Typical genetics laboratory setup
Modern computing has paved the way for large-scale in-depth research into the field of genetics. Until the recent boom in the power of computers, genetics was a purely theoretical field, consisting of many hypotheses about how things worked, but without any solid evidence to back it up. With the advent of modern computers, it became possible to delve into large-scale sequencing and develop the field known as genomics. In looking at the history of genetic research, it is obvious that without modern computing power, most modern developments in genetics would not have been possible. Even with modern sequencing techniques, reliance on human resources in a divide and conquer strategy could not come close to completing the sequencing of the human genome within its predicted 15 year period. The development of a technique that eliminates the need for this divide and conquer strategy and completely relies on an algorithm utilizing high amounts of computing power, however, resulted in the completion of the project from scratch in under a year. This clearly shows the power that modern computing offers to the field of genetics. In addition, genomics is centered around databases and algorithms that predict functionality and activity of genes that control cellular physiology, and ultimately the physiology of the organism. In addition, networks such as the public MLST network enable the use of collaborative intelligence to share information through an online database, making research much quicker and less expensive. Modern computing, thus increases the capacity of laboratories to perform their research, allowing more to be done with a set amount of funding.
The data collected from computational and functional geomics can be applied to a variety of fields, including gene therapy. After genes for molecules such as insulin were located and sequenced, methods of treating diabetes were developed. Transfection of a working allele of diabetes into beta-Islet cells in the pancreas of diabetic organisms have been met with some success. Transfection of the gene using retroviruses have been used experimentally in Type I diabetic organisms and have proven to be successful in treating diabetes, but many developed cancer due to the random placement of the insulin gene into regions near proto-oncogenes. More recently, a method called raw DNA transfection, involving the transfecting of these pancreatic cells with plasmids containing the gene have been successful to some degree in producing insulin without the risk of cancerous development. Similar treatments for other genetic defects such as X-SCID immunodeficiency have also been proven moderately successful in human children, but with similar risks when using the retrovirus method. While these methods are not perfect, they are the beginnings of potential treatments for genetic diseases and the development of the field of Gene Therapy. This field, however, would not be possible without the use of modern computing power, as they provide the data for genomics research to be used in such methods of therapy. It is clear that most genetic research in the near future will be based almost entirely on computing power for important developments.
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