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As the cell line intrinsic properties may obscure expression patterns related to PIP gene expression, we appreciated the range of biological variability through unsupervised clustering of the entire gene expression profiles (Figure 2).
An important aspect of any toxicogenomics validation strategy is the need to measure the range of biological variability of gene responses for a given test system.
This is an important issue for toxicogenomics, as studies conducted on cell culture populations demonstrate a wide range of biological variability in gene expression measurements for individual cells under both baseline and challenged conditions (Kuang et al. 2004).
With this range of biological variability in mind, we searched for a "lever" that can vary the shape (height, timing, and "shoulder") of the acute phase viral load trajectory without changing setpoint viral load.
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Despite the value of 1/ ϕ falls in the range defined for stance phase in the literature (60 62%, i.e., 0.60 0.62), the fact that stance/swing is not different from ϕ needed to be statistically tested on data specifically collected in a sample of healthy subjects of both genders and with a wide age range for taking into account of biological variability.
In contrast, most (4 of 6) of the reference genes were disqualified as appropriate reference controls based on fold changes that exceeded this range at more than one contiguous time point with GAPDH and TfR displaying marked increases (>4-fold) clearly indicative of biological variability.
A major difficulty in the interpretation of test results is that of biological variability.
Under these conditions, most (4 of 6) reference genes tested were disqualified as suitable reference genes as expression exceeded the delimiter range at more than one contiguous time point with TfR and GAPDH displaying marked increases and α-tubulin marked decreases in relative expression clearly indicative of biological variability.
How about "cell to cell variability" instead of "biological variability"?
We found no significant increase in variability among biological replicates indicating that pools of 25 individuals captured the majority of biological variability (Additional File 1).
To minimize effects of biological variability, proteinuria on Days 1 and 2 was averaged.
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