Although ISOpure has demonstrated success for the analysis of lung adenocarcinoma and prostate tumor samples, future development may be needed to incorporate the possibility of multiple sub-types in a single patient cohort.
Biochemical analyses are required to demonstrate the functionality of these motifs, especially in the absence of an appropriate validation dataset, but the success of this analysis suggests that significant components of the AHR transcriptional network remain to be elucidated.
The success of this analysis approach is based on the use of a unique metal film planar-support that has a total thickness that is amenable for IRRAS analysis while providing an ideal surface conducive for surface-enhanced Raman scattering experiments.
The success of this analysis strategy is further demonstrated by other biological systems [45], [46].
While the propensity analysis is a powerful tool for pair matching groups to remove possible hidden confounders in the data, by its very nature it is not possible to validate fully the success of this analysis.
However, success of the inverse analysis greatly depends on the initial guess of model parameters and its analysis technique.
However, the success of the statistical analysis strongly depends on the total size of the data set characterized by the specific spatial coverage, spatial resolution, temporal resolution, and overall length in time.
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