Sentence examples for methods in prioritizing from inspiring English sources

They conclude that random walks outperform other distance-based methods in prioritizing related disease genes, and similar approaches have been applied in genome-phenome networks [ 26, 27].

Our study also demonstrated the efficacy of network-based methods in prioritizing genes for complex traits.

The success of this strategy implies that there might still be a chance to further improve the performance of network-based methods in prioritizing candidate disease genes.

Comprehensive experimental results on the Online Mendelian Inheritance in Man (OMIM) database show that D AD A outperforms existing methods in prioritizing candidate disease genes.

We also showed the capability of our method in prioritizing candidate genes for diseases whose genetic bases are completely unknown.

To examine the performance of our method in prioritizing candidate diseases for a fixed query gene, we perform the following leave-one-out cross-validation experiment.

We demonstrate the effectiveness of this method in prioritizing candidate genes through a series of cross-validation experiments, and we show the possibility of using this method to identify diseases with which a query gene may be associated.

We perform three large-scale leave-one-out cross-validation experiments to examine the performance of the proposed method in prioritizing genes that are known to be associated with certain diseases (i.e., disease genes) from a set of candidates.

To validate our method in prioritizing malaria genes, we performed a "leave-one-out" cross validation analysis and examined the ranks of a set of malaria genes extracted from literature.

Feedback from the organization is that the method has been effective in prioritizing architectural concerns, that data collection and analysis is more extensive compared to traditional prioritization practices, but that extensive analysis seems inevitable in architecture improvement work.

Tiffin et al. [ 34] recently surveyed some of the methods for computational disease gene identification and concluded that using the methods in concert was more successful in prioritizing candidate genes for disease, than when each was used alone.