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To explain the observed deformation pattern, we performed both forward and inverse modeling.
Because of the change in headache pattern we performed a new brain MRI, which showed a cystic structure in the pituitary gland.
Using the in vitro evolved sequence pattern we performed a bioinformatics analysis to identify potential novel DYNLL-binding proteins.
Considering that the distribution of FDI and ADM MEPs amplitude data followed approximately a log-normal pattern, we performed the log-trasformation to improve their gaussianity, to stabilise variances across conditions and to reduce outliers effects [49].
To confirm the differential expression pattern, we performed qRT-PCR to validate the expression of miR-126, miR-222, and miR-345 in the validation cohort samples with or without CNS relapse (N = 3 and N = 26, respectively) as shown in Figure 2D.
To investigate its local expression pattern, we performed in situ hybridization experiments.
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To formally validate these patterns, we performed a series of post-hoc randomization analyses to assess the correlation between genetic distance patterns and latitude [24].
In order to test the hypothesis of preservation of patterns, we performed computer simulation experiments in which we allowed for random mutations of current genomes during three billion years.
To further address the reliability of these patterns, we performed repeated adhesion assays on ten cell lines on two separate days.
To find regulatory networks that associated with distinct chromatin patterns, we performed an unsupervised homogeneity based cluster analysis to obtain nine functional feature modules.
Second, to examine whether or not additional areas beyond AIP and LOC would display interesting activation patterns, we performed voxelwise contrasts between conditions in our group data averaged in stereotaxic space [37].
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