...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>BMC Veterinary Research >Prediction of protein-RNA residue-base contacts using two-dimensional conditional random field with the lasso
【24h】

Prediction of protein-RNA residue-base contacts using two-dimensional conditional random field with the lasso

机译：带有套索的二维条件随机场预测蛋白质-RNA残基与蛋白质的接触

获取原文
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

BackgroundTo uncover molecular functions and networks in biological cellular systems, it is important to dissect interactions between proteins and RNAs. Many studies have been performed to investigate and analyze interactions between protein amino acid residues and RNA bases. In terms of interactions between residues in proteins, it is generally accepted that an amino acid residue at interacting sites has coevolved together with the partner residue in order to keep the interaction between residues in proteins. Based on this hypothesis, in our previous study to identify residue-residue contact pairs in interacting proteins, we made calculations of mutual information (M I) between amino acid residues from some multiple sequence alignment of homologous proteins, and combined it with a discriminative random field (DRF) approach, which is a special type of conditional random fields (CRFs) and has been proved useful for the purpose of extracting distinguishing areas from a photograph in the image processing field. Recently, the evolutionary correlation of interactions between residues and DNA bases has also been found in certain transcription factors and the DNA-binding sites.ResultsIn this paper, we employ more generic two-dimensional CRFs than such DRFs to predict interactions between protein amino acid residues and RNA bases. In addition, we introduce labels representing kinds of amino acids and bases as local features of a CRF. Furthermore, we examine the utility of L 1-norm regularization (lasso) for the CRF. For evaluation of our method, we use residue-base interactions between several Pfam domains and Rfam entries, conduct cross-validation, and calculate the average AUC (Area under ROC Curve) score. The results suggest that our CRF-based method using mutual information and labels with the lasso is useful for further improving the performance, especially provided that the features of CRF are successfully reduced by the lasso approach.ConclusionsWe propose simple and generic two-dimensional CRF models using labels and mutual information with the lasso. Use of the CRF-based method in combination with the lasso is particularly useful for predicting the residue-base contacts in protein-RNA interactions.
机译：背景技术要揭示生物细胞系统中的分子功能和网络，剖析蛋白质与RNA之间的相互作用非常重要。已经进行了许多研究以调查和分析蛋白质氨基酸残基与RNA碱基之间的相互作用。就蛋白质中残基之间的相互作用而言，为了保持蛋白质中残基之间的相互作用，通常认为相互作用位点处的氨基酸残基已经与伴侣残基一起共同进化。基于这一假设，在我们先前的研究中，我们确定了相互作用蛋白中的残基-残基接触对，我们根据某些同源蛋白的多序列比对计算了氨基酸残基之间的互信息（MI），并将其与判别性随机场结合（DRF）方法，它是一种特殊类型的条件随机场（CRF），并已被证明可用于从图像处理领域的照片中提取区分区域的目的。最近，在某些转录因子和DNA结合位点也发现了残基与DNA碱基之间相互作用的进化相关性。结果在本文中，我们使用比此类DRF更通用的二维CRF来预测蛋白质氨基酸残基之间的相互作用。和RNA碱基。另外，我们介绍了代表CRF局部特征的代表氨基酸和碱基种类的标签。此外，我们研究了CRF的L 1 -范数正则化（套索）的效用。为了评估我们的方法，我们使用了多个Pfam域和Rfam条目之间的残基相互作用，进行交叉验证，并计算平均AUC（ROC曲线下的面积）得分。结果表明，我们基于互斥信息和带有套索的标签的基于CRF的方法对于进一步提高性能非常有用，特别是在套索方法成功地降低了CRF的特征的情况下。结论我们提出了简单且通用的二维CRF模型使用标签和套索的共同信息。基于CRF的方法与套索的结合使用对于预测蛋白质-RNA相互作用中的残基-碱基接触特别有用。

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