Sentence examples for occurrence correlation from inspiring English sources

The time of cell body shrinkage and neurite retraction is correlated positively and well with the time of Ca2+ peak occurrence (correlation coefficient r = 0.66 and significance p = 1E-3 betimen time of cell body shrinkage and Ca2+, and r = 0.85 and p = 2E−6 between time of neurite retraction and Ca2+).

For the genome co-occurrence correlation score the probability of identifying functionally related genes is lower than the other methods.

This makes even more remarkable the match discussed above between the preference-occurrence correlations of groups of simulated and native sequences of similar GC content.

Therefore the strikingly high preference-occurrence correlations observed when GC content is close to 0.5 –that reach 99% in non-genic and intronic DNA (below)– may be due to the fact that when GC content is intermediate the primary-structural dynamics are favorable to the occurrence-preference correlation.

We then show that the trinucleotide preferences, the preference-occurrence correlations, and the trinucleotide occurrences themselves, as well as the correlation between GC content and the GCvsAT balance must be to a great extent the product of mutation rates that depend strongly on the bases present at the site preceding and the site following each mutating site.

We found that the anomaly occurrence rate correlation coefficient (R) was highest on the day of the anomaly, as shown in Fig. 5.

Their occurrence in correlation with gene activity and chromatin structural alterations, suggests a role in the regulation of gene expression.

As shown in Figure 4, the performance gain of MIL3D over 5-mer counting is negatively correlated with 7-mer occurrences (Pearson correlation coefficient = −0.42, p-value = 0.07).

Medium reins correlated positively with horses' high neck occurrences (Spearman correlation test, rs = 0.59, N = 19, P<0.01) and negatively with horizontal height (Spearman correlation test, N = 19, rs = −0.51, P<0.05).

To study the seeding mechanism of ionospheric irregularity occurrences, a correlation study has been carried out between the global monthly/latitudinal (m/l) distributions of irregularity occurrences and the deep atmospheric convective clouds in the intertropical convergence zone (ITCZ) indicated by the outgoing longwave radiation (OLR) measurements.

This function calculates pairwise phylogenetic distances among species using an input phylogeny and then compares this to an index of species co-occurrence using correlation.