A Systems Approach to Genomic Signal Processing: From Signal Extraction to Regulatory Intervention

基因组信号处理的系统方法：从信号提取到监管干预

• 批准号: 0514644
• 负责人: Edward Dougherty
• 金额: $ 79万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-05-01 至 2009-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0514644&HistoricalAwards=false
• 关键词: Systems; Approach; Genomic; Signal; Processing

A Systems Approach to Genomic Signal Processing: Signal Extraction to Regulatory InterventionThe Human Genome Project recently announced the sequencing of the human genome with enormous potential implications such as customized medicine. New analytic methods and computational technologies are needed to fulfill this promise. This study focuses on the development and integration of signal processing approaches for aiding the diagnosis and treatment of diseases such as cancer. The massive amount of data generated by high-throughput microarray technology provides a gateway to the discovery of key genes and gene combinations that explain specific diseases on a mechanistic level, to the classification of diseases on a molecular level, and to the development of optimal therapeutic strategies for various diseases. This study is concerned with (i) developing signal processing based solutions to individual sub-problems that arise in functional genomics; and (ii) ensuring that these solutions can be pieced together to provide solutions to the original overall problems of disease diagnosis and therapy.Microarray-based genomic signal processing can be broadly broken into five categories: signal extraction, clustering, classification of phenotypes (diagnosis), modeling genetic regulatory networks, and developing strategies for regulatory intervention (therapy). There tends to be a natural hierarchy among the five categories which are, therefore, studied from a systems perspective to ascertain the manner in which processing, analysis, and estimation on one level propagates through the system to affect downstream analyses, and how the subordinate issues within a category interact among each other. These questions are addressed within a unified theoretical framework, their solutions are applied to real biological problems, and a large body of integrated software to facilitate further investigation and application is developed.

基因组信号处理的系统方法：从信号提取到调控干预人类基因组计划最近宣布了人类基因组的测序，这具有巨大的潜在意义，如定制医学。需要新的分析方法和计算技术来实现这一承诺。本研究的重点是开发和整合信号处理方法，以帮助诊断和治疗癌症等疾病。高通量微阵列技术产生的大量数据为发现在机制水平上解释特定疾病的关键基因和基因组合、在分子水平上对疾病进行分类以及为各种疾病开发最佳治疗策略提供了途径。本研究关注的是（i）开发基于信号处理的解决方案，以解决功能基因组学中出现的单个子问题;（ii）确保这些解决方案可以拼凑在一起，为疾病诊断和治疗的原始整体问题提供解决方案。基于微阵列的基因组信号处理可以大致分为五类：信号提取、聚类、表型分类（诊断）、遗传调控网络建模以及调控干预（治疗）策略的开发。在这五个范畴之间往往有一个自然的层次结构，因此，从系统的角度来研究，以确定一个层面上的处理、分析和估计通过系统传播影响下游分析的方式，以及一个范畴内的从属问题如何相互作用。这些问题在一个统一的理论框架内解决，他们的解决方案被应用到真实的生物学问题，并开发了大量的集成软件，以促进进一步的调查和应用。