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Implementing more robust surrogate models, will facilitate the use of this algorithm in numerous other process design applications and beyond.
Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.
Such models will facilitate the evaluation of the impact of genetic modifications on cellular physiology and guide subsequent rounds of modifications to attain the goals of metabolic engineering.
The new guidelines, termed STARD-BLC M(Standards for Reporting of Diagnostic accuracy studies that use Bayesian Latent Class Models), will facilitate improved quality of reporting on the design, conduct and results of diagnostic accuracy studies that use Bayesian latent class models.
These models will facilitate early predictions from which investment and management decisions can be made for kauri forestry in New Zealand in the future.
These models will facilitate higher-throughput compound screens in 3D, allowing quantitative measurement of growth, size, shape, cellular dynamics and morphology of acinar structures.
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This model will facilitate quantification of the effects of parenterally and neuraxially administered analgesics in dogs.
Robust algorithms on inverse modelling will facilitate model updating if an object is directly modified in a virtual environment (VE).
The extended PBD model will facilitate thermodynamic and dynamic simulations of important genomic regions such as CpG islands and disease-related repeats.
The ability to model lung cancer in vivo in a laboratory model will facilitate the development of new therapeutic and diagnostic tools to combat this disease.
This model will facilitate study of autotransplant physiology as well as vascularized composite allotransplantation as an evolving method for reconstructing previously nonreconstructable injuries.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com