A framework for predictive modeling of microbiome multi-omics data: latent interacting variable-effects (LIVE) modeling
LIVE makes a distinct, complementary contribution to current methods to integrate microbiome data and offers key advantages to existing approaches in the interpretable integration of multi-omics data with clinical variables to predict to disease outcomes and identify microbiome mechanisms of disease.
Authors
- Douglas K. Brubaker (ORCID: https://orcid.org/0000-0001-5083-0334)
- Javier Muñoz Briones (ORCID: https://orcid.org/0009-0003-1129-8105)
Institutions
- Purdue University West Lafayette (US)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-04-29
- DOI
- https://doi.org/10.1186/s12859-025-06134-z
- Citations
- 1
- Primary Topic
- Bioinformatics and Genomic Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.81
Funders
- Directorate for Biological Sciences
- National Institute of Child Health and Human Development