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Efficient Analysis of Clinical Genomic Database
S. Dasgupta,
Published in Springer
2020
Volume: 990
   
Pages: 233 - 241
Abstract
Clinical genomic database is a database consisting of human genomic data which can be analysed to get information about diagnosis of a particular disease. Data mining is the process of extracting meaningful information from data stored in huge database. Among several data mining algorithms Association rule mining algorithm is used for frequent pattern analysis. In case of Clinical genomic database, Association rule mining algorithm can be used for determination of genes which are responsible for a particular disease. However sequential implementation will consume a lot of processing time. In order to increase the speed of processing parallel implementation Association Rule mining algorithm can be used. In this paper parallel implementation of Association Rule mining algorithm using analytical big data technology have been proposed for efficient analysis of Clinical genomic database. © 2020, Springer Nature Singapore Pte Ltd.
About the journal
JournalData powered by TypesetAdvances in Intelligent Systems and Computing
PublisherData powered by TypesetSpringer
ISSN21945357