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Genesis-DB: a database for autonomous laboratory systems
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 l...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432352/ https://www.ncbi.nlm.nih.gov/pubmed/37600845 http://dx.doi.org/10.1093/bioadv/vbad102 |
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author | Reder, Gabriel K Gower, Alexander H Kronström, Filip Halle, Rushikesh Mahamuni, Vinay Patel, Amit Hayatnagarkar, Harshal Soldatova, Larisa N King, Ross D |
author_facet | Reder, Gabriel K Gower, Alexander H Kronström, Filip Halle, Rushikesh Mahamuni, Vinay Patel, Amit Hayatnagarkar, Harshal Soldatova, Larisa N King, Ross D |
author_sort | Reder, Gabriel K |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10432352 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-104323522023-08-18 Genesis-DB: a database for autonomous laboratory systems Reder, Gabriel K Gower, Alexander H Kronström, Filip Halle, Rushikesh Mahamuni, Vinay Patel, Amit Hayatnagarkar, Harshal Soldatova, Larisa N King, Ross D Bioinform Adv Application Note 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. Oxford University Press 2023-08-02 /pmc/articles/PMC10432352/ /pubmed/37600845 http://dx.doi.org/10.1093/bioadv/vbad102 Text en © The Author(s) 2023. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Application Note Reder, Gabriel K Gower, Alexander H Kronström, Filip Halle, Rushikesh Mahamuni, Vinay Patel, Amit Hayatnagarkar, Harshal Soldatova, Larisa N King, Ross D Genesis-DB: a database for autonomous laboratory systems |
title | Genesis-DB: a database for autonomous laboratory systems |
title_full | Genesis-DB: a database for autonomous laboratory systems |
title_fullStr | Genesis-DB: a database for autonomous laboratory systems |
title_full_unstemmed | Genesis-DB: a database for autonomous laboratory systems |
title_short | Genesis-DB: a database for autonomous laboratory systems |
title_sort | genesis-db: a database for autonomous laboratory systems |
topic | Application Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10432352/ https://www.ncbi.nlm.nih.gov/pubmed/37600845 http://dx.doi.org/10.1093/bioadv/vbad102 |
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