Computational identification of promoters and first exons in the human genome
Computational identification of promoters and first exons in the human genome
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DOI：
10.1038/ng780
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发表时间：
2001-12-01
期刊：
影响因子：
30.8
通讯作者：
Zhang, MQ
中科院分区：
文献类型：
--
作者：
Davuluri, RV;Grosse, I;Zhang, MQ
启动子和第一外显子的鉴定一直是基因发现中最困难的问题之一。我们提出了一套判别函数，可以识别结构和组成特征，如CpG岛，启动子区和第一剪接供体位点。我们解释的判别函数到一个决策树，构成一个新的程序称为FirstEF的实施。通过使用不同的模型来预测CpG相关和非CpG相关的第一外显子，我们通过交叉验证表明，该程序可以预测86%的第一外显子，假阳性率为17%。我们还通过将其应用于人类染色体21和22的完成序列以及通过将预测与实验验证的第一外显子的位置进行比较，证明了FirstEF在基因组水平上的预测准确性。最后，我们提出了分析预测的第一外显子的所有24条染色体的人类基因组。
The identification of promoters and first exons has been one of the most difficult problems in gene-finding. We present a set of discriminant functions that can recognize structural and compositional features such as CpG islands, promoter regions and first splice-donor sites. We explain the implementation of the discriminant functions into a decision tree that constitutes a new program called FirstEF. By using different models to predict CpG-related and non-CpG-related first exons, we showed by cross-validation that the program could predict 86% of the first exons with 17% false positives. We also demonstrated the prediction accuracy of FirstEF at the genome level by applying it to the finished sequences of human chromosomes 21 and 22 as well as by comparing the predictions with the locations of the experimentally verified first exons. Finally, we present the analysis of the predicted first exons for all of the 24 chromosomes of the human genome.