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Our method relates firms' market return on equity to information about patent citation patterns.
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It was proven that the number of CTCs detected by our method directly relates to survival of MBC patients and is associated to various clinical factors.
Our method is related to the works in [20, 21] in the sense of pairwise comparison of region similarity.
The consistent results that we obtain for different species pairs indicate that our method of relating alignment -based sequence identity to conserved sequence information is an effective way to project % identity figures from species pairs with different mutational distances onto a comparable scale.
Apart from the first method, the second method relates to nonlinear analysis.
The problem with the dynamic reference method relates to content-specific normalization.
An additional important distinction between IE and the leaving group method relates to purification techniques.
Virtually all of the global experience with this method relates to hospital settings in LMICs.
Surprisingly, by integrating topologies of bakers' yeasts protein protein interaction, genetic interaction (GI) and co-expression networks, our method reports as related 96% of GO terms that are directly related in GO.
Experimental results based on synthetic dataset and benchmark datasets demonstrate the better performance of our method over other related methods.
Our method finds the related gene functions in a sentence based on semantic similarity of the sentence to GO terms.
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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