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Andrew Holt supervised and optimized the design of the direct MgATPase assay, provided advice on enzyme kinetics and contributed to the manuscript writing.
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- Supervised and semi-supervised training – We distinguish between supervised and semi-supervised training.
The structure was modeled with MODELLER57 and optimized with Rosetta58.
Workloads and applications are migrated and optimized.
and optimized manufacturing processes.
and optimized fermentation conditions may vary [ 10].
Moreover, supervised and unsupervised classification experiments with plant leaves accomplished high Precision and Recall rates as well as Bulls-eye scores with the optimized parameters.
SERVICE Attentive, well supervised and trained.
overall guided, supervised and interpreted the results.
Formulation of supervised and unsupervised learning problems.
We might use a combination of supervised and unsupervised learning.
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CEO of Professional Science Editing for Scientists @ prosciediting.com