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KCI등재 학술저널

Metastasis Related Gene Exploration Using TwoStep Clustering for Medulloblastoma Microarray Data

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.

1. Introduction

2. DNA Microarray

3. The TwoStep Clustering Algorithm

4. Data Construction

5. Analysis

6. Conclusion

References