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Our method first selects the sample-level differentiated genes from each individual sample, capturing genes missed by other analysis methods, ascertains the enrichment levels of associated pathways from each of those lists, and then ranks annotated pathways based on the consistency of enrichment levels of individual samples from both sample classes.
The MCMC method first selects 111 candidate SNPs.
As shown in Figure 5, this method first selects an authentication value x and then uses the Gen function, with x and the registered biometric value w to generate a key v as follows: (1) Gen : v = w ⊕ C (x ), where C is the encoding function of a type of error correction code (e.g., Hamming code).
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The method first carefully selects pocket points and labels them by physico-chemical characteristics of their local neighborhood.
Our method operates by first selecting the reaction with non-zero flux of maximum magnitude from the given flux distribution.
In this method, first, a row (period) is selected at random.
The proposed methods hinges on first selecting the appropriate baseline covariates.
This method first calculates the average color contained in the two ROIs selected in each image.
However, when using LAMBDA method, one needs to first select out the subset of ambiguities that can be reliably fixed, since it is usually impossible to always fix full set of ambiguities.
The simplest method attempted was to first select a subset of markers by using LASSO on the whole data set, and then re-estimate the effects of those markers one-by-one with a simple regression model by the OLS method and perform the standard t-test (including the standard Bonferroni correction for multiple testing).
You can try this method to restart it: First, select explorer.exe from the task list, and click to End Process.
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CEO of Professional Science Editing for Scientists @ prosciediting.com