Analyzing Big Data in DNA to Find Diseases

September 20, 2012

Mass amounts of raw data cause problems for more fields than just computer science. Life scientists struggle to wade through the amounts of data surrounding sequencing human genes and genetic characteristics. However, according to “Computational Method for Pinpointing Genetic Factors That Cause Disease” on Science Daily, Researchers are Roswell Park Cancer Institute and the Center for Human Genome Variation at Duke University Medical Center have developed an approach for analyzing this data to quickly cull out relevant genetic patterns and find variants that lead to particular disorders.

The study is outlined in the September issue of The American Journal of Human Genetics. We learn:

“[Zhu, the paper's first author, notes,] ‘We’re confident that our method can be applied to genome-wide association studies related to diseases for which there are no known causal variants, and by extension may advance the development of targeted approaches to treating those diseases.’
‘This approach helps to intergrade the large body of data available in GWASs with the rapidly accumulating sequence data,’ adds David B. Goldstein, [...]Director of the Center for Human Genome Variation at DUMC and senior author of the paper.’”

The technological advancement allowing scientists to pinpoint such causal variants is fascinating. However, as this technology advances, we are left to wonder how insurers will begin to use these predictive methods. Could faulty genes be analyzed in the future to justify declining policies?

Andrea Hayden, September 20, 2012

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