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Based on inspection of individual representative aggregate types and verified using our tracking system, we assigned specific dimensional characteristics to specific aggregate types.
As a first assessment of the performance of the GCI scoring system, we assigned scores to all accessible genes in consecutive releases of the human genome and followed GCI score distribution and attribute selection of the MARS model.
Using this classification system we assigned each TCGA tumor as being either MS1, MS2 or MS3.
By identifying similar sequences in this classification system, we assigned unigene sequences with putative gene family identities.
To produce the scoring system, we assigned the simplest integers proportional to the coefficient β of each predictor.
Using the system, we assigned a stability rating of Low to the estimated diagnostic odds ratio of 12.7 (95% CI 5.5 to 29.7).
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For every processor in our Biogrid system, we assign n/ p rows of matrix to this processor for the calculation of their corresponding association values.
If there is no agreement among the three systems, we assign the label predicted by the method which has the highest overall F-score for the current word.
Using functional annotation from an expert system (Pfam) we assigned domains, families and repeats by 4400 keywords that cover 73% of the sequences.
Based on this naming system we have assigned the name KIF27 to this new family member with the suffixes A, B and C to designate the splice variants described above (figure 3B).
Using a random permutation algorithm and training sets of known nervous system development genes we assigned weighted scores to each screen (Supplementary Figure S7).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com