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Based on these results, models are clustered into two groups.
The models are clustered using pair-wise similarity or distance measures between a model pair as described earlier.
The numerous models are clustered and representative models are selected based on the gap metric as the distance measure.
The models are clustered using pair-wise similarity or distance measures between a model pair described by their representative classifiers as described earlier.
The above ab initio and blast evidence based gene models and manual gene models are clustered into potential gene loci.
The top scoring 500 models are clustered using the Rosetta Cluster application, as described in Gray et al. [41], with a cluster radius cutoff of 2 Å peptide backbone atom RMSD.
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The resulting models were clustered and the clusters were ranked based on a reweighted version of the Rosetta generic full-atom energy score, in which interface and peptide residuesare given additional weight, and which improves the performance of the protocol compared to the standard Rosetta score (see Table S2 and Methods).
Then, within each topology, the models were clustered with respect to loop conformation.
The 200 models were clustered by ROSETTA, and the centroid of several large clusters were chosen as predicted models.
The models were clustered based on their RMSD and the top 20 clusters based on the total-score were visually evaluated.
Regression models were clustered by NC-FM-RN practitioner site and used the category of highest SES as the referent level.
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