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A Comparative Analysis of Software Engineering Approaches for Sequence Analysis

A Comparative Analysis of Software Engineering Approaches for Sequence Analysis

Muneer Ahmad, Low Tang Jung, Noor Zaman
Copyright: © 2013 |Pages: 11
ISBN13: 9781466636798|ISBN10: 1466636793|EISBN13: 9781466636804
DOI: 10.4018/978-1-4666-3679-8.ch014
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MLA

Ahmad, Muneer, et al. "A Comparative Analysis of Software Engineering Approaches for Sequence Analysis." Software Development Techniques for Constructive Information Systems Design, edited by Khalid A. Buragga and Noor Zaman, IGI Global, 2013, pp. 285-295. https://doi.org/10.4018/978-1-4666-3679-8.ch014

APA

Ahmad, M., Jung, L. T., & Zaman, N. (2013). A Comparative Analysis of Software Engineering Approaches for Sequence Analysis. In K. Buragga & N. Zaman (Eds.), Software Development Techniques for Constructive Information Systems Design (pp. 285-295). IGI Global. https://doi.org/10.4018/978-1-4666-3679-8.ch014

Chicago

Ahmad, Muneer, Low Tang Jung, and Noor Zaman. "A Comparative Analysis of Software Engineering Approaches for Sequence Analysis." In Software Development Techniques for Constructive Information Systems Design, edited by Khalid A. Buragga and Noor Zaman, 285-295. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-3679-8.ch014

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Abstract

DNA is considered the building block of living species. DNA sequence alignment and analysis have been big challenges for the scientists for many years. This research presents a comparative analysis of state of the art software engineering approaches for sequence analysis, i.e. genome sequences in particular. Sequence analysis problems are NP hard and need optimal solutions. The underlying problems stated are duplicate sequence detection, sequence matching by relevance, and sequence analysis by approximate comparison in general and by using tools, i.e. Matlab and multi-lingual sequence analysis. The usefulness of these operations is also highlighted, and future expectations are described. The proposal describes the concepts, tools, methodologies, and algorithms being used for sequence analysis. The sequences contain the precious information that needs to be mined for useful purposes. There is high concentration required to model the optimal solution. The similarity and alignments concepts cannot be addressed directly with one technique or algorithm; a better performance is achieved by the comprehension of different concepts.

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