(SEI+II (BIO)) Interactive Visualization and Analysis of Large-Scale Graphs for Biological Network Modeling

(SEI II (BIO)) 用于生物网络建模的大规模图的交互式可视化和分析

• 批准号: 0612240
• 负责人: Eve Wurtele
• 金额: --
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0612240&HistoricalAwards=false
• 关键词: SEI+II; BIO; Interactive; Visualization; Analysis

The ultimate goal of this research is to integrate visual and computational descriptions of complex metabolic and regulatory networks to aid biologists in evaluating hypotheses for how these dynamic networks function under different conditions. These networks will combine graph models from pathway databases, text-mining programs, machine learning systems, and other sources, together with multiple classes of experimental data. The unique features of the proposed graph visualization and analysis platform are: 1) Evaluation of the structural effects of dynamic links that change depending on time and other conditions. 2) The ability to immediately integrate current research hypotheses with available published results to evaluate their impact and explanatory power. 3) Interactive display of large metabolic and regulatory networks in either user- or automatically selected levels of detail. 4) Creation of visual graph display tools specifically designed for improved biological network display, comparison, and analysis. As part of this process, significant problems in the analysis of variable graph structures, incremental graph layout, and effective visualization and labeling will be addressed with an interdisciplinary focus. The software will be open source and freely available to academic institutions. It will be evaluated and validated using three interrelated but only partially understood signal transduction networks: ethylene, jasmonate and salicylic acid. These pathways interact complexly to direct specific plant defense responses to stress. The software will contribute to the research community's open source software toolbox by providing more effective ways to visualize and manipulate graphs. By actively integrating biologists in the design and development we will ensure practical applicability and usability for non-computer-expert users. Education and outreach activities will promote research, K-12 and undergraduate education, and dissemination of results to a broad audience, while developing a new generation of scientists that employ the powers of computers to their fullest to advance all sciences.

这项研究的最终目的是整合复杂代谢和调节网络的视觉和计算描述，以帮助生物学家评估这些动态网络在不同条件下如何运作的假设。这些网络将结合路径数据库，文本挖掘程序，机器学习系统和其他来源的图形模型，以及多种类别的实验数据。提出的图形可视化和分析平台的独特特征是：1）评估根据时间和其他条件而改变的动态链接的结构效应。 2）能够立即将当前的研究假设与可用公开的结果相结合以评估其影响和解释能力的能力。 3）在用户或自动选择的细节级别中，大型代谢和调节网络的交互式显示。 4）创建专门设计用于改进生物网络显示，比较和分析的视觉图表显示工具。 作为此过程的一部分，将以跨学科的焦点解决可变图结构，增量图布局以及有效的可视化和标记的重大问题。该软件将是开源的，并可以免费提供给学术机构。它将使用三个相互关联但仅部分理解的信号转导网络对其进行评估和验证：乙烯，jasmonate和水杨酸。 这些途径复杂地相互作用，以指导特定的植物防御反应对压力。 该软件将通过提供更有效的可视化和操纵图的方法来为研究社区的开源软件工具箱做出贡献。通过将生物学家积极整合到设计和开发中，我们将确保对非计算机 - 专家用户的实际适用性和可用性。 教育和外展活动将促进研究，K-12和本科教育，并将结果传播给广泛的受众，同时开发新一代的科学家，这些科学家将计算机的力量充分促进了所有科学。