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The model predictions are compared to datasets gathered at GEA Process Engineering's test facility.
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Clinical follow-up studies were compared to datasets from arthroplasty registers.
The resulting dataset (dataset 4) was compared to dataset 3 to determine the best assembly strategy.
The resulting sequences with significant similarities to known Mollicutes genes (dataset 6) were compared to dataset 5.
In compliance with the method described in (Oti et al., 2009), the datasets are not directly compared, instead they are compared to randomized datasets to correct for gene annotation biases.
Data was also verified during the validation process where the results are compared to similar datasets (e.g. Cycle 1), and/or reviewed by external experts to identify and remove invalid data prior to the data release.
Nineteen percent of records could not be linked to latitude/longitude coordinates during geocoding; therefore characteristics of the final geocoded dataset are compared to the original dataset (Additional file 1: Table S1).
The calibrated datasets are compared to ground-based observations, showing an improvement for more than 65% of the sites tested.
The classification accuracies from using wet season, dry season and multi-seasonal datasets are compared to gain insights about the optimal timing for image acquisition.
The mean eigenvalues of the factors extracted from the random parallel datasets are compared to the samples' eigenvalues.
The numbers of detected time series from the datasets are compared to evaluate the robustness of the methods against noise.
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