Network Dynamic Analysis Figure 2. Bimodal distribution of transcription rate and mRNA abundance profile similarity between S. cerevisiae genes with bacterial orthologs. Distribution of correlations for mRNA abundance (A), as well as the distribution of correlations for corresponding transcription rate profiles (B), under oxidative stress are shown. doi:10.1371/journal.pone.0009908.g002 Thus, steady-state mRNA abundance does not always correlate well with transcription rate. For example, ,41% of S. cerevisiae genes exhibit lower than 0.5 correlation coefficients between their mRNA abundance and transcription rate profiles in the glucose- to-galactose shift experiment; ,8% exhibit significant negative correlation [3]. Another type of discrepancy, a time-delay effect, was observed in this study (Figure 4). Shown in figure 4A is a correlation matrix of the datasets from the osmotic stress experiment. The datasets contain 6 columns (time points) for transcription rate (TR) analysis and 6 columns (time points) for steady state mRNA abundance (RA) analysis; a column contains a reading for each gene at the corresponding time point and analysis. The correlation matrix display pair-wise Pearson correlation coefficients among the 12 columns. Each column correlates perfectly with itself as shown by the diagonal in figure 4A. Part of the matrix that correlates TR columns with RA columns was enlarged in figure 4B. TR columns display better forward correlation. The 1st TR time point (TR1) correlated better with the 2nd RA time point (RA2) than with the 1st RA time point (RA1). Similarly, The 2nd TR time point (TR2) correlated better with the 3rd RA time point (RA3) than with the 2nd RA time point (RA2); the 3rd TR time point (TR3) correlated better with the 4th RA time point (RA4) than with the 3rd RA time point (RA3); and etc. Consistently, the RA column correlated better backward; the 6th RA time point (RA6) correlated better with the 5th TR time point (TR5) than with the 6th TR time point (TR6). Thus, a time-delay effect, as our analysis suggested, exists from TR to RNA. D. Transcription rate correlates better with functional relatedness Transcription takes time. The delay effect discussed above was therefore biologically meaningful. Moreover, it confirms the quality of the datasets and the way they are processed in this study. Figure 3. Explanation of the bi-modal distribution by simulation analysis. Distribution of correlations generated from simulations with s = 10 (A) and 40 (B) are shown. doi:10.1371/journal.pone.0009908.g003 PLoS ONE | www.plosone.org 4 March 2010 | Volume 5 | Issue 3 | e9908