| Title: | BioMOBS: A multi-omics visual analytics workflow for biomolecular insight generation |
| Journal: | PLOS ONE |
| Published: | 14 Dec 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/38096184/ |
| DOI: | https://doi.org/10.1371/journal.pone.0295361 |
| URL: | http://dx.doi.org/10.1371/journal.pone.0295361 |
Publication 9166
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Abstract
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.</p>
5 Authors
- Dries Heylen
- Jannes Peeters
- Jan Aerts
- Gökhan Ertaylan
- Jef Hooyberghs
1 Application
| Application ID | Title |
|---|---|
| 71521 | Establishing individual metabolic health from clinical biochemistry, metabolomics and genome data for precision health |
Enabling scientific discoveries that improve human health