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.