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For example, the differences between the dataset in DRTF and the results of Xiong et al. [ 3] are mostly because of new annotation in the latest version (Release 4) of the TIGR database that uses a broader definition of TFs.
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As for the degree distribution, while all analyzed datasets present similar general shapes, their range and their fine shape differ due to differences between the datasets, the construction scheme, the size, or the time span of the collection period.
The differences between the datasets could result from the criterion used by different groups.
The main differences between the datasets were in their patterns of regional bias, which are different in each dataset.
While this work shows that it is possible to understand discrepancies between MSU/AMSU datasets there are still important differences between the datasets that need further scrutiny.
Results show that there are significant differences between the datasets, even though they were essentially all interpolated from almost the same climate databases.
There are larger differences between the datasets in some regions, such as the Rocky Mountains of Northwest Wyoming and Southwest Montana, where the Landsat dataset indicates 54% less PISC area.
For the PGTAZ/rocking correlation, there are only slight differences between the datasets.
The differences between the Datasets were motivated by the continuous need to improve the procedures for subjective image quality testing.
The background data and the experimental data were compared, and differences between the datasets were tested for significance using multivariate analysis at the 0.001 significance level.
Both contain >2000 SNPs with a low p-value for association in at least one GWAS, although there are several differences between the datasets which are discussed below.
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