Sentence examples for most negative correlation from inspiring English sources

Regarding employment, the most distinguishing hours are 1am (most negative correlation) and 12pm (most positive correlation).

The most negative correlation we calculated was between ORF and 5'-UTR length.

However it is noticeable that the most negative correlation is from chicken (-0.95, -0.96) – figures in brackets are for 500 kb windows (masked, unmasked) – which has a body temperature of around 40 42°C.

For example, "the Connectivity Map" (CMAP) project developed a reference collection of gene expression profiles by treating cultured human cells with small molecules, and searched for the compounds that have the most negative correlation with the disease's gene expression profiles as the potential candidate [ 7, 8].

Note also that among the 10 IFE sub-scores, the variables that reflect financial market freedom (Fin, Ivst) have the most negative correlations with IR.

The most positive correlations (r = 0.87 to 0.91) between milk FA concentrations and methane output were observed for saturated FA from 6 0 to 16:0 and for 10 1, and the most negative correlations (r = −0.86 to −0.90) were observed for trans-16+cis-14 trans-16+cis-14 trans-16+cis-14 18 1 16:1; and trans-12 18:1.

The same is true of the means of the 100K most negative correlations in cardiac and full cohorts (p<1e-16), as well as for both positive and negative genecentric distributions (p<1e-16).

The most negative correlations to the clinically important agent VP-16 were: cisplatin (-70); BCNU (-68); camptothecin (-38); bleomycin (-33), gemcitabin (-32); ara-C (-21); topotecan (-17); melphalan (-3); and to the other main drug in SCLC treatment cisplatin were: doxorubicin (-70); VP-16 (-70); VM-26 (-69); mAMSA (-64); taxotere (-58); taxol (-58).

The most significant negative correlation was between miR-98 and SERBP1 (qFDR = 3.97×10−7), which was ranked 111th of the most significant pairs.

This analysis revealed that the most significant differentiation (most negative Pearson correlation) across all treatment groups, was the sickle versus healthy RBC phenotype, with 201 phosphopeptides being up-regulated in SS vs AA RBCs at a fold-increase of >1.75.

In order to create a gene set that best predicts the pharmacological response to IFNß we selected those genes whose expression shows the most significant negative correlation between baseline and biological response (with a cut off of p<0.01 and R<−0.65).