SBIR Phase I: Bio-molecular Sequence Recovery Using Statistical Signal Processing

SBIR 第一阶段：使用统计信号处理恢复生物分子序列

• 批准号: 0320167
• 负责人: Nader Pourmand
• 金额: $ 9.94万
• 依托单位: Xagros Technologies
• 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
• 起止时间: 2003-07-01 至 2003-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0320167&HistoricalAwards=false
• 关键词: SBIR; Phase; Bio; molecular; Sequence

This Small Business Innovation Research (SBIR) Phase I project will develop signal processing methods that allow for real-time sequence recovery of bio-molecules such as DNA. The idea is to use a single simple experiment and to shift the burden of analysis and identification to signal processing. The methodology allows for the use of simple instrumentation (platforms, detectors, sensors, etc.) and compensates for them by using advanced signal processing techniques, thereby making it ideally suited for many biotechnology applications. Although the problem encountered is mathematically one of blind de-convolution, what distinguishes the problem in its molecular biology applications is the sheer number of signature signals involved that form the aggregate signal. In this project, a novel solution based on statistical signal processing will be developed. The technique will explicitly exploit the large number of signals involved and will use a combination of the law of large numbers and Wiener filtering theory.The commercial application of this project is in the area of Genomics. The methodology will allow for inexpensive real-time DNA sequencing. Since the required instrumentation is relatively simple and the burden is shifted to signal processing and computation (which can be implemented directly in standard digital-signal-processing (DSP) chips), the detection method could be readily integrated into a hand-held device. Such a Point-of-Care (POC) device could be used for industrial and laboratory molecular diagnostics applications.

该小型企业创新研究（SBIR）第一阶段项目将开发信号处理方法，以实现DNA等生物分子的实时序列恢复。 这个想法是使用一个简单的实验，并将分析和识别的负担转移到信号处理。 该方法允许使用简单的仪器（平台、探测器、传感器等）。并通过使用先进的信号处理技术来补偿它们，从而使其理想地适用于许多生物技术应用。 虽然所遇到的问题在数学上是盲去卷积的问题之一，但在其分子生物学应用中区分该问题的是形成聚合信号的所涉及的签名信号的绝对数量。 在这个项目中，将开发一种基于统计信号处理的新解决方案。 该技术将明确地利用大量的信号，并将使用大数定律和维纳滤波理论相结合，该项目的商业应用是在基因组学领域。该方法将考虑到 廉价的实时DNA测序 由于所需的仪器相对简单，并且负担转移到信号处理和计算（可以直接在标准数字信号处理（DSP）芯片中实现），因此检测方法可以容易地集成到手持设备中。 这样的床旁（POC）设备可以用于工业和实验室分子诊断应用。