A signal transduction pathway database/modeling system

信号转导通路数据库/建模系统

• 批准号: 6798470
• 负责人: ERIC D MJOLSNESS
• 金额: $ 57.21万
• 依托单位: UNIVERSITY OF CALIFORNIA-IRVINE
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-09-01 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6798470
• 关键词: Internet; biological signal transduction; chemical reaction; computer data analysis; computer program /software; computer simulation; computer system design /evaluation; data management; mathematical model; mitogen activated protein kinase; model design /development; molecular biology information system; yeasts

DESCRIPTION (provided by applicant): Our goal is to develop a computational framework for cell signaling networks, and to demonstrate its effectiveness by developing high-quality models for several pathways of special biological interest. Its purpose is to enable biologists to use mathematical modeling to frame and constrain hypotheses before experimental testing. The need for the system and its design are driven by the hallmarks of cell signaling - complexity and dynamics. Web-like diagrams of cross-talking pathways and information flow currently convey the complexity. Dynamic properties include both transient and permanent changes in network architecture in which pathway components move from one subcellular location to another, components associate in different protein complexes, and the entire repertoire of receptors, transducers and targets and connectivity change as the cell state changes. To mathematically probe signaling processes, we are developing a "pathway modeling database" (SIGMOID) designed to: 1) Capture and organize diverse expert knowledge and data in a manner that computationally mirrors the underlying biochemistry. Pathways are therefore represented as their underlying chemical reactions and molecular associations. It also specifies signal-ontingent spatial compartmentalization of reactants and products, and provides for biologically appropriate dependence of reactions on the molecular state of reactants (phosphorylation, methylation, GDP binding, etc). 2) Provide automated generation of computational models based on the stored reaction network architecture that is coupled with an expandable suite of modeling programs. 3) Ingest and store results from computational simulations and provide tools for comparing, visualizing and mining simulation results.

描述（由申请人提供）：我们的目标是为细胞信号网络开发一个计算框架，并通过为具有特殊生物学意义的几种途径开发高质量模型来证明其有效性。它的目的是使生物学家能够在实验测试之前使用数学建模来构建和约束假设。对系统及其设计的需求是由细胞信号传导的标志-复杂性和动态性驱动的。目前，网络式的交叉对话路径和信息流图传达了复杂性。动态特性包括网络结构的瞬时和永久变化，其中通路组分从一个亚细胞位置移动到另一个亚细胞位置，组分在不同的蛋白质复合物中缔合，以及受体、换能器和靶标的整个库和连接性随着细胞状态的变化而变化。为了在数学上探测信号传导过程，我们正在开发一个“途径建模数据库”（SIGMOID），旨在：1）以计算反映基础生物化学的方式捕获和组织各种专家知识和数据。因此，通路被表示为它们的潜在化学反应和分子缔合。它还规定了反应物和产物的信号-依赖性空间区室化，并提供了反应对反应物分子状态（磷酸化、甲基化、GDP结合等）的生物学适当依赖性。2)提供基于存储的反应网络体系结构的计算模型的自动生成，该体系结构与可扩展的建模程序套件相结合。3)从计算模拟中获取和存储结果，并提供用于比较、可视化和挖掘模拟结果的工具。