Identification of coding and non-coding sequences in a complete genome using local Hölder exponent formalism and Multi-affinity analysis

摘要

Accurate prediction of genes in genomes has always been a challenging task for bioinformaticians and computational biologists. Therefore, the discovery of relations in coding and non-coding sequences has led to new perspectives in the understanding of the DNA sequences. This has motivated us to find new methods to distinguish coding and non-coding sequences. We first introduce a number sequence representation of DNA sequences. Multi-affinity analysis and local Hölder exponent are then performed on the representation of the obtained number sequence. Three suited exponents are selected to form a parameter space. The two exponents γ(−2), γ(6) are from Multi-affinity analysis, the exponent h is from local Hölder exponent. Thus, each coding or non-coding sequence may be represented by a point in the three-dimensional parameter space. We can see the points corresponding to coding and non-coding sequences in the complete genome of many prokaryotes be divided to different regions roughly. If the point (γ(−2), γ(6), h) for a DNA sequence is situated in the region corresponding to coding sequences, the sequence is discriminated as a coding sequence; otherwise, the sequence is classified as a non-coding one. Therefore these exponents can be used to distinguish coding and non-coding sequences. The Fisher''s discriminant algorithm is used to give the discriminant accuracies. The average discriminant accuracies pc, pnc, qc and qnc of all 51 prokaryotes obtained by the present method reach 69.08%, 83.34%, 72.08% and 83.54%, respectively.