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图谱推断遗传网络的方法。开发的方法也被设想为能够进行实验设计。该方法是一个分阶段的方法，首先建立一个符合观测数据的低分辨率动态模型，然后对该模型进行改进以识别隐藏变量，以增加其预测能力。为了实现这一目标，将开发一系列基因表达的动力学函数，并在因特网上提供(在因特网上将对它们进行同行审查)。这些模型将用于生成人造基因表达数据。因此，将使用已知的电子信息源开发和测试数据分析算法，以评估稳健性和有待进一步改进的领域。

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.