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Those similarities can be explored by iterative testing and refinement of the analogue coupled with related wet-lab experiments.
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The model can also increase efficiency in the evaluation of chemical series by optimizing iterative testing and promoting rational drug design.
An iterative test-and-learn process is critical to developing an accurate model.
We finalized a functional model by iterative testing until it passed a predefined set of 260 validation tests.
To minimize CIM estimate based inflation of QTL effects (Zeng 1993; Beavis et al. 1994), we performed regressions with the genetic markers nearest to the detected QTL. Regression models were built by iterative testing of the fit of each marker.
Such testing could simultaneously simplify the diagnostic algorithm by replacing gene-specific or panel-based tests, remove the need for iterative testing and validation of the results by Sanger sequencing, and decrease the burden on those reviewing cases.
This simultaneously removes the need for iterative testing and decreases the burden on those reviewing and signing out cases.
Moreover, complicated analyses often require iterative testing and refinement.
Instead, we must use a statistical classifier based on supervised machine learning, where the model is fitted and evaluated by iterative training and testing on independent, randomly selected subsets of the data.
Small-scale iterative testing suggested it was acceptable and useful for researchers.
In practice, it is estimated by experience and iterative tests.
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