Abstract
DNA microarray images consist of thousands of spots with weak intensity arranged in a matrix whose rows correspond to genes and columns correspond to experiments. The DNA microarray technology has emerged as a powerful and cost-effective tool for understanding of gene expression, regulation and interaction though a simultaneous study of thousands of genes. A successful microarray technology depends on seven main stages: experiment design, microarray fabrication, microarray image processing, data mining, biological illustration, data publication and data management. The focus of this paper is thus on a survey of recent advances in image analysis and data mining for DNA microarray technology. In image analysis, we discuss techniques for grid recognition, sport segmentation and quantification. In data mining, we discuss techniques for missing data imputation and classifications. We thoroughly survey recent literature on these tasks and briefly describe the fundamentals behind recent developments. We also present simulation results to illustrate the applications of some typical techniques.
Original language | English |
---|---|
Title of host publication | New Signal Processing Research |
Editors | Takumi Maeda |
Place of Publication | U.S.A. |
Publisher | Nova |
Pages | 89-126 |
Number of pages | 38 |
ISBN (Print) | 9781604564792 |
Publication status | Published - 2009 |
Keywords
- DNA microarrays