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In addition to updating existing gene models, analysis identified 403 putative novel protein-coding genes that did not overlap with existing gene annotations and >25,000 new putative alternatively spliced isoforms as compared to the AaegL3.3 geneset (Fig. 3a and b).
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The model analysis identified several kinetic orders with relatively high sensitivities, but because these reflect structural features of enzymatic processes, they are unlikely to present accessible targets for drug treatment.
Our latent class model analysis identified interesting patterns of chromosomal aberrations.
The multivariate Cox model analysis identified PAK1 as a possible prognostic factor in pancreatic cancer patients.
The path model analysis identified direct effects of both strain-based scales on self-reported work ability.
The stringent liner model analysis identified 128 significantly differentially expressed coding and non-coding RNA transcripts in ESCC relative to normal tissue.
The path model analysis identified direct effects of both strain-based scales on the WAI (strain-based WIF on WAI: β = −0.33; 95% CI: −0.42 to −0.21; strain-based FIW on WAI: β = -0.14; 95% CI: −0.24 to −0.04; Figure 2).
Multivariate proportional hazard model analysis identified HER3 (IHC 1+/2+) (HR; 1.53, 95% CI, 1.11 2.16, P = 0.0078) as the sole RTK that was a poor prognostic factor independent of stage.
Mixture model analysis identified three classes in the LRRK2 PD and nonmanifesting carriers, suggesting that there are subgroups with poor olfactory identification in both LRRK2 PD and nonmanifesting carriers.
Model based analysis identified no significant difference in batch laboratory parameters vs pilot-scale continuous parameters, and no change in speed or extent of degradation.
Mixed model clustering analysis identified three risk groups with probabilities for low-risk <0.333; intermediate-risk 0.333-0.606; and high-risk ≥0.606.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com