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...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhu, Yi-Heng, Zhang, Chengxin, Yu, Dong-Jun, Zhang, Yang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
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

Internet

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

Ejemplares similares