Sentence examples for descriptor data from inspiring English sources

Digital elevation and terrain descriptor data were essential in the model for achieving acceptable results.

The main objective was to test the effect of the addition of terrain descriptor data to the AVHRR data set on the classification results.

The potential of a principal component analysis of the molecular descriptor data to improve the TQSPR performance is assessed and a new stopping criterion for QSPR refinement based on the discrepancy principle is introduced.

However, simply examining the activity and descriptor data readily identifies such anomalous landscapes.

If the dataset has not been normalized, the program can be used to normalize descriptor data.

Accordingly, we analyzed how this influences the LE trends for ligand-target binding, economic big data or molecular descriptor data.

The tests were repeated using N=8 and R=2 for the eight LBP descriptors (data not shown).

In FE methods, by the use of principal component analysis (PCA), the information contained in the descriptors data matrix is extracted into new orthogonal variables with lower dimensions.

Consequently, they do not integrate additional related data (e.g. approval application, affinity data, molecular descriptors, data references, adverse effects) and metadata required for in-depth predictive modeling analyses.

Unfortunately the layout of the self-completed MDP used in this study failed to focus the subject's attention on the requirement to choose the best descriptor, thus best-descriptor data were insufficient for analysis.

Thus, in this article, we have presented an approach to mine molecular descriptors data for virtual screening, having a DW schema as support for providing mining inputs.