Exact(7)
Representing each bio-sample using its pathway metrics allows us to look for patterns in the collection of pathways.
Using pathway activity and pathway consistency scores [26], we clustered the individuals according to their pathway metrics and performed survival analysis.
Each sample was thus re-represented using its pathway metrics.
Only the combined effect of the relationships among the genes, the measure of their co-dependency through the different pathway metrics we use, drives the phenotypic classification.
We combined pathway metrics with clinical data to determine the association of network behavior with phenotype in the five independent datasets.
To apply this network-based methodology, we used The PathOlogist [ 27] which is an automated Matlab tool that uses gene-expression data RMA levels) to deduce pathway metrics.
Similar(53)
These findings show that FET pathway based metrics are a powerful tool to identify similarity between experiments.
We initially defined two main classes of pathway activation metrics on a given gene module.
These methods quantify expression behavior in specific subnetworks (such subnetworks can be specific pathways or any other defined subnetwork) and produce two metrics: pathway activity and pathway consistency.
For all pathways, the response metrics aligned with model predictions.
Design choices about the geographic scale, inclusion of sectors, the generation and delineation of adaptation options, specification of possible pathways, the related performance metrics and the type of assessment are interdependent, but they are also influenced by contextual aspects.
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