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In this way, one can assign statistical significance to observed differences in functional category expression levels.
In the functional category, expression of genes involved in "metabolism", "cell rescue, defense and virulence", and "energy" were significantly activated.
In this biological category expression profiles of important genes involved in stress signaling systems and other stress regulated genes like chaperons (including dehydrins and late embryogenesis abundant, LEA) and some other important families were analysed (Additional file 4).
In line with this, if we considered the average of inoculated FPKM values for each functional category, expression levels of common DEGs were found invariably much higher in CO441 and the three classes with the higher average FPKM values were: resistance, secondary metabolism and response to stress.
Differential category expression analysis showed significant differences between hNAG-1 mice and WT mice in key pathways in the regulation of metabolism and mammalian lifespan, including down regulation of IGF-1, PI3K, AMPK, and RPS6K families (Supplementary Fig. 7, Table 2).
In considering a model with both main and interaction effects of behavioral category, expression level, and connectivity, connectivity had the strongest effect (glm with quasibinomial residuals: t = 24.5, p < 10−16, for the presence of S. invicta orthologs; t = 32.2, p < 10−16, for the presence of A. mellifera orthologs), with more highly connected genes being more likely to have an ortholog.
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These rules govern only basic and functor category expressions.
Included are each gene's expression bias category, GenBank identifier and accession number, within-category expression rank, four microarray fold change estimates based on different absolute expression analyses, and qPCR 95% confidence interval for fold change.
Interestingly, with all four categories, expression ratios are reduced following TwoRA.
Next, we obtained the log2 fold-change values for leukemia patients with respect to healthy donors and derived the 1492 (mRNA) × 4 (patient categories) expression matrix.
Generally, selection of proteins can be divided into two categories: expression-based selection and function-based selection.
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