Detalle de: FANTASIA leverages language models to decode the functional dark proteome across the animal tree of life
| Title | FANTASIA leverages language models to decode the functional dark proteome across the animal tree of life |
| Abstract |
Protein functional annotation is crucial in biology, but many protein-coding genes remain uncharacterized, especially in non-model organisms. FANTASIA (Functional ANnoTAtion based on embedding space SImilArity) integrates protein language models for large-scale functional annotation. Applied to ~1000 animal proteomes, FANTASIA predicts functions to virtually all proteins, including up to 50% that remained unannotated by traditional homology-based methods. This enables the discovery of novel gene functions, enhancing our understanding of molecular evolution and organismal biology. FANTASIA holds particular promise for functional discovery in non-model taxa, offering advantages over homology-based tools in sensitivity and generalizability. FANTASIA is available on GitHub at https://github.com/CBBIO/FANTASIA . |
| Apa Reference | Martínez-Redondo, G. I., Perez-Canales, F. M., Carbonetto, B., Fernández, J. M., Barrios-Núñez, I., Vázquez-Valls, M., Cases, I., Rojas, A. M., & Fernández, R. (2025). FANTASIA leverages language models to decode the functional dark proteome across the animal tree of life. Communications Biology, 8(1). 10.1038/s42003-025-08651-2 |
| Doi | 10.1038/s42003-025-08651-2 |
| Publication Date | 14 Aug 2025 |
| Publication Type | Article |
| Researcher | Ildefonso Cases |
| Ontology | Model organisms, Large language models, Functional genomics, Functional annotation, Function prediction, Molecular evolution, Proteomics, Non-model organisms |
| Research Groups | |
| Tools |