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SEEK: a systems biology data and model management platform

机译:SEEK:系统生物学数据和模型管理平台

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Background Systems biology research typically involves the integration and analysis of heterogeneous data types in order to model and predict biological processes. Researchers therefore require tools and resources to facilitate the sharing and integration of data, and for linking of data to systems biology models. There are a large number of public repositories for storing biological data of a particular type, for example transcriptomics or proteomics, and there are several model repositories. However, this silo-type storage of data and models is not conducive to systems biology investigations. Interdependencies between multiple omics datasets and between datasets and models are essential. Researchers require an environment that will allow the management and sharing of heterogeneous data and models in the context of the experiments which created them. Results The SEEK is a suite of tools to support the management, sharing and exploration of data and models in systems biology. The SEEK platform provides an access-controlled, web-based environment for scientists to share and exchange data and models for day-to-day collaboration and for public dissemination. A plug-in architecture allows the linking of experiments, their protocols, data, models and results in a configurable system that is available 'off the shelf'. Tools to run model simulations, plot experimental data and assist with data annotation and standardisation combine to produce a collection of resources that support analysis as well as sharing. Underlying semantic web resources additionally extract and serve SEEK metadata in RDF (Resource Description Format). SEEK RDF enables rich semantic queries, both within SEEK and between related resources in the web of Linked Open Data. Conclusion The SEEK platform has been adopted by many systems biology consortia across Europe. It is a data management environment that has a low barrier of uptake and provides rich resources for collaboration. This paper provides an update on the functions and features of the SEEK software, and describes the use of the SEEK in the SysMO consortium (Systems biology for Micro-organisms), and the VLN (virtual Liver Network), two large systems biology initiatives with different research aims and different scientific communities.
机译:背景系统生物学研究通常涉及异构数据类型的集成和分析,以便建模和预测生物学过程。因此,研究人员需要工具和资源来促进数据的共享和集成,以及将数据链接到系统生物学模型。有大量的公共存储库用于存储特定类型的生物数据,例如转录组学或蛋白质组学,并且有几个模型存储库。但是,这种筒仓式的数据和模型存储方式不利于系统生物学研究。多个组学数据集之间以及数据集和模型之间的相互依赖性至关重要。研究人员需要一种环境,该环境应允许在创建异类数据和模型的实验中进行管理和共享。结果SEEK是一套工具,可支持系统生物学中数据和模型的管理,共享和探索。 SEEK平台为科学家提供了一个访问控制的,基于Web的环境,以便共享和交换数据和模型以进行日常合作和进行公共传播。插件架构允许链接实验,其协议,数据,模型和结果,从而构成可“现成”使用的可配置系统。用于运行模型仿真,绘制实验数据以及协助数据注释和标准化的工具结合在一起,可以生成支持分析和共享的资源集合。底层语义Web资源还提取并以RDF(资源描述格式)提供SEEK元数据。 SEEK RDF支持在SEEK内部以及链接的开放数据Web中的相关资源之间进行丰富的语义查询。结论SEEK平台已被欧洲许多系统生物学联盟所采用。它是一种数据管理环境,具有较低的使用障碍,并提供了丰富的协作资源。本文提供了SEEK软件功能和特性的更新,并介绍了SEEK在SysMO联盟(微生物的系统生物学)和VLN(虚拟肝脏网络)中的使用,这两个大型系统生物学举措具有不同的研究目标和不同的科学共同体。

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