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In Table 1, the predicted expression levels of highly expressed degradation genes are reported.
The predicted expression levels of several other highly expressed genes of specific regulatory proteins are listed in Table 1.
This will result in an alternative model (say MU) whose predicted expression for each of the 37 CRMs is very close to the predictions from the baseline model.
These paths describe a set of mutations wherein the predicted expression pattern does not significantly vary at any point along the path.
Single-gene constructs pUb1-D-T and pUb1-R-T were made with Dm-AMP1 leader peptide, in which the predicted expression product consisted of the Dm-AMP1 (Jha et al. 2009) and Rs-AFP2 mature proteins, respectively (Fig. 1a).
Again, both predicted expression patterns were supported by real-time RT-PCR experiments.
We plotted disease rates against size, fit quadratic models to the data and differentiated the predicted expression to determine where rates peaked.
The predicted expression (dashed line, panel 1) closely approximates the observed (red line, panel 1) dynamic gene expression for LPS; showing an initial amplification followed by gradual decline.
Overall effect of changes in expression was visualized using color gradient for overlay of predicted expression changes onto pathway diagrams (Supplemental Figures).
The PAttern based Correlation (PAC) algorithm is then used to calculate the predicted expression level of each exon (or probe set).
We then identify outlier exons by subtracting the predicted expression level of exons from their measured expression level, with values equaling zero when the measured expression level of an exon was similar to its predicted expression level (formulated in detail under Methods).
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