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Motifs, or the most frequent patterns, are detected and further aggregated using k-means clustering.
Repeat steps 2 and 3 until no more frequent patterns are generated. .
However, only frequent patterns are regarded as interesting, since only those can be informative for prediction.
The resulting fluctuations may be cyclic, as in so-called periodic diseases [7], [8], but the most frequent patterns are more or less irregular, both in frequency and amplitude.
Frequent patterns are different for each network.
The set of all and maximal frequent patterns are also made available in BicPAM.
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Second, the number of homomorphic and embedded frequent patterns is substantially reduced if only maximal patterns are selected (Column 6 of Table 2).
After the 16th round of annotation, the minimum support was 3, no frequent patterns were extracted, and the last 3695 phrases mainly contained low-frequency words.
Actually, mining maximal frequent patterns is done by mining closed frequent patterns.
The discovery of surprisingly frequent patterns is of paramount interest in bioinformatics and computational biology.
The identification of frequent patterns was performed using the Association Rule Mining algorithm implemented in the R package arules ver. 1.1.5 [ 32].
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