Your English writing platform
Free sign upSuggestions(1)
Exact(2)
Monte Carlo simulations show that the proposed method performs substantially better than the traditional (i.e., frequency-based) kernel density estimation (trKDE) which has been used in applied settings while two illustrative examples demonstrate that the proposed approach can yield superior results compared to the popular trKDE approach.
The results demonstrate that our method performs substantially better than state-of-the-art classification methods, and is able to make new clinically relevant predictions for key amplicons and candidate marker genes.
Similar(58)
The enrichment plot, Figure 11, shows that the pharmacophore filtering method performed substantially better with this target than any of the traditional scoring functions.
The accuracy obtained for small spheres was similar to that achieved with the 40% threshold (errors ~40 60%), but for larger objects, the CT-based method performed substantially better than the 40% threshold.
Expectedly, EEM scores the best performance among the three methods, while BEEM performs substantially well, as compared to SSA (Figure 2A).
Based in this observation, we considered it unlikely that another peak finding method would perform substantially better on our data than ChIP-peak with optimized parameter settings.
Our methods always performed substantially better on the membrane-only subset, and usually better on the soluble-only subset.
Both methods performed well on our data.
All methods performed well with no errors.
Our hybrid SA-GD optimization method does not perform substantially better than the SA_geom method, as seen in Figure 3.
When applied to synthetic data, the model performs substantially better than existing methods that consider each network snapshot in isolation.
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