Sirajuddin K, Nagashima T, Ono K
Department of Computer Science and Systems Engineering, Muroran Institute of Technology 27-1, Japan.
Comput Appl Biosci. 1995 Aug;11(4):349-59. doi: 10.1093/bioinformatics/11.4.349.
The splicing signals which govern the excision of introns are not yet well explained, since actual splice site sequences are to some extent different from the generally accepted consensus sequences. While a quantification method (categorical discriminant analysis: CDA) has been proposed to analyze splice site signals, sample sequences lying in the overlapping region of sample scores are not discriminated well by CDA, thus limiting the predictive ability of this analytical technique. In this paper, we propose a method to improve the performance of CDA, which is applicable to the analysis of 5'-splice site signals in various mammalian genes. The proposed algorithm has revealed a distinct enhancement in the predicting ability compared to that of traditional CDA and could explain point mutations in the 5'-splice site region of rabbit beta-globin gene fairly well.
由于实际的剪接位点序列在一定程度上与普遍接受的共有序列不同，因此控制内含子切除的剪接信号尚未得到很好的解释。虽然已经提出了一种定量方法（分类判别分析：CDA）来分析剪接位点信号，但位于样本分数重叠区域的样本序列不能被CDA很好地区分，从而限制了这种分析技术的预测能力。在本文中，我们提出了一种提高CDA性能的方法，该方法适用于分析各种哺乳动物基因中的5'-剪接位点信号。与传统的CDA相比，所提出的算法在预测能力上有显著提高，并且能够很好地解释兔β-珠蛋白基因5'-剪接位点区域的点突变。
