Sentence examples for model that ideally from inspiring English sources

The concepts regarding receptor function have been accommodated over time to a reductionist model that ideally considers one ligand and one receptor.

However, there is no single animal model that ideally replicates the entire metastatic process from primary breast tumor to bone metastasis.

These primary stem cell lines provide an experimental model that is ideally suited to cell-based drug discovery or genetic screens in order to identify tumour-specific vulnerabilities.

The Optimal Foraging theory is a basic decision model that is ideally applied within a larger framework of constraining conditions such as differential prey distributions, food-consumer imbalances and/or competition, among others.

A simple model that assumes an ideally mixed bulk phase and a stagnant layer of catalyst particles in the cavity describes the observed phenomena well.

This is a disease model that lends itself ideally to research, and understanding of its molecular pathophysiology can provide insights and a better understanding of meningiomas in general with ultimate therapeutic targets being identified.

The successful identification of new, effective anticancer drugs largely depends on appropriate preclinical experimental models that should ideally mimic the complexity of different cancer forms.

Ideally, a model that predicts absolute risk of SSI, rather than relative risk or OR values, would greatly enhance the discussion of safety of spine surgery.

Ideally, a model that predicts absolute risk of medical complication, rather than relative risk or odds ratio values, would greatly enhance the discussion of safety of spine surgery.

Ideally, we would like to perform digital cancellation based on a model that includes all non-idealities.

This problem can be dealt with by implementing a locally developed risk prediction model that can be updated over time, ideally in an automated way, e.g. by retraining the SVM algorithm or other artificial intelligence learning algorithms such as artificial neural networks by excluding one month of data at the start of the time series analysis and adding the last month's data [ 22].