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The coherence (synchrony) of the subband peaks is analyzed and employed to detect an optimal peak sequence representing the beat locations.
We use these motifs to represent each peak sequence as a binary vector, indicating whether a motif is present or not in the peak sequence.
Then, we apply MEME (http://meme.sdsc.edu/) to each peak sequence cluster.
The predicted score is computed by PeakRegressor using the peak sequence information.
To ensure sequences reflected single templates from in vivo populations, we excluded amplicons with "double peak" sequence chromatograms, indicating co-amplification of >1 template.
Due to the noisy nature of ChIP-Seq data, the motifs we are looking for may not be exactly on the provided peak sequence, but in the surrounding DNA neighborhood.
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They all feature regular peak sequences, where each signal peak has been assigned to the most stable high-temperature-formed PAHs.
In Fig. 11, several peak sequences can be found radiating with increasing peak values from positions where w 2 and w 3 are small.
We widen short peak sequences.
To conduct our analysis, we modify the peak sequences in the following way: We shorten long peak sequences for two reasons.
Therefore, we decide to choose a uniform length for all the peak sequences.
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