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There were no significant differences when all patients in clusters were compared with all patients with non-clustered isolates.
Two gene clusters were compared using the online software anti-SMASH, Glimmer 3.02 and Subsystem Technology (RAST).
The 40 clusters were compared with Japanese geological and geomorphological data and were then reclassified into 12 groups that had different geomorphological and geological characteristics.
To assess potential contributions to host- and tissue-specificity, pathogenesis-associated gene clusters were compared across genomes of eight Xanthomonas strains representing vascular or non-vascular pathogens of rice, brassicas, pepper and tomato, and citrus.
However, the inclusion of the duplicate isoforms of A of D. mojavensis, D. virilis and D. grimshawii increased θ to 0.28 0.38 (P<0.0001), when the A and B clusters were compared.
The optimal clustering parameters were applied to the full GenBank dataset, and the resulting clusters were compared with the organism entries of the respective accessions to screen for discrepancies.
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Instead, representative vectors from different clusters are compared.
The results from two large GPU clusters are compared to the performance of corresponding CPU clusters.
In Figure 7, the CDFs of in the controlled and uncontrolled clusters are compared.
The performance of these clusters was compared to a system using only one CPU, referred below as serial test.
The execution times obtained on different clusters are compared to a single node standard computer having the same technical specifications.
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