Sentence examples for comparable clusters from inspiring English sources

The pattern of concerted evolution is complex, however, as sequence similarity within clusters is uncorrelated with gene order and orientation, and no comparable clusters occur within similarly compact arrays of the RR-1 group in mosquitoes or in either group in D. melanogaster.

We also found undescribed but comparable clusters of regulation in previously reported transcriptomic analyses of intracellular bacteria, including Rickettsia sp. and Listeria monocytogenes.

From these data, we easily observed undescribed but comparable clusters of differentially expressed genes in different conditions for Rickettsia sp. [15], [16], [28], [50] and T. whipplei [13] (Figure 6 and Table S9).

For comparable clusters, k-means gives better values.

In fact, the EI effect on pBLS is lower for clusters with OBP genes than for random samples of 31 comparable clusters (P = 0.034).

We found that the EN effect (path coefficient from EN to pBLS) is higher for clusters including OBP genes than for random samples of 31 comparable clusters (P = 0.035), whereas the EI effect is lower (P = 0.034).

The experiment has shown that our proposed method has achieved a comparable clustering quality compared with the baselines while being significantly faster than them.

It could be that a comparable cluster of fiction is emerging now – Britain's most-admired original TV drama last year, Doctor Foster, also centred on a wronged wife driven so crazy that she eventually attacked her husband.

Experiments we have conducted show that lexical clustering phase of I-TWEC can produce results with comparable clustering quality in a fraction of the time required by the baseline methods which use Longest Common Subsequence and Suffix Tree.

We have also experimented with a k-means document clustering as well as a state-of-the-art word-based suffix tree clustering algorithm and the results show that I-TWEC outperforms the state-of-the-art in terms of time with comparable clustering quality.

Thus it can be determined that k-means or fuzzy k-means offers better performance and scalability with comparable clustering results as discussed in the next section.