MultiMod, flexible management for multi-scale multi-approach models in biology

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数学模型，这些模型可以用计算机模拟。这种方法被称为“计算系统生物学”。正如在大多数科学领域一样，数据库对于“站在巨人的肩膀上”是必不可少的。biommodels提供了已在科学文献中发表并被验证为准确的定量生物学模型的访问。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。生物模型自2005年在EMBL-EBI创建以来，并自2008年以来得到了BBSRC的支持，经历了指数级的增长，成为全球生物过程定量模型的参考。数百个科学期刊建议在发布时保存模型，该资源每年收到大约65000个不同用户的大约100万次页面请求。近年来，生物过程的数学模型变得越来越大，越来越复杂。为了能够更准确地表示有生命的结构，开发了多尺度模型，通过耦合在一起的组件来描述发生在不同尺度上的过程。由于过程的性质以及可用的实验信息，使用了各种建模方法。2012年，一份具有里程碑意义的出版物描述了一种细菌（生殖支原体）的第一个这样的模型，该模型解释了它的所有成分及其相互作用。器官和生物体的多尺度模型（例如bbsrc资助的拟南芥模型）现在是可用的。必须使这些模型可用，而不管它们的结构、所使用的建模方法和编码格式如何。由Babraham研究所和EMBL-EBI合作开发的MultiMod项目将大大扩展生物模型的覆盖范围，以支持生物科学中开发的各种数学模型。这将通过接受更多的文件格式、改进对标准格式的支持和扩展分布的信息（例如包括必要的实验数据集、模拟描述等）来实现。我们还将通过复制已发表的结果来扩展我们验证的模型的范围。在扩大范围的同时，将改进作为资源基础的软件和硬件基础结构。为了使资源更有用，我们将开发更好的浏览、搜索和下载功能。最后，我们将改进和进一步发展我们的文档和培训服务，包括在线和面对面的教程和课程。我们期望MultiMod能够显著改善用户体验，增加使用该资源的用户和社区的数量，并使其对英国生物科学更有用。

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 mathematical models of them which can be simulated using computers. This approach is known as "Computational Systems Biology". As in most domains of science, databases are essential to allow the proverbial "standing on the shoulders of giants". BioModels provides access to quantitative biology models that have been published in the scientific literature, and verified to be accurate. 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. Since its creation at EMBL-EBI in 2005 - and supported by the BBSRC since 2008 - BioModels has undergone an exponential growth to become the worldwide reference for quantitative models of biological processes. Deposition of models upon publication is advised by several hundred scientific journals, and the resource receives around a million page requests a year from around 65 000 distinct users.Over the recent years, mathematical models of biological processes have become larger and more complex. To be able to represent more accurately living structures, multi-scale models are developed, with processes taking place at different scales described by components coupled together. Because of the nature of the processes as well as the experimental information available, a variety of modelling approaches are use. In 2012, a landmark publication described the first such model of a bacterium (Mycoplasma genitalium) that accounts for all of its components and their interactions. Multi-scale models of organs and organisms (for instance the BBSRC-funded model of Arabidopsis) are now available. Those models must be made available, regardless of their structure, the modelling approach used and the formats they are encoded with.The MultiMod project, developed in collaboration by the Babraham Institute and EMBL-EBI, will extend BioModels coverage considerably, to support a large variety of mathematical models developed in the biosciences. This will be achieved by accepting more file formats, improving support for standard formats and expanding the information distributed (for instance including necessary experimental datasets, simulation descriptions etc). We will also expand the spectrum of models we verify by reproducing published results. Such an increase in scope will be accompanied by an improvement of the software and hardware infrastructure underlying the resource. To make the resource more useful we will develop better browsing, search and download capabilities. Finally, we will improve and further develop our documentation and training offer, including online and in person tutorial and courses. We expect that MultiMod will improve the user experience significantly, increase the number of users and the communities using the resource, and make it more useful for the UK biosciences.