基于无导数神经网络的两两轮廓对齐动态规划评分函数优化
Optimizing scoring function of dynamic programming of pairwise profile alignment using derivative free neural network
摘要：
具有位置特异性评分矩阵（PSSM）的谱比较方法是最准确的比对方法之一。目前，余弦相似度和相关系数被用作动态规划的评分函数来计算PSSM之间的相似度。然而，不清楚这些函数对于轮廓对准方法是最佳的。至少，根据定义，这些函数不能捕获配置文件之间的非线性关系。因此，在本研究中，我们试图发现一种新的评分函数，这是更适合的轮廓比较方法比现有的。首先将传统的神经网络与进化策略优化方法相结合，实现了一种新的无导数神经网络。接下来，使用该框架，优化评分函数以用于比对远程序列对。Nepal，与具有现有功能的对准器相比，具有新评分功能的成对轮廓对准器显著提高了对准灵敏度和精度。Nepal改进了比对质量，因为它适应了远程序列比对并提高了相似性得分的表达能力。新的评分功能可以实现使用一个简单的矩阵运算，很容易纳入其他对齐。利用我们的评分函数，同源性检测和/或远程同源序列的多个序列比对的性能将进一步提高。
英文摘要：
A profile comparison method with position-specific scoring matrix (PSSM) is one of the most accurate alignment methods. Currently, cosine similarity and correlation coefficient are used as scoring functions of dynamic programming to calculate similarity between PSSMs. However, it is unclear that these functions are optimal for profile alignment methods. At least, by definition, these functions cannot capture non-linear relationships between profiles. Therefore, in this study, we attempted to discover a novel scoring function, which was more suitable for the profile comparison method than the existing ones. Firstly we implemented a new derivative free neural network by combining the conventional neural network with evolutionary strategy optimization method. Next, using the framework, the scoring function was optimized for aligning remote sequence pairs. Nepal, the pairwise profile aligner with the novel scoring function significantly improved both alignment sensitivity and precision, compared to aligners with the existing functions. Nepal improved alignment quality because of adaptation to remote sequence alignment and increasing the expressive power of similarity score. The novel scoring function can be realized using a simple matrix operation and easily incorporated into other aligners. With our scoring function, the performance of homology detection and/or multiple sequence alignment for remote homologous sequences would be further improved.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
