BioModels Database, the comprehensive resource for computational models in biology

即使是最简单的生物体也会执行大量不同的过程，这些过程以复杂的方式相互关联，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的生物体不同，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重视的特性，例如为新药治疗铺平道路。这种方法被称为“计算系统生物学”，由于“组学”努力全面记录生物体的组成部分，科学家们正在积累许多生物体的详细部件列表，这种方法正变得越来越流行。BioModels数据库提供了已在科学文献中发表并经验证准确的生物化学和细胞生物学系统的定量模型。其中一些模型非常简单，只包含几个过程或反应;另一些模型包含数百甚至数千个过程或反应。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样。人工管理员将模型的注释和交叉链接组件添加到相关的外部数据资源。这使用户能够准确地识别模型的组成部分，并帮助他们检索适当的模型，然后他们可以可视化，模拟（在线或使用适当的专用软件）和下载（以各种格式）。例如，为了开发细胞肿瘤发生的定量模型，可以选择合适的细胞周期模型，并尝试将其与相关细胞信号传导途径（如MAP激酶级联）的模型合并。只有一个可信的、经过同行审查的、附有注释的最新最先进的模型数据库才能提供适当的“积木”选择。用户可以根据许多不同的标准搜索模型，可视化并以各种标准格式下载它们以供进一步使用。自2005年创建以来-自2008年以来得到BBSRC的支持- BioModels数据库经历了指数级增长，成为生物过程定量模型的全球参考。数百种科学期刊建议在出版时存放模型，该资源每年收到约100万页的请求。在一个成熟的资源服务于不断增长的英国系统生物学社区的需要，生物模型数据库现在必须提供整个生物科学。这将通过将BioModels数据库的覆盖范围扩展到更多类型的模型来实现：使用不同的方法并以不同的尺度表示生物过程。我们还将改进软件支持，使模型的访问、分析和重复使用更容易。我们将提供更多的信息，而不仅仅是模型本身（模拟配方，相关数据集，.）以及更多的历史数据（允许用户探索模型如何演变为当前形式）。最后，资源的一个核心方面：检索感兴趣的模型，将大大方便。我们将为用户提供排名的搜索结果和更灵活的搜索策略，充分利用模型中包含的大量本体论注释。这一发展将对基础，应用和翻译研究产生重大影响。特别是药物发现、生物工程和合成生物学等以计算建模为核心的学科，将受益于更好的生物模型数据库，最终导致更好的老龄化、生物燃料的开发、更好的和更可持续的粮食供应。

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 computers. 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 or even thousands. The models are checked to verify that they behave as described in the reference publication. Human curators add annotations and cross link components of the models to relevant external data resources. This allows users to identify precisely the components of models, and helps them to retrieve appropriate models, which they can then visualise, simulate (online or by using appropriate dedicated software) and download (in various formats). 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 up-to-date state of the art models will provide the adequate choice of "building bricks". Users can search models based on many different criteria, visualise and download them in various standard formats for further use.Since its creation in 2005 - and supported by the BBSRC since 2008 - BioModels Database has undergone an exponential growth to become the worldwide reference forquantitative models of biological processes. Deposition of models upon publication is advised by several hundreds scientific journals and the resource receives around a million page requests a year. Having developed in a mature resource serving the need of a growing UK Systems Biology community, BioModels Database must now provides for the entire biosciences. This will be achieved by expanding the coverage of BioModels Database to more types of models: using different approaches and representing biological processes at different scales. W e will also improvee the software support to make access, analysis and re-use of the models easier. We will provide access to more information than just the models themselves (simulation recipes, associated dataset, ...) as well as more historical data (to allow users to explore how a model evolved to its current form). Finally, one core aspect of the resource: the retrieval of models of interest, will be greatly facilitated. We will provide users with ranked search results and more flexible search strategies, making full use of the plethora of ontological annotations contained in the models.This development will have a significant effect on basic, applied, and translational research. In particular drug discovery, bioengineering and synthetic biology, disciplines in which computational modelling is central, will benefit from a better BioModels Database, ultimately resulting on better ageing, development of biofuels, improved and more sustainable food supplies.