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

在系统生物学中整合自上而下和自下而上的模型并应用于

基本信息

批准号：
8027139
负责人：
T M Murali
金额：
$ 36.7万
依托单位：
VIRGINIA POLYTECHNIC INST AND ST UNIV
依托单位国家：
美国
项目类别：
财政年份：
2011
资助国家：
美国
起止时间：
2011-05-01 至 2016-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8027139
关键词：
Algorithms Apoptosis Attention Automobile Driving Bacteriophages Beds Binding Biological Biological Process Cell Cycle Cell Cycle Regulation Cell division Cell model Cell physiology Cells Chemotaxis Communicable Diseases Complex Computers Data Data Set Databases Development Environment Escherichia coli Experimental Designs Feedback Gene Expression Gene Expression Profile Gene Proteins Generations Genes Genetic Genome Genotype Graph Life Link Literature Macromolecular Complexes Malignant Neoplasms Maps Messenger RNA Metabolic Methodology Methods Modeling Molecular Movement Pattern Phenotype Physiological Processes Property Proteome Regulation Saccharomycetales Signal Transduction Simulate System Systems Biology Testing Validation Yeast Model System Yeasts cell growth data mining design flexibility interest mutant novel predictive modeling protein metabolite repository response success tool

项目摘要

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. PUBLIC HEALTH RELEVANCE: Project Narrative This project will meld two distinct approaches for studying complex cellular systems, one top-down and the other bottom-up, into a single framework. The project will combine the power of fast database searches with hand-crafted models. The project will validate this system by studying the mechanism of cell division, a system involved in the development of cancer.

描述（由申请人提供）：项目摘要两种不同的方法被用来研究复杂的细胞系统。第一种方法自动搜索大型数据集以查找基因和蛋白质之间的相关性，并将它们表示为带有节点和边的图形。第二种方法精心制作可以由计算机模拟的详细模型。到目前为止，这些方法基本上都是单独开发的。该项目将把这两种方法融合到一个框架中，从而允许快速数据库搜索来增强可模拟的模型。具体来说，该项目将 1. 开发快速算法来搜索分子数据数据库，以建议对细胞控制系统模型的扩展 2. 开发新原理来测试这些扩展模型与实验数据的匹配程度，以及 3. 设计可以验证前两步做出的预测。该项目将通过研究细胞分裂机制（参与癌症发展的系统）来验证该系统。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，例如与传染病有关的细胞系统。公共卫生相关性：项目叙述该项目将融合两种不同的研究复杂细胞系统的方法，一种是自上而下的，另一种是自下而上的，到一个框架中。该项目将把快速数据库搜索的能力与手工制作的模型结合起来。该项目将通过研究细胞分裂机制（参与癌症发展的系统）来验证该系统。