Continued Support and Development of SBML

描述（由申请人提供）：系统生物学标记语言（SBML）是生物系统中生物化学网络计算模型的流行存储和交换格式。本申请作为补充拨款（1 R01 GM070923-01）资助SBML语言和一些相关软件工具的基础研究和开发。为了响应来自用户社区的频繁请求，我们建议开发一种新的相关资源：带注释的模型数据库。该数据库（我们称其为“biomodels.net”，以我们为其使用保留的网站名称命名）将是一个免费的资源，并将具有浏览、搜索、可视化和导出功能，可通过web浏览器界面和远程API（应用程序编程接口）访问。它将专门面向生物系统中生化网络的计算模型。除了SBML之外，该系统将提供以多种格式导出模型的能力，最大限度地利用各种软件工具为建模者提供实用工具。

DESCRIPTION (provided by applicant): The Systems Biology Markup Language (SBML) is a popular storage and exchange format for computational models of biochemical networks in biological systems. The grant to which this application is a supplement (1 R01 GM070923-01) funds basic research and development on the SBML language and some associated software tools. In response to frequent requests from the user community, we propose to develop a new, related resource: an annotated model database. The database (which we call "biomodels.net", after the website name we have reserved for its use) will be a freely available resource and will feature browsing, searching, visualization and exporting capabilities, accessible from both a web browser interface and remote API (application programming interface). It will be oriented specifically to computational models of biochemical networks in biological systems. The system will provide the ability to export models in a number of formats besides SBML, maximizing its utility to modelers using a variety of software tools. There are three main aspects to the work proposed here: (a) developing the software infrastructure of the database/web system, (b) developing SBML extensions for supporting better categorization of models and their components in a database context, and (c) performing manual examination and annotation (curation) of models submitted to the database. In order to achieve these aims, we will expand the size of our team at our current work sites and also add collaborators at the European Bioinformatics Institute (EBI) in the UK. Computational modeling is becoming increasingly important in biology for helping us cope with the vast size and complexity of natural organisms. The use of quantitative models by experimental scientists promises to pave the way for more rigorous analyses of biological functions, leading to deeper understanding and ultimately to new and better treatments for diseases. But for this to happen, the computational models themselves must reach a wider audience. We believe biomodels.net will act as a crucial community resource enabling greater exchange of models, ideas and research results, accelerating the uptake of computational modeling in biology.