Integrating Top-Down and Bottom-Up Models in Systems Biology with Application to

描述（由申请人提供）： 两种不同的方法被用于研究复杂的细胞系统。第一种方法自动搜索基因和蛋白质之间相关性的大型数据集，并将其表示为具有节点和边的图。第二种方法是精心制作可以用计算机模拟的详细模型。到目前为止，这些方法在很大程度上是单独开发的。该项目将把这两种方法融合到一个框架中，从而允许快速的数据库搜索来增强可以模拟的模型。具体而言，该项目将1。开发快速算法来搜索分子数据的数据库，以建议细胞控制系统模型的扩展2。开发新的原则来测试这些扩展模型与实验数据的匹配程度，3.设计实验测试，以验证前两步所做的预测。该项目将通过研究细胞分裂的机制来验证这一系统，细胞分裂是一个参与癌症发展的系统。从长远来看，该项目开发的方法可用于研究任何复杂的细胞系统，例如，那些与传染病有关的人

DESCRIPTION (provided by applicant): Project Summary Two distinct approaches are being used to study complex cellular systems. The first approach automatically searches large datasets for correlations between genes and proteins and represents these as a graph with nodes and edges. The second approach painstakingly crafts detailed models that can be simulated by computer. These approaches have largely been developed separately until now. This project will meld these two approaches into a single framework, thereby allowing fast database searches to augment models that can be simulated. Specifically, the project will 1. Develop fast algorithms to search databases of molecular data to suggest extensions to models of cellular control systems 2. Develop new principles to test how well these extended models match experimental data and 3. Design experimental tests that can validate the predictions made by the first two steps. The project will validate this system by studying the mechanism of cell division, a system involved in the development of cancer. In the long term, the methods developed by this project can be used to study any complex cellular system, e.g., those implicated in infectious diseases.