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Negative correlations imply an onset of synchronization for smaller coupling, whereas positive correlations shift the critical coupling towards larger interaction strengths.
We measured G1 length vs Cln3 intensity in cln1Δ and cln2Δ strains and observed that Cln3 c s increase and the inverse correlations shift upward in log log scale as predicted.
Indeed, we found that in suboptimal nutrient conditions, the Cln3- T G1 correlations shift towards right with higher Whi5 tot intensity and A. Similar shift was observed with the MCM marker as a measure of G1 length.
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For P1, the pattern of correlations shifts with development.
Instead, the IONB-QoL short form scale correlations shifted from those with the domains of the EORTC measures to the "global health" dimension of the same QLQ C30 questionnaire.
miR-218, also reported in the above two studies, was not among our most highly positively correlated miRNAs, but did have a high positive weighted correlation
To analyze the functions of those highly correlated (positively or negatively) miRNAs and mRNAs, we generalized the idea of weighted correlation shift from RNAs to groups of RNAs, in this case defined by GO biological processes.
To further validate these new methods, we examined the correlation shift in two other miRNA/mRNA expression datasets: the NCI-60 cell line panel [17], and a panel of primary breast tumor cells [18].
The time correlation shift was a single frame, and all velocities were converted to micrometers per minute.
However, when we examined the distribution of p-values for mRNA weighted correlation shifts, we again found that a number of mRNAs were significantly positively correlated with their regulating miRNAs, while a similar number were significantly negatively correlated (Figure 4A).
In particular, the direction of this correlation shifted depending on the condition of landscape characteristics (Fig. 3).
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