Sentence examples for both data sets use from inspiring English sources

In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals.

Phylogenetic relationships were reconstructed for both data sets using Bayesian analyses and maximum likelihood (ML) searches (Figure 1).

On both data sets used in this study, TMMTOP_RA achieves better performance when multiple sequence mode is used as input.

We were able to achieve high sensitivity (on a par with the manual annotator) on both data sets using our proposed sampling and cost-sensitive methods.

Both data sets used a pool of normal samples as a common baseline sample, respectively derived from human and dog samples (see Methods).

All significant differentially expressed genes were identified in both data sets using LIMMA (Array) and EdgeR (RNA-Seq) with a FC > 2 and a FDR < 0.05.

Tree reconstruction for both data sets used the CAT profile mixture model with four discrete gamma categories and the exchange rates fixed by the LG model.

jModeltest (Posada 2008) was used to find the best substitution model and associated parameters for phylogenetic analysis in both data sets using the Akaike (Hirotugu 1974) and Bayesian (Schwarz 1978) information criteria.

Pearson's correlation coefficients were calculated in Microsoft Excel and P=0.001 levels of significance were calculated for both data sets using the formula: R=(U−1)/(U+1), where, Z 0.001)=3.09, N=54, or N=111.

However, after combining and analyzing both data sets using the two different methods, only 722 (14.8%) of genes in the genome were found to be diurnally regulated or light inducible, and 448 genes (9.2%) could be classified as circadian controlled.

We calculated absolute annual trends for both data sets using a general least squares regression of 5-month box-car filtered (i.e., median of ± 5 months from the center date), deseasonalized monthly mean values following Zhang and Reid (2010).