启动子识别是生物信息学的一个重要研究方向,根据启动子本身的特点已经有基于信号、内容和CpG岛等多种识别算法.针对基因序列数据数据量大、维数高、非线性的特点,提出了基于流形结构重建的启动子识别算法,先利用非线性降维方法压缩数据,然后再进行启动子识别.实验结果表明,该方法能够取得较好的结果.%Promoter recognition is one of the important research directions in bioinformatics. Due to the characteristics of the promoters, there have been many kinds of identification algorithms based on the signal, the content and the CpG islands. Gene sequences are large scale nonlinear data with high dimensionality, so a new promoter recognition method based on manifold reconstruction is proposed,u-sing nonlinear dimensionality reduction method to compress the data before promoter recognition. The experimental results show that this method can obain better results.
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