Discovering Content through Text Mining for a Synthetic Biology Knowledge System.

Scientific articles contain a wealth of information about experimental methods and results describing biological designs. Due to its unstructured nature and multiple sources of ambiguity and variability, extracting this information from text is a difficult task. In this paper, we describe the development of the synthetic biology knowledge system (SBKS) text processing pipeline.

Synthetic Biology Knowledge System.

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.