Ontologies and software tools for describing reproducible biomodels and biosimulations

技术研究与开发2：项目总结 TR&D 2旨在通过增强模型注释、模拟实验和 模拟结果随着模型在公共存储库中的积累， 新的研究，并将联合收割机模型组合成整个生物系统的综合元模型。但 目前，重用和联合收割机模型是一个挑战，因为很少有模型是可复制的或可理解的。 因此，建模人员目前浪费了大量的时间试图理解、复制和联合收割机 其他建模者（包括同一研究小组的其他建模者）发布的模型。 为了更容易理解、复制和联合收割机模型，我们必须做出假设、含义、 和模型的局限性。为了实现这一点，我们将开发模式、本体和软件工具， 明确描述（a）用于构建模型的数据和假设，（B）每个变量的含义， 模型中的方程，（c）每个模拟预测的含义，以及（d）实验验证， 给出模型预测的置信度以及哪些模型预测应该被信任。 我们还将开发几个软件工具，使用注释来可视化、分解、合并和转换 Antimony、BioNetGen、BISEN、CellML、MATLAB、MML、Python、SBML和SimBiology之间的模型。我们 通过将这些工具集成到我们的SemGen注释软件工具中，将使建模人员更容易使用这些工具。 为了确保这些工具加速生物建模，该TR&D将由四个合作项目驱动， 需要增强的注释模式和工具来理解、复制、重用和合并他们的模型。的 协作项目将推动我们为我们的工具开发用户友好的图形界面，我们将把 协作项目使用我们的新注释来更深入地注释他们的模型。 为了进一步帮助研究人员注释他们的模型，通过几个服务项目，我们还将提供几个 期刊、模型存储库和实验室注释服务，建模人员可以在其中提交模型进行验证 和专业策展人的注释。 本TR&D提供的方法、工具和服务将帮助建模者发现新研究的模型， 更好地理解已发布的模型，并增加和合并模型，以测试关于 生理学和病理生理学。 本TR&D基于我们在以下方面的丰富经验：（a）开发用于描述模型的模式，包括 用于描述基于物理学的模型的SemSim模式，（B）开发用于描述生物医学的本体 知识，包括生物学物理本体论，以及（c）开发用于注释的软件工具， 可视化和合并模型，包括SemGem软件程序和PhysioMap可视化。

TECHNOLOGY RESEARCH & DEVELOPMENT 2: PROJECT SUMMARY TR&D 2 aims to accelerate biomodeling through enhanced annotation of models, simulation experiments, and simulation results. As models accumulate in public repositories, there is an opportunity to reuse models for new studies and to combine models into comprehensive meta-models of entire biological systems. However, it is currently challenging to reuse and combine models because few models are reproducible or understandable. Consequently, modelers currently waste huge amounts of time trying to understand, reproduce, and combine models published by other modelers, including other modelers in the same research group. To make it easier to understand, reproduce, and combine models, we must make the assumptions, meanings, and limitations of models explicit. To achieve this, we will develop schemas, ontologies, and software tools for clearly describing (a) the data and assumptions used to build models, (b) the meaning of each variable and equation in a model, (c) the meaning of each simulation prediction, and (d) the experimental validations that give confidence in model predictions and which model predictions should be trusted. We will also develop several software tools that use annotations to visualize, decompose, merge, and convert models among Antimony, BioNetGen, BISEN, CellML, MATLAB, MML, Python, SBML, and SimBiology. We will make it easy for modelers to use these tools by integrating them into our SemGen annotation software tool. To ensure these tools accelerate biomodeling, this TR&D will be driven by four Collaborative Projects which need enhanced annotation schemas and tools to understand, reproduce, reuse, and merge their models. The Collaborative Projects will push us to develop user-friendly graphical interfaces to our tools, and we will pull the Collaborative Projects to use our new annotations to annotate their models more deeply. To further help researchers annotate their models, via several Service Projects, we will also provide several journals, model repositories, and labs annotation services where modelers can submit models for validation and annotation by an expert curator. The methods, tools, and services provided by this TR&D will help modelers discover models for new studies, better understand published models, and augment and merge models to test new hypotheses about physiology and pathophysiology. This TR&D builds on our extensive experience in (a) developing schemas for describing models including the SemSim schema for describing physics-based models, (b) developing ontologies for describing biomedical knowledge including the Ontology of Physics for Biology, and (c) developing software tools for annotating, visualizing, and merging models including the SemGem software program and the PhysioMap visualization.