This resulted in a small set of 29 genes, 8 of which were negatively correlated with signalling entropy and 21 of which were positively correlated (S4 Table).

An SE score was then defined again as the t-statistic evaluating the hypothesis that the positively correlated genes are expressed more highly than the negative.

This resulted in a small set of 81 genes, 10 of which were negatively correlated with signalling entropy and 71 of which were positively correlated 82 Table.

A Signalling Entropy prognostic score (SE score) was then defined as the t-statistic evaluating the hypothesis that the 71 positively correlated genes are expressed more highly than the 10 negatively correlated genes (after z-score normal-ising the data).

This gene list was slightly shorter than for the discovery set (55 genes, 34 positively correlated and 13 negatively correlated with signalling entropy) but had an overlap of 4 genes, significantly more than would be eXpected by chance (p = 0.012, based on re-sam-pling size matched sets of prognostic genes and assessing overlap).

Genes are separated into those found to positively correlate With signalling entropy and those negatively correlated.

Genes are separated into those found to positively correlate With signalling entropy and those negatively correlated, the genes Which overlap With the discovery set derived set are highlighted in yellow.

Genes are separated into those found to positively correlate With signalling entropy and those negatively correlated.

However for the rest of mutations outside of the active site we observed a weak yet statistically significant positive correlation between thermal stability and catalytic activity indicating the lack of a stability-activity tradeoff for DHFR.

However our observation of a small positive correlation argues against an obligate relation between global protein dynamics and activity for DHFR, at least for the aspects of dynamics that are correlated with stability.

A straightforward explanation for the weak yet statistically significant positive correlation between activity and stability observed in our case might be that more stable proteins have greater effective concentration of the folded (i.e.

It is also important to note that a weak yet statistically significant positive correlation between activity and stability for DHFR can be revealed only when stabilizing mutations are included in the analysis.

There is a weak positive correlation between minimum and maximum melting temperatures (r = 0.30, p 2 10‘4).

Our data, however, paints a different picture for DHFR—of a weak positive correlation between Tm and kcat or kcat/KM (r = 0.46, p = 0.02 and r = 0.41, p = 0.03 respectively) with one notable outlier D27F, where the stabilizing mutation is made right in the active site (Fig.

In particular, host cells with fewer than threshold numbers of receptors do not take up bacteria; above a threshold, uptake is positively correlated with the number of host receptors.

Likewise, our modeling results demonstrate a positive correlation between invasin-mediated uptake of E. coli and the relative abundance of available Bl-integrins expressed by hosts.

In each population, single-cell measurements revealed a positive correlation between the infected host cells and the corresponding level of Bl-integrins (Fig 3C).

Uptake in all the cell lines we tested, most of which are cancer models, was positively correlated with MOI but the amount of uptake was quite variable.

Among the 1594 pairs with positive, nonzero MI extracted from the MSA, 1275 pairs are common to our deep sequencing dataset; we chose these 1275 PR-PR positively correlated pairs to assess our bounding procedure.

Given our bounding procedure, the most positively correlated pairs of mutations are those With the largest MI.

Shown in S7 Fig is the recovery of positively correlated PR-PR pairs identified in [3] using MIp and the recovery is similar to that using MI shown in Fig 5.

Tables 3 and 4 show the strongest 20 positively correlated pairs for Gag-PR and Gag-Gag; the top 1% positively correlated pairs with highest MI values for each region are displayed in S4 and S5 Tables respectively.

2: while their absolute abundances over time are strongly positively correlated , if someone (inappropriately) used correlation to measure the association between the relative abundances of these two mRNAs they would form the opposite view (Fig.

We calculated gb for the relative abundances of all pairs of mRNAs and compared it to the correlations between their absolute abundances (S4 Fig): clearly, the absolute abundances of most mRNA pairs are strongly positively correlated ; far fewer are also strongly proportional.

The few mRNA pairs that are strongly proportional (within the red rectangle) are also strongly positively correlated .

However, the converse is not true: strong positive correlation between mRNAs does not imply that they are strongly proportional.

Networks in Fig 3 show only positive correlation (yellow) and PPI (grey) edges between RTKs and co-clustered effector proteins, with proteins that link to three or more receptors grouped in the center of the graphs (Fig 3).

This graph is similar to Fig 2 except that edges represent Spearman correlation 2 absolute value of 0.5; positive correlations are yellow; negative, blue.

Edges represent Spearman correlation 2 absolute value of 0.5, with positive correlation represented as yellow, negative correlation, blue, filtered to show only co-clustered phosphorylation sites.