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We have used r = 0.6 as a "hard" threshold value for the CC.
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The diagonal sparse transformation matrix P can be re-formulated as a "hard threshold -like operathreshold -like8: x^{k + 1} = Hleft( {y^{k + 1} } right) = left{ {begin{array}{*{20}c} {0,} & {{text{if}} quad y^{k + 1} < 0} {y^{k + 1},} & {{text{if}} quad y^{k + 1} ge 0} end{array} } right., (8)where y k+1 is the intermediate updating result operation + 1)th iterasinn.
We chose PRIMA as a representative of a group of methods that use a hard threshold to identify putative appearances of motifs in any given promoter.
The transform coefficients are then subjected to a hard threshold.
The output is compared to a hard threshold, selected according to P FA (Figure1).
Because of errors in the database, a hard threshold cannot be used for land and sea.
As mentioned in the main text, the simplest method for constructing gene coexpression networks involves calculating Pearson correlations for all pair-wise genes and applying a hard threshold to determine which genes should be connected.
It also suggests that, in general, one should avoid using a hard threshold for stopping the iterative removal process.
Thus, we want to avoid the decision based on a hard thresholding and propose an approach that exploits a modeling of the power ratios as was similarly proposed by the authors in[31].
In effect, this approach is a dynamic significance thresholding strategy where a local hard threshold is determined for each GIL separately using the correlation matrix of each GIL.
Noise suppression can also be achieved using a fixed hard threshold.
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