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The data set was analyzed by maximum-likelihood using RAxML31) applying the General Time Reversible model of nucleotide substitution.
Finally, the data set was analyzed with a custom excel procedure for 3D arch analysis.
The data set was analyzed using GSEA, t-test, 2000 gene-set permutations.
The data set was analyzed by the NLREG algorithm, with approximation by Gauss-Newton and Levenberg-Marquardt methods [16] [17].
We did not have to obtain informed consent, because our research was based on insurance claims data and the data set was analyzed anonymously (as regulated by German law in §75 SGB X).
The data set was analyzed according to the BGI bioinformatics protocols for RNA-seq.
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In addition to the base case of 273 samples, systematic subsets of the data set were analyzed by PMF.
Our results showed that the best models depend on the data set being analyzed.
The data set is analyzed using a hybrid and novel k-means cluster centroid-based method for missing value imputation and C4.5, NB Tree and multilayer perceptron for modeling to predict CAD patients.
The best method the one that most accurately constructs the null data will depend on the data set being analyzed.
For estimating the conditional probabilities P(I|D) and P ∼I|D), we calculated the fraction of annotated gene pairs in the data set being analyzed that were found in the positive or negative reference sets, respectively.
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