...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Soft computing: A fusion of foundations, methodologies and applications >A novel approach for predicting DNA splice junctions using hybrid machine learning algorithms
【24h】

A novel approach for predicting DNA splice junctions using hybrid machine learning algorithms

机译：使用混合机器学习算法预测DNA剪接点的新方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Accurate identification of splice junctions in a DNA sequence is an active area of research. The knowledge of splice junction's occurrence provides valuable information about its internal genomic structure and aids in its deeper analysis and interpretation. The major problems faced during gene analysis are diversity, complexity and the uncertainty nature of DNA sequences. The application of computational techniques using machine learning algorithms in this direction has attracted enormous attention in the last few decades. In this study, the development of hybrid machine learning ensembles approaches is presented that address the splice junction problem more effectively. Multiple classifier systems consisting of random subspace, rotation forest and boosting methods are implemented and are validated over the real genome sequence dataset. A novel feature selection technique based on attribute's correlation estimation using Best first strategy is proposed. The average prediction accuracy achieved is more than 98 % in identifying the splice junctions. All the computations are performed with 95 % confidence interval. The results presented in this study are superior as compared to the state-of-the-art approaches in the literature. This work strengthens the viability of expanding and using machine learning models to similar problems.
机译：准确鉴定DNA序列中的剪接点是研究的活跃领域。拼接连接的发生的知识提供了有关其内部基因组结构的有价值的信息，并有助于其更深入的分析和解释。基因分析过程中面临的主要问题是DNA序列的多样性，复杂性和不确定性。在过去的几十年中，使用机器学习算法的计算技术在这个方向上的应用引起了极大的关注。在这项研究中，提出了混合机器学习集成方法的发展，该方法可以更有效地解决拼接连接问题。实现了由随机子空间，旋转森林和增强方法组成的多个分类器系统，并在真实的基因组序列数据集上进行了验证。提出了一种基于属性相关估计的基于最佳优先策略的特征选择技术。在识别拼接结时，平均预测精度达到了98％以上。所有计算均以95％置信区间执行。与文献中的最新方法相比，本研究中提出的结果更好。这项工作增强了将机器学习模型扩展和使用到类似问题的可行性。

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