Table 1 Validation of pathway activation strategies
From: Dynamic optimization identifies optimal programmes for pathway regulation in prokaryotes
- Test of hypotheses on factors influencing operon sizes for different metabolic pathways across the organisms of the MicroCyc collection31. The first column denotes the name of the pathway, the second column the number of organisms in which it occurs and the next three columns the Spearman’s correlation of the relationship between operon size and the factors considered by hypotheses 1–3. These relationships are: ‘hypothesis 1’: correlation between genes per operon (GpO; of the specific metabolic pathway) and number of protein-coding genes; ‘hypothesis 2’: correlation between GpO and number of rRNA operons; ‘hypothesis 3’: correlation between GpO and average codon adaptation index of enzymes of the pathway. The correlations are highlighted in green if the correlation is significant at a false discovery rate (FDR) of 5% and agree with the prediction of the corresponding hypothesis. Correlations are highlighted in light green if they are significant at a FDR of 20%. Correspondingly, correlations are highlighted in red and light red if they are significant at a FDR of 5% and 20%, respectively, but disagree with the corresponding hypothesis. Only pathways with at least one significant correlation at a FDR of 5% are shown.
