CRCNS Data Sharing: NeuroML Database for Multiscale Neuroscience Models

CRCNS 数据共享：用于多尺度神经科学模型的 NeuroML 数据库

• 批准号: 8313860
• 负责人: Sharon Marie Crook
• 金额: $ 9.53万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8313860
• 关键词: Archives; Area; Commit; Communities; Complex; Computer software; Data; Databases; Development; Discipline; Documentation; Education; Educational Curriculum; Educational process of instructing; Ensure; Excitatory Synapse; Extensible Markup Language; Feedback; Funding; Goals; Individual; International; Ion Channel; Language; Mentors; Minority; Modeling; Morphology; Neurons; Neurosciences; Neurosciences Research; Pathology; Potassium Channel; Publications; Publishing; Research; Research Infrastructure; Research Personnel; Stream; Structure; Students; Synapses; System; Testing; Training Programs; Woman; Work; base; computational neuroscience; computer science; data exchange; data modeling; data sharing; design; information model; multi-scale modeling; network models; portability; programs; relating to nervous system; role model; tool; undergraduate student; user-friendly; web based interface

DESCRIPTION (provided by applicant): Intellectual Merit: The complexity of problems associated with structure and function in neuroscience requires that research from multiple groups across many disciplines be combined. In order to combine research from multiple groups, there must be an infrastructure for sharing data and exchanging models; however, the current use of multiple formats for encoding model information in the computational neuroscience community has hampered model exchange. The PI has collaborated extensively on the Neural Open Markup Language project, NeuroML, which is an international, collaborative initiative to develop a structured, declarative language for describing complex neuronal and neuronal network models. The goals of the project are to create a simulator-independent description language that facilitates data archiving, data and model exchange, database creation, and model publication. This collaborative initiative focuses on the key objects that need to be exchanged among existing software applications, such as descriptions of neuronal morphology, ion channels, synaptic mechanisms, and network structure. This modular approach brings additional benefits: not only can entire models be published and exchanged, but each individual object--such as a specific potassium channel or excitatory synapse--can be shared and re-implemented in a different model. The openness of the standards and the encouragement of feedback from many sections of the community are some of the guiding principles of the NeuroML initiative. The use of XML as a definition language provides the transparency, portability and extensibility required in these efforts, and also brings an infrastructure of established tools for efficient software and database development. The activities described in this proposal will take advantage of this infrastructure to provide a stream-lined set of tools for the computational neuroscience community to share, find, view, and test NeuroML models and their components. The specific aims of the proposed data sharing activities are to (1) develop and populate a XMLbased database system for multiscale models in neuroscience that are described using NeuroML, (2) integrate the web-based interface for the database with other NeuroML tools, including a LEMS-based model viewer, and (3) create user-friendly documentation and tutorials to ensure that the database will be useful for research and education. Broader Impacts: The database system proposed here is complementary to other existing model database efforts. In contrast to these other efforts, the modular design of NeuroML and use of XML provides for efficient searching and makes it much easier for a researcher to choose components from different models to combine for re-use. The development of a stream-lined tool chain for finding, viewing and testing these complex models and model components and the ease of re-implementing them on a different simulator could have a large impact on the field of computational neuroscience and also makes these complex models accessible for educational purposes. The PI and co-PI are both heavily committed to interdisciplinary teaching, bringing computer science and computational concepts into other areas of the curriculum. Drs. Crook and Dietrich also both work in areas where women are underrepresented and have demonstrated a commitment to serve as role models and mentors for other underrepresented groups in these fields. Dr. Crook has been involved with many training programs that target minority access to research. Dr. Crook works with underrepresented undergraduate students through programs funded by other mechanisms at ASU, and several of these students will have the opportunity to work on this project as part of those programs.

描述（由申请人提供）：智力优点：神经科学中与结构和功能相关的问题的复杂性要求将来自多个学科的多个小组的研究结合起来。为了结合多个小组的研究，必须有一个共享数据和交换模型的基础设施；然而，当前计算神经科学界使用多种格式来编码模型信息阻碍了模型交换。 PI 在神经开放标记语言项目 NeuroML 上进行了广泛合作，这是一项国际合作计划，旨在开发一种结构化的声明性语言来描述复杂的神经元和神经元网络模型。该项目的目标是创建一种独立于模拟器的描述语言，以促进数据归档、数据和模型交换、数据库创建和模型发布。该合作计划重点关注现有软件应用程序之间需要交换的关键对象，例如神经元形态、离子通道、突触机制和网络结构的描述。这种模块化方法带来了额外的好处：不仅可以发布和交换整个模型，而且每个单独的对象（例如特定的钾通道或兴奋性突触）都可以在不同的模型中共享和重新实现。标准的开放性和鼓励社区许多部门提供反馈是 NeuroML 计划的一些指导原则。使用 XML 作为定义语言提供了这些工作所需的透明度、可移植性和可扩展性，并且还为高效软件和数据库开发带来了现有工具的基础结构。本提案中描述的活动将利用该基础设施为计算神经科学界提供一套简化的工具，以共享、查找、查看和测试 NeuroML 模型及其组件。拟议数据共享活动的具体目标是 (1) 为使用 NeuroML 描述的神经科学多尺度模型开发和填充基于 XML 的数据库系统，(2) 将数据库的基于 Web 的界面与其他 NeuroML 工具（包括基于 LEMS 的模型查看器）集成，以及 (3) 创建用户友好的文档和教程，以确保数据库对研究和教育有用。更广泛的影响：这里提出的数据库系统是对其他现有模型数据库工作的补充。与这些其他努力相比，NeuroML 的模块化设计和 XML 的使用提供了高效的搜索，并使研究人员更容易从不同模型中选择组件以进行组合以进行重用。开发用于查找、查看和测试这些复杂模型和模型组件的简化工具链，以及在不同模拟器上重新实现它们的便捷性，可能会对计算神经科学领域产生巨大影响，也使得这些复杂模型可用于教育目的。 PI 和 co-PI 都致力于跨学科教学，将计算机科学和计算概念引入课程的其他领域。博士。克鲁克和迪特里希也都在女性代表性不足的领域工作，并承诺为这些领域的其他代表性不足的群体充当榜样和导师。克鲁克博士参与了许多针对少数群体获得研究机会的培训项目。克鲁克博士通过亚利桑那州立大学其他机制资助的项目与代表性不足的本科生合作，其中一些学生将有机会参与该项目，作为这些项目的一部分。