Sentence examples for using computational models to from inspiring English sources

Using computational models to simulate the generation and dispersion of gaseous species within dairy housing can facilitate the exploration of cost-effective gas mitigation strategies.

A kinetic rate expression for the global Sabatier reaction is developed and validated using computational models to interpret packed-bed experiments with catalysts in powder form.

The methodology examines variation across the genome using computational models to compare the genotypes of people with and without disease to identify SNPs associated with disease.

Also, we demonstrate the feasibility of using computational models to predict one of the determinants for the evaluation of drug sensitivities.

" The Max Planck UCL Centre for Computational Psychiatry and Ageing Research centre, which opened on Tuesday, aims to use computational models to bridge the gap between neuroscience and the phenomena seen in psychiatric disorders.

We used computational models to study mechanisms by which intra-RE inhibition abbreviates and desynchronizes intrathalamic oscillations.

This paper uses computational models to evaluate strategies for scaling electrochemical partial oxidation (EPOX) processes from the laboratory scale to practical application.

Finally, in order to assess the therapeutic relevance of genomic classification, we used computational models to determine the activation status of oncogenic pathways, for which specific targeted inhibitors are in clinical development in sarcoma, and studied the association of pathway activation with histologic subtype and chemoresponse.

The success of molecular systems biology hinges on the ability to use computational models to design predictive experiments, and ultimately unravel underlying biological mechanisms.

Such manipulations could also apply to other well-characterized systems, as enticingly proposed by Behar et al. They used computational models to virtually screen for conditions yielding specific dynamics, then applied their findings to NF- κB-driven transcription.

Savage et al. (2012) used computational models to simulate a number of dispersal events and showed that sampling strategies based on mobile platforms have a much greater probability of detecting airborne spores than strategies based on stationary traps, and that mobile trap strategies required a far lower number of traps to achieve a reasonable probability of detection.