Sentence examples for predictions which demonstrates from inspiring English sources

We found that when taking into account the modularity levels, the CIPHER-HIT method can significantly improve the performance of disease gene predictions, which demonstrates modularity is one of the key features for credible inference of disease genes on the phenotype-gene heterogeneous network.

A logical approach to using information for genomic prediction is introduced, which demonstrates the appropriate weights for analyzing observations with heterogeneous variance and explains the need for and the manner in which EBV should have parent average effects removed, be deregressed and weighted.

Reasonably good agreement has been obtained between the numerical predictions and published experimental measurements, which demonstrates the reliability and accuracy of the model.

Part of TCMn3+ cations result from the migration of layer Mn3+ to the interlayer, which demonstrates that prediction of vernadite to tectomanganate transformation requires a sound understanding of vernadite structure, including quantification of both TCMn3+ and layer Mn3+ in starting material.

MHC2SK outperformed GS in allele specific prediction using a benchmark dataset, which demonstrates the effectiveness of MHC2SK.

The results suggest that the relative amount of the hydrogen bonds has similar profile with the relative viscosity, which demonstrates the present predictions of the relative viscosity.

MHC2SK outperformed GS in the allele-specific prediction task on a benchmark dataset, which demonstrates the effectiveness of MHC2SK.

The estimated prediction error of our final model is 0.81, whereas that of the naive model is 1.57, which demonstrates a much better prediction ability of our final model compared with the naive model.

Finally, GreenGenie2 completes 2,261 incomplete FGC07 models, which demonstrates another benefit of including GreenGenie2 whole-genome predictions into current and future Chlamydomonas gene catalogs.

The importance of prediction errors is based on Kamin's blocking effect [ 7] which demonstrates that learning and extinction advance only to the extent at which a reinforcer is better or worse than predicted; learning slows progressively as the prediction approaches asymptotically the value of the reinforcer.

A prediction accuracy of 86% (ANN model with ensemble approach) is achieved, which demonstrates the feasibility of applying the ANN approach to decision-making in pedestrian flows.