Sentence examples for significantly comparative from inspiring English sources

Exact(1)

To determine whether measurements of IOP obtained from the three instruments, differed significantly, comparative plots of the NCT and GAT, the ICare and the GAT and the NCT and ICare were plotted as shown in Figures 2a), b) and c) respectively.

Similar(59)

Here, we use a significantly expanded comparative dataset, a recent Bayesian inference of primate phylogeny, and the latest advances in phylogenetic methods to investigate how the spatiotemporal distribution of females influences the number of males in primate groups.

EST-SSRs reported here can significantly advance comparative linkage analysis among Rubus species.

Estimated marginal means revealed that women gave significantly lower comparative risk judgement of gum disease than did men (-.39 versus -.19, p < 0.05).

In addition, the current data can contribute significantly to comparative genomics in general and gene expression and regulation among different mouse tissues.

Significantly, a comparative genome-scale transcriptional analysis of two T-cell subsets (CD4+ and CD8+) against each other and against the naturally mixed population (CD3+ cells) remains unexplored.

At this stage, we do not know what genes are contained in the insertions and what genes are involved and deletions, but localization of these insertions and deletions on the genome will significantly facilitate comparative studies among the typhoid agents.

Significantly, our comparative analyses of cpDNAs revealed that Pinaceae and cupressophytes each lost a different IR copy, which suggests that in the two groups, loss of an IR copy is homoplasious rather than synapomorphic.

Even when the accuracy per genome is high, the aggregation of errors among groups of genomes can produce a large fraction of flawed results and significantly undermine comparative analyses.

Significantly, a comparative analysis of the programs of two T-cell subsets (CD4+ and CD8+) against each other and against the natural CD3+ population remains unexplored, and would likely yield significant new information.

Experimental results clearly demonstrate that RMI significantly outperforms comparative methods in terms of Normalized Root Mean Square Error (NRMSE), especially for datasets with large missing rates and less complete genes.

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