Sentence examples for Unified scoring from inspiring English sources

Further, in order to achieve the unified scoring patterns needed for generalizability, we made a final balancing of the original scoring patterns included.

To integrate four complementary large-scale transcriptomic and comparative genomic data sets of gene-to-gene (protein-to-protein) associations we adopted a unified scoring schema that has been applied successfully in other eukaryotes [ 11, 12].

More importantly, this unified scoring schema allows accounting for the variability in the predictive quality between both binary data, such as predicted protein-protein interactions, as well as continuous data with an intrinsic scoring schema, such as the similarity between gene expression profiles.

We applied a unified scoring model to give each PPI a measure of its reliability that can place each PPI at one of the five star rank levels from 1 to 5. We assessed the quality of PPIs contained in the new HAPPI database, using evolutionary conserved co-expression pairs called "MetaGene" pairs to measure the extent of MetaGene pair and PPI pair overlaps.

We developed a unified scoring scheme to assess the reliability of integrated human protein-protein interactions from the public domain.

But, where that show is built round an artfully unified score, here he seems to try on different hats: we get revivalist hymns, soaring romantic ballads, 1950s rock.

The first is less data intensive and provides a unified score that can be used to compare and screen process alternatives, while the second level studies the contribution of individual degradation products to different EHS hazard categories in detail.

These two values were then combined in unified score, called intensity weighted frequency score (IwF).

The main forces, Facebook, Twitter, LinkedIn, certainly weight their own users' activity for various reasons, but Klout has built one single, unified score based on its own independent algorithm across these services.

A better solution is to develop a unified score (or a score of scores) based on training data sets and infer predictions from it.

The scores were combined into an unified score by summing all confidence scores for a particular functional linkage and transforming the resulting number to a 0 – 0.5 scale.