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The number of references chosen by the LLR method and SparseMap is a simple function of the number of sequences.
The time taken to cluster ESTs is a function of the number of sequences and the number of bases (usually quadratic).
In a rarefaction curve, the number of assigned taxa (on a specified level) is plotted as a function of the number of sequences within a selected sub-sample.
The average over all sites of the correlation coefficients between predicted and observed amino acid distributions, for all mutational biases simulated, lies in the range < r> = 0.83 and < r> = 0.92 and increases as a function of the number of sequences examined (we simulated about 106 sequences for each mutational bias).
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The figure demonstrates that both the number of structures known to carry out a given function, and the structural promiscuity of a function increase with the number of sequences that are associated with the function.
For this data set, Figure S1a shows the distribution of the number of sequences per structure, and Figure S1b shows the number of sequences per function.
It can thus give different results from simpler measures based on counting the number of sequences or structures per function.
Considering the number of sequences (n.
The number of possible POS sequences n is given in Eq. 4, as a function of the number of different POS tags |P|.
As the number of sequenced genomes rapidly grows, the function of the majority of proteins can only be annotated computationally.
However, we can get hints about intrinsic differences among functions in the number of associated sequences if we study the number of functions per structure, in particular if we control for the different number of sequences per structure.
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