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Integrating unsupervised language model with triplet neural networks for protein gene ontology prediction
Accurate identification of protein function is critical to elucidate life mechanisms and design new drugs. We proposed a novel deep-learning method, ATGO, to predict Gene Ontology (GO) attributes of proteins through a triplet neural-network architecture embedded with pre-trained language models from...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9822105/ https://www.ncbi.nlm.nih.gov/pubmed/36548439 http://dx.doi.org/10.1371/journal.pcbi.1010793 |