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Thus, also in the process of model building used within CEASAR, we dedicated the highest attention of the quality of the data used as input for our models.
Model building used O.
The cross-validated prediction error is an estimate of the prediction error associated with the algorithm for model building used.
Model building used "forced" entry to account for factors known to be associated with outcomes based on existing literature, to avoid exclusion of such factors in stepwise models.
As new biochemical information becomes available, the machine learning approach to model building used here should be easier to update than a heuristic approach.
Model building used backwards elimination method to decide on the factors to exclude from the model using the likelihood ratio test (P < 0.05).
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Repeated cycles of refinement using REFMAC5 (ref. 35) and model building using COOT36 were performed.
A few cycles of refinement using Refmac5 [45] and Phenix.refine [46], interspersed with manual model building using Coot [47], were necessary to complete the model.
Subsequent density modification and model building using the program SHARP and wARP enabled the tracing of the main chain atoms for up to ∼55% of the model [29].
The initial model was subjected to iterative cycles of crystallographic refinement with the Refmac 5.2 [41] and graphic sessions for model building using the program O [42].
Structures were solved by molecular replacement using PHASER [48] and refined using Refmac5 [49] and PHENIX [50] with manual model building using O [51] and Coot [52].
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