題目:microarray data warehouse allowing for inclusion of experiment annotations inf statistical analysis

Abstract

I am often thinking, “Do you have a good data of thousands of genes, I can use information tools on analysis of array data ? ”

The information in that file will prompt questions such as: How is it scaled? What is the error in the data? When can I say that a certain gene is up-regulated? What do I do with the thousands of genes that show some regulation? How much information can I get out of my data?

Here we develop a data warehouse and statistical analysis concept called Multi-conditional Hybridization Intensity Processing System (M-CHIPS).

It integrates different data sources and data formats into the M-CHIPS.

Data sources, e.g. raw signal intensities, gene annotations and experiment annotations.

Here we sketch how these concepts have been implemented in our databases.

REFERENCES

Ballard,C., Herreman,D., Schau,D., Bell,R., Kim,E. and Valencic, A. (1998) Data Modeling Techniques for Data Warehousing. IBM International Technical Support Organization, San Jose, CA, www.redbooks.ibm.com.

Fellenberg,K., Hauser,N.C., Brors,B., Neutzner,A., Hoheisel,J.D. and Vingron,M. (2001) Correspondence analysis applied to microarray data. Proc. Natl Acad. Sci. USA, 98, 10781–10786.

URL http://bioinformatics.oupjournals.org/