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Therefore, in order to interpret the compositional data based on isolated samples in a physiological context, it is necessary to compare the in vivo 30S intermediates obtained under different experimental conditions.
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Expression data based on oligoarrays for isolate Lmb v.23.1.3 previously obtained [ 9] and deposited in the gene Expression Omnibus under accession code GSE27152 were used.
We observed that the isolate FSC186 was classified as belonging to MLVA group B3 by Johansson et al 2004, but our data based on slowly mutating canonical SNPs and INDELs indicate that the isolate belongs to group B1.
First, we isolated the collectives of the 10% smallest and the 10% tallest trees in our data based on the stem volume.
For example, searches in PlasmoDB can be used to identify genes (antigens) with increased immunogenicity based on available metadata followed by defining the subset of these genes that are under diversifying selection (containing a high number of non-synonymous mutations) based on isolate sequencing data.
Cluster designation was based on isolates showing ≥80% relatedness.
Nonetheless, according to Kovalenko et al. [42], molecular modeling calculations, based on the isolated propanoate ion, were in agreement with experimental data.
Our data are based on invasive S. enterica Typhimurium isolates collected in a nonsystematic health care facility based approach and do not include noninvasive strains of S. enterica Typhimurium.
Our data show that, based on lesion size, isolate #68, but not #46, was significantly (p<0.01) more aggressive on leaves from cv. 'Katahdin' compared to the other isolates.
Because big data is based on... well... data.
The data varied based on geography.
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