There are numerous websites providing many links about microarrays and expression profiling. GenomicsHome.org includes almost everything about the microarray technology, users are encouraged to look at this site. However, for impatient users, a list of key web links is provided below.

Public Databases

• ArrayExpress – A public repository for microarray data developed by European Bioinformatics Institute.
• ExpressDB – A relational database containing yeast and E. coli RNA expression data developed by Church’s lab.
• Gene Expression Omnibus – A public gene expression database maintained by NCBI.
• GeneX – A gene expression database developed by National Center for Genome Resources.
• Standford Microarray Database (SMD) – developed by Standford University , a public microarray database implemented with web-based data analysis and visualization tools.

Microarray Standards

• MAGE-ML (MicroArray and Gene Expression Markup Language) – a XML language for microarray data exchange, supported by Microarray Gene Expression Database (MGED) group.

• MIAME (Minimum Information About a Microarray Experiment) – proposed by Microarray Gene Expression Database (MGED) group. It specifies the minimum information that must be reported about an array experiment for the data interpretability and verification by third parties.

Group/Mailing list

• bionet.molbio.genearrays – the first USENET newsgroup dedicated to microarray discussion
• Microarray mailing lists – A mailing list maintained by EBI
• Microarray mailing list at eGroups – A mailing list maintained at eGroups.
• Microarray Gene Expression Database Group – The MGED group is an international organizatrion to facilitate sharing microarray data.
• Microarray User Group – A user group for glass or filter cDNA arrays, maintained by SIGs of NIH.

Key References on Microarray Data Analysis

• Yang YH, Dudoit S, Luu P, Lin DM, Peng V, Ngai J, Speed TP. Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation. Nucleic Acids Res. 2002 Feb 15;30(4):e15.
• G. K. Smyth, Y. H. Yang and T. P. Speed Statistical Issues in cDNA Microarray Data Analysis
• Tseng GC, Oh MK, Rohlin L, Liao JC, Wong WH. Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects. Nucleic Acids Res 2001 Jun 15 ; 29 (12): 2549-57
• Kerr MK, Churchill GA (2000b) Experimental design for gene expression microarrays. Biostatistics (to appear).
• Kerr MK, Churchill GA (2001) Statistical design and the analysis of gene expression microarrays. Genet Res 77: 123-128.
• Dudoit S, Yang YH, Callow MJ, Speed TP (2000) Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments. TR, Department of Statistics, UC-Berkeley
• Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Nat Acad Sci USA 95: 14863-14868.
• Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML, Downing JR, Caligiuri MA, Bloomfield CD, Lander ES (1999) Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 286: 531-537.
• Alter O, Brown P, Botstein D (2000) Singular value decomposition for genome-wide expression data processing and modeling. Proc Nat Acad Sci USA 97: 10101-10106.
• Chen Y, Dougherty ER, Bittner ML (1997) Ratio-based decisions and the quantitative analysis of cDNA microarray images. J Biomed Opt 2: 364-374