对遗传数据进行分析，实现阿尔茨海默病数据库的压缩算法

2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES) Pub Date : 2010-11-01 DOI:10.1109/IECBES.2010.5742291

I. Yassin, H. Z. Abidin, R. Baharom, E. H. Mat Saat, A. Zabidi

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引用次数: 1

摘要

一个存储阿尔茨海默病(AD)患者遗传信息的数据库对于促进适合当地患者的药物开发研究是必要的。Abdul Rahman等人的作品创建了这个数据库。然而，该数据库包含大量冗余的遗传数据。未压缩数据的存储是次优的，因为它会消耗大量的存储空间，并降低网络传输速度。本文提出将压缩算法集成到AD遗传数据库中，以优化其存储空间。我们描述了我们的实施和结果。压缩算法成功地将AD数据库的存储空间减少到原来存储空间的38.89%。

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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 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.

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2010 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES)

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