(647e) A Synthetic Biology Knowledge System Accelerates Design and Learning for Synthetic Biology Researchers

Rational design of engineered organisms is an inherently knowledge-rich process. Literature review on a paper-by-paper basis is time-consuming, and information gleaned from papers is often difficult to wrangle into a format suitable for downstream design workflows. This is particularly true for sequence level data, where pointers to external databases may require several steps to locate and verify the sequence referenced in a particular paper. We have developed a Synthetic Biology Knowledge System, which uses automated and manually-curated text and data mining approaches to create a repository of knowledge entities including parts, characterization data, and interactions relevant to synthetic biology. We present several workflows that highlight how this system can accelerate the design process and enable exploration of existing designs without reading papers.