Bacterial chromosomes are highly polarized in their nucleotide composition through mutational selection related to replication. Using compositional skews such as the GC skew, replication origin and terminus can be predicted in silico by observing the shift points. However, the genome sequence is affected by myriad functional requirements and selection on numerous subgenomic features, and elimination of this "noise" should lead to better predictions. Here, we present a noise-reduction approach that uses low-pass filtering through Fast Fourier transform coupled with cumulative skew graphs. It increases the prediction accuracy of the replication termini compared with previously documented methods based on genomic base composition.
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