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Define the χ2 divergence (distance) between the joint density h and the product density fg (of independent random variables) by χ 2 ( h ; f, g ) = ∫ ∫ S F × S G h ( x, y ) f ( x ) g ( y ) - 1 2 f ( x ) g ( y ) dxdy, (10).
Branch length indicates divergence distance.
We directly used these conservation levels as the measurement of divergence distance to build the distance matrix for all six higher vertebrates.
Using the Kullback-Leibler divergence distance, we found that cn.MOPS is the closest to array CGH in terms of duplication or deletion proportion across samples.
The only major topology where anatomical data alone probably fail to generate a realistic divergence distance occurs in the branch including Todea and Leptopteris.
To identify the exome CNV tool with the most similar deletion duplication ratio, we conducted pairwise Kullback-Leibler divergence distance on both duplication and deletions proportions (Table 1).
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Other possible choices for distance between (mathbb {P}) and (mathbb {Q}) are absolute, squared, Hellinger, and absolute divergence distances [28].
The proposed log likelihood ratio and KL divergence distances make use of the GMM labels on both the test and the training frames.
All standard errors of divergence distances were determined using 500 bootstrap replicates.
We plotted uncorrected pairwise sequence divergence distances against corresponding dS and dN values to test change in lineage-specific selection pressure.
Therefore, a multivariable matrix including the −ln L scores and divergence distances for all the genes of the GI and guaA was constructed.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com