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用于研究复杂的细胞系统。第一种方法会自动搜索大型数据集以了解基因和蛋白质之间的相关性，并将其表示为带有节点和边缘的图形。第二种方法艰苦地制作了可以通过计算机模拟的详细模型。到现在为止，这些方法已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单个框架中，从而允许快速数据库搜索以增强可以模拟的模型。具体而言，该项目将1。开发快速算法以搜索分子数据的数据库，以暗示向蜂窝控制系统模型扩展2。开发新的原理，以测试这些扩展模型与实验数据和3的符合3。设计实验测试可以验证前两个步骤的预测。该项目将通过研究细胞分裂的机理来验证该系统，该机制涉及癌症的发展。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：项目叙事该项目将融合两种不同的方法，用于研究复杂的蜂窝系统，一个自上而下，另一个自下而上，将其分解为一个框架。该项目将将快速数据库搜索的功能与手工制作的模型相结合。该项目将通过研究细胞分裂的机理来验证该系统，该机制涉及癌症的发展。