Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems
High processing time is required to classify genomic sequences and to identify protein coding of a DNA sequence. While computer performance has been driven largely by decreasing the size of chips while increasing the number of transistors they contain, the current computing trend is multicore system...
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iium-271872013-02-15T07:40:13Z http://irep.iium.edu.my/27187/ Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems Gunawan, Teddy Surya Ambikairajah, Eliathamby TA164 Bioengineering High processing time is required to classify genomic sequences and to identify protein coding of a DNA sequence. While computer performance has been driven largely by decreasing the size of chips while increasing the number of transistors they contain, the current computing trend is multicore system in which two or more independent cores are integrated into a single package. This paper presents the parallel implementation of the gene and exon identification of DNA sequences using the previously developed modified Gabor wavelet transform on multicore systems. Single Program Multiple Data (SPMD) parallel paradigm will be used in the parallel implementation. Furthermore, the efficiency of the proposed algorithm will be analyzed using Amdahl’s law. 2012-02-27 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/27187/4/Parallel_implementation_of_genomic_sequences.pdf Gunawan, Teddy Surya and Ambikairajah, Eliathamby (2012) Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems. In: International Conference on Biomedical Engineering (ICoBE2012), 27-28 Feb 2012, Penang. (Unpublished) |
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International Islamic University Malaysia |
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TA164 Bioengineering |
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TA164 Bioengineering Gunawan, Teddy Surya Ambikairajah, Eliathamby Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
description |
High processing time is required to classify genomic sequences and to identify protein coding of a DNA sequence. While computer performance has been driven largely by decreasing the size of chips while increasing the number of transistors they contain, the current computing trend is multicore system in which two or more independent cores are integrated into a single package. This paper presents the parallel implementation of the gene and exon identification of DNA sequences using the previously developed modified Gabor wavelet transform on multicore systems. Single Program Multiple Data (SPMD) parallel paradigm will be used in the parallel implementation. Furthermore, the efficiency of the proposed algorithm will be analyzed using Amdahl’s law. |
format |
Conference or Workshop Item |
author |
Gunawan, Teddy Surya Ambikairajah, Eliathamby |
author_facet |
Gunawan, Teddy Surya Ambikairajah, Eliathamby |
author_sort |
Gunawan, Teddy Surya |
title |
Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
title_short |
Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
title_full |
Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
title_fullStr |
Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
title_full_unstemmed |
Parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
title_sort |
parallel implementation of genomic sequences classification using modified gabor wavelet transform on multicore systems |
publishDate |
2012 |
url |
http://irep.iium.edu.my/27187/ http://irep.iium.edu.my/27187/4/Parallel_implementation_of_genomic_sequences.pdf |
first_indexed |
2023-09-18T20:40:25Z |
last_indexed |
2023-09-18T20:40:25Z |
_version_ |
1777409327842197504 |