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The data was converted using PRIDE converter [80] (http://code.google.com/p/pride-converter). Feature predictions for protein sequences in the proteomic output were automated using local installations of several software packages and Perl scripts.
The data was converted with the PRIDE Converter (Barsnes et al., 2009) (http://code.google.com/p/pride-converter).
The data was converted using PRIDE Converter http://code.google.com/p/pride-converter[ 58].
The data was converted to VAMAS format and processed using CasaXPS software.
The data were band-passed between 0.01 0.5 Hz using a zero phase-shift Butterworth band-pass filter to remove long-period drift and high-frequency noise, then the data was converted to a ground displacement with a sampling interval of 0.2 s.
The data was converted to percentage reaction values (milliequivalent percentages), and expressed as the difference between alkaline earths (Ca + Mg) and alkali metals (Na + K) for cations, and the difference between weak acidic anions (HCO3 + CO3) and strong acidic anions (Cl + SO4).
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The data were converted from vector into raster.
However, after preprocessing, the data are converted to a self-describing hybrid XML/Binary format.
Hence, the sooner the data is converted to the digital domain, the better the technology can be used.
Once the data are converted into the expression of particle volume, the maximum value is found with 1.9 μm particles instead of nanoparticles.
In the process of analyzing the data, the pixel sizes of all the data are converted (layer stacking and re-sampling) into consistent same size of 15 m.
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