QSB: Reverse Engineering of Biochemical Networks from Whole-Genome Dynamics

QSB：全基因组动力学生化网络的逆向工程

• 批准号: 0120306
• 负责人: Pedro Mendes
• 金额: $ 10万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-10-01 至 2002-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0120306&HistoricalAwards=false
• 关键词: QSB; Reverse; Engineering; Biochemical; Networks

The long range goal of this project is to build methods to infer genetic networks from gene chip or microarray transcription profiles. The methods developed are also envisioned to enable experimental design. The approach proposed is a staged one consisting of initially building a low-resolution dynamic model that fits observed data, and then to improve such a model to identify hidden variables in order to increase its predictive power. To achieve that objective, a series of kinetic functions for gene expression will be developed and made available on the Internet (where they will be peer-reviewed). These models will be used to generate artificial gene expression data. The data analysis algorithms will thus be developed and tested using a known in silico source to assess robustness and areas for further improvement.

本项目的长期目标是建立从基因芯片或微阵列转录谱推断遗传网络的方法。开发的方法也设想，使实验设计。提出的方法是一个分阶段的，包括最初建立一个低分辨率的动态模型，适合观察到的数据，然后改进这样的模型，以确定隐藏的变量，以提高其预测能力。 为实现这一目标，将开发一系列基因表达的动力学函数，并在互联网上公布（将在互联网上对这些函数进行同行审查）。 这些模型将用于生成人工基因表达数据。 因此，将使用已知的计算机数据源开发和测试数据分析算法，以评估稳健性和进一步改进的领域。