A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform
The problems of biological sequence analysis have great theoretical and practical value in modern bioinformatics. Numerous solving algorithms are used for these problems, and complex similarities and differences exist among these algorithms for the same problem, causing difficulty for researchers to...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Tsinghua University Press
2023-03-01
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| Series: | Big Data Mining and Analytics |
| Subjects: | |
| Online Access: | https://www.sciopen.com/article/10.26599/BDMA.2022.9020030 |
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| _version_ | 1832557688081350656 |
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| author | Haipeng Shi Huan Chen Qinghong Yang Jun Wang Haihe Shi |
| author_facet | Haipeng Shi Huan Chen Qinghong Yang Jun Wang Haihe Shi |
| author_sort | Haipeng Shi |
| collection | DOAJ |
| description | The problems of biological sequence analysis have great theoretical and practical value in modern bioinformatics. Numerous solving algorithms are used for these problems, and complex similarities and differences exist among these algorithms for the same problem, causing difficulty for researchers to select the appropriate one. To address this situation, combined with the formal partition-and-recur method, component technology, domain engineering, and generic programming, the paper presents a method for the development of a family of biological sequence analysis algorithms. It designs highly trustworthy reusable domain algorithm components and further assembles them to generate specifific biological sequence analysis algorithms. The experiment of the development of a dynamic programming based LCS algorithm family shows the proposed method enables the improvement of the reliability, understandability, and development efficiency of particular algorithms. |
| format | Article |
| id | doaj-art-14e5b03a71474c5d8f3ac325179fde7f |
| institution | Kabale University |
| issn | 2096-0654 |
| language | English |
| publishDate | 2023-03-01 |
| publisher | Tsinghua University Press |
| record_format | Article |
| series | Big Data Mining and Analytics |
| spelling | doaj-art-14e5b03a71474c5d8f3ac325179fde7f2025-02-03T03:00:39ZengTsinghua University PressBig Data Mining and Analytics2096-06542023-03-0161112010.26599/BDMA.2022.9020030A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR PlatformHaipeng Shi0Huan Chen1Qinghong Yang2Jun Wang3Haihe Shi4School of Software, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, ChinaSchool of Computer and Information Engineering, Jiangxi Normal University, Nanchang 330022, ChinaThe problems of biological sequence analysis have great theoretical and practical value in modern bioinformatics. Numerous solving algorithms are used for these problems, and complex similarities and differences exist among these algorithms for the same problem, causing difficulty for researchers to select the appropriate one. To address this situation, combined with the formal partition-and-recur method, component technology, domain engineering, and generic programming, the paper presents a method for the development of a family of biological sequence analysis algorithms. It designs highly trustworthy reusable domain algorithm components and further assembles them to generate specifific biological sequence analysis algorithms. The experiment of the development of a dynamic programming based LCS algorithm family shows the proposed method enables the improvement of the reliability, understandability, and development efficiency of particular algorithms.https://www.sciopen.com/article/10.26599/BDMA.2022.9020030partition-and-recur (par)domain engineeringbiological sequencesfeature modelcomponent assembly |
| spellingShingle | Haipeng Shi Huan Chen Qinghong Yang Jun Wang Haihe Shi A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform Big Data Mining and Analytics partition-and-recur (par) domain engineering biological sequences feature model component assembly |
| title | A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform |
| title_full | A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform |
| title_fullStr | A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform |
| title_full_unstemmed | A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform |
| title_short | A Method for Bio-Sequence Analysis Algorithm Development Based on the PAR Platform |
| title_sort | method for bio sequence analysis algorithm development based on the par platform |
| topic | partition-and-recur (par) domain engineering biological sequences feature model component assembly |
| url | https://www.sciopen.com/article/10.26599/BDMA.2022.9020030 |
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