The resulting weighted ENO schemes are based on cell averages and a TVD Runge-Kutta time discretization.
Importantly, current genomic approaches cannot replace cytogenetic tests since the latter provide important information concerning the proportion of aberrant cells, while the genomic approaches are based on cell averages.
When the number of integration pulses and reference cells are different, the detection probability versus the single-pulse SCR for the BINGS detection and the binary integration parametric detector based on cell-averaging (CA -CFAR (BIPCA -CFAR detection for the false alarm probability ({P_{{f_{text {BGS}}}}} = {10^{- 8}}) are shown in Fig. 9. M is the number of integration pulses.
However, these methods are based on cell-averages in a staggered grid and are thus a bit complicated to extend to multiple dimensions.
Perhaps you have informative data from occasionally closer pairs of labeled cells that might lend support to calculations based on cell number, average arbor size, and cortical volume, etc.
U2OS and S2 cells in G2 phase were binned to 12 and 8 bins based on cell size (FSC-A), respectively, and the average and standard error calculated.
Working at the level of individual cells is important due to cell-cell variability [1], [2], [3], [4], which is masked in assays based on averaging cell populations.
In this paper two improvements are discussed: a simple TVD Runge-Kutta type time discretization, and an ENO construction procedure based on fluxes rather than on cell averages.
To account for differential proliferation, viable cells were enumerated at each time point and changes in metabolite concentrations normalized based on average cell numbers.
