Abstract
Artificial intelligence (AI)-driven laboratory automation - combining robotic labware and autonomous software agents - is a powerful trend in modern biology. We developed Genesis-DB, a database system designed to support AI-driven autonomous laboratories by providing software agents access to large quantities of structured domain information. In addition, we present a new ontology for modeling data and metadata from autonomously performed yeast microchemostat cultivations in the framework of the Genesis robot scientist system. We show an example of how Genesis-DB enables the research life cycle by modeling yeast gene regulation, guiding future hypotheses generation and design of experiments. Genesis-DB supports AI-driven discovery through automated reasoning and its design is portable, generic, and easily extensible to other AI-driven molecular biology laboratory data and beyond.
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CITATION STYLE
Reder, G. K., Gower, A. H., Kronström, F., Halle, R., Mahamuni, V., Patel, A., … King, R. D. (2023). Genesis-DB: a database for autonomous laboratory systems. Bioinformatics Advances, 3(1). https://doi.org/10.1093/bioadv/vbad102
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