Cargando…
NetGO 2.0: improving large-scale protein function prediction with massive sequence, text, domain, family and network information
With the explosive growth of protein sequences, large-scale automated protein function prediction (AFP) is becoming challenging. A protein is usually associated with dozens of gene ontology (GO) terms. Therefore, AFP is regarded as a problem of large-scale multi-label classification. Under the learn...
Autores principales: | Yao, Shuwei, You, Ronghui, Wang, Shaojun, Xiong, Yi, Huang, Xiaodi, Zhu, Shanfeng |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8262706/ https://www.ncbi.nlm.nih.gov/pubmed/34038555 http://dx.doi.org/10.1093/nar/gkab398 |
Ejemplares similares
-
NetGO: improving large-scale protein function prediction with massive network information
por: You, Ronghui, et al.
Publicado: (2019) -
NetGO 3.0: Protein Language Model Improves Large-scale Functional Annotations
por: Wang, Shaojun, et al.
Publicado: (2023) -
agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update
por: Tian, Tian, et al.
Publicado: (2017) -
iNetModels 2.0: an interactive visualization and database of multi-omics data
por: Arif, Muhammad, et al.
Publicado: (2021) -
WEGO 2.0: a web tool for analyzing and plotting GO annotations, 2018 update
por: Ye, Jia, et al.
Publicado: (2018)