首页> 外文会议>International Conference on Grid and Cooperative Computing; 20061021-23; Hunan(CN) >Feature Mining and Integration for Improving the Prediction Accuracy of Translation Initiation Sites in Eukaryotic mRNAs
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Feature Mining and Integration for Improving the Prediction Accuracy of Translation Initiation Sites in Eukaryotic mRNAs

机译:特征挖掘和集成,提高真核mRNA翻译起始位点的预测准确性

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Accurate prediction of translation initiation sites (TISs) is important for the annotation of genomes.Although many methods have been proposed to solve this problem, the prediction accuracy is still limited. In this paper, the features that have been widely used for predicting TISs are further analyzed, and it is found that some features of TISs and non-TISs are heavily dependent on the C+G content of sequences around AUG codons, and some features are quite different for non-TISs located in untranslated regions and coding regions considering different reading frames. Further,the strategy of using multiple support vector machines to fully make use of the information is proposed, and a new program TISKey for the prediction of TISs is developed. Testing results on widely used dataset demonstrate that TISKey could get better prediction accuracy. TISKey can be accessed at http: //infosci. hust. edu. cn .
机译:准确预测翻译起始位点(TIS)对于基因组注释非常重要。尽管已经提出了许多解决此问题的方法,但预测准确性仍然受到限制。在本文中,进一步分析了广泛用于预测TIS的特征,发现TIS和非TIS的某些特征在很大程度上取决于AUG密码子周围序列的C + G含量,其中一些特征是考虑到不同的阅读框,位于非翻译区域和编码区域中的非TIS会有很大不同。此外,提出了使用多个支持向量机充分利用信息的策略,并开发了用于预测TIS的新程序TISKey。在广泛使用的数据集上的测试结果表明,TISKey可以获得更好的预测准确性。可以通过以下网址访问TISKey:http:// infosci。必要edu。 cn。

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