Shi Haipeng, Shi Haihe, Xu Shenghua
School of Information Management, Jiangxi University of Finance and Economics, Nanchang, China.
School of Software, Jiangxi Normal University, Nanchang, China.
Front Genet. 2021 Feb 4;11:628175. doi: 10.3389/fgene.2020.628175. eCollection 2020.
As a key algorithm in bioinformatics, sequence alignment algorithm is widely used in sequence similarity analysis and genome sequence database search. Existing research focuses mainly on the specific steps of the algorithm or is for specific problems, lack of high-level abstract domain algorithm framework. Multiple sequence alignment algorithms are more complex, redundant, and difficult to understand, and it is not easy for users to select the appropriate algorithm; some computing errors may occur. Based on our constructed pairwise sequence alignment algorithm component library and the convenient software platform PAR, a few expansion domain components are developed for multiple sequence alignment application domain, and specific multiple sequence alignment algorithm can be designed, and its corresponding program, i.e., C++/Java/Python program, can be generated efficiently and thus enables the improvement of the development efficiency of complex algorithms, as well as accuracy of sequence alignment calculation. A star alignment algorithm is designed and generated to demonstrate the development process.
作为生物信息学中的一种关键算法，序列比对算法在序列相似性分析和基因组序列数据库搜索中得到了广泛应用。现有研究主要集中在算法的具体步骤或针对特定问题，缺乏高层次的抽象领域算法框架。多序列比对算法更为复杂、冗余且难以理解，用户不易选择合适的算法；还可能出现一些计算错误。基于我们构建的双序列比对算法组件库和便捷的软件平台PAR，针对多序列比对应用领域开发了一些扩展域组件，可以设计特定的多序列比对算法，并能高效生成其相应的程序，即C++/Java/Python程序，从而提高复杂算法的开发效率以及序列比对计算的准确性。设计并生成了一种星型比对算法来演示开发过程。
