FUNCTIONAL CLUSTERING APPROACH TO GENOMIC ANALYSIS

基因组分析的功能聚类方法

• 批准号: 6211903
• 负责人: Raymond Jaihyun Cho
• 金额: $ 13.09万
• 依托单位: INGENUITY SYSTEMS, INC.
• 依托单位国家: 美国
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-08-02 至 2002-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6211903
• 关键词: artificial intelligence; computer data analysis; computer system design /evaluation; functional /structural genomics; gene expression; genetic regulation; genetic transcription; molecular biology information system; neoplasm /cancer genetics

DESCRIPTION: (Applicant's Description) Regulation of mRNA transcription is one of the major determinants of cellular phenotype. Recent genome-wide expression studies establish that cancerous cells display global alterations in transcript abundance that i) determine neoplastic behavior and ii) predict clinical course and outcome. Here we describe the fIrst intelligent, scaleable, and automated approach to identifying the broader biological significance of these data. Specifically, these methods computationally detect the altered regulation of components of biological pathways in large-scale expression data, using a knowledge base of information about gene function. In Phase I of this grant, we will: Populate a functional genetic knowledge base with more than 45,000 published facts on at least 200 genes involved in two well-established neoplastic subprocesses (programmed cell death and the mitotic cell cycle). Develop two algorithms that will identify functionally related subsets of these genes from standard expression data. Evalute the ability of these algorithms to detect biologically meaningful clusters of genes within I) the complete set of 200 genes in our knowledge base and ii) differentially regulated genes from a limited set of cancer-related expression data. PROPOSED COMMERCIAL APPLICATION: NOT AVAILABLE

描述：（申请人的描述） mRNA转录调控是细胞凋亡的主要决定因素之一， 表型最近的全基因组表达研究表明， 细胞显示转录本丰度的整体改变，i）决定 肿瘤行为和ii）预测临床过程和结果。这里我们 描述第一个智能、可扩展和自动化的方法， 确定这些数据的更广泛的生物学意义。具体地说， 这些方法通过计算来检测改变的调节成分， 大规模表达数据中的生物途径，使用知识库， 关于基因功能的信息。在第一阶段，我们将： 填充功能遗传知识库，已发表超过45，000篇 事实上，至少有200个基因参与了两个公认的肿瘤 程序性细胞死亡和有丝分裂细胞周期（Programmed cell death and mitotic cell cycle） 开发两种算法，将识别功能相关的子集， 这些基因来自标准表达数据。 评估这些算法检测生物学意义的能力 I）我们所知的200个基因的完整集合 碱基和ii）来自有限的一组差异调节基因， 癌症相关表达数据。 拟议商业应用：不可用