Collaborative Research: Design and Analysis of Compressed Sensing DNA Microarrays

合作研究：压缩传感 DNA 微阵列的设计和分析

• 批准号: 0728867
• 负责人: Richard Baraniuk
• 金额: $ 30万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-15 至 2012-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0728867&HistoricalAwards=false
• 关键词: Collaborative; Research; Design; Analysis; Compressed

The diverse functions performed by a living cell during her life cycle are controlled and regulated through complicated gene- and protein- interaction networks. Any pattern of irregular behavior of genes in the network can lead to cell malfunctioning, cell death, or the emergence of diseases like cancer. It is therefore of crucial importance to recognize erroneous gene interaction patterns and compare them to those in healthy cells. For this type of study, one of the most frequently used bioengineering systems is the well known DNA microarray device. DNA microarrays consist of grids of spots containing unique genetic identifiers for each of the tested genes, capable of generating snapshots of gene activity in terms of selective DNA sequence annealing. Microarrays have also found many other applications in the field of molecular biology, most notably for the purpose of detecting hostile microbial agents in food, water, and in the air. One of the main drawbacks of current microarray designs is that they are, for the purpose of whole genome studies, severely underutilized; similarly, for biosensing applications, existing microarray systems cannot be used for simultaneous identification of a large number of microorganisms and their strains due to technological limitations.The investigators study novel array architectures, termed compressed sensing DNA microarrays. The research involves finding DNA probes that serve as group identifiers for classes of microorganisms; designing sparse sensing matrices for DNA group identifiers; developing compressed sensing reconstruction algorithms capable of handling saturation effects arising due to high agent concentration levels; characterizing the fundamental trade-offs between distortion and sensor dimension for non-linear arrays; and, analyzing the complexity of integrating compressed sensing microarrays into existing biosensor networks.

活细胞在其生命周期中执行的各种功能是通过复杂的基因和蛋白质相互作用网络来控制和调节的。网络中基因的任何不规则行为模式都可能导致细胞故障、细胞死亡或癌症等疾病的出现。因此，识别错误的基因相互作用模式并将其与健康细胞中的基因相互作用模式进行比较至关重要。对于这种类型的研究，最常用的生物工程系统之一是众所周知的DNA微阵列装置。DNA微阵列由含有每个测试基因的唯一遗传标识符的斑点网格组成，能够根据选择性DNA序列退火生成基因活性的快照。微阵列在分子生物学领域也有许多其他应用，最显著的是用于检测食物、水和空气中的有害微生物。目前的微阵列设计的主要缺点之一是，它们是，为全基因组研究的目的，严重利用不足;同样，生物传感应用，现有的微阵列系统不能用于同时识别大量的微生物和它们的菌株由于技术的局限性。该研究涉及寻找DNA探针作为微生物类别的组标识符;设计用于DNA组标识符的稀疏传感矩阵;开发能够处理由于高试剂浓度水平而产生的饱和效应的压缩传感重建算法;表征非线性阵列的失真和传感器尺寸之间的基本权衡;并分析了将压缩传感微阵列集成到现有生物传感器网络中的复杂性。