Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling
Bioinformatics is a branch of science that uses computers, algorithms, and databases to solve biological problems. To achieve more accurate results, researchers need to use large and complex datasets. Sequence alignment is a well-known field of bioinformatics that allows the comparison of different...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/11/12/5426 |
| _version_ | 1797530560718962688 |
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| author | Doaa M. Talaat Dorgham Nahla A. Belal Walid Abdelmoez |
| author_facet | Doaa M. Talaat Dorgham Nahla A. Belal Walid Abdelmoez |
| author_sort | Doaa M. Talaat Dorgham |
| collection | DOAJ |
| description | Bioinformatics is a branch of science that uses computers, algorithms, and databases to solve biological problems. To achieve more accurate results, researchers need to use large and complex datasets. Sequence alignment is a well-known field of bioinformatics that allows the comparison of different genomic sequences. The comparative genomics field allows the comparison of different genomic sequences, leading to benefits in areas such as evolutionary biology, agriculture, and human health (e.g., mutation testing connects unknown genes to diseases). However, software engineering best practices, such as software performance engineering, are not taken into consideration in most bioinformatics tools and frameworks, which may lead to serious performance problems. Having an estimate of the software performance in the early phases of the Software Development Life Cycle (SDLC) is beneficial in making better decisions relating to the software design. Software performance engineering provides a reliable and observable method to build systems that can achieve their required performance goals. In this paper, we introduce the use of the Palladio Component Modeling (PCM) methodology to predict the performance of a sequence alignment system. Software performance engineering was not considered during the original system development. As a result of the performance analysis, an alternative design is proposed. Comparing the performance of the proposed design against the one already developed, a better response time is obtained. The response time of the usage scenario is reduced from 16 to 8.6 s. The study results show that using performance models at early stages in bioinformatics systems can help to achieve better software system performance. |
| first_indexed | 2024-03-10T10:30:45Z |
| format | Article |
| id | doaj.art-e470cbac27d147568f0e545da5d79eac |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T10:30:45Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-e470cbac27d147568f0e545da5d79eac2023-11-21T23:40:46ZengMDPI AGApplied Sciences2076-34172021-06-011112542610.3390/app11125426Early Performance Prediction in Bioinformatics Systems Using Palladio Component ModelingDoaa M. Talaat Dorgham0Nahla A. Belal1Walid Abdelmoez2College of Computing and Information Technology, Arab Academy for Science, Technology, and Maritime Transport, Alexandria 1029, EgyptCollege of Computing and Information Technology, Arab Academy for Science, Technology, and Maritime Transport, Alexandria 1029, EgyptCollege of Computing and Information Technology, Arab Academy for Science, Technology, and Maritime Transport, Alexandria 1029, EgyptBioinformatics is a branch of science that uses computers, algorithms, and databases to solve biological problems. To achieve more accurate results, researchers need to use large and complex datasets. Sequence alignment is a well-known field of bioinformatics that allows the comparison of different genomic sequences. The comparative genomics field allows the comparison of different genomic sequences, leading to benefits in areas such as evolutionary biology, agriculture, and human health (e.g., mutation testing connects unknown genes to diseases). However, software engineering best practices, such as software performance engineering, are not taken into consideration in most bioinformatics tools and frameworks, which may lead to serious performance problems. Having an estimate of the software performance in the early phases of the Software Development Life Cycle (SDLC) is beneficial in making better decisions relating to the software design. Software performance engineering provides a reliable and observable method to build systems that can achieve their required performance goals. In this paper, we introduce the use of the Palladio Component Modeling (PCM) methodology to predict the performance of a sequence alignment system. Software performance engineering was not considered during the original system development. As a result of the performance analysis, an alternative design is proposed. Comparing the performance of the proposed design against the one already developed, a better response time is obtained. The response time of the usage scenario is reduced from 16 to 8.6 s. The study results show that using performance models at early stages in bioinformatics systems can help to achieve better software system performance.https://www.mdpi.com/2076-3417/11/12/5426software performance engineeringbioinformaticsPalladio Component Modeling (PCM) |
| spellingShingle | Doaa M. Talaat Dorgham Nahla A. Belal Walid Abdelmoez Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling Applied Sciences software performance engineering bioinformatics Palladio Component Modeling (PCM) |
| title | Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling |
| title_full | Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling |
| title_fullStr | Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling |
| title_full_unstemmed | Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling |
| title_short | Early Performance Prediction in Bioinformatics Systems Using Palladio Component Modeling |
| title_sort | early performance prediction in bioinformatics systems using palladio component modeling |
| topic | software performance engineering bioinformatics Palladio Component Modeling (PCM) |
| url | https://www.mdpi.com/2076-3417/11/12/5426 |
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