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A Novel Method for Splice Sites Recognition Using Comprehensive Information

机译:采用综合信息剪切网站识别的新方法

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To identify splice sites more accurately and efficiently, a method for the recognition of splice sites based on comprehensive information is proposed. By analyzing the splicing signals, splicing sequences, secondary structures of flank sequence, different splicing factor mechanism of action and other characteristics of donor sites and acceptor sites, donor sites identification signal model, acceptor sites identification signal model, donor sites identification sequence model, acceptor sites identification sequence model were built respectively. Then the Mfold package in Vienna soft was used to predict the most stable secondary structure of flank sequences. The traditional four-letter alphabet was converted into eight-letter alphabet sequence. The sequence-structure combination strings were used for training signal models, sequence models, then recognized splice sites by the well trained models. Our results show that the accuracy of splice site recognition is greater than 95%, suggesting that the method has great potential to achieve a good performance for splice sites identification.
机译:为了更准确且有效地识别接头站点,提出了一种基于综合信息识别剪接站点的方法。通过分析拼接信号,拼接序列,侧翼序列的二次结构,不同的剪接因子机制和施主部位的其他特征和受体部位,施主网站识别信号模型,受体网站识别信号模型,捐赠部位识别序列模型,受体站点分别构建了识别序列模型。然后使用维也纳软件的MFOLD包装来预测侧面序列最稳定的二级结构。传统的四个字母字母表被转换为八个字母的字母序列。序列结构组合字符串用于训练信号模型,序列模型,然后通过训练良好的模型识别剪接位点。我们的研究结果表明,拼接站点识别的准确性大于95%,表明该方法具有巨大的潜力,以实现接头位点识别的良好性能。

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