Sentence examples for multiple samples based from inspiring English sources

Many methods, including the BRLMM-P algorithm developed by Affymetrix [ 3], employ clustering of multiple samples based on the contrast between allelic probe intensities.

Key steps in sequence signature methods include the counting of frequencies of all k-tuples to compose the sequence signature vector for each sample, calculating the dissimilarity measure between samples based on their sequence signature vectors, and analyzing relationships between multiple samples based on dissimilarities of all sample pairs.

Therefore the sample size was also calculated based on this demonstrated difference of 7% and examples of multiple sample sizes based on varying assumptions are illustrated in Table  1.

Because the 3'-ends of viral genes are associated with the least variance among triplicate probes based on mapped P-values (data not shown), the relative levels of individual transcripts across multiple samples were assessed based on the data from 10 probe sets (in triplicate) at their 3'-end.

Actually, one can find that the real absorbed power threshold of each sample is almost identical regardless of laser incidence from the substrate or film side if one calculates the absorptivity of each sample based on multiple-beam interference of multiple layer films for the two incidences of each sample from the substrate and film sides.

The sampling based Monte Carlo Analysis (MCA) is adopted to carry out multiple regression analyses between selected input parameters and output indices.

Gibbs sampling based posterior inference is developed.

Because the sample was based on those who self-selected for participation rather than a sample based on probabilities, estimates of sampling error cannot be calculated.

Another important future direction to extend MixClone is to implement joint analysis based on multiple samples, which is supported by PyClone and PhyloSub [ 5, 7].

We also showed how to construct confidence intervals for p j, μ j, and σ j (1 <= j <= k) based on multiple samples from the same population, even if those samples overlapped.

We address a number of methodological issues, including how the number of components selected depends on the sample size, how the choice of model selection criterion influences the results, and how estimates of mixture model parameters based on multiple samples from the same population can be combined to produce confidence intervals.