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KMID : 0379920010260010044
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Journal of The Korea Socity of Health Informatics and Statistics
2001 Volume.26 No. 1 p.44 ~ p.49
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Detection of Significant Genes in Microarrays
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박태성/Park, Tae Sung
이용성/이승연/이승묵/이성곤/강성현/최호식/Lee, Yong sung/Lee, Seung Yeoun/Lee, Seung Mook/Yi, Sung Kon/Kang, Seung Hyeon/Choi, Ho Sik
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Abstract
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Microarrays are novel biotechnologies which are being used increasingly in medical research. By allowing the monitoring of expression levels for thousands of genes simultaneously, such a microarray technique may lead to a more complete understanding of the molecular variations and may detect differentially expressed genes. However, except for some basic classification and clustering analyses, and testing procedures, not many sophisticated statistical analysis methods have been developed. In this paper, we consider a regression model approach to detect a differentially expressed genes in a single microarray and compare it with other approaches.
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