Gene expression microarrays nucleic acids

Karsten SL, Van Deerlin VM, Sabatti C et al. An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis. Nucleic Acids Res 2002 30 E4. 

D. Z. Wetmore, T.J. Mariani, I.S. Kohane, Z. Szallasi, Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements, Nucleic Acids Res. 2004, 32, e74. 

Tai, Y.C. Speed, T.P. (2006). A multivariate empirical Bayes statistic for replicated microarray time course data. Ann. Statist, Vol. 34, pp. 3287-2412 Tan, Y. Shi, L. Tong W. Wang, C. (2005). Multi-class cancer classification by total principal component regression (TPCR) using microarray gene expression data. Nucleic Acids Research, Vol. 33, pp. 56-65. 

Figure 2.8 Microarray cross-platform showing differentially expressed gene clusters obtained from Amersham, Agilent, and Affymetrix products. (From Barczak, A., etal., Genome Res., 13, 1775-1785, 2003 [Copyright 2003 Cold Spring Harbor Laboratory Press] and Tan, P.K. etal.. Nucleic Acid Res., 31(19), 5676-5684, 2003. With permission.)...

This chapter will review some of the key applications presented by protein microarrays. The use of profein microarrays sfems from works on gene expression arrays described earlier. However, rmlike ifs predecessors whose process formats (mutation detection, polymorphism screening, gene expression analysis, etc.) are essentially based upon solid-phase hybridization of nucleic acid complementary strands, the protein array may play different roles and comprise a variety of formafs. 

Brazma A, Parkinson HS, Sarkans U et al. ArrayExpress a publie repository for microarray gene expression data at the EBl. Nucleic Acids Res 2003 31 68-71. 

Brazma A, Parkinson H, Sarkans U, Shojatalab M, Vilo J, Abeygunawardena N, Holloway E, Kapushesky M, Kemmeren P, Lara GG, Oezcimen A, Rocca-Serra P, Sansone SA. ArrayExpress-a public repository for microarray gene expression data at the EBI. Nucleic Acids Res 2003 31 68-71. 

Nowadays the genomics-based techniques mainly employed include microarrays [31], serial analysis of gene expression (SAGE) [32] and circulating nucleic acids isolated from plasma or serum (CNAPS) [33]. 

A typical gene expression profiling experiment takes place in five separate processes. They are (i) microarray fabrication, (ii) purification and labeling of the target material, (iii) hybridization, (iv) detection and (v) data analysis. The characteristics of each step were briefly discussed in the introduction. A closer look at each of these steps is the object of this section. Here we mainly refer to biochips where the probe is constituted by nucleic acids (DNA microarrays). 

Tsai CA, Chen YJ, Chen JJ, Testing for differentially expressed genes with microarray data, Nucleic Acids Res., 31 E52, 2003... 

DNA and protein microarray technology has revolutionized the way scientists study complex biological processes. These arrays consist of thousands of nucleic acids or proteins immobilized on a solid support. The array format allows one to rapidly evaluate interactions with a large number of molecules simultaneously. For example, one can examine the expression profiles of thousands of genes in a single experiment. 

Nanomaterials can bind also to nucleic acids and, e.g., interfere with different methods used to assess changes in mRNA expression (PCR, real-time-PCR, and gene microarrays). In this case problems related to the presence of NMs are due to, e.g., decreased efficiency of RNA extraction from NP-exposed cells, lower quality of the extracted RNA, or altered mRNA stability [65],... 

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