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Due to the high computational cost of phylogenetic methods, we removed the snake toxins, the TFP domains found in Ser/Thr kinases, the sequences of uPARs and BMP and activin membrane-bound inhibitors (BAMBI), as well as the sequences from non-Craniata species.
After executing these methods, we removed modules containing <5 proteins and obtained 1290 modules.
For the above four recombination detection methods, we removed C. muridarum genes because of the much greater evolutionary separation of this genome from the other twelve.
To ensure a fair comparison across the three risk adjustment methods, we removed the influence of these variables and only included the clinical condition categories to generate the CMS-HCC risk score.
Second, to find activations selective to reward or punishment, by using the exclusive masking methods, we removed activations reflecting the V-shaped regressor from activations associated with linear increases for reward or punishment.
To obtain a fair appraisal of the PriMir method relative to other methods, we removed those pre-miRNAs that were included in the PriMir training set from the 208 pre-miRNAs, which left us with a positive set of 75 pre-miRNAs.
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To improve the convergence of iterative procedures for maximum likelihood estimation and the accuracy of large-sample methods, we remove range restrictions on parameters through the parameterizations α ∗=′, where κ ∗= logκ, γ ∗= logγ and ρ ∗= logρ.
In our method, we removed retweets from the training set so that the recommendation results do not get affected by retweets.
In the case of the Viola-Jones landmark method, we removed 997 of the 15982 images from the query set of [4, Experiment ], because 3 or less landmarks where found in these images which often resulted in poor alignments.
To achieve the BP method, we removed dichroics DM2 and DM4 and placed emission filters BP460-490 (Olympus, Tokyo, Japan) and 535DF35 (Omega Optical, Bratelboro, VT, USA) in front of detectors GD and RD.
Before evaluating any method, we removed the smallest predicted bins (1%) as likely errors.
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