Exact(60)
We generated data from an ex-Gaussian distribution that generally fits RT data well (Ratcliff, 1979), for each stimulus response category for one participant (see Table 1 and online Supplementary material).
Particularly, we generated data sampled at f s =4 kHz.
On the other hand, as an optimal best case reference, we considered the complete data situation, that is when r is available and the separation is performed based on X 0. In our simulations, we generated data according to the following models: sources satisfying Example 1 in Section 2. We chose the process a(t) as a mixture of Gaussians as defined in Equation (15), with μ=0.5.
For our analyses we generated data using a BPP comprising 10 levels and an initial rate of 0.05.
Because we generated data in which the association phase was allowed to proceed to equilibrium, affinity data were derived independently from the kinetic.
For each population clustering level, detection probability and proportion surveyed, we generated data sets of observed survey counts for each method.
Releasing the restriction of a constant spike rate, we generated data using a doubly stochastic Poisson process (or Cox process) [14], [35], [96].
Furthermore, we generated data supporting that Muscleblind can induce apoptosis in vivo in imaginal disc tissue and identified a conserved motif in the MblC protein isoform that conferred pro-apoptotic activity in Drosophila cell culture when mutated.
However, during ongoing studies of the interaction of GBS with human blood, we generated data suggesting that the transcriptome of strain NEM316 was significantly different when incubated with the blood of an eighth donor (arbitrarily referred to as donor A) (Mereghetti unpublished data), suggesting inter-individual variability in GBS gene expression.
In this manner, we generated data via sequencing by synthesis.
We generated data with seven similarly responding clusters of compounds, each compound producing seven peaks.
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