Sentence examples for the identification of modules from inspiring English sources

Yet, the identification of modules and standardised interaction routes remains a non-trivial problem.

The identification of modules in complex networks has attracted much attention of the scientific community in the last years, and social networks constitute a prominent example.

For the identification of modules within a dendrogram, we consider both global cuts, including the one suggested by the gap statistic [17], and local cuts.

We introduce a novel approach for the identification of modules based on the persistence of isolated gene groups within an evolving graph process.

This approach for the detection of module isolation, which we refer to as the Miso method, permits the identification of modules with differing internal cohesion and determines the statistical significance of each candidate module.

Moreover, the identification of modules as hills of the community landscape is a new approach, including traditional threshold-based algorithms and the novel local maxima based algorithms (as our ProportionaHill, GradientHill and TotalHill methods).

This extension allows the identification of module-based prognostic markers, rather than gene-based markers.

Considering that the subnetwork marker extracted from protein interaction databases are more reproducible than individual gene markers [15], [16], we assume that the identification of module-module interactions is more robust than that of gene-gene interactions.

Equally interesting was the identification of module genes participating in multiple stress responsive pathways.

Quantitative data from diverse genome-scale experiments can be exploited for the identification of new modules and the expansion of known modules.

For example [ 70] focused on the identification of conserved modules in metabolic pathways, and showed that many such modules exist, have a skewed size distribution, and may be hierarchically organized.