Consequence screening quantitative

Quantitative Consequence Screening Based on Site-Specific Conditions... 

Site-specific consequence screening for explosion can be performed either qualitatively or quantitatively, depending upon the explosion potential of the materials being handled, as well as processing conditions and other site-specific factors. In performing a consequence screening, it is necessary to select "Evaluation-case" events for consideration. This is defined as follows ... 

If the slopes of the absorption/time curves differ considerably, a positive hit is indicated (i.e., an enantioselective lipase-variant has been identified) (16). Figure 5 shows two typical experimental plots, illustrating the presence of a non-selective lipase (top) and a hit (bottom) (16). As a consequence of the crudeness of the test, quantitative evaluation is not possible. Therefore, the hits need to be investigated separately in laboratory-scale reactions and evaluated quantitatively by conventional chiral GC. About 800 plots of this kind can easily be recorded per day. A total of 40 000 lipase-variants were generated by epPCR, saturation mutagenesis, cassette mutagenesis, and DNA shuffling and screened in the model reaction. 

To undertake partial, or complete, genome screens by association-based methodology for quantitative trait loci, multiple individuals have to be screened for large numbers of genetic markers. Consequently, much recent interest has focused on methods enabling accurate allele quantification in pooled DNA samples. Microsatellites were the favored markers in initial studies, but the extraordinary wealth of data concerning SNPs has turned attention to the quantification of SNP alleles in pools. All such approaches require accurate estimation of DNA concentrations, followed by the preparation of replicate pools, validation, and application of procedures for determining allele frequencies. 

Structure-activity relationship (SAR) and, more generally, stracture-property relationship (SPR) analysis are integral to the rational drag design cycle. Quantitative (QSAR, QSPR) methods assume that biological activity is correlated with chemical structures or properties and that as a consequence activity can be modelled as a function of calculable physiochemical attributes. Such a model for activity prediction could then be used, for instance, to screen candidate lead compounds or to suggest directions for new lead molecules. 

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