首页> 外文期刊>Journal of computational biology: A journal of computational molecular cell biology >Strong/Weak Feature Recognition of Promoters Based on Position Weight Matrix and Ensemble Set-Valued Models
【24h】

Strong/Weak Feature Recognition of Promoters Based on Position Weight Matrix and Ensemble Set-Valued Models

机译:基于位置重量矩阵和集合设定值模型的推动者强/弱特征识别

获取原文
获取原文并翻译 | 示例
           

摘要

In this article, we propose a method to recognize the strong/ weak property of the promoters based on the nucleotide sequence. To the best of our knowledge, it is the first time to predict the strong/weak property of the promoters. First, position weight matrix (PWM) is used to evaluate the contributions of the nucleotides to the promoter strength. Then, the set-valued model is used to describe the relation between the nucleotide sequence and the strength. Considering the small-sample and imbalance features of the promoter data, we propose an ensemble approach to predict the strong/ weak property of the promoters. The proposed method is used to recognize 60 d E promoters of Escherichia coli. The results show the effectiveness of the proposed method. This article provides a simple way for a biologist to evaluate the strong/ weak feature of promoters from the nucleotide sequence.
机译:在本文中,我们提出了一种方法来识别基于核苷酸序列的启动子的强/弱特征。 据我们所知,这是第一次预测启动子的强/弱财产。 首先,使用位置重量矩阵(PWM)来评估核苷酸对启动子强度的贡献。 然后,设定值模型用于描述核苷酸序列与强度之间的关系。 考虑到启动子数据的小样本和不平衡特征,我们提出了一种集合方法来预测启动子的强/弱财产。 该方法用于识别大肠杆菌的60 d E启动子。 结果表明了该方法的有效性。 本文为生物学家提供了一种简单的方法,以评估来自核苷酸序列的启动子的强/弱特征。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号