Researchers such as those at the University of Alaska Fairbanks' (UAF) Institute of Arctic Biology (IAB) and the Arctic Region Supercomputing Center (ARSC) seek to understand how organisms deal with the demands of their natural environment-as shown by the discovery of many remarkable adaptations that organisms have acquired living in the extremes of Alaska. Many of these adaptations have significant biomedical relevance in areas such as stroke, cardiovascular disease, and physiological stress. Somehow, our wild counterparts have adapted to severe environmental demands over long periods of time. Simultaneous to this research, scientists are also investigating the molecular changes that can be observed in humans as a result of their environment, such as through smoking or exposure to contaminants. This push in research has resulted in the integration with life science research of approaches from many fields, including engineering, physics, mathematics, and computer science. One of the most well-known results of this is the Human Genome Project. Through this project, researchers * were able to design instruments capable of performing many different types of molecular measurements so that statistically significant and large scale sampling of these molecules could be achieved. Now, biomedical research is producing data that show researchers that things are not always where they expected them to be, while at the same time researchers are at a rapidly expanding phase of discovery and analysis of large, highly repeatable measurements of complex molecular systems. One of the more important and generally applicable tools that has emerged from this type of research is called DNA micro arrays, or DNA chip technology This technology uses the fundamentals of Watson and Crick base-pairing along with hybridization to customize applications of DNA micro arrays to simultaneously interrogate a large number of genetic loci (those locations on the DNA molecules that have differing biological roles). The result of this type of analysis is that experiments that once tool ten years in thousands of laboratories can now be accomplished with a small number of experiments in just one laboratory. |
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