模式匹配性能比较作为丙型肝炎病毒(HCV)序列DNA的大数据分析建议

Berlian Al Kindhi, T. A. Sardjono
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引用次数: 9

摘要

如果挖掘得当,数据库可以提供非常有用的信息为了最优提取数据,可以通过观察数据的容量和特征来进行数据挖掘;因此,它可以按照预期在数据库中生成知识发现。例如,在基因库中,每一个DNA记录,至少有一万个序列记录。如果数据超过一百条记录,那么要处理的数据将是一个大序列。丙型肝炎病毒(HCV)是一种可以通过血液感染人类的肝脏疾病。HCV感染可以是无症状的,也可以是急性、慢性肝炎,甚至肝硬化。丙型肝炎在早期阶段一般不表现出症状。大约75%的丙型肝炎患者直到几年后肝脏受损才意识到自己已经感染了丙型肝炎。因此,无论是否感染HCV,都需要进行序列DNA挖掘来分析DNA历史。本研究比较了几种字符串匹配方法,以发现哪种方法在处理DNA挖掘中具有最佳性能。此外,本研究还分析了DNA HCV基因突变趋势,作为DNA挖掘数据库中的知识发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pattern Matching Performance Comparisons as Big Data Analysis Recommendations for Hepatitis C Virus (HCV) Sequence DNA
A data bank can provide very useful information while mined properly.[27] In order to be optimally extracted, data mining can be done by observing capacity and characteristics of the data; so it can generates Knowledge Discovery in Databases as expected. For instance in Gene Bank, every single record of DNA, there are at least ten thousand sequences recorded. If the data is more than a hundred records, it will be a big sequence of data to be processed. Hepatitis C Virus (HCV) is a liver disease which can infect humans through blood. HCV infection can be asymptomatic, or it can be hepatitis acute, chronic, furthermore cirrhosis. Hepatitis C is generally does not show symptoms in the early stages. About 75 percent people with hepatitis C did not realize that they had infected until liver damage years later. Therefore needed a sequences DNA Mining is needed to analyse the DNA history whether it is infected by HCV or not. This study compares several methods of string matching to discover which methods have the best performance in processing DNA mining. In addition, this study also analyzed DNA HCV genetic mutations trend as a Knowledege Discovery in Database in DNA mining.
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