OpenHelix Joins Coalition For Genetic Fairness

OpenHelix joins forces with other academic and industry luminaries in effort to pass Genetic Information Nondiscrimination Act (GINA).

April 15, 2008 (Seattle WA) OpenHelix today announced its membership in the Coalition for Genetic Fairness (www.geneticfairness.org), a group of organizations, industry groups, individuals and employers dedicated to addressing the potential misuse of genetic information.

The coalition’s current objective is to urge Congress to pass the Genetic Information Nondiscrimination Act (GINA). The intent of GINA is to protect individuals from insurance and employment discrimination based on their genetic information. By protecting against discrimination based on genetic data, individuals will also be more likely to take advantage of their personal genomics information for their personal health care.

“As a company that provides information on the use of public databases of genomic information, we are aware of the tremendous power for good that genetic information can yield for medical research and human health,” explained Dr. Mary Mangan, President of OpenHelix “But it is clear that in the future, personal genetic information could be misused. We must ensure that our personal genetic code will not be used against us in employment or insurance situations.”

More information on the position of OpenHelix and the opinions of its founders on the issue can be found at www.openhelix.com/blog/?p=212. More information on GINA can be found at http://www.genome.gov/24519851

About OpenHelix
OpenHelix, LLC, (www.openhelix.com) provides the genomics knowledge you need when you need it. OpenHelix provides online self-run tutorials and on-site training for institutions and companies on the most powerful and popular free, web based, publicly accessible bioinformatics resources. In addition, OpenHelix is contracted by resource providers to provide comprehensive, long-term training and outreach programs.

2 thoughts on “OpenHelix Joins Coalition For Genetic Fairness

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