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For both datasets, a substantial fraction of the compounds (57.7% and 73.5%, respectively) demonstrated single target activity.
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Second, the absence of non-trivial timing signatures for significant parts of both datasets may pose a substantial problem if data is used for detailed timing (or causal) analysis.
In both datasets, less substantial changes in these markers were observed in the golimumab monotherapy treatment group as compared with the golimumab plus MTX groups, indicating a stronger modulation of the overall biomarker response for golimumab treatment in combination with MTX compared with golimumab monotherapy.
This system and the >250 datasets establish a substantial new resource for investigation of how genetic variation affects cellular phenotypes.
The high-throughput datasets contain a substantial amount of missing values, due to experimental limitations or instrument failures.
Nonetheless, BLAST searches identified a total of approximately 9,771 unique protein accessions, indicating that our transcriptome assembly datasets represented a substantial fraction of A. mongolicus root genes.
The results are therefore generalisable to datasets with a substantial proportion of records with incomplete information on names, dates of birth and/or sex.
Results: Our analysis of three publically available datasets showed a substantial improvement in RNA structure prediction by RNAG over extant prediction methods.
Similar to the individual fractional analysis, this direct comparison of the combined datasets reveals a substantial relative accumulation of Group II intermediates across the entire 30S peak in Δ rimP.
Nevertheless, only 25% less genes were identified in dataset A-rep compared to dataset A (Table 1), implying that the lower depth of metatranscriptome analysis performed for dataset A-rep (relative to dataset A) still generated a substantial amount of information with respect to the main microbiome activity patterns (see metabolic pathway mapping below).
This dataset shows a substantial overlap with ours both in terms of binding regions (supplementary material Fig. S3A-C) and target genes (Fig. 3A).
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