Synthetic Biology Knowledge System
Synthetic Biology Knowledge System
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DOI：
10.1021/acssynbio.1c00188
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发表时间：
2021-08-13
影响因子：
4.7
通讯作者：
Myers, Chris J.
中科院分区：
文献类型：
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作者：
Mante, Jeanet;Hao, Yikai;Myers, Chris J.
合成生物学知识系统（SBKS）是SynBioHub知识库的一个实例，它包括从ACS合成生物学发表的论文中挖掘出来的文本和数据信息。本文描述了正在开发的SBKS管理框架，该框架用于构建存储在此存储库中的知识。文本挖掘管道使用自然语言处理技术对文章执行自动注释，以识别重要内容，如关键术语、术语之间的关系和主题。数据挖掘管道对从补充文档中提取的序列（其中使用了遗传部分）执行自动注释。这两条管道将基因部分与描述其使用背景的论文联系起来。最终，SBKS将减少合成生物学家寻找完成设计所需信息的时间。
The Synthetic Biology Knowledge System (SBKS) is an instance of the SynBioHub repository that includes text and data information that has been mined from papers published in ACS Synthetic Biology. This paper describes the SBKS curation framework that is being developed to construct the knowledge stored in this repository. The text mining pipeline performs automatic annotation of the articles using natural language processing techniques to identify salient content such as key terms, relationships between terms, and main topics. The data mining pipeline performs automatic annotation of the sequences extracted from the supplemental documents with the genetic parts used in them. Together these two pipelines link genetic parts to papers describing the context in which they are used. Ultimately, SBKS will reduce the time necessary for synthetic biologists to find the information necessary to complete their designs.