Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database
A database to store genetic information of Alzheimer's Disease (AD) patients is necessary to spur research in development of drugs suitable for local patients. Works by Abdul Rahman et. al. had created this database. However, the database contains large amounts of redundant genetic data. The st...
Published in: | Proceedings of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010 |
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2-s2.0-79955449868 Yassin I.M.; Abidin H.Z.; Baharom R.; Mat Saat E.H.; Zabidi A. Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database 2010 Proceedings of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010 10.1109/IECBES.2010.5742291 https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955449868&doi=10.1109%2fIECBES.2010.5742291&partnerID=40&md5=08d33edd4705bb37c2b87014f8ef5a32 A database to store genetic information of Alzheimer's Disease (AD) patients is necessary to spur research in development of drugs suitable for local patients. Works by Abdul Rahman et. al. had created this database. However, the database contains large amounts of redundant genetic data. The storage of uncompressed data is suboptimal because it would consume large storage space as well as slow down transmissions over networks. In this paper, we propose the integration of compression algorithm into the AD genetic database to optimize its storage space. We describe our implementation as well as the results. The compression algorithm had managed to reduce the storage space of the AD database to 38.89% of the original storage space. © 2010 IEEE. English Conference paper |
author |
Yassin I.M.; Abidin H.Z.; Baharom R.; Mat Saat E.H.; Zabidi A. |
spellingShingle |
Yassin I.M.; Abidin H.Z.; Baharom R.; Mat Saat E.H.; Zabidi A. Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
author_facet |
Yassin I.M.; Abidin H.Z.; Baharom R.; Mat Saat E.H.; Zabidi A. |
author_sort |
Yassin I.M.; Abidin H.Z.; Baharom R.; Mat Saat E.H.; Zabidi A. |
title |
Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
title_short |
Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
title_full |
Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
title_fullStr |
Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
title_full_unstemmed |
Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
title_sort |
Analysis of genetic data in for implementation of compression algorithm in Alzheimer's disease database |
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2010 |
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Proceedings of 2010 IEEE EMBS Conference on Biomedical Engineering and Sciences, IECBES 2010 |
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doi_str_mv |
10.1109/IECBES.2010.5742291 |
url |
https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955449868&doi=10.1109%2fIECBES.2010.5742291&partnerID=40&md5=08d33edd4705bb37c2b87014f8ef5a32 |
description |
A database to store genetic information of Alzheimer's Disease (AD) patients is necessary to spur research in development of drugs suitable for local patients. Works by Abdul Rahman et. al. had created this database. However, the database contains large amounts of redundant genetic data. The storage of uncompressed data is suboptimal because it would consume large storage space as well as slow down transmissions over networks. In this paper, we propose the integration of compression algorithm into the AD genetic database to optimize its storage space. We describe our implementation as well as the results. The compression algorithm had managed to reduce the storage space of the AD database to 38.89% of the original storage space. © 2010 IEEE. |
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English |
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Scopus |
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1809677914956890112 |