Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms
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 se...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2020-02-01
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| Series: | Frontiers in Genetics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/article/10.3389/fgene.2020.00105/full |
| _version_ | 1819199890036621312 |
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| author | Haihe Shi Xuchu Zhang |
| author_facet | Haihe Shi Xuchu Zhang |
| author_sort | Haihe Shi |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-23T03:23:31Z |
| format | Article |
| id | doaj.art-068a50e61b2a46a19a4cc60789b8d4a5 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-12-23T03:23:31Z |
| publishDate | 2020-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Genetics |
| spelling | doaj.art-068a50e61b2a46a19a4cc60789b8d4a52022-12-21T18:01:54ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-02-011110.3389/fgene.2020.00105506816Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment AlgorithmsHaihe ShiXuchu ZhangIn 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.https://www.frontiersin.org/article/10.3389/fgene.2020.00105/fullheuristic multiple sequence alignment algorithmsfeature modelgenerative programmingcomponent interaction modelpartition and recur platform |
| spellingShingle | Haihe Shi Xuchu Zhang Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms Frontiers in Genetics heuristic multiple sequence alignment algorithms feature model generative programming component interaction model partition and recur platform |
| title | Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms |
| title_full | Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms |
| title_fullStr | Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms |
| title_full_unstemmed | Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms |
| title_short | Component-Based Design and Assembly of Heuristic Multiple Sequence Alignment Algorithms |
| title_sort | component based design and assembly of heuristic multiple sequence alignment algorithms |
| topic | heuristic multiple sequence alignment algorithms feature model generative programming component interaction model partition and recur platform |
| url | https://www.frontiersin.org/article/10.3389/fgene.2020.00105/full |
| work_keys_str_mv | AT haiheshi componentbaseddesignandassemblyofheuristicmultiplesequencealignmentalgorithms AT xuchuzhang componentbaseddesignandassemblyofheuristicmultiplesequencealignmentalgorithms |