Foundation Models for Microbiome Research: From Sequence Semantics to Community Dynamics and Multimodal World Models
Haohong Zhang, Zixin Kang, Kang Ning · 2026
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Description
Haohong Zhang and co-authors review foundation models for microbiome science in a 2026 paper. Sequence data on microbes pile up faster than sense made of them, and most studies stay locked to one cohort. Foundation models learn reusable codes from vast unlabeled sets, which may loosen that lock.
The review stacks the field by scale: sequence models that read DNA and protein grammar, community models that learn from abundance maps, and mixed models that add host and habitat context. Design picks on tokens, training aims, and tests get a hard look. The path ends at world models that can simulate interventions.
Catalog record
| CREATOR | Haohong Zhang, Zixin Kang, Kang Ning |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 55 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |