Functional Genomics:Complex Biological Systems

功能基因组学:复杂的生物系统

• 批准号: 6575480
• 负责人: STUART K KIM
• 金额: $ 2.5万
• 依托单位: KEYSTONE SYMPOSIA
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-01-01 至 2003-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6575480
• 关键词: computer data analysis; functional /structural genomics; genetic models; genetic techniques; informatics; meeting /conference /symposium; quantitative trait loci; technology /technique development; travel

DESCRIPTION (provided by applicant): The revolution in functional genomics has provided a windfall of expression, functional and protein interaction data. These have led to remarkable advances in molecular profiles for cancer, assembly of genetic regulatory hierarchies, genome-wide analysis of development and systematic searches for drug targets. The success of functional genomics has relied heavily in interdisciplinary interactions from diverse fields such as genetics, computer science, medicine and engineering. A current challenge in functional genomics is to develop analytical methods and data mining algorithms to keep up with the avalanche of data being generated. Methods are also needed to integrate data from diverse genome-wide expression profiles and to apply common themes from model organisms to human disease. Progress in holistic approaches will shed light on complex biological systems, such as cancer profiling, developmental morphogenesis, and quantitative genetics. The goal of the meeting is to integrate advances in human disease, modeling of genetic networks, quantitative trait mapping, and data mining techniques.

描述（由申请人提供）： 功能基因组学的革命提供了表达、功能和蛋白质相互作用数据的意外收获。这些导致了癌症分子谱、基因调控层次结构的组装、发育的全基因组分析和药物靶标的系统搜索方面的显着进步。功能基因组学的成功在很大程度上依赖于遗传学、计算机科学、医学和工程学等不同领域的跨学科相互作用。 功能基因组学当前的挑战是开发分析方法和数据挖掘算法，以跟上正在生成的大量数据。还需要方法来整合来自不同全基因组表达谱的数据，并将模型生物的共同主题应用于人类疾病。整体方法的进展将揭示复杂的生物系统，例如癌症分析、发育形态发生和定量遗传学。 会议的目标是整合人类疾病、遗传网络建模、数量性状图谱和数据挖掘技术的进展。