Software Integration between JSim and Systems Biology Workbench

描述（由申请人提供）：该软件开发项目结合了来自三个经验丰富的团队的观点和软件，以创建和维护将是系统生物学和生理数据分析研究和临床实践中最先进和最完整的软件包。该项目汇集了：(1)基于模型分析的JSim系统，使用普通和一维偏微分方程进行运输和代谢的单尺度或多尺度模型（Butterworth和Bassingthwaighte，华盛顿大学）；(2)Herbert Sauro（华盛顿大学）发明的系统生物学工作台和相关软件编码包；(3)从反应平衡和动力学数据库中自动创建的生化反应的热力学约束和详细方程（Daniel Beard，威斯康星医学院）。这三种强大的技术都利用了档案数据库标记语言（如SBML和CellML），它们的结合将促进使用JSim内置的错误识别和纠正机制的模型构建。这些工具包和模型将以易于理解的代码在全球范围内传播，并将在包括Windows、Macintosh和Linux在内的广泛计算平台上提供准确而直接的可复制解决方案。模型将用于实验设计和分析，模型的开源代码和分析包将免费提供给各地的研究者。这种强大的结合与健康的改善有关，因为它为基因组学、分子生物学、生理学和药理学的研究人员提供了预测和理解综合细胞器官和身体功能的实用机制。当前一代的许多生物学家在复杂系统的定量分析方面没有受过深入的训练，因此这些工具的可用性将极大地促进他们对生物学的理解，以及他们设计更精确的目标实验，更有效的数据分析和改进治疗的能力。公共卫生相关性：这项研究将加速从基因组学、遗传网络调控、生化网络行为和细胞功能的基础研究向临床应用的转化，提供长期的公共卫生效益。它将通过建模和改进的治疗结果预测来实现更好的定向实验。

DESCRIPTION (provided by applicant): This software development project combines the perspectives and software from three experienced groups to create and maintain what will be the most advanced and complete software package available for systems biology and the analysis of physiological data for research and clinical practice. The project brings together: (1) The JSim system for model based analysis using single or multi-scale models using ordinary and 1- dimensional partial differential equations for transport and metabolism (Butterworth and Bassingthwaighte, University of Washington), (2) the System Biology Workbench and related software coding packages invented by Herbert Sauro (Unversity of Washington), and (3) thermodynamically constrained and detailed equations for biochemical reactions created automatically from databases on reactions equilibria and kinetics (Daniel Beard, Medical College Wisconsin). The coalescence of these three powerful techniques, all of which utilize archival database markup languages like SBML and CellML, will foster model construction using JSim's inbuilt error identification and correction mechanisms. The toolkits and models will be disseminated worldwide in easily understood code, and will provide exactly and directly reproducible solutions on a wide range of computational platforms including Windows, Macintosh, and Linux. The models will be designed for experiment design and analysis, and the open source code for models and the analysis packages will be freely available to investigators everywhere. This powerful combination is relevant to the betterment of health as it provides investigators in genomics, molecular biology, physiology, and pharmacology with practical mechanisms for predicting and understanding integrated cellular organ and body function. Many of the current generation of biologists are not deeply trained in quantitative analysis of complex systems, so the availability of these tools will greatly facilitate their understanding of the biology and their ability to design more precisely targeted experimentation, more efficient data analysis, and improved therapies. PUBLIC HEALTH RELEVANCE: This research will expedite the translation from basic research in genomics, genetic network regulation, biochemical network behavior, and cell function to clinical applications that provide long range public health benefits. It will occur via better directed experimentation through modeling, and through improved prediction of therapy outcomes.