SBIR Phase II: Bioinformatic FPGA Appliance

Award Information
National Science Foundation
Award Year:
Phase II
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Phase II
Solicitation Number:
Small Business Information
Stone Ridge Technology
2015 Emmorton Road, Suite 204, Bel Air, MD, 21015-5701
Hubzone Owned:
Minority Owned:
Woman Owned:
Principal Investigator:
Vincent Natoli
(410) 670-4535
Business Contact:
Vincent Natoli
(410) 670-4535
Research Institution:

This Small Business Innovation Research (SBIR) Phase II project will build an FPGA based Bio-informatic appliance for processing DNA sequence data faster, at lower cost and with less power. Over the last decade the cost of sequencing a genome has dropped by six orders of magnitude and the throughput of the process has increased by five orders of magnitude. The trend shows no sign of abating and industry experts expect the $1,000 genome mark to be reached in the next year. The combination of lower prices and higher throughput has lead to what is being called "the data deluge" or the "the data tsunami". Taming this deluge has become a major issue in Bio-informatics and a principle bottleneck to further advances. The objective of this Phase II project is to contribute a solution to the processing problem based on Field Programmable Gate Arrays (FPGAs), non-conventional computing platforms that operate at significantly higher efficiency measured in cost and power per performance unit. The mechanism of genetic coding, identified by Watson and Crick in 1953, was one of the premier scientific advances of the twentieth century. It took twenty more years to identify a feasible approach to decipher the genetic code of a particular individual and twenty more to actually implement it. The first human genome was sequenced in 2003. By 2010 less than 1,000 humans have been sequenced but rapidly decreasing costs and increasing throughput promise that the number will increase exponentially and medical researchers foresee the day in the near future when the whole population will be sequenced as part of standard medical practice. The advances that will be enabled by partial or full sequencing of the population will bring a revolution to health care ushering in an era of personal genetic based medicine. If successfully deployed, the proposed approach has the potential to address the so-called data deluge and bring about significant savings in both processing time and power consumption.

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