Title |
DNA Microarrays: a Powerful Genomic Tool for Biomedical and Clinical Research
|
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Published in |
Molecular Medicine, September 2007
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DOI | 10.2119/2006-00107.trevino |
Pubmed ID | |
Authors |
Victor Trevino, Francesco Falciani, Hugo A. Barrera-Saldaña |
Abstract |
Among the many benefits of the Human Genome Project are new and powerful tools such as the genome-wide hybridization devices referred to as microarrays. Initially designed to measure gene transcriptional levels, microarray technologies are now used for comparing other genome features among individuals and their tissues and cells. Results provide valuable information on disease subcategories, disease prognosis, and treatment outcome. Likewise, they reveal differences in genetic makeup, regulatory mechanisms, and subtle variations and move us closer to the era of personalized medicine. To understand this powerful tool, its versatility, and how dramatically it is changing the molecular approach to biomedical and clinical research, this review describes the technology, its applications, a didactic step-by-step review of a typical microarray protocol, and a real experiment. Finally, it calls the attention of the medical community to the importance of integrating multidisciplinary teams to take advantage of this technology and its expanding applications that, in a slide, reveals our genetic inheritance and destiny. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 50% |
Unknown | 1 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Mexico | 5 | 1% |
United States | 3 | <1% |
Brazil | 2 | <1% |
Germany | 2 | <1% |
United Kingdom | 2 | <1% |
Canada | 1 | <1% |
Chile | 1 | <1% |
Japan | 1 | <1% |
India | 1 | <1% |
Other | 0 | 0% |
Unknown | 352 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 92 | 25% |
Student > Bachelor | 62 | 17% |
Student > Master | 48 | 13% |
Researcher | 33 | 9% |
Professor > Associate Professor | 12 | 3% |
Other | 42 | 11% |
Unknown | 81 | 22% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 96 | 26% |
Biochemistry, Genetics and Molecular Biology | 64 | 17% |
Medicine and Dentistry | 31 | 8% |
Computer Science | 16 | 4% |
Chemistry | 16 | 4% |
Other | 56 | 15% |
Unknown | 91 | 25% |