996 resultados para Isoenergetical Non-Degeneracy


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We study pathwise invariances and degeneracies of random fields with motivating applications in Gaussian process modelling. The key idea is that a number of structural properties one may wish to impose a priori on functions boil down to degeneracy properties under well-chosen linear operators. We first show in a second order set-up that almost sure degeneracy of random field paths under some class of linear operators defined in terms of signed measures can be controlled through the two first moments. A special focus is then put on the Gaussian case, where these results are revisited and extended to further linear operators thanks to state-of-the-art representations. Several degeneracy properties are tackled, including random fields with symmetric paths, centred paths, harmonic paths, or sparse paths. The proposed approach delivers a number of promising results and perspectives in Gaussian process modelling. In a first numerical experiment, it is shown that dedicated kernels can be used to infer an axis of symmetry. Our second numerical experiment deals with conditional simulations of a solution to the heat equation, and it is found that adapted kernels notably enable improved predictions of non-linear functionals of the field such as its maximum.

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Back in 2003, we published ‘MAX’ randomisation, a process of non-degenerate saturation mutagenesis using exactly 20 codons (one for each amino acid) or else any required subset of those 20 codons. ‘MAX’ randomisation saturates codons located in isolated positions within a protein, as might be required in enzyme engineering, or else on one face of an alpha-helix, as in zinc finger engineering. Since that time, we have been asked for an equivalent process that can saturate multiple, contiguous codons in a non-degenerate manner. We have now developed ‘ProxiMAX’ randomisation, which does just that: generating DNA cassettes for saturation mutagenesis without degeneracy or bias. Offering an alternative to trinucleotide phosphoramidite chemistry, ProxiMAX randomisation uses nothing more sophisticated than unmodified oligonucleotides and standard molecular biology reagents. Thus it requires no specialised chemistry, reagents nor equipment and simply relies on a process of saturation cycling comprising ligation, amplification and digestion for each cycle. The process can encode both unbiased representation of selected amino acids or else encode them in pre-defined ratios. Each saturated position can be defined independently of the others. We demonstrate accurate saturation of up to 11 contiguous codons. As such, ProxiMAX randomisation is particularly relevant to antibody engineering.

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ProxiMAX randomisation achieves saturation mutagenesis of contiguous codons without degeneracy or bias. Offering an alternative to trinucleotide phosphoramidite chemistry, it uses nothing more sophisticated than unmodified oligonucleotides and standard molecular biology reagents and as such, requires no specialised chemistry, reagents nor equipment. When particular residues are known to affect protein activity/specificity, their combinatorial replacement with all 20 amino acids, or a subset thereof, can provide a rapid route to generating proteins with desirable characteristics. Conventionally, saturation mutagenesis replaced key codons with degenerate ones. Although simple to perform, that procedure resulted in unnecessarily large libraries, termination codons and inherent uneven amino acid representation. ProxiMAX randomisation is an enzyme-based technique that can encode unbiased representation of all or selected amino acids or else can provide required codons in pre-defined ratios. Each saturated position can be defined independently of the others. ProxiMAX randomisation is achieved via saturation cycling: an iterative process comprising blunt end ligation, amplification and digestion with a Type IIS restriction enzyme. We demonstrate both unbiased saturation of a short 6-mer peptide and saturation of a hypervariable region of a scfv antibody fragment, where 11 contiguous codons are saturated with selected codons, in pre-defined ratios. As such, ProxiMAX randomisation is particularly relevant to antibody engineering. The development of ProxiMAX randomisation from concept to reality is described.

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Back in 2003, we published ‘MAX’ randomisation, a process of non-degenerate saturation mutagenesis using exactly 20 codons (one for each amino acid) or else any required subset of those 20 codons. ‘MAX’ randomisation saturates codons located in isolated positions within a protein, as might be required in enzyme engineering, or else on one face of an alpha-helix, as in zinc finger engineering. Since that time, we have been asked for an equivalent process that can saturate multiple, contiguous codons in a non-degenerate manner. We have now developed ‘ProxiMAX’ randomisation, which does just that: generating DNA cassettes for saturation mutagenesis without degeneracy or bias. Offering an alternative to trinucleotide phosphoramidite chemistry, ProxiMAX randomisation uses nothing more sophisticated than unmodified oligonucleotides and standard molecular biology reagents. Thus it requires no specialised chemistry, reagents nor equipment and simply relies on a process of saturation cycling comprising ligation, amplification and digestion for each cycle. The process can encode both unbiased representation of selected amino acids or else encode them in pre-defined ratios. Each saturated position can be defined independently of the others. We demonstrate accurate saturation of up to 11 contiguous codons. As such, ProxiMAX randomisation is particularly relevant to antibody engineering.

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Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

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In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.