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To identify such strongly varying descriptors, we generated multiple conformers of all odorants using MOE's stochastic conformer generation functionality, using an energy cutoff of 5 kcal/mol.
By combining different molar ratios of FMP014 to FMP014D0D1 monomers before self-assembly, we generated multiple nanoparticles and investigated their biophysical characteristics, immunogenicity and protective efficacy.
To confirm some of these observations in vivo, we generated multiple AN2R and 2NAR transgenic lines and analyzed embryo extracts by IP-Western analysis as in Figure 1.
To address this, we generated multiple cohorts of mice (Cohorts I and II) for regression analysis to detect associations between morphological and gene expression phenotypes as previously described.
In order to improve vaccine efficacy and safety of the ΔsecA2 mutant, we generated multiple double and triple mutants of the ΔsecA2 mutant strain via incorporation of other attenuating mutations of M. tuberculosis.
From 926 annotated type I PKS domain sequences in the PKSDB dataset [27], we generated multiple alignments and constructed eight Hidden Markov Models (one for each domain) that were searched against 6,613,204 predicted proteins in six metagenomics samples and UniRef (for details see methods).
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Tensor Generation We generated multiple-biomarker tensors using two biomarkers, spoligotype deletions and MIRU patterns, as explained earlier.
For this, we generated multiple-imputed data sets (n=10) using the proc mi of SAS.
We generated multiple-biomarker tensors to represent multiple biomarkers of the MTBC genome and used multiway models for dimensionality reduction.
To this end, we generate multiple hypotheses representing possible locations for roadsides.
Whenever a customer places an order on Instacart for groceries delivered through a retailer, we generate multiple streams of revenue.
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