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1) While Cheng and Li only assess miRNA target sites, our implementation evaluates all words of a given length.
At the beginning, we randomly allocate all N words of a given core dictionary as points in a high-dimensional unit ball, i.e. as vectors with length ≤1.
Our algorithm starts by enumerating all nucleotide combinations (words) of a given length, usually six.
The corresponding procedures (for class size calculations and structure generations) are actually required for (uniform) random generation of words of a given CFG by means of unranking.
As we can see on table 4, the computational time to obtain the pattern statistics for all simple words of a given length are quite similar with both approaches.
Our principal method is positional word counting (PWC), in which all sequence words of a given length (tetramers and hexamers in this work) are counted, recording both the occurrence and the position with respect to the 3'-processing site.
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In particular, the projection of a word on a given axis reflects its semantic amount along the corresponding component.
As no prior model of the distribution of words for a given segment is available, generalized probabilities are used.
Within the "bag of words" for a given sound, different words were often used to denote the same or very similar concept.
Other minor modifications included changing individual words to make it easier for the child to understand or read; or reducing the number of words for a given question where possible.
In other words, for a given level of productivity, females produce better quality work than males.
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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