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Impact of Normalization Techniques in Microarray Data Analysi

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dc.contributor.author Thant, Lwin May
dc.contributor.author Phyu, Sabai
dc.date.accessioned 2022-07-05T04:12:08Z
dc.date.available 2022-07-05T04:12:08Z
dc.date.issued 2021-02-25
dc.identifier.uri https://onlineresource.ucsy.edu.mm/handle/123456789/2727
dc.description.abstract In a medical problem, investigation of powerful new tools is involved in essential role of high-throughput sequencing technologies. Microarray data sequencers produced a large and complex sets of data for the advancement of computational and statistical methods are appliance in the data analysis of medical area. In recent years, the researchers have processed on different methods that can accurately come out the gene expression on microarray data. In this paper, the several normalization algorithms for the analysis of RNA-seq differential data with differential species values are reviewed. Based on the studies, we present the reviews of normalization algorithms according their data nature to get the accurate data for building effective model. en_US
dc.language.iso en en_US
dc.publisher ICCA en_US
dc.subject microarray data, normalization, methods, techniques, features en_US
dc.title Impact of Normalization Techniques in Microarray Data Analysi en_US
dc.type Presentation en_US


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