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

这个小型企业创新研究（SBIR）第一阶段项目将开发信号处理方法，允许生物分子（如DNA）的实时序列恢复。这个想法是使用一个简单的实验，将分析和识别的负担转移到信号处理上。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进行补偿，从而使其非常适合许多生物技术应用。尽管遇到的问题在数学上是一个盲反卷积问题，但在分子生物学应用中，问题的区别在于构成聚合信号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所涉及的大量信号，并将大数定律和维纳滤波理论相结合。这个项目的商业应用是在基因组学领域。这种方法将使廉价的实时DNA测序成为可能。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），因此检测方法可以很容易地集成到手持设备中。这种点护理（POC）设备可用于工业和实验室分子诊断应用。

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.