Genesis-DB: a database for autonomous laboratory systems

Author:

Reder Gabriel K1ORCID,Gower Alexander H1,Kronström Filip1,Halle Rushikesh2,Mahamuni Vinay2,Patel Amit2,Hayatnagarkar Harshal2,Soldatova Larisa N3ORCID,King Ross D145

Affiliation:

1. The Department of Computer Science and Engineering, Chalmers University of Technology , Gothenburg, 412 58, Sweden

2. Engineering for Research (e4r™), Thoughtworks Technologies (India) Pvt Ltd , Pune, 411006, India

3. Department of Computing, Goldsmiths, University of London , London, SE14 6AD, United Kingdom

4. Department of Chemical Engineering and Biotechnology, University of Cambridge , Cambridge, CB3 0AS, United Kingdom

5. Alan Turing Institute , London, NW1 2DB, United Kingdom

Abstract

Abstract Summary 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. Availability and implementation Genesis-DB code and installation instructions are available at the GitHub repository https://github.com/TW-Genesis/genesis-database-system.git. The database use case demo code and data are also available through GitHub (https://github.com/TW-Genesis/genesis-database-demo.git). The ontology can be downloaded here: https://github.com/TW-Genesis/genesis-ontology/releases/download/v0.0.23/genesis.owl. The ontology term descriptions (including mappings to existing ontologies) and maintenance standard operating procedures can be found at: https://github.com/TW-Genesis/genesis-ontology.

Funder

Chalmers AI Research Centre

Publisher

Oxford University Press (OUP)

Subject

Computer Science Applications,Genetics,Molecular Biology,Structural Biology

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