Microarray image analysis and gene expression ratio statistics

Yidong Chen; Edward R. Dougherty; Michael L. Bittner; Paul Meltzer; Jeffery Trent

doi:10.1007/0-387-26288-1_1

Microarray image analysis and gene expression ratio statistics

Yidong Chen, Edward R. Dougherty, Michael L. Bittner, Paul Meltzer, Jeffery Trent

Research output: Chapter in Book/Report/Conference proceeding › Chapter

2 Scopus citations

Abstract

4. Conclusions: Various image analysis issues have been addressed: target segmentation, background detection, target detection, and intensity measurement. Since microarray technology is still under development and image quality varies considerably, a robust and precise image analysis algorithm that reduces background interference and extracts precise signal intensity and expression ratios for each gene is critical to the success of further statistical analysis. The overall methodology discussed in this chapter has been developed and enhanced through five years of experience working with cDNA microarray images. It continues to be expanded and revised as new issues arise.

Original language	English (US)
Title of host publication	Computational and Statistical Approaches to Genomics
Publisher	Springer US
Pages	1-19
Number of pages	19
Volume	9780387262871
ISBN (Electronic)	9780387262888
ISBN (Print)	0387262873, 9780387262871
DOIs	https://doi.org/10.1007/0-387-26288-1_1
State	Published - 2006
Externally published	Yes

ASJC Scopus subject areas

General Medicine

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10.1007/0-387-26288-1_1

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abstract = "4. Conclusions: Various image analysis issues have been addressed: target segmentation, background detection, target detection, and intensity measurement. Since microarray technology is still under development and image quality varies considerably, a robust and precise image analysis algorithm that reduces background interference and extracts precise signal intensity and expression ratios for each gene is critical to the success of further statistical analysis. The overall methodology discussed in this chapter has been developed and enhanced through five years of experience working with cDNA microarray images. It continues to be expanded and revised as new issues arise.",

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T1 - Microarray image analysis and gene expression ratio statistics

AU - Chen, Yidong

AU - Dougherty, Edward R.

AU - Bittner, Michael L.

AU - Meltzer, Paul

AU - Trent, Jeffery

PY - 2006

Y1 - 2006

N2 - 4. Conclusions: Various image analysis issues have been addressed: target segmentation, background detection, target detection, and intensity measurement. Since microarray technology is still under development and image quality varies considerably, a robust and precise image analysis algorithm that reduces background interference and extracts precise signal intensity and expression ratios for each gene is critical to the success of further statistical analysis. The overall methodology discussed in this chapter has been developed and enhanced through five years of experience working with cDNA microarray images. It continues to be expanded and revised as new issues arise.

AB - 4. Conclusions: Various image analysis issues have been addressed: target segmentation, background detection, target detection, and intensity measurement. Since microarray technology is still under development and image quality varies considerably, a robust and precise image analysis algorithm that reduces background interference and extracts precise signal intensity and expression ratios for each gene is critical to the success of further statistical analysis. The overall methodology discussed in this chapter has been developed and enhanced through five years of experience working with cDNA microarray images. It continues to be expanded and revised as new issues arise.

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M3 - Chapter

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BT - Computational and Statistical Approaches to Genomics

PB - Springer US

ER -

Microarray image analysis and gene expression ratio statistics

Abstract

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