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Once all output identifiers had been annotated in this manner, we calculated a score based on the number of input identifiers (In), the number of input identifiers for which at least one output identifier was returned (Hits), the total number of returned output identifiers (Out), and the number of preferred output identifiers (Matches).
In this manner we calculated the independent contribution of each of these variables (age and TOT scores) to FA variance.
To determine whether slow-translating codons can cluster in a consecutive manner, we calculated the Consecutive Codon Score (CCSi), ranging from two adjacent codons to stretches of seven contiguous codons that pair to minor tRNAs (Figure 2).
To determine the transition area in an unbiased manner, we calculated two values, l and m (such that l< = m) that also minimizes the sum of the SEM of rj<l and the SEM of rj> = m.
In a similar manner, we calculated the distribution of donor and acceptor splice site motifs within the same set of large introns and their complementary strands (Tables 3 and 4 respectively).
To assess the strength of this structure in a more quantitative manner, we calculated three summary statistics (association index AI, parsimony score PS and maximum monophyletic clade size MC) describing the correlation between the geographic and phylogenetic relationships from the posterior distribution of genealogies generated by the Bayesian coalescence analysis.
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In the similar manner, we calculate the case of ( j, l, k ), ( k, j, l ), ( k, l, j ), ( l, k, j ) and ( l, j, k ) as follows.
In the similar manner, we calculate the segmented distribution of the normalized frequency of the secondary structure elements from the SPINE-M (SPINE-SD) using F S = 5, 10, and 25 (where F s is used as the distribution factor for the SPINE-M equivalent to F P used for the PSSM) and extract 3 × 20, 3 × 10, and 3 × 4 features in total for all three elements, respectively.
The first is the manner in which we calculated QALYs from the trial data.
The probability to increase the fitness due to a new mutation is given by (10) p (W ¯ > d ) = p (W ¯ > d ∣ a > c, b > d ) ︸ 2 θ − θ 2 p (a > c, b > d ) ︸ θ 2 + p (W ¯ > d ∣ a < c, b > d ) ︸ 2 θ − θ 2 p (a < c, b > d ) ︸ θ 2 + p (W ¯ > d ∣ b < d ) ︸ 0 p (b < d ) ︸ 1 − θ = 2 θ 2 − θ 3 In a similar manner, we can calculate the probability to decrease the average fitness due to a new mutation.
In order to present results in a consistent manner for all studies, we calculated effect sizes (or standardised mean difference (SMD)) with 95% CIs for the primary outcomes of each study.
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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