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Bhattacharyya distance for identifying differentially expressed genes in colon gene experiments

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dc.contributor.authorTian, X.W.-
dc.contributor.authorLim, J.S.-
dc.date.available2020-02-29T01:41:47Z-
dc.date.created2020-02-12-
dc.date.issued2013-
dc.identifier.issn0000-0000-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14949-
dc.description.abstractIdentify a small number of differentially expressed genes for accurate classification of gene samples is essential for the development of diagnostic tests. We present an approach for cancer molecular feature selection method based on their gene expression profiles. Tumor and normal colon tissues were classified in this research. The Bhattacharyya distance was used as the gene selection method to identify the small number of differentially expressed genes for the colon cancer analysis. Finally we selected 7 genes for the colon cancer analysis with 95.16% accuracy by using a fuzzy neural networks classifier. Compare with other colon cancer analysis results, our method selected the smallest number of differentially expressed genes and get the highest classification accuracy. © 2013 IEEE.-
dc.language영어-
dc.language.isoen-
dc.relation.isPartOf2013 International Conference on Information Science and Applications, ICISA 2013-
dc.subjectBhattacharyya distance-
dc.subjectClassification accuracy-
dc.subjectcolon-
dc.subjectDiagnostic tests-
dc.subjectDifferentially expressed gene-
dc.subjectGene expression profiles-
dc.subjectGene selection-
dc.subjectMolecular feature-
dc.subjectFuzzy neural networks-
dc.subjectGene expression-
dc.subjectInformation science-
dc.subjectDiseases-
dc.titleBhattacharyya distance for identifying differentially expressed genes in colon gene experiments-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.doi10.1109/ICISA.2013.6579506-
dc.identifier.bibliographicCitation2013 International Conference on Information Science and Applications, ICISA 2013-
dc.identifier.scopusid2-s2.0-84883757312-
dc.citation.title2013 International Conference on Information Science and Applications, ICISA 2013-
dc.contributor.affiliatedAuthorTian, X.W.-
dc.contributor.affiliatedAuthorLim, J.S.-
dc.type.docTypeConference Paper-
dc.subject.keywordAuthorbhattacharyya distance-
dc.subject.keywordAuthorcolon-
dc.subject.keywordAuthordifferentially expressed genes-
dc.subject.keywordAuthorfuzzy neural networks-
dc.subject.keywordAuthorgene expression profiles-
dc.subject.keywordPlusBhattacharyya distance-
dc.subject.keywordPlusClassification accuracy-
dc.subject.keywordPluscolon-
dc.subject.keywordPlusDiagnostic tests-
dc.subject.keywordPlusDifferentially expressed gene-
dc.subject.keywordPlusGene expression profiles-
dc.subject.keywordPlusGene selection-
dc.subject.keywordPlusMolecular feature-
dc.subject.keywordPlusFuzzy neural networks-
dc.subject.keywordPlusGene expression-
dc.subject.keywordPlusInformation science-
dc.subject.keywordPlusDiseases-
dc.description.journalRegisteredClassscopus-
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College of IT Convergence (컴퓨터공학부(컴퓨터공학전공))
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