COVID-19 is a global pandemic that aroused the interest of scientists to prevent it and design a drug for it. Nowadays, presenting intelligent biological data analysis tools at a low cost is important to analyze the biological structure of COVID-19. The global alignment algorithm is one of the important bioinformatics tools that measure the most accurate similarity between a pair of biological sequences. The huge time consumption of the standard global alignment algorithm is its main limitation especially for sequences with huge lengths. This work proposed a fast global alignment tool (G-Aligner) based on meta-heuristic algorithms that estimate similarity measurements near the exact ones at a reasonable time with low cost. The huge length of sequences leads G-Aligner based on standard Sine–Cosine optimization algorithm (SCA) to trap in local minima. Therefore, an improved version of SCA was presented in this work that is based on integration with PSO. Besides, mutation and opposition operators are applied to enhance the exploration capability and avoiding trapping in local minima. The performance of the improved SCA algorithm (SP-MO) was evaluated on a set of IEEE CEC functions. Besides, G-Aligner based on the SP-MO algorithm was tested to measure the similarity of real biological sequence. It was used also to measure the similarity of the COVID-19 virus with the other 13 viruses to validate its performance. The tests concluded that the SP-MO algorithm has superiority over the relevant studies in the literature and produce the highest average similarity measurements 75% of the exact one.

COVID-19 是一种全球性流行病，引起了科学家们对其预防和设计药物的兴趣。如今，以低成本提供智能生物数据分析工具对于分析 COVID-19 的生物结构具有重要意义。全局比对算法是衡量一对生物序列之间最准确相似性的重要生物信息学工具之一。标准全局比对算法的巨大时间消耗是其主要限制，特别是对于长度很大的序列。这项工作提出了一种基于元启发式算法的快速全局对齐工具（G-Aligner），该算法可以在合理的时间内以低成本估计接近精确值的相似性测量。巨大的序列长度导致基于标准正余弦优化算法（SCA）的 G-Aligner 陷入局部最小值。因此，基于与 PSO 集成的这项工作提出了 SCA 的改进版本。此外，应用变异和反对算子来增强探索能力并避免陷入局部最小值。改进的 SCA 算法 (SP-MO) 的性能在一组 IEEE CEC 函数上进行了评估。此外，还测试了基于SP-MO算法的G-Aligner来衡量真实生物序列的相似度。它还用于测量 COVID-19 病毒与其他 13 种病毒的相似性，以验证其性能。