We comprehensively reviewed the mouse literature, including 827 literature-derived genes, and compared it to human data.
More specifically, we computed the overlap between the MolSigDB gene sets and our set of genes and compared what would be expected by chance if equivalent number of genes were drawn uniformly at random from the background set of genes.
In order to characterize the T helper 1 (Th1) cytokines of llama, we have cloned several llama cytokine genes and compared them to those of other mammalian species.
When we overexpressed 6 newly identified genes (copA, yccT, htpX, yobB, nuoN, and alx) among OmpR-repressed genes and compared their growth rates with that of wild-type under both normal and osmotic stress conditions, only overexpression of yccT showed 40% decrease in growth rate under osmotic stress (Fig. 4a,d).
Phylogenetic analyses were performed on both MAT genes and compared with multigene genealogies using sequences of the ribosomal internal transcribed spacer region, translation elongation factor 1-alpha and beta-tubulin.
We also estimated the copy number for Neandertal genes and compared it with those from three previously analyzed human genomes (SOM Text 12).
To survey whether functionally characterized genes were also arranged in such clusters, we calculated the distribution of functionally characterized genes and compared it with the genomic locations of the QTL clusters (Figure 3).
To validate the data obtained by microarray analysis, we randomly sampled 14 of the 37 candidate genes and compared their expression levels in both Rio and BTx623 by performing quantitative reverse transcription polymerase chain reaction (qRT-PCR; Fig. 2a).
She also condemned the "mixing of genes" and compared her beliefs with previous generations who had "given their lives to push out invaders".
On the basis of the pattern (Fig. 2A), we identified non-, moderandly-, and highly-silenced genes and compared their average noise strength (Fig. 2B).
We analyzed overrepresentation of transcription factor binding sites in promoters of differentially expressed genes and compared the importance of transcription factors for transgenic and tumor gene sets.
