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It remains unclear how these pathways are selected and regulated.
Notably, when using elastic net, we select correlated variables in groups ensuring that genes operating in pathways are selected together.
When multiple pathways are selected at the same time, the view will show all unique gene components within selected pathways.
The pathway gene method is a combination of both methods; instead of candidate genes, candidate pathways are selected based on the pharmacodynamic and pharmacokinetic behaviour of a drug.
Pathways are selected for annotation based on the various roles they play in the context of the broader systems biology or physiological networks or in the context of diseases associated with a Disease Portal.
Furthermore, we applied our method for lung cancer data analysis and found that our method achieves higher predictive accuracy than L1 regularization, the old L1/2 penalized solver, and the Elastic net approaches, while fewer but informative biomarkers and pathways are selected.
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Immunity-related pathways were selected for further analysis, and our results demonstrated that a total of 13 and 50 DEGs were annotated in the humoral immune-related and cellular immune-related pathways, respectively.
Process and pathways were selected based on a p-value < 0.05.
These pathways were selected on the basis of corrected gamma p value ≤0.05 and a minimum input of 4 genes.
Canonical pathways were selected and overlayed onto the biological pathway based on known biological significance from the most highly overlapping pathways.
The EGFR and Rho signaling pathways were selected since EGF is known to be required for nsph propagation and CSPG signals via RhoA in neurons.
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