Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms

• Main Authors: Haihe Shi, Xuchu Zhang
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2020-02-01
• Series: Frontiers in Genetics
• Subjects: heuristic multiple sequence alignment algorithms; feature model; generative programming; component interaction model; partition and recur platform
• Online Access: https://www.frontiersin.org/article/10.3389/fgene.2020.00105/full

In recent years, there has been an explosive increase in the amount of bioinformatics data produced, but data are not information. The purpose of bioinformatics research is to obtain information with biological significance from large amounts of data. Multiple sequence alignment is widely used in sequence homology detection, protein secondary and tertiary structure prediction, phylogenetic tree analysis, and other fields. Existing research mainly focuses on the specific steps of the algorithm or on specific problems, and there is a lack of high-level abstract domain algorithm frameworks. As a result, multiple sequence alignment algorithms are complex, redundant, and difficult to understand, and it is not easy for users to select the appropriate algorithm, which may lead to computing errors. Here, through in-depth study and analysis of the heuristic multiple sequence alignment algorithm (HMSAA) domain, a domain-feature model and an interactive model of HMSAA components have been established according to the generative programming method. With the support of the PAR (partition and recur) platform, the HMSAA algorithm component library is formalized and a specific alignment algorithm is assembled, thus improving the reliability of algorithm assembly. This work provides a valuable theoretical reference for the applications of other biological sequence analysis algorithms.