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To allow comparisons between methods using sliding windows and using gene based calculations, we reported each score per window into scores per genes.
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Additionally, we report each off-target's GC content and provide a hyperlink to the UCSC genome browser.
While we report each patient's age and sex and bisphosphonate use, we have only described fracture type, T-score, and time since fracture for the group as a whole in order to protect participants' identities.
However, we report each model's accuracy as the correlation coefficient between its output and the true velocity, an intuitive metric that is equivalent to the mean squared error for correctly scaled model outputs ('Materials and methods').
As above, we report each gene's LSM expression level, calculated by the mixed model ANOVAs, and express fold changes at different treatments relative to C levels (within strain; see Figures 4 and 5).
Because we report each complete study in the data analyses, including those with technical failures, the failures may have led us to underestimate the potential of the control approach.
Clearly all three themes overlap and interlink, but we have reported each separately in order to facilitate understanding.
Well, not quite, for later we reported to each other the same experience.
In Table 5 we reported for each considered impact category the percentage contributions of the infrastructure (pavement + guardrail) and of the traffic flow to the whole environmental impact of the system (infrastructure + traffic).
In Table 1 we reported, for each gene of interest, forward (F) and reverse (R) primer sequence and their NCBI accession number, amplicon length and cycle number at the exponential phase.
By using network integration and gene prioritization methods, we reported for each disease the 10 unannotated top-ranked genes, available for further bio-medical analysis.
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