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Open-source software designed to minimize synthetic biology risks
Date:3/21/2011

A software package designed to minimize the potential risks of synthetic biology for the nation's defense and security is now available to the gene synthesis industry and synthetic biology community in an open-source format.

Virginia Tech has licensed GenoTHREAT, a software tool that helps detect the use of synthetic DNA as bioterrorism agents. Developed as an open-source project by a team led by Jean Peccoud, associate professor at Virginia Bioinformatics Institute at Virginia Tech, it is being released using the Apache License Version 2.0 to ensure broad accessibility.

GenoTHREAT implements the "best match" screening protocol method recommended by the federal government to minimize the risk that unauthorized individuals or those with malicious intent will obtain toxins and other potentially dangerous materials from DNA synthesis providers. The process of developing GenoTHREAT allowed Peccoud's team to conduct a rigorous bioinformatic analysis of the strengths and limitations of the best match method which was published in the March issue of Nature Biotechnology <http://www.nature.com/nbt/journal/v29/n3/full/nbt.1802.html>.

"It was natural to start developing GenoTHREAT around the federal guidance on synthetic DNA," said Peccoud. "Since this regulation is only one of many regulations and policies that providers of synthetic DNA need to comply with, our current efforts aim at developing a more comprehensive biosecurity solution that can be customized for a variety of users."

Five of the report's co-authors Arunima Srivastava of Delhi, India, a sophomore majoring in computer science in the College of Science; Michael Kozar of Harwich, Mass., a junior majoring in biology in the College of Science and French in the College of Liberal Arts and Human Sciences; Tyler Stewart of Springfield, Va., a junior majoring in biological sciences in the College of Sc
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Contact: Susan Trulove
strulove@vt.edu
540-231-5646
Virginia Tech
Source:Eurekalert

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