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The adaptive neural-fuzzy inference system training datasets are extracted from the fuzzy logic controller model developed in MATLAB Simulink and its robustness has been verified experimentally under different measurement noises and disturbances.
The experimental datasets are extracted from two public project websites, namely yeast cycle and human liver cancer projects.
Apart from UniProtKB data which is downloaded using UniProtJAPI, the rest of the datasets are extracted from files provided in ftp servers of each database.
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From these, 16 dichotomous datasets were extracted.
Individual datasets were extracted from accepted articles.
The nature of the atomic planes in both datasets was extracted and analysed.
Surface temperature anomalies at higher spatial resolution than the reanalysis and climate datasets were extracted from the Moderate resolution Imaging Spectrometer (MODIS) products at 0.05° spatial resolution (Supplementary Fig. S14).
All the datasets were extracted from the original data source, reprojected to UTM17N (WGS84) and bi-linearly interpolated to the domain grid system at 1km (Figure 1).
Three hundred fifty-nine historical (123I FP-CIT datasets were extracted from the archives at Sheffield Teaching Hospitals NHS Foundation Trust, for patients scanned between May 2007 and May 20123I FP-CITxcludatasetsges wereextractedcant vascular disease was identifrom in concomithet MRI brarchivess, or where the imateSheffielded significanTeachingcts.
The common genes in these datasets were extracted, resulting in 5337 genes for analysis.
On each case six different large pooled datasets were extracted, with an increasing level of phenocopy error (i.e. 0%, 5%, 10 %, 20 %, 30 % and 45
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com