Real Time Proteomic Analysis of Peptides and Proteins

肽和蛋白质的实时蛋白质组分析

• 批准号: 7125162
• 负责人: Ross Kenneth Snider
• 金额: $ 14.98万
• 依托单位: SNIDER TECHNOLOGY, INC.
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-23 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7125162
• 关键词: bioengineering /biomedical engineering; bioinformatics; biotechnology; computational biology; computer assisted sequence analysis; computer system design /evaluation; mass spectrometry; protein quantitation /detection; protein structure function; proteomics; supercomputer; time resolved data

DESCRIPTION (provided by applicant): Hylitech, Inc. proposes a solution to overcome a major computational bottleneck in proteomics-by building a dedicated low-cost supercomputer system that performs real time peptide and protein identification from mass spectral data. Current peptide and protein identification requires computational processing that lags mass spectral data acquisition by hours or even days. The utilization of an FPGA platform will allow matches between experimental data and possible peptides or modified peptides to be evaluated in real time, while data acquisition is in progress. Fast identification of peptides and modified peptides will allow more efficient use of scarce mass spectrometer time and enable a much deeper investigation to discover low abundance regulatory species in the proteome. This time and cost effective approach to proteomic data analysis will speed research, improve discovery of disease markers, facilitate development of more effective diagnostics, and foster the creation of personalized medicine. Real time analysis will be accomplished by designing a peptide processing unit (PPU) that will be replicated across FPGAs. A system level design will achieve the supercomputing performance required to provide a real-time solution. This will bring major acceleration of proteomic data analysis to biomedicine, while providing significant cost savings compared to conventional multi-microprocessor based systems.

描述（由申请人提供）：Hylitech，Inc。提出了一种解决方案，以克服蛋白质组学中主要的计算瓶颈 - 构建专用的低成本超级计算机系统，该系统从质谱数据中执行实时肽和蛋白质识别。当前的肽和蛋白质鉴定需要计算处理，以将质谱数据获取持续数小时甚至几天。 FPGA平台的利用将允许实验数据与可能的肽或修改的肽之间进行匹配，而数据采集正在进行。快速鉴定肽和改良的肽将使稀缺质谱仪时间更有效地使用，并能够进行更深入的研究以发现蛋白质组中的低丰度调节物种。这次和具有成本效益的蛋白质组学数据分析方法将加快研究，改善疾病标记的发现，促进更有效的诊断，并促进个性化医学的创造。实时分析将通过设计将在FPGA中复制的肽加工单元（PPU）来完成。系统级设计将实现提供实时解决方案所需的超级计算性能。这将使蛋白质组学数据分析的主要加速性加速到生物医学，同时与常规的基于多微透剂的系统相比，可节省大量成本。