Abstract
In today's field of genomics, traditional gene-by-gene approach is not adequate to meet the demand of processing information generated from mapping the complex biology of the human genome. More global views of analyzing the magnitude of information are necessary, such as with microarrays. Microarray technology today is rapidly uncovering broad patterns of genetic activity and showing insight into gene functions, processes, and pathways. With the growing technology, imminent knowledge is being generated looking into transcriptional processes and biological mechanisms from many different organisms and phylogeny. Many tools are being developed to assist with the analysis of such high-throughput data, many applications are being utilized by this technology, and the field is growing and expanding rapidly to accommodate the expanding genomics era.
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Shrimpton, A. E., Levinsohn, E. M., Yozawitz, J. M., et al. (2004) A HOX gene mutation in a family with isolated congenital vertical talus and Charcot-Marie-Tooth disease. Am. J. Hum. Genet. 75, 92–96.
Middleton, F. A., Pato, M. T., Gentile, K. L., et al. (2004) Genomewide linkage analysis of bipolar disorder by use of a high-density single-nucleotide-polymorphism (SNP) genotyping assay: a comparison with microsatellite marker assays and finding of significant linkage to chromosome 6q22. Am. J. Hum. Genet. 74, 886–897.
Faraone, S. V. and Tsuang, M. T. (2003) Heterogeneity and the genetics of bipolar disorder. Am. J. Med. Genet. 123C 1–9.
Lieberfarb, M. E., Lin, M., Lechpammer, M., et al. (2003) Genome-wide loss of heterozygosity analysis from laser capture microdissected prostate cancer using single nucleotide polymorphic allele (SNP) arrays and a novel bioinformatics platform dChip SNP. Cancer Res. 63, 4781–4785.
Schoumans, J., Anderlid, B. M., Blennow, E., Teh, B. T., and Nordenskjold, M. (2004) The performance of CGH array for the detection of cryptic constitutional chromosome imbalances. J. Med. Genet. 41, 198–202.
De Leeuw, R. J., Davies, J. J., Rosenwald, A., et al. (2004) Comprehensive whole genome array CGH profiling of mantle cell lymphoma model genomes. Hum. Mol. Genet. 13, 1827–1837.
Harwanegg, C. and Hiller, R. (2004) Protein microarrays in diagnosing IgE-mediated diseases: spotting allergy at the molecular level. Expert Rev. Mol. Diagn. 4, 539–548.
Boutell, J. M., Hart, D. J., Godber, B. L., Kozlowski, R. Z., and Blackburn, J. M. (2004) Functional protein microarrays for parallel characterisation of p53 mutants. Proteomics 4, 1950–1958.
Sun, Z., Fu, X., Zhang, L., Yang, X., Liu, F., and Hu, G. (2004) A protein chip system for parallel analysis of multi-tumor markers and its application in cancer detection. Anticancer Res. 24, 1159–1165.
Wang, H., Yang, U., Lee, C., and Blume, J. (2004) Pacific Symposium on Biocomputing 9:3–4 (www.Affymetrix.com).
Watters, J. W. and McLeod, H. L. (2003) Cancer pharmacogenomics: current and future applications. Biochim. Biophys. Acta 1603(2), 99–111.
Branca, M. (2003) Roche unveils two pharmacogenomic developments. Bio. IT World (online).
Fukushima, H. (1999) Forensic DNA analysis—past and future. Nippon Hoigaku Zasshi 53, 276–284.
Radtkey, R., Feng, L., Muralhidar, M., et al. (2000) Rapid, high fidelity analysis of simple sequence repeats on an electronically active DNA microchip. Nucleic Acids Res. 28, E17.
Dalma-Weiszhausz, D. D., Chicurel, M. E., and Gingeras, T. R. (2002) Microarrays and genetic epidemiology: a multipurpose tool for a multifaceted field. Genet. Epidemiol. 23, 4–20.
Konstantinov, I. E., Coles, J. G., Boscarino C., et al. (2004) Gene expression profiles in children undergoing cardiac surgery for right heart obstructive lesions. J. Thorac Cardiovasc. Surg. 127, 746–754.
Kruse, J. J., te Poele, J. A., Russell, N. S., Boersma, L. J., and Stewart, F. A. (2004) Microarray analysis to identify molecular mechanisms of radiation-induced microvascular damage in normal tissues. Int. J. Radiat. Oncol. Biol. Phys. 58, 420–426.
Golub, T. R., Slonim, D. K., Tamayo, P., et al. (1999) Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286, 531–537.
Beer, D. G., Kardia, S. L., Huang, C. C., et al. (2002) Gene-expression profiles predict survival of patients with lung adenocarcinoma. Nat. Med. 8, 816–824.
Claudio, J. O., Masih-Khan, E., and Stewart, A. K. (2004) Insights from the gene expression profiling of multiple myeloma. Curr. Hematol. Rep. 3, 67–73.
Bullinger, L., Dohner, K., Bair, E., et al. (2004) Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukaemia. N. Engl. J. Med. 350, 1605–1616.
Valk, P. J., Verhaak, R. G., Beijen, M. A., et al. (2004) Prognostically useful gene-expression profiles in acute myeloid leukemia. N. Engl. J. Med. 350, 1617–1628.
Hardiman, G. (2004) Microarray platforms—comparisons and contrasts. Pharmacogenomics 5, 487–502.
Vingron, M. (2001) Bioinformatics needs to adopt statistical thinking. Bioinformatics 17(5), 389, 390.
Storey, J. D. (2002) A direct approach to false discovery rates. J. Roy. Stat. Soc. B 64, 479–498.
Tibshirani, R., Hastie, T., Narasimhan, B., and Chu, G. (2002) Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99, 6567–6572.
Harris, M. A., Clark, J., Ireland, A., Lomax, J., et al. (2004) The Gene Ontology (GO) database and informatics resource. Nucleic Acids Res. 32(Database issue), D258-D261.
Ashburner, M., Ball, C. A., Blake, J. A., et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29.
Smid, M. and Dorssers, L. C. (2004) GO-Mapper: functional analysis of gene expression data using the expression level as a score to evaluate gene ontology terms. Bioinformatics 20, 1–8.
Stubbs, A. and van der Spek, P. (2003) Microarray bioinformatics, in Nature Encyclopedia of the Human Genome, (Cooper, D. N., ed.), Macmillan (UK) and Nature Publishing (NY) groups, pp. 912–917.
Comelli, E. M., Amado, M., Head, S. R., and Paulson, J. C. (2002) Custom microarray for glycobiologists: considerations for glycosyltransferase gene expression profiling. Biochem. Soc. Symp. 69, 135–142.
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Peeters, J.K., Van der Spek, P.J. Growing applications and advancements in microarray technology and analysis tools. Cell Biochem Biophys 43, 149–166 (2005). https://doi.org/10.1385/CBB:43:1:149
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DOI: https://doi.org/10.1385/CBB:43:1:149