title: Classification of short human exons and introns based on statistical features.
abstract: The classification of human gene sequences into exons and introns is a difficult problem in DNA sequence analysis. In this paper, we define a set of features, called the simple Z (SZ) features, which is derived from the Z-curve features for the recognition of human exons and introns. The classification results show that SZ features, while fewer in numbers (three in total), can preserve the high recognition rate of the original nine Z-curve features. Since the size of SZ features is one-third of the Z-curve features, the dimensionality of the feature space is much smaller, and better recognition efficiency is achieved. If the stop codon feature is used together with the three SZ features, a recognition rate of up to 92% for short sequences of length <140 bp can be obtained.
authors.affiliation: Department of Computer Engineering and Information Technology, City University of Hong Kong, Kowloon, Hong Kong. itwyh@cityu.edu.hk
authors.forename: Yonghui
authors.initials: Y
authors.lastname: Wu
authors.forename: Alan Wee-Chung
authors.initials: AW
authors.lastname: Liew
authors.forename: Hong
authors.initials: H
authors.lastname: Yan
authors.forename: Mengsu
authors.initials: M
authors.lastname: Yang
mesh_terms: D000465:Algorithms; D001703:Biophysics / Q000379:methods; D003062:Codon; D018388:Codon, Terminator; D019295:Computational Biology / Q000379:methods*; D005091:Exons; D006801:Humans; D007438:Introns; D008957:Models, Genetic; D015233:Models, Statistical; D017422:Sequence Analysis, DNA / Q000379:methods*
chemical_list: D003062:Codon; D018388:Codon, Terminator