Sentence examples for models revealed a from inspiring English sources

Docking to homology models revealed a possible halogen bond formation in complexes of the most potent ligands and the target receptors.

PLS-DA modeling predicted postoperative hypoxemia at 72 h with 72.2%% sensitivity and 81.0 % specificity based on blood samples collected just before CPB, while PLS models revealed a correlation of r2 equal to 0.7.

Studies in rodent models revealed a peculiar feature of hepatic insulin resistance, in which hepatic glucose metabolism becomes unresponsive to insulin but hepatic lipogenesis continues unabated, recognized as selective hepatic insulin resistance (Brown and Goldstein, 2008, Li et al., 2010b, Cook et al., 2015).

Surface and contour plots of the regression models revealed a maximum hydrogen production rate of 0.566 mmol H2/L/h at 27.5 °C and 287 W/m2 and a maximum hydrogen yield of 0.326 mol H2/mol substrate at 26.8 °C and 285 W/m285

Linear regression models revealed a significant negative relationship between PiB retention and CA and a significant positive relationship between glucose metabolism and CA. These data suggest that CA may have a direct beneficial effect on the pathophysiology of AD or reflect another underlying process that results in both higher CA and lower AD pathophysiology.

For the two surveys, spatial analyses and generalised linear models revealed a significant effect on the current geographical distribution of A. ostoyae disease of the proportion of pre-existing forest in the vicinity of afforested areas and a significant effect of the proximity of the first forests planted in the coastal dunes.

Immune-deficient animal models revealed an amelioration of cerebral ischemic-reperfusion injury [12], [18], [19].

Even simple models reveal a range of interesting behaviors.

Recent models reveal a hierarchy within the seemingly chaotic cloud of sand.

(Q SAR models reveal a relationship between the structural characteristics of the compounds and their biological activity or environmental behavior [5, 6].

Recent developments in the direction of target-class-specific scoring methods and machine-learning-based classification models reveals a significant improvement in binding mode and activity prediction [1].