Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences

In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In the life sciences, the anticipated growth of sequencing promises unprecedented data on natur...

Descripción completa

Detalles Bibliográficos
Autores principales: Rives, Alexander, Meier, Joshua, Sercu, Tom, Goyal, Siddharth, Lin, Zeming, Liu, Jason, Guo, Demi, Ott, Myle, Zitnick, C. Lawrence, Ma, Jerry, Fergus, Rob
Formato: Online Artículo Texto
Lenguaje:English
Publicado: National Academy of Sciences 2021
Materias:
Biological Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053943/
https://www.ncbi.nlm.nih.gov/pubmed/33876751
http://dx.doi.org/10.1073/pnas.2016239118

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053943/
https://www.ncbi.nlm.nih.gov/pubmed/33876751
http://dx.doi.org/10.1073/pnas.2016239118

Ejemplares similares