| 학회 |
한국화학공학회 |
| 학술대회 |
2001년 가을 (10/19 ~ 10/20, 한밭대학교) |
| 권호 |
7권 2호, p.2937 |
| 발표분야 |
공정시스템 |
| 제목 |
다변량 통계분석에 의한 간암관련 특이 유전자 발굴과 해석 |
| 초록 |
Numerous approaches have been used to scrutinize the genetic causes or composition of HCC. Methods used to identify overexpressed genes include serial analysis of gene expression, PCR and Northern blotting. However, none of these techniques provides a complete, easy, systematic and reliable gene expression between morphologically different HCC. We have analyzed the genetic composition of HCC by combining a cDNA library subtraction and a microarray high throughput screening procedure. In this study, we present a novel systematic methodology for discovering genes that determines the morphologic subtypes of HCC. We mainly describe how multivariate data analysis can be applicable for molecular classification and mining biologically invaluable factors from the data rather than discuss manners of cDNA microarray experiment itself. The suggested methodology is constructed by three major stages; identification of subtypes and its class prediction, HCC-specific gene selection, validation of selected genes by clustring. |
| 저자 |
이동권1, 박진현2, 최상욱2, 김명수3, 이인범, 김영희, 정은정, 임상욱, 김문규, 김정철
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| 소속 |
1(주)피앤아이컨설팅, 2포항공과대, 3경북대 |
| 키워드 |
Hepatocellular carcinoma; SVM; K-means clustering; cDNA chip
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| E-Mail |
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| VOD |
VOD 보기 |
| 원문파일 |
초록 보기 |
