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On the basis of the I V measurements, the readout margin and power dissipation of a cross-point array were calculated depending on the existence and characteristics of the selector.
The intensity data on the array were calculated from the images generated by the BeadArray Reader (Illumina).
Copies of the DYZ1 array were calculated by extrapolation of the standard curve obtained with known copies of the recombinant plasmid.
For the disruptant dataset log2 ratios against a virtual median array were calculated and these ratios were then z-transformed within each microarray prior to network inference.
For hybridization control the signals of the controls (BioB, BioC, BioD, and Cre), the scale factors and the background intensities of each array were calculated and compared.
After passing array quality control, expression values for each array were calculated using the robust multi-array average (RMA) algorithm, (Affy package version 1.22.0) [ 30] available from the Bioconductor project (http://www.bioconductor.org) for the R statistical language (http://cran.r-project.org).org
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The evaporation rate of each particle in an array is calculated as a function of the particle separation.
Then λ i (t) is normalized and the standard deviation σ of the normalized array is calculated.
Then the difference array was calculated by taking the sum of derivative value along each detector pixel.
The exact reflection and transmission coefficients of the array are calculated by means of a multiple scattering formalism taking into account all the interactions between the cavities.
The optimal dispatch strategy, as well as the optimal sizing, especially of the PV array is calculated simultaneously by linear programming.
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