BioMOBS: A multi-omics visual analytics workflow for biomolecular insight generation

One of the challenges in multi-omics data analysis for precision medicine is the efficient exploration of undiscovered molecular interactions in disease processes. We present BioMOBS, a workflow consisting of two data visualization tools integrated with an open-source molecular information database...

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Veröffentlicht in:PloS one 2023-12, Vol.18 (12), p.e0295361-e0295361
Hauptverfasser: Heylen, Dries, Peeters, Jannes, Aerts, Jan, Ertaylan, Gökhan, Hooyberghs, Jef
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Sprache:eng
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Zusammenfassung:One of the challenges in multi-omics data analysis for precision medicine is the efficient exploration of undiscovered molecular interactions in disease processes. We present BioMOBS, a workflow consisting of two data visualization tools integrated with an open-source molecular information database to perform clinically relevant analyses (https://github.com/driesheylen123/BioMOBS). We performed exploratory pathway analysis with BioMOBS and demonstrate its ability to generate relevant molecular hypotheses, by reproducing recent findings in type 2 diabetes UK biobank data. The central visualisation tool, where data-driven and literature-based findings can be integrated, is available within the github link as well. BioMOBS is a workflow that leverages information from multiple data-driven interactive analyses and visually integrates it with established pathway knowledge. The demonstrated use cases place trust in the usage of BioMOBS as a procedure to offer clinically relevant insights in disease pathway analyses on various types of omics data.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0295361