Software tools for reproducibly simulating, analyzing, and visualizing biomodels

用于可重复地模拟、分析和可视化生物模型的软件工具

• 批准号: 10676069
• 负责人: Ion I. Moraru
• 金额: $ 15.94万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-06-13 至 2024-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10676069
• 关键词: Address; Algorithms; Archives; Big Data Methods; Biochemical; Biological Process; Collaborations; Computer software; Data; Databases; Deposition; Educational workshop; Ensure; Genus Mentha; Individual; Journals; Knowledge; Language; Maps; Metadata; Modeling; Online Systems; Ontology; Pythons; Reporting; Reproducibility; Research Personnel; Resources; Running; Semantics; Services; Software Engineering; Software Tools; Source Code; System; Systems Biology; Testing; Training; Validation; Visual; Visualization; Visualization software; Work; biochemical model; biological systems; data visualization; design; digital; digital models; experimental study; improved; interactive tool; interoperability; models and simulation; new technology; novel; open source; outreach; predictive modeling; repository; simulation; technology research and development; tool; user-friendly; web platform; web server; web site; web-based tool

TECHNOLOGY RESEARCH & DEVELOPMENT 3: PROJECT SUMMARY Models represent our knowledge, observations and hypotheses in a testable digital framework. Because models are digital, it should be easy to reuse models and reproduce simulation results. However, many dynamic biochemical models are not reusable and many simulation results are not reproducible, including models and simulation results reported in standard formats such as the Systems Biology Markup Language (SBML) and the Simulation Experiment Description Markup Language (SED-ML). This irreproducibility limits the impact of modeling by inhibiting researchers from reusing models and simulation results for additional studies and combining models of individual biological processes into meta-models of entire biological systems. Currently, models are hard to reuse and simulations are hard to reproduce because (a) few researchers report the metadata needed to reproduce simulations, (b) there are many incompatible simulators, (c) there is no simulation results repository, (d) there is no standard for reducing simulation results, (e) there is no standard for describing results visualizations, and (f) there are inadequate tools for visualizing simulation results. To address these problems, we will develop novel tools and public servers for (a) using existing simulators to reproducibly simulate a wide range of models and (b) storing and (c) visualizing simulation results: 1. We will build a database for storing models, simulation experiments, their results, and their metadata which will mint DOIs and support queries over simulation results. The system will help researchers share and retrieve simulation results and apply big data analytics to simulation results. In turn, the system will help researchers reuse simulation experiments and reproduce simulation results. 2. We will build a simulation system which provides a common interface to multiple simulators that each support individual simulation algorithms and modeling domains. This will make it easy for researchers to reuse models and reproduce simulations without having to install domain-specific simulators. 3. We will build a web-based system for using the simulation system and simulation results database to interactively simulate and visualize models in a browser. This will enable researchers to retrieve deposited simulation results, request new simulations, and visually analyze simulation results. To ensure our tools advance biomodeling, we will develop our tools in conjunction with several CPs and SPs which will provide model repositories and journals web-based tools for interactively simulating and visualizing reported models. These CPs will push us to develop user-friendly tools, and we will pull the CPs to require model authors to annotate their simulation experiments so they are reproducible. To help researchers use our software, we will work with TR&Ds 1 and 2 to combine our software into a reproducible modeling workflow. We will also extensively document our software and distribute it open-source. In addition, as part of the Training and Dissemination Core, we will develop tutorials and organize workshops.

技术研发3：项目概要 模型在可测试的数字框架中代表了我们的知识、观察和假设。因为 模型是数字化的，应该易于重用模型并重现仿真结果。然而，许多 动态生化模型不可重复使用，许多模拟结果不可重现，包括 以系统生物学标记语言等标准格式报告模型和模拟结果 (SBML) 和仿真实验描述标记语言 (SED-ML)。这种不可重复性限制了 通过阻止研究人员重复使用模型和模拟结果来实现建模的影响 研究并将个体生物过程的模型组合成整个生物系统的元模型。 目前，模型很难重用，模拟也很难重现，因为 (a) 很少有研究人员报告 重现模拟所需的元数据，(b) 有许多不兼容的模拟器，(c) 没有 模拟结果存储库，(d) 没有减少模拟结果的标准，(e) 没有标准 用于描述结果可视化，以及 (f) 用于可视化模拟结果的工具不足。 为了解决这些问题，我们将开发新颖的工具和公共服务器，以便 (a) 使用现有的模拟器 可重复地模拟各种模型，并 (b) 存储和 (c) 可视化模拟结果： 1. 我们将建立一个数据库，用于存储模型、模拟实验、结果及其元数据 这将生成 DOI 并支持对模拟结果的查询。该系统将帮助研究人员 共享和检索模拟结果并将大数据分析应用于模拟结果。反过来， 系统将帮助研究人员重复使用模拟实验并再现模拟结果。 2. 我们将构建一个模拟系统，为多个模拟器提供通用接口，每个模拟器 支持单独的仿真算法和建模领域。这将使研究人员更容易 重用模型并重现模拟，而无需安装特定于领域的模拟器。 3. 我们将建立一个基于网络的系统，使用仿真系统和仿真结果数据库来 在浏览器中交互式地模拟和可视化模型。这将使研究人员能够检索 存储模拟结果、请求新的模拟以及直观地分析模拟结果。 为了确保我们的工具推进生物建模，我们将与多个 CP 和 SP 联合开发我们的工具 它将提供模型存储库和基于网络的期刊工具，用于交互式模拟和可视化 报告的模型。这些CP将推动我们开发用户友好的工具，我们将拉动CP来要求 模型作者注释他们的模拟实验，以便它们是可重复的。 为了帮助研究人员使用我们的软件，我们将与 TR&D 1 和 2 合作，将我们的软件整合到一个 可重复的建模工作流程。我们还将广泛记录我们的软件并以开源方式分发它。 此外，作为培训和传播核心的一部分，我们将开发教程并组织研讨会。