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dc.contributor.author문영식-
dc.date.accessioned2020-04-13T02:04:18Z-
dc.date.available2020-04-13T02:04:18Z-
dc.date.issued2004-06-
dc.identifier.citation대한전자공학회 학술대회, Page. 807-810en_US
dc.identifier.urihttp://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE01715245&language=ko_KR-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/149398-
dc.description.abstractAlthough gene expression data classification has improved over the past 30 years, there has been no general approach for identifying new gene data classes (class discovery) or for assigning gene datato known classes (class prediction). Here, a approach to classification based on gene expression monitoring by DNA microarray is described and applied to human leukemias as a test case. Proposed method composed of membership generating procedure from gene expression data and neural networks. The results demonstrate the feasibility of gene expression classification based solely on gene expression monitoring.en_US
dc.language.isoko_KRen_US
dc.publisher대한전자공학회en_US
dc.title퍼지 신경망을 이용한 유전자 데이터 분류 기법en_US
dc.title.alternativeClassification of Gene Expression Data Using Membership Function and Neural Networken_US
dc.typeArticleen_US
dc.contributor.googleauthor김재협-
dc.contributor.googleauthor염해영-
dc.contributor.googleauthor문영식-
dc.sector.campusE-
dc.sector.daehakCOLLEGE OF COMPUTING[E]-
dc.sector.departmentDIVISION OF COMPUTER SCIENCE-
dc.identifier.pidysmoon-
Appears in Collections:
COLLEGE OF COMPUTING(소프트웨어융합대학)[E] > COMPUTER SCIENCE(소프트웨어학부) > Articles
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