Classification of Short Human Exons and Introns based on Statistical Features
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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.
Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)