Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 문영식 | - |
dc.date.accessioned | 2020-04-13T02:04:18Z | - |
dc.date.available | 2020-04-13T02:04:18Z | - |
dc.date.issued | 2004-06 | - |
dc.identifier.citation | 대한전자공학회 학술대회, Page. 807-810 | en_US |
dc.identifier.uri | http://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE01715245&language=ko_KR | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/149398 | - |
dc.description.abstract | Although 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.iso | ko_KR | en_US |
dc.publisher | 대한전자공학회 | en_US |
dc.title | 퍼지 신경망을 이용한 유전자 데이터 분류 기법 | en_US |
dc.title.alternative | Classification of Gene Expression Data Using Membership Function and Neural Network | en_US |
dc.type | Article | en_US |
dc.contributor.googleauthor | 김재협 | - |
dc.contributor.googleauthor | 염해영 | - |
dc.contributor.googleauthor | 문영식 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF COMPUTING[E] | - |
dc.sector.department | DIVISION OF COMPUTER SCIENCE | - |
dc.identifier.pid | ysmoon | - |
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