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For AN, 26% were derived from its own lineage based on the gain model.
In the gain model, some clans lost in MG or NC lineages first appeared in branch 1.
For the gain model, gain (0->1) is more possible than loss when two equally parsimonious paths existed and verse visa for the loss model.
Comparing the virtues of the gain and loss models, we believe the gain model more closely represents the real world situation for the following reasons.
For example, in the gain model, 26 new clans appear in the AN lineage and no loss events from the LCA.
We rank the importance of each gene with complete interaction network centrality (CINC), which integrates each gene's differential co-expression effects in the GAIN model along with each gene's individual differential expression measure.
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Moreover, total collector area of the gained model is 9.42 m2.
The gained model can be used both for timing analysis and for Failure Propagation Analysis (FPA).
A special case of the value-added model in equation (2) is the gains model, where the dependent variable is measured as test score growth.
The gained model can be used both for timing analysis and for a logical description, which builds the basis for Failure Propagation Analysis (FPA).
Therefore, the value-added model is much more common than the gains model, and we follow the traditional approach by estimating a value-added model as in equation (2).
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