Abstract
Transcription factors (TFs) are responsible for regulating the temporal and tissue specific expression of the genome. Identifying the complete battery of genes that are targeted by individual TFs, how these target genes interact within a cellular network, and the role these networks play in various disease states is essential to pharmacology and toxicology research. Genomic tools have been and are being developed to address these issues on a global scale. The most widely used tool among them is the microarray. cDNA and oligonucleotide arrays have become standard tools to study TFs and identify regulatory networks. Understanding microarray data requires careful attention to experimental design, platforms, model systems and data analysis. Microarray data analysis has also become increasingly complex with the use of various error models and clustering algorithms. Finally, new in silico approaches have been utilized to further characterize TF signaling networks. These approaches utilize computer based modeling, chromatin immunoprecipitation and microarray experiments. The application of these approaches and some concerns with the various approaches and their application to TF research are discussed.
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Zacharewski, T.R., La Pres, J.J. (2004). Genomic Approaches to the Study of Transcription Factors. In: Gossen, M., Kaufmann, J., Triezenberg, S.J. (eds) Transcription Factors. Handbook of Experimental Pharmacology, vol 166. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18932-6_3
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