Genesis-DB: a database for autonomous laboratory systems
Journal article, 2023
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.
Author
Gabriel Reder
Chalmers, Life Sciences, Systems and Synthetic Biology
Alexander Gower
Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI
Filip Kronström
Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI
Rushikesh Halle
Thoughtworks
Vinay Mahamuni
Thoughtworks
Amit Patel
Thoughtworks
Harshal Hayatnagarkar
Thoughtworks
Larisa N. Soldatova
Goldsmiths, University of London
Ross King
Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI
University of Cambridge
Alan Turing Institute
Bioinformatics Advances
26350041 (eISSN)
Vol. 3 1 vbad102Subject Categories
Signal Processing
Computer Science
DOI
10.1093/bioadv/vbad102