Cargando…
Collectively encoding protein properties enriches protein language models
Pre-trained natural language processing models on a large natural language corpus can naturally transfer learned knowledge to protein domains by fine-tuning specific in-domain tasks. However, few studies focused on enriching such protein language models by jointly learning protein properties from st...
Autores principales: | An, Jingmin, Weng, Xiaogang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9641823/ https://www.ncbi.nlm.nih.gov/pubmed/36348281 http://dx.doi.org/10.1186/s12859-022-05031-z |
Ejemplares similares
-
Small Protein Enrichment Improves Proteomics Detection of sORF Encoded Polypeptides
por: Fijalkowski, Igor, et al.
Publicado: (2021) -
Properties of virion transactivator proteins encoded by primate cytomegaloviruses
por: Nicholson, Iain P, et al.
Publicado: (2009) -
Large language models encode clinical knowledge
por: Singhal, Karan, et al.
Publicado: (2023) -
EWS and FUS bind a subset of transcribed genes encoding proteins enriched in RNA regulatory functions
por: Luo, Yonglun, et al.
Publicado: (2015) -
Protein language models can capture protein quaternary state
por: Avraham, Orly, et al.
Publicado: (2023)