Detalle de: Leveraging Natural Language Processing models to decode the dark proteome across the Animal Tree of Life
| Title | Leveraging Natural Language Processing models to decode the dark proteome across the Animal Tree of Life |
| Abstract |
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 ∼1,000 animal proteomes, it predicts functions to virtually all proteins, revealing previously uncharacterized functions that enhance our understanding of molecular evolution. FANTASIA is available on GitHub at https://github.com/CBBIO/FANTASIA . |
| Apa Reference | Martínez-Redondo, G. I., Perez-Canales, F. M., Fernández, J. M., Barrios-Núñez, I., Vázquez-Valls, M., Cases, I., Rojas, A. M., & Fernández, R. (2024). Leveraging Natural Language Processing models to decode the dark proteome across the Animal Tree of Life. 10.1101/2024.02.28.582465 |
| Doi | 10.1101/2024.02.28.582465 |
| Publication Date | 29 Feb 2024 |
| Publication Type | Preprint |
| Researcher | Ana Rojas |
| Ontology | Large language models, Functional genomics, Structural bioinformatics, Molecular evolution |
| Research Groups | Computational Biology and Bioinformatics (CBBIO.CABD) |
| Tools |