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These methods may generate sequences that may not be necessarily feasible [12].
In fact, integration of these two methods may generate some distinct benefits.
The comparison between the MAFU and traditional method shows that both methods may generate some ranking of project alternative based on the average utility value (i.e., the middle bar of the box plot), but the traditional method generates an overlapping confidence interval and min max ranges among the project alternatives, which complicates the decision marking and alternative selection process.
Although several studies demonstrated the presence of moderate to poor correlations between microarray and proteomic analyses [13], [14], [15], [16], implementing both methods may generate complementary and more informative data that cannot be obtained by either method alone.
Although it is difficult to judge which system offers more biologically relevant results, great caution should be taken when interpreting the interaction data as both two-hybrid screenings as well as biochemical methods may generate false positive and false negative interactions.
Each run of optimization methods may generate different results, depending on the initial settings.
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Note that although co-expression based methods may
The proposed method may generate uniformly distributed sparse sampling points in the flat areas and necessary higher density in the high curvature regions.
However, using probabilistic method may generate time delay in mobile localization environment.
Presented method may generate one joint solution for each solution from JI SI) and JII SII).
This method may generate measurement error correlated, almost by construction, with the regressors of interest.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com