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Reder, G., Bjurström, E. Y., Brunnsåker, D., Kronström, F., Lasin, P., Tiukova, I., . . . King, R. D. (2024). AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting. Journal of the American Society for Mass Spectrometry, 35(3), 542-550
Open this publication in new window or tab >>AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting
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2024 (English)In: Journal of the American Society for Mass Spectrometry, ISSN 1044-0305, E-ISSN 1879-1123, Vol. 35, no 3, p. 542-550Article in journal (Refereed) Published
Abstract [en]

Automation is dramatically changing the nature of laboratory life science. Robotic lab hardware that can perform manual operations with greater speed, endurance, and reproducibility opens an avenue for faster scientific discovery with less time spent on laborious repetitive tasks. A major bottleneck remains in integrating cutting-edge laboratory equipment into automated workflows, notably specialized analytical equipment, which is designed for human usage. Here we present AutonoMS, a platform for automatically running, processing, and analyzing high-throughput mass spectrometry experiments. AutonoMS is currently written around an ion mobility mass spectrometry (IM-MS) platform and can be adapted to additional analytical instruments and data processing flows. AutonoMS enables automated software agent-controlled end-to-end measurement and analysis runs from experimental specification files that can be produced by human users or upstream software processes. We demonstrate the use and abilities of AutonoMS in a high-throughput flow-injection ion mobility configuration with 5 s sample analysis time, processing robotically prepared chemical standards and cultured yeast samples in targeted and untargeted metabolomics applications. The platform exhibited consistency, reliability, and ease of use while eliminating the need for human intervention in the process of sample injection, data processing, and analysis. The platform paves the way toward a more fully automated mass spectrometry analysis and ultimately closed-loop laboratory workflows involving automated experimentation and analysis coupled to AI-driven experimentation utilizing cutting-edge analytical instrumentation. AutonoMS documentation is available at https://autonoms.readthedocs.io.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2024
National Category
Analytical Chemistry
Identifiers
urn:nbn:se:kth:diva-367056 (URN)10.1021/jasms.3c00396 (DOI)001159213100001 ()38310603 (PubMedID)2-s2.0-85184806692 (Scopus ID)
Note

QC 20250714

Available from: 2025-07-14 Created: 2025-07-14 Last updated: 2025-07-14Bibliographically approved
Lei, W., Fuster-Barcelo, C., Reder, G., Munoz-Barrutia, A. & Ouyang, W. (2024). BioImage.IO Chatbot: a community-driven AI assistant for integrative computational bioimaging [Letter to the editor]. Nature Methods, 21(8)
Open this publication in new window or tab >>BioImage.IO Chatbot: a community-driven AI assistant for integrative computational bioimaging
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2024 (English)In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 21, no 8Article in journal, Letter (Refereed) Published
Place, publisher, year, edition, pages
Springer Nature, 2024
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:kth:diva-353008 (URN)10.1038/s41592-024-02370-y (DOI)001297657900018 ()39122937 (PubMedID)2-s2.0-85200738078 (Scopus ID)
Note

QC 20240911

Available from: 2024-09-11 Created: 2024-09-11 Last updated: 2024-09-11Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-8918-0789

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