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Text-mining-assisted biocuration workflows in Argo

机译：Argo中的文本挖掘辅助生物固化工作流程

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Biocuration activities have been broadly categorized into the selection of relevant documents, the annotation of biological concepts of interest and identification of interactions between the concepts. Text mining has been shown to have a potential to significantly reduce the effort of biocurators in all the three activities, and various semi-automatic methodologies have been integrated into curation pipelines to support them. We investigate the suitability of Argo, a workbench for building text-mining solutions with the use of a rich graphical user interface, for the process of biocuration. Central to Argo are customizable workflows that users compose by arranging available elementary analytics to form task-specific processing units. A built-in manual annotation editor is the single most used biocuration tool of the workbench, as it allows users to create annotations directly in text, as well as modify or delete annotations created by automatic processing components. Apart from syntactic and semantic analytics, the ever-growing library of components includes several data readers and consumers that support well-established as well as emerging data interchange formats such as XMI, RDF and BioC, which facilitate the interoperability of Argo with other platforms or resources. To validate the suitability of Argo for curation activities, we participated in the BioCreative IV challenge whose purpose was to evaluate Web-based systems addressing user-defined biocuration tasks. Argo proved to have the edge over other systems in terms of flexibility of defining biocuration tasks. As expected, the versatility of the workbench inevitably lengthened the time the curators spent on learning the system before taking on the task, which may have affected the usability of Argo. The participation in the challenge gave us an opportunity to gather valuable feedback and identify areas of improvement, some of which have already been introduced. Database URL: http://argo.nactem.ac.uk
机译：生物治疗活动大致分为相关文件的选择，感兴趣的生物学概念的注释以及概念之间相互作用的识别。事实证明，文本挖掘在所有三个活动中都有可能显着减少生物管理者的工作量，并且各种半自动方法已集成到管理管道中以支持它们。我们研究了Argo（一种使用丰富图形用户界面构建文本挖掘解决方案的工作台）在生物固化过程中的适用性。 Argo的中心是可定制的工作流，用户可通过安排可用的基本分析来形成特定于任务的处理单元，从而构成这些工作流。内置的手动注释编辑器是工作台上最常用的生物固化工具，因为它允许用户直接在文本中创建注释以及修改或删除由自动处理组件创建的注释。除了句法和语义分析之外，不断增长的组件库还包括多个数据读取器和使用者，它们支持完善的以及新兴的数据交换格式（例如XMI，RDF和BioC），从而促进Argo与其他平台或平台的互操作性。资源。为了验证Argo在策展活动中的适用性，我们参加了BioCreative IV挑战赛，该挑战赛的目的是评估基于Web的系统，以解决用户定义的生物固化任务。在定义生物固化任务的灵活性方面，Argo被证明比其他系统具有优势。不出所料，工作台的多功能性不可避免地延长了策展人在执行任务之前花时间学习系统的时间，这可能会影响Argo的可用性。参与挑战使我们有机会收集宝贵的反馈意见并确定需要改进的地方，其中一些已经引入。数据库网址：http：//argo.nactem.ac.uk

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