Software Integration between JSim and Systems Biology Workbench

描述(申请人提供)：这个软件开发项目结合了来自三个经验丰富的小组的观点和软件，以创建和维护可用于系统生物学和生理数据分析的最先进和完整的软件包，用于研究和临床实践。该项目包括：(1)JSim系统，用于使用普通和一维运输和代谢偏微分方程进行单尺度或多尺度模型分析(Butterworth和Bassingthwaighte，华盛顿大学)，(2)系统生物学工作台和相关软件编码包，由Herbert Sauro(华盛顿大学)发明，以及(3)热力学约束和详细的生化反应方程，从反应平衡和动力学数据库自动创建(Daniel Beard，威斯康星州医学院)。这三种强大的技术的结合，都利用了SBML和CellML等档案数据库标记语言，将促进使用JSim内置的错误识别和纠正机制进行模型构建。这些工具包和模型将以易于理解的代码在全球传播，并将在包括Windows、Macintosh和Linux在内的各种计算平台上提供准确和直接可重现的解决方案。这些模型将被设计用于实验设计和分析，模型和分析包的开放源代码将免费提供给世界各地的研究人员。这种强大的结合与改善健康有关，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了解完整的细胞器官和身体功能的实用机制。许多当代生物学家在复杂系统的定量分析方面没有接受过深入的培训，因此这些工具的可用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靶向实验、更有效的数据分析和改进疗法的能力。公共卫生相关性：这项研究将加快从基因组学、遗传网络调控、生化网络行为和细胞功能的基础研究向提供长期公共健康益处的临床应用的转变。它将通过建模进行更好的定向实验，并通过改进治疗结果的预测来实现。

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.