Sentence examples for negative datasets from inspiring English sources

Hence, we created negative datasets synthetically based on co-localization enrichment of interaction between two proteins.

We think that this strategy of deriving negative datasets is more sophisticated than Jansen et al.'s [34] approach.

Because there is no experimentally verified set of non-interacting pairs, negative datasets are usually generated synthetically.

As a result, we constructed an evaluation system for assessing protein interaction reliability using positive datasets obtained from known protein complex and negative datasets derived based on co-localization characteristics.

These entries were used as the "Negative" datasets.

This idea was tested on the same positive dataset and negative datasets.

If the i-th feature has a high F-score, then this feature effectively discriminates between positive and negative datasets.

Homology reductions within positive and negative datasets were performed with similarity threshold 70% between any two peptide sequences.

Both positive and negative datasets were scattered across all major SCOP classes (SCOP class IDs are from a to g).

MCC is always introduced when the positive and negative datasets are out-of-balance from each other.

For this purpose, we used the second SVM model, due to its consistency on both positive and negative datasets of the native-native interfaces.