Sentence examples for predictions by including from inspiring English sources
The full NOx chemistry model was able to achieve good NO predictions by including ammonia as a NOx precursor and incorporating a hydrocarbon mechanism to recycle NO to HCN.
The results contribute to the ongoing debate concerning the nature of MHC ligand-containing proteins and can be used to extend the existing methods for MHC ligand predictions by including the source protein's localisation and expression profile.
Future studies may be able to improve these predictions by including combinations of regions.
Older pairwise methods for detecting sequence conservation (e.g. VISTA and PipMaker [ 37, 38]) required the careful selection of species to avoid biasing predictions by including closely related species (e.g. human, mouse, rat).
When analyzing global network properties, we limit our analysis to high quality predictions by including only TFs that have a leave-one-out cross-validated classification accuracy greater than 0.6 (there are 130 such TFs), and targets that have a Platt score ≥ 0.95.
The research aims to improve the accuracy and reliability of simulation prediction by including models of human factors.
It was found that Cakir mathematical model produce reliable result and a new model was proposed to increase the reliability of separation angle prediction by including the particle shape factor.
The ambitious aim is to reach thermodynamic accuracy of 1 3 kT in free energy of binding prediction, by including all relevant interactions, using soft potentials, thermodynamic integration and calibration using engineering thermodynamics data.
In our model, however, we found improvement of prediction by including those clinical variables listed above in addition to cognitive tests.
Our findings offer the possibility of extending the existing methods for MHC ligand prediction by including the source protein's localisation and expression profile.
We estimated dominance and epistatic effects of SNPs on various traits in beef cattle and the variance explained by dominance, and quantified the increase in accuracy of phenotype prediction by including dominance deviations in its estimation.
