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The current work offers a new way to virtually screen active components of herbal medicine, and it might be helpful to accelerate the process of new drug discovery from natural products.
In this paper, we introduce a variable selection procedure, called the PLSVS method, to screen active effects in mixed-level SSDs based on the variable importance in projection which is an important concept in the partial least-squares regression.
We cannot assume that more data implies people playing, due to how the game works: the user has to keep the screen active for the game, and most of the game data-transfers are text-encoded packages of information (e.g., position updates about nearby pocket monsters, in JSON format).
In the present study, we also used affinity biosensor technology to establish the platform to screen active ingredients from traditional Chinese herbs targeting lipid-A.
In this study, we used serum free medium to mimic the low nutrient environment to screen active compounds from the Garcinia compounds library.
In order to assess the effects of these candidate components on the growth of CTLs, a fractional factorial design was employed to screen active factors for cell growth, followed by response surface designs to optimize their concentration.
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This case will show us how to use TCMSP for screening active ingredients, identifying drug targets and diseases.
A new strategy for screening active factors is proposed and named as contrast-orthogonality cluster analysis (COCA) method.
The conclusion emerging from all schemes of experiments (screening active compounds against truly inactive, DUD, and ZINC decoys) is that high coverage of the conformational space of the receptor models leads to more effective screening.
A Bayesian variable selection strategy which combines the advantages of the componentwise Gibbs sampler (see Chen et al., 2011) and the functionally induced priors (see Joseph and Delaney, 2007) is presented for screening active effects in SSDs.
We are currently screening active site inhibitors in this assay to determine what structural properties might favor inhibition of the initial processing step and how these properties relate to their ability to block protease activity and protease dimerization.
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