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An average expression value for each gene at each time point was generated from the normalized data.
A single secondary point was generated close to each seed point by drawing from a uniform random distribution centered at that seed point.
For the remainder of the time acquisition, the time for each point was generated by adding 38 min. The integration of the CO peak was corrected for T1 with a time delay of 2.0 s and plotted versus time.
Each data point was generated from quantifying all cells in five randomly chosen microscopic fields, totaling 2000 3500 nuclei for C2C12 cells and 300 900 nuclei for primary myoblasts.
The external noise is assumed to be spatially uncorrelated, and so noise at each spatial point was generated by selecting independent and identically distributed stationary random variables at a given time step.
The negative first derivative of each fluorescence acquisition point was generated using the following Excel equation: − dF/dT = SUM (((LOG (X n ) ) − (LOG (X n − 1 ) ) ) * − 1 ) where Xn is equal to a particular y-axis fluorescence value, and Xn-1 is equal to the fluorescence value preceding the Xn y-axis value.
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The current zero-crossing point is generated by an oscillating current.
The topology-based watermark for each marked connection point is generated from selected attributes of its joint plant component.
This process continues in an iterative manner until we get the same design point repeatedly and no new training point is generated.
To overcome the inaccuracy problem resulted from extrapolation and interpolation, feature lines for a query point are generated from the k nearest neighborhood prototypes.
Data for each time point were generated using microglial cell isolated from four different brain specimens.
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CEO of Professional Science Editing for Scientists @ prosciediting.com