title: Predicting promoters by pseudo-trinucleotide compositions based on discrete wavelets transform.
abstract: In this paper, the discrete wavelet transform was introduced into the trinucleotide compositions and a novel DNA sequence representation technique, namely pseudo-trinucleotide compositions was proposed. The pseudo-trinucleotide compositions based on discrete wavelets transform were then employed to model support vector machines (SVM) for the prediction of promoters. The model was evaluated on the genie dataset, and the overall prediction accuracy (ACC) by jackknife validation for the classification of promoters, introns and exons was 82.46%, while the ACC for the classification of promoters and unpromoters was 82.18%, which was far better than the previous results. The satisfied prediction result revealed that the pseudo-trinucleotide composition based on discrete wavelet transform was an effective representation method for DNA sequence, and plays a very important role in the prediction of DNA function.
authors.affiliation: School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, PR China. veego_z@hotmail.com
authors.forename: Xuan
authors.initials: X
authors.lastname: Zhou
authors.forename: Zhanchao
authors.initials: Z
authors.lastname: Li
authors.forename: Zong
authors.initials: Z
authors.lastname: Dai
authors.forename: Xiaoyong
authors.initials: X
authors.lastname: Zou
mesh_terms: D030561:Databases, Nucleic Acid; D011401:Promoter Regions, Genetic / Q000502:physiology*; D017422:Sequence Analysis, DNA / Q000379:methods*; D060388:Support Vector Machine