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The SNR of the reconstructed signal versus the precision of the time quantizer 1 T C for different over sampling rates is shown in Figure 9. Similarly to Table 1, the number of bits that are needed to encode the difference time between samples for different timer resolutions 1 T C is shown in Table 2.
Moreover, the correlation between differences in gene expression between amplified and unamplified samples for different tumors is weak, suggesting that genes that differ through amplification depend on the sample rather than on systematic changes from amplification.
The number of bits that are needed to encode the difference time of between samples for different timer resolutions 1 T C is shown in Table 1.
To examine the relationship between genetic and methylation divergence, the average number of nucleotide differences per site among samples for different genomic regions was calculated using SNPs obtained from the above step with 50 kb sliding window and a step of 25 kb through the whole genome, which was used to measure genetic divergence.
In addition, technical factors such as time of preparation of samples for different populations have been proposed to explain some of the wide range of differences in gene expression observed between HapMap populations [ 55, 73].
This makes it possible to reuse irradiance samples for different evaluations of the diffusion equation.
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Although single spot urine samples were generally predictive, there were differences in the predictive ability of a single urine sample for different phthalate mono-esters.
Quantitative comparative analysis indicated that distinct conformational landscapes of structural heterogeneity are sampled for different calmodulin-target complexes.
Figure 5c f shows the thermographic analysis of the sample for different illumination times.
Thermographic analysis of the sample for different illumination times (c f).
Thermographic analysis of the sample for different temperatures (c f) T = frac{{({textit{AP}} - 0.142)}}{0.0061}.
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