No dataset was analyzed in the current study.
The entire dataset was analyzed with SPSS 22 (Landau and Everitt 2004).
The alignment dataset was analyzed using maximum likelihood (ML), maximum parsimony (MP) and Bayesian methods.
This dataset was analyzed by principal component analysis and projections to latent structures by means of partial least square.
This multi-resolution dataset was analyzed using Principal Components Analysis (PCA) to identify the dominant variance structure in the dataset.
For IDW method, after normalization of dataset, the power function was optimized and the cross-validation dataset was analyzed.
Prior to analysis, the dataset was analyzed for missing data (see Table 1 for variable level missing data percentages).
This dataset was analyzed in detail to determine the wave energy potential to enable a reliable and optimal design of wave energy conversion devices in the Black Sea.
The combined dataset was analyzed with MrBayes 3.1.2 [36], [36].
The combined dataset was analyzed under maximum parsimony, maximum likelihood and Bayesian search criteria.
First, the Novartis expression dataset was analyzed to assess human gene expression evenness across tissues.
