Sentence examples for predictions are commonly from inspiring English sources
Performance predictions are commonly made using simulation software (bespoke or generic) based on mathematical functions (empirical or analytical) to model heat loads, heat transfer and many other effects; [2] and [3] present typical examples.
The statistical significance determination of the MLSA algorithms' results is still an open problem [ 15, 22], so the reliability of the predictions is commonly validated based on their robustness - i.e. the predictions obtained by multiple runs of the same MLSA algorithm, or by different implementations of MLSA algorithm (e.g. BioProspector and Gibbs Motif Sampler), should match.
Although Pfam prediction is commonly accepted, it does not predict all structural and functional motifs and domains.
Statistical prediction is commonly presented under either probabilistic or deterministic settings.
In clinical practice, this prediction is commonly made on the basis of clinical and routine biochemical parameters, which are combined in prognostic scores as the Child-Turcotte-Pugh (CTP) [ 10] or the Model for the End-Stage Liver Disease (MELD) scores [ 11], and, less commonly, on the basis of the invasive measurement of portal pressure.
Network analysis and pathway prediction methods are commonly used to study groups of genes and predict their functional associations.
For this reason, prediction models are commonly used to obtain desired parameters indirectly.
Prediction tools are commonly used in pre-clinical research to assist target selection, to optimize drug potency or to predict the pharmacological profile of drug candidates.
After an environmental change occurs, prediction strategies are commonly used in dynamic multi-objective optimization algorithms to find the new Pareto optimal set (POS).
Several methods of evaluating the accuracy of miRNA target prediction algorithms are commonly used.
Sequence-based prediction algorithms are commonly used to categorize nsSNPs into damaging and non-damaging, and to predict the effects (small or large) of nsSNPs with respect to undesirable phenotypes.
