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However, SFP marker approaches require multiple parental hybridizations for permutation testing to identify viable SFPs among the features on a given array [3], [11].
In addition many of these modification approaches require multiple manipulations steps, cloning and modification of the protein encoding gene, expression and incorporation of the affinity label or functional group, and finally attachment to the solid support.
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Furthermore, we note that our method is computationally more demanding than common methods that rely on standard supervised classification approaches, requiring multiple mixed integer optimizations.
Shared database, separate schema: This approach requires multiple tenants to be accommodated into a single database.
This approach requires multiple views in order to obtain a smooth cost function that can be optimized robustly.
This approach requires multiple frames and varied scene geometry such that sufficient corresponding edges can be found and a smooth cost function can be obtained.
While these high-throughput methods are powerful, there are practical limitations: DNA microarrays are limited to detecting genes for which allelic variants have already been characterized and may miss emerging mutations; the PAML-based approach requires multiple genomes of phenotypic variants of the same species, which are not always available.
Thus, this approach requires multiple repeats to yield the percentage of positive reactions for every dilution.
As this approach required multiple comparisons, a conservative Bonferroni correction with an adjusted α level of p=0.0033 (0.05/15 tests) was used.
The pseudo-CNL approach, requiring multiple injections, is more time-consuming and susceptible to instrument variability than traditional CNL.
However, such an approach requires multiple testing of the same individuals, which imposes logistic constraints on comparative analyses like our present study.
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