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Enhanced HMM for the Recognition of Sigma70 Promoters in Escherichia coli

机译:增强培养型肝脏在大肠杆菌中识别Sigma70启动子

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In this paper, we propose an enhanced HMM for the recognition of sigma70 promoters in E. coli. HMMs for -10 and -35 boxes have been proposed to model the positional dependency of motifs which is lost in methods based on weight matrices. We also propose to use a set of spacer states sharing the observation densities to achieve the desired spacer duration probability functions. We have conducted two sets of experiments on recognizing promoters and locating DNA binding sites and the proposed method has achieved very promising results in comparison with earlier neural network approaches.
机译:在本文中,我们提出了一种增强的HMM,用于识别大肠杆菌中的Sigma70启动子。已经提出了-10和-35盒的HMMS以模拟基于权重矩阵的方法丢失的图案的位置依赖性。我们还建议使用一组间隔国家共享观察密度以实现所需的间隔持续时间概率函数。我们对识别启动子进行两组实验,并定位DNA结合位点,并且所提出的方法与早期的神经网络方法相比,实现了非常有前途的结果。

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