Signature analysis tools for the life sciences

适用于生命科学的特征分析工具

• 批准号: 238978-2011
• 负责人: Hallett, Michael
• 金额: $ 2.91万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=570537
• 关键词: Signature; analysis; tools; life; sciences

Cells have evolved a set of complex, inter-connected processes that perform a wide variety of functions. When a cell is stressed by an environmental challenge or genetic defect, it activates specific processes that attempt to circumvent the problem. Processes are essentially a list of genes or gene products that interact in special ways to accomplish their task. In biological and biomedical research, there is a need to identify if a specific molecular pathway or process is active within a target cell. It is still very hard to do this in the laboratory for even a single process, and it is impossible with current technologies to directly measure the status of all pathways and processes simultaneously. The use of high-throughput technologies such as microarrays and next generation sequencing has provided researchers with a type of experiment that allows all processes within the cell to be identified but it does so in an indirect way. For example, microarrays can be used to measure the expression levels of all genes in the cell simultaneously. If a specific process is active in the cell, it is highly likely that this process will eventually change the expression of some genes. With the use of computers and statistical techniques, these profiles can be searched for evidence of this "signature" of the process. That is, it will identify those genes that are changed when the process is activated. This proposal is aimed at developing bioinformatics/biostatistics methodology that address the many technical difficulties associated with identifying signatures. Our goal is to produce software that helps biologists identify which process are active in their data. In the recent past, systems biology research has established beyond a doubt that cells react to challenges in broad, comprehensive ways, modulating many processes simultaneously in order to survive. Our approach for identifying signatures allows us to form so-called signature networks. These networks provide clues as to how different processes are interconnected and co-modulated. One long-term application may be to assist clinicians in reliably determining those tumors that have a set of processes firing that play a protective role against tumors (thus potentially sparing the patient painful and expensive chemotherapy).

细胞已经进化出一套复杂的、相互连接的过程，执行各种各样的功能。当一个细胞受到环境挑战或遗传缺陷的压力时，它会激活特定的过程，试图绕过这个问题。过程本质上是一系列基因或基因产物，它们以特殊的方式相互作用以完成它们的任务。在生物学和生物医学研究中，需要确定特定的分子途径或过程是否在靶细胞内活跃。即使是在实验室中对单个过程也很难做到这一点，并且目前的技术不可能同时直接测量所有途径和过程的状态。微阵列和下一代测序等高通量技术的使用为研究人员提供了一种实验，可以识别细胞内的所有过程，但它是以间接的方式进行的。例如，微阵列可用于同时测量细胞中所有基因的表达水平。如果一个特定的过程在细胞中是活跃的，那么这个过程很可能最终会改变某些基因的表达。通过使用计算机和统计技术，可以搜索这些概况，以寻找该过程的这种“特征”的证据。也就是说，它将识别那些在过程激活时发生变化的基因。该提案旨在开发生物信息学/生物统计学方法，以解决与识别特征有关的许多技术难题。我们的目标是开发软件，帮助生物学家识别数据中活跃的过程。在最近的过去，系统生物学研究已经毫无疑问地确定了细胞以广泛，全面的方式对挑战做出反应，同时调节许多过程以生存。我们识别签名的方法使我们能够形成所谓的签名网络。这些网络为不同的过程如何相互联系和共同调节提供了线索。一个长期的应用可能是帮助临床医生可靠地确定那些具有一组对肿瘤起保护作用的过程发射的肿瘤（从而可能使患者免于痛苦和昂贵的化疗）。