BioModels Database: a Unified resource for Systems Biology models

即使是最简单的生物体也要进行大量不同的过程，这些过程以复杂的方式相互联系，以确保生物体对其环境做出适当的反应。确保我们真正理解这些过程是如何结合在一起的方法之一是建立它们的定量模型，可以用计算机模拟。如果计算机模拟的行为与真实生物体不同，我们就知道我们忽略了系统的一个重要组成部分。定量模型还可以揭示复杂系统以前未被认识到的特性，例如为新药治疗铺平道路。这种被称为“计算系统生物学”的方法现在正变得越来越流行，因为科学家们正在为许多生物体积累详细的部件列表，这要归功于“组学”对生物体组成的全面记录。生物模型数据库提供访问生物化学和细胞生物学系统的定量模型，已发表在科学文献中，并证实是准确的。其中一些模型非常简单，只包含几个过程或反应；其他的包含数百个。检查模型以验证它们的行为是否与参考出版物中描述的一致。人工管理员注释模型的组件，并将其与其他相关数据资源交叉链接。这允许用户精确地识别模型的组件，并帮助他们检索适当的模型，然后他们可以使用适当的软件对模型进行可视化和模拟。例如，为了建立细胞肿瘤发生的定量模型，可以选择一个合适的细胞周期模型，并尝试将其与相关的细胞信号通路模型（如MAP激酶级联）合并。只有一个可信的、同行评审的、带注释的模型数据库才能提供足够的“积木”选择。用户可以根据许多不同的标准搜索模型，将其可视化，并以各种标准格式下载以供进一步使用。在过去的两年里，生物模型数据库经历了指数级的增长。它现在是定量模型的参考数据资源。一些科学期刊建议在发表时沉积模型，并且该数据库已被独立社区调查投票为系统生物学中最常用的数据资源。作为概念的证明，生物模型数据库已经证明了它的相关性和需要在一个更成熟的资源中发展，以便最好地服务于不断增长的英国系统生物学社区的需要。

Even the simplest living organisms perform a huge number of different processes, which are interconnected in complex ways to ensure that the organism responds appropriately to its environment. One of the ways of ensuring that we really understand how these processes fit together is to build quantitative models of them, that can be simulated using computer. If a computer simulation behaves differently than the real organism, we know that we've neglected an important component of the system. Quantitative models can also reveal previously unappreciated properties of complex systems, for instance paving the way toward new drug treatments. This approach, known as 'Computational Systems Biology', is becoming increasingly popular now that scientists are accumulating detailed parts lists for many organisms, thanks to the 'omics' efforts to comprehensively document the components of living entities. BioModels Database provides access to quantitative models of biochemical and cell biological systems that have been published in the scientific literature, and verified to be accurate. Some of these models are very simple, containing just a few processes or reactions; others contain hundreds. The models are checked to verify that they behave as described in the reference publication. Human curators annotate and cross link components of the models to other relevant data resources. This allows users to identify precisely the components of models, and helps them to retrieve appropriate models, which they can then visualise and simulate using appropriate software. For instance, in order to develop a quantitative model of cell tumorigenesis, one may choose a suitable model of cell-cycle, and attempt to merge it with models of relevant cell signalling pathways such as the MAP kinase cascade. Only a database of trusted, peer-reviewed, annotated models will provide the adequate choice of 'building bricks'. Users can search models on many different criteria, visualise and and download them in various standard formats for further use. Over the last two years, BioModels Database has undergone an exponential growth. It is now the reference data resource for quantitative models. Deposition of models upon publication is advised by several scientific journals, and the atabase has been voted most used data resource in Systems Biology by an independent community survey. Developed as a proof of concept, BioModels Database has demonstrated its relevance and needs to evolve in a more mature resource in order to best serve the need of a growing UK Systems Biology community.