STTR Phase I: Analysis of Comprehensive Two Dimensional Gas Chromatography with Mass Spectrometry for High-Throughput Metabolomics
STTR Phase I: Analysis of Comprehensive Two Dimensional Gas Chromatography with Mass Spectrometry for High-Throughput Metabolomics
批准号:
0320427
负责人:
Erik Nilsson
金额:
$10.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-07-01 至 2004-06-30
中文摘要
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英文摘要
This Small Business Technology Transfer (STTR) Phase I project will investigate a new method for analyzing metabolites using novel instrumentation and software. Currently, metabolomics offers critical new information to pharmaceutical and other biological research. However, few researchers can exploit metabolomics, because appropriate methods have not been developed. Recently, gas chromatography has been successfully applied to metabolomics, although peak capacities have been insufficient. This project will combine a leading multidimensional gas chromatography research facility with a seasoned team of software experts, to bring the power of multidimensional GC to metabolomics. Comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detection (GC x GC xTOF-MS) will be combined with pattern recognition to analyze the reaction of metabolites of methylotrophic bacteria to perturbations. The collaborative effort between the Synovec Laboratory at the University of Washington and the Company will produce a software platform for analysis of GC x GC x TOF-MS data. This platform will use data management and analysis technologies that have not previously been commercially available for GC x GC x TOF-MS, and enable GC x GC x TOF-MS for high throughput metabolite analysis. The result will be an enabling technology for the elucidation of biological function.The commercial applications of this project include metabolomics and proteomics. The current market for proteomics is over $1 billion per year worldwide and growing at the rate of 34% per year. The market for metabolomics is $38 million, and growing at the rate of 46% per year. This project will address the current unmet need for multidimensional separations software in both metabolomics and proteomics.
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依托单位:
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