Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.
PLoS Comput Biol. 2022 Nov 21;18(11):e1010665. doi: 10.1371/journal.pcbi.1010665. eCollection 2022 Nov.
In response to the imperfections of current sequence alignment methods, originated from the inherent serialism within their corresponding electrical systems, a few optical approaches for biological data comparison have been proposed recently. However, due to their low performance, raised from their inefficient coding scheme, this paper presents a novel all-optical high-throughput method for aligning DNA, RNA, and protein sequences, named HELIOS. The HELIOS method employs highly sophisticated operations to locate character matches, single or multiple mutations, and single or multiple indels within various biological sequences. On the other hand, the HELIOS optical architecture exploits high-speed processing and operational parallelism in optics, by adopting wavelength and polarization of optical beams. For evaluation, the functionality and accuracy of the HELIOS method are approved through behavioral and optical simulation studies, while its complexity and performance are estimated through analytical computation. The accuracy evaluations indicate that the HELIOS method achieves a precise pairwise alignment of two sequences, highly similar to those of Smith-Waterman, Needleman-Wunsch, BLAST, MUSCLE, ClustalW, ClustalΩ, T-Coffee, Kalign, and MAFFT. According to our performance evaluations, the HELIOS optical architecture outperforms all alternative electrical and optical algorithms in terms of processing time and memory requirement, relying on its highly sophisticated method and optical architecture. Moreover, the employed compact coding scheme highly escalates the number of input characters, and hence, it offers reduced time and space complexities, compared to the electrical and optical alternatives. It makes the HELIOS method and optical architecture highly applicable for biomedical applications.
针对当前序列比对方法的不完善之处，源于其相应电子系统中的固有序列化，最近提出了几种用于生物数据比较的光学方法。然而，由于其低效的编码方案导致性能低下，本文提出了一种新颖的全光学高通量方法，用于对齐 DNA、RNA 和蛋白质序列，名为 HELIOS。HELIOS 方法采用高度复杂的操作来定位各种生物序列中的字符匹配、单个或多个突变以及单个或多个插入缺失。另一方面，HELIOS 光学架构利用光学中的高速处理和操作并行性，通过采用光束的波长和偏振。为了进行评估，通过行为和光学模拟研究验证了 HELIOS 方法的功能和准确性，同时通过分析计算估计了其复杂性和性能。准确性评估表明，HELIOS 方法实现了两个序列的精确两两比对，高度类似于 Smith-Waterman、Needleman-Wunsch、BLAST、MUSCLE、ClustalW、ClustalΩ、T-Coffee、Kalign 和 MAFFT 的比对。根据我们的性能评估，HELIOS 光学架构在处理时间和内存需求方面优于所有替代的电气和光学算法，这依赖于其高度复杂的方法和光学架构。此外，所采用的紧凑编码方案极大地增加了输入字符的数量，因此与电气和光学替代方案相比，它提供了减少的时间和空间复杂度。这使得 HELIOS 方法和光学架构非常适用于生物医学应用。
