DMoVGPE: predicting gut microbial associated metabolites profiles with deep mixture of variational Gaussian Process experts
Through extensive evaluations on various datasets, DMoVGPE consistently achieves higher prediction performance than existing models. Furthermore, our model reveals significant associations between specific microbial taxa and metabolites, aligning well with findings from existing studies. These results highlight DMoVGPE's potential to provide accurate predictions and to uncover biologically meaningful relationships, paving the way for its application in disease research and personalized healthcare strategies.
Authors
- Jinlin Zhu (ORCID: https://orcid.org/0000-0002-4296-5914)
- Guohao Peng (ORCID: https://orcid.org/0000-0001-9967-4934)
- Qian Weng (ORCID: https://orcid.org/0000-0002-5307-4770)
- Mingyi Hu (ORCID: https://orcid.org/0000-0002-3927-0281)
Institutions
- Jiangnan University (CN)
- Nanyang Technological University (SG)
- State Key Laboratory of Food Science and Technology (CN)
Publication Details
- Journal
- BMC Bioinformatics
- Published
- 2025-03-27
- DOI
- https://doi.org/10.1186/s12859-025-06110-7
- Primary Topic
- Metabolomics and Mass Spectrometry Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00