The identification of human cryptic ezons based on SVM
Alternative splicing is the main mechanism expanding proteome diversity. Cryptic exon is an important alternative splicing form that is different from skipped exon in statistical characters. We introduce a process to identify the human cryptic exons in candidate ones. This method contains two steps performed by two classifiers based on the support vector machine (SVM). The first classifier distinguishes authentic exons from pseudo exons; the second classifier distinguishes cryptic exons from constitutive and skipped exons. It can achieve the accuracy of 94.25％ and 69.75％ in the two steps, respectively. This method uses no expressed sequence tags (ESTs) or conservation information, so it can be used more widely and easily. The performances are higher than an existing method predicting splice sites of cryptic exons.
Cryptic ezons Support vector machine (SVM) Authentic ezons Sequence features
Gang Su Ying-Fei Sun Jun Li
School of Information Science and Engineering,Graduate University of Chinese Academy of Sciences,Bei Fundamental Department of Armored Force Engineering Academy,Beijing,P.R.China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）