Systems Biology and Gene Networks

系统生物学和基因网络

• 批准号: 9754669
• 负责人: ALBERT-LASZLO BARABASI
• 金额: $ 38.16万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9754669
• 关键词: Airway Disease; Animal Model; Asthma; Binding; Biological; Budgets; Chronic Obstructive Airway Disease; Complex; DNA Methylation; Data; Data Collection; Disease; Doctor of Philosophy; Elements; Epigenetic Process; Etiology; Faculty; Gene Expression; Genes; Genetic; Genomics; Goals; Human; Medical Research; Medicine; Methylation; MicroRNAs; Modeling; Molecular; Network Infrastructure; Network-based; Pathway Analysis; Pathway interactions; Physics; Predictive Value; Property; Proteins; Research; Research Assistant; Research Personnel; Resources; Role; Science; Seeds; Senior Scientist; Systems Biology; Two-Hybrid System Techniques; Universities; Variant; Work; Yeasts; Zebrafish; airway obstruction; base; design; exome; experience; genome-wide; graph theory; improved; instructor; medical schools; member; molecular array; molecular scale; network models; novel therapeutics; professor; programs; scaffold; tool; trait; transcriptomics

ABSTRACT The primary role of Core A – “Systems Biology and Gene Networks” — is to explore in a predictive fashion the molecular and network-based similarities and differences between asthma and COPD. Networks provide frameworks for deriving information from a set of relationships among entities in the program project. We aim to develop tools to identify the disease modules for asthma and COPD, and the molecular relationships between them. The work will initially rely on the data already collected by the PPG investigators, leading to a first round of mechanistic predictions. These predictions will drive the design of subsequent experimental work and data collection, iteratively improving the Core's predictive power. Core A has two specific aims: Aim 1: Construct the network infrastructure to predict the disease module relying on data collected by the PPG Projects and Cores. The goal is to develop and improve on the existing tools to identify the disease module for asthma and COPD, and to offer an initial set of experimentally testable predictions. Aim 2: Iteratively enhance the predictive value of the disease module by overlaying data collected by the PPG Projects and Cores. We plan to explore the network-based relationships between asthma and COPD by identifying common pathways, genes and potentially common disease mechanisms. Core A will apply network analysis support at different levels: (1) selection and prioritization of the variants and genes associated with airflow obstruction from Project 1; (2) integrating different levels of genomics and transcriptomics data associated with asthma and COPD with the molecular interaction networks (interactome) from Project 2; and (3) identifying and interpreting epigenetic changes (methylation and miRNA) associated with asthma and COPD from Project 3 by integration with protein interactome models. The networks of interactions will serve as a scaffold for information to extract global and local graph theory properties to inform about the initial seed gene choices and about the different “omics” data in Projects 1, 2 and 3.

抽象的 核心A（“系统生物学和基因网络”）的主要作用是以预测方式探索 基于分子和网络的相似性以及哮喘和COPD之间的差异。网络提供 从程序项目中的实体之间的一系列关系中得出信息的框架。我们的目标 开发工具以识别哮喘和COPD的疾病模块以及分子关系 他们之间。这项工作最初将依靠PPG调查人员已经收集的数据，从而导致 第一轮机械预测。这些预测将推动随后的实验工作的设计 和数据收集，迭代地改善了核心的预测能力。核心A有两个具体的目标：目标1： 构建网络基础设施以预测依赖于收集的数据的疾病模块 PPG项目和核心。目的是开发和改进现有工具以识别疾病 目标2： 通过覆盖PPG收集的数据，迭代地增强了疾病模块的预测价值 项目和核心。我们计划通过 确定常见途径，基因和潜在的常见疾病机制。核心A将应用网络 分析支持不同级别：（1）选择和优先级与相关的变体和基因的优先级 项目1的气流异议； （2）整合不同级别的基因组学和转录组学数据 与项目2的分子相互作用网络（Interconome）相关联与哮喘和COPD相关；和 （3）识别和解释与哮喘和哮喘和相关的表观遗传变化（甲基化和miRNA） 通过与蛋白质相互作用组模型集成项目3的COPD。互动网络将服务 作为提取全球和本地图理论属性的信息的脚手架，以告知初始种子 基因选择以及项目1、2和3中不同的“ OMIC”数据。