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

该项目的长期目标是建立从基因芯片或微阵列转录谱中推断遗传网络的方法。所开发的方法也被设想为能够进行实验设计。提出的方法是一个分阶段的方法，首先建立一个低分辨率的动态模型来拟合观测数据，然后对该模型进行改进，以识别隐藏变量，以提高其预测能力。为了实现这一目标，将开发一系列基因表达的动力学功能，并在互联网上提供（这些功能将经过同行评审）。这些模型将用于生成人工基因表达数据。因此，将使用已知的硅源开发和测试数据分析算法，以评估稳健性和需要进一步改进的领域。

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.