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An optimized binary classification system (symphony), which integrates predictions from five in silico methods, can predict the risk of ccRCC associated with VHL missense mutations with high sensitivity and specificity.
We consider the general class of material interface problems where numerical methods can predict pressure and velocity adequately, but fail miserably in their prediction of density and temperature.
It was found that both methods can predict the condition of the drainage pipe, i.e., whether the pipes are empty or occupied by water or soil.
However, few convenient methods can predict the dynamic distribution of contaminants, because the dynamic supply air concentrations resulting from air recirculation are unknown, especially over long time periods, such as months or years.
The results showed that DCN-based methods can predict protein function rather accurately, probably because DCNs constructed from all the proteins of a genome are rather complete and reliable in comparison with other protein networks.
Computational methods can predict many miRNA-binding sites in mRNAs.
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This noncausal predictive method can predict data in a single pass.
As shown in Section 3.4, the proposed prediction method can predict a pixel with its four immediate pixels, and all the pixels can be predicted completely with original pixels as context.
This method can predict the NDZ of IDM but not the detection time.
The proposed method can predict the vision output image of any retina with known photoreceptors distribution.
The results indicate that the proposed method can predict the load deflection behaviour satisfactorily.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com