Metastasis Related Gene Exploration Using TwoStep Clustering for Medulloblastoma Microarray Data

• 발행기관: 한국자료분석학회
• 저자명: 반성수(Sung-Su Ban) 박희창(Hee-Chang Park)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.10 No.3, 1227~1238쪽, 전체 12쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2008.06.30

영문 초록

Microarray gene expression technology has applications that could refine diagnosis and therapeutic monitoring as well as improve disease prevention through risk assessment and early detection. Especially, microarray expression data can provide important information regarding specific genes related with metastasis through an appropriate analysis. Various methods for clustering analysis of microarray data have been introduced so far. We used TwoStep clustering for ascertaining metastasis related gene distingue metastatic medulloblastoma from nonmetastatic. Through t-test between metastatic and non metastatic groups for two publicly available medulloblastoma microarray data sets, we intended to find significant gene for metastasis and to conform. The paper describes the process in detail showing how the process is applied to clustering analysis and t-test for microarray data sets and how the metastasis-associated genes are explored.

목차

1. Introduction

2. DNA Microarray

3. The TwoStep Clustering Algorithm

4. Data Construction

5. Analysis

6. Conclusion

References

키워드

microarray TwoStep clustring medulloblastoma metastasis