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On the other hand, real-time DNA microarrays are capable of taking multiple temporal samples of a binding process [7 9].
Two general approaches to estimating Ne were explored: 1) analyzing single time period population samples, and 2) analyzing multiple temporal samples from the same population.
Multiple temporal samples within each simulation are not entirely independent, but (as shown in Results) overall replication was more than sufficient to produce robust measures of central tendency.
From the original dataset, we removed all but one set of sequences in cases where there were multiple temporal samples from a single host.
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To estimate Ne based on multiple temporal sampling periods for the Greenland population, we used MLNE 2.3 while assuming 1) a closed population (NeCLOSED), and 2) accounting for immigration from a potential source population (NeOPEN).
In MSE analysis (Costa et al. 2002, 2005), each single-trial time series is downsampled to multiple temporal scales and sample entropy (SE) (Richman and Moorman 2000) is calculated for each scale.
Nonetheless, if the number of individuals sampled is low (≤25), the temporal method might be a better option, especially if multiple generations pass between temporal samples.
In wild populations, especially those that are actively managed, there are often multiple factors that simultaneously act on a population, sometimes in ways that confound simple interpretation, especially if temporal samples are separated by many years.
Recently, researchers have become interested in hierarchical architecture, such as multiple levels, and multiple temporal and spatial scales.
Memory formation has multiple temporal phases that engage specific molecular, cellular and systems mechanisms [1], [2].
Furthermore, accurate synchronisation with sounds separated by more than 8 s demonstrate that multiple temporal levels are employed for facilitating temporal organisation and integration by the human brain.
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