小波变换及滚球算法在单分子荧光能量共振转移图像分析中的应用

单分子荧光共振能量转移技术是通过检测单个分子内的荧光供体及受体间荧光能量转移的效率来研究分子构象的变化．要得到这些生物大分子的信息就需要对大量的单分子信号进行统计分析，人工分析这些信息，既费时费力又不具备客观性和可重复性，因此本文将小波变换及滚球算法应用到单分子荧光能量共振转移图像中对单分子信号进行统计分析．在保证准确检测到单分子信号的前提下，文章对滚球算法和小波变换算法处理图像后的线性进行了分析，结果表明，滚球算法和小波变换算法不但能够很好地去除单分子FRET图像的背景噪声，同时还能很好地保持单分子荧光信号的线性．最后本文还利用滚球算法处理单分子FRET图像及统计15 bp DNA的FRET效率的直方图，通过计算得到了15 bp DNA的FRET效率值．

Application of Wavelet Transform Algorithm and Rolling Ball Algorithm in Single Molecule Fluorescence Resonance Energy Transfer Images

Single molecule fluorescence resonance energy transfer (smFRET) is a technique used to study the conformational change of a molecule by detecting the transfer efficiency of fluorescence energy between donor and acceptor fluorescence inside a single molecule. However, to obtain the information of these biological macromolecules, the statistical analysis of a large number of single molecular signals is required. Manual analysis is time-consuming and laborious and lacks objectivity and reproducibility. Therefore, the wavelet transform and rolling ball algorithms are applied to smFRET images to analyze single molecule signals. Based on the accurate detection of single molecule signals, we analyzed the linearity of the images processed by the rolling ball and wavelet transform algorithms. The results show that the two methods can not only remove the background noise of smFRET images but also maintain the linearity of single molecule fluorescence signals. At the end of this paper, we draw a statistics histogram of 15 bp DNA FRET efficiency and calculated the FRET efficiency value using rolling ball algorithm processing.