1 research outputs found
Computational prediction of replication sites in DNA sequences using complex number representation
Computational prediction of origin of replication (ORI) has been of great
interest in bioinformatics and several methods including GC-skew,
auto-correlation etc. have been explored in the past. In this paper, we have
extended the auto-correlation method to predict ORI location with much higher
resolution for prokaryotes and eukaryotes, which can be very helpful in
experimental validation of the computational predictions. The proposed complex
correlation method (iCorr) converts the genome sequence into a sequence of
complex numbers by mapping the nucleotides to {+1,-1,+i,-i} instead of {+1,-1}
used in the auto-correlation method (here, i is square root of -1). Thus, the
iCorr method exploits the complete spatial information about the positions of
all the four nucleotides unlike the earlier auto-correlation method which uses
the positional information of only one nucleotide. Also, the earlier
auto-correlation method required visual inspection of the obtained graphs to
identify the location of origin of replication. The proposed iCorr method does
away with this need and is able to identify the origin location simply by
picking the peak in the iCorr graph.Comment: 4 Figures, 1 Table. arXiv admin note: substantial text overlap with
arXiv:1701.0070