Your English writing platform
Discover LudwigSuggestions(2)
Exact(1)
The presented code includes a model-tuning scheme, which is applied after the inversion of field data, where the inversion of the synthetic data is performed based on an initial guess, and the absolute difference between the field and synthetic inverted models is minimized.
Similar(59)
A benefit of these non-parametric models is minimizing statistical issues that frequently arise when using traditional parametric models such as logistic regression.
Both solvent and homology models were minimized until a convergence of 5e−3, using a conjugate gradient minimization.
The cognitive dissonance between virtual and real models was minimized by using a 3D CAD model, and the virtual model of optimum solutions in this study employed a rapid prototyping machine to generate real models efficiently.
Finally the models were minimized without constraints.
Finally, the top DFIRE-scoring models are minimized and scored using CHARMM, as described above.
The dimeric models were minimized for 2000 steps to remove structural clashes using the conjugate gradient algorithm.
The resulting models were minimized by ENCAD and SCWRL3.0, and subsequently the iterative density calculation was again applied to cyclically remove outliers and re-cluster, and finally select the centroid for each of the five largest clusters.
Models were minimized by removing non-significant terms (P > 0.05), beginning with the interaction.
In this way, statistically suboptimal, manual alterations of models are minimized.
Finally, both models were minimized (50,000 steps) and a trajectory of 1 ns was obtained by molecular dynamics using the CHARMM force field [ 70] in NAMD program [ 71].
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com