Software Integration between JSim and Systems Biology Workbench

项目摘要 这个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 创建和维护可用于系统的最先进、最完整的软件包 生物学和生理数据分析，用于研究和临床实践。该项目包括：(1) JSim系统用于基于模型的分析，使用普通和1- 运输和新陈代谢的维偏微分方程(Butterworth和Bassingthwaighte， 华盛顿大学)，(2)发明了系统生物学工作台和相关的软件编码包 由Herbert Sauro(华盛顿大学)提出，以及(3)热力学约束和详细的方程 从反应平衡和动力学数据库中自动创建生化反应(Daniel Beard， 威斯康星医学院)。这三项强大技术的结合，所有这些技术都利用了档案 像SBML和CellML这样的数据库标记语言将促进使用JSim的内置错误进行模型构建 识别和纠正机制。工具包和模型将轻松地在全球范围内传播 理解代码，并将在广泛的计算范围内提供准确和直接可重现的解决方案 平台包括Windows、Macintosh和Linux。这些模型将用于实验设计和 分析，模型和分析包的开放源代码将免费提供给 到处都是调查人员。这种强大的组合与改善健康有关，因为它提供了 具有实用机制的基因组学、分子生物学、生理学和药理学的研究人员 预测和了解完整的细胞器官和身体功能。许多当代的 生物学家在复杂系统的定量分析方面没有受过深入的培训，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和他们更精确地设计目标的能力 实验、更有效的数据分析和改进的治疗方法。

Project Summary 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.