Green Buckeye RN

EHN: Data Mining Predicts Chemical-Gene-Cancer Associations
September 10, 2010, 11:59 am
Filed under: News

Sep 09, 2010

Patel, CJ and AJ Butte. 2010. Predicting environmental chemical factors associated with disease-related gene expression data. BMC Medical Genomics
Synopsis by Thea Edwards

Researchers link information from two public databases in an effort to predict which chemicals might change gene expression and influence disease.

A mix of data gathered from two large databases is one of the next steps in understanding how the environment interacts with genes to influence disease, according to two Stanford scientists who are trying to untangle the interrelated effects. The pair analyzed information that was collected through new analytical methods – such as gene arrays – to better understand and predict environment-gene-disease patterns.

This so-called data-mining approach is a useful and cost-effective way to identify interactions among hundreds of chemicals and thousands of genetic measurements associated with a disease. The associations can then be targeted for more efficient and specific experimental tests or epidemiological studies.

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