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

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

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Podrobná bibliografie

Vydáno v:	bioRxiv
Hlavní autoři:	Rives, Alexander, Meier, Joshua, Sercu, Tom, Goyal, Siddharth, Lin, Zeming, Liu, Jason, Guo, Demi, Ott, Myle, Zitnick, C Lawrence, Ma, Jerry, Fergus, Rob
Médium:	Paper
Jazyk:	angličtina
Vydáno:	Cold Spring Harbor Cold Spring Harbor Laboratory Press 15.12.2020 Cold Spring Harbor Laboratory
Vydání:	1.4
Témata:	Amino acid sequence Artificial intelligence Evolution Learning Protein families Protein structure Proteins Scaling Secondary structure Structure-function relationships Synthetic Biology
ISSN:	2692-8205, 2692-8205
On-line přístup:	Získat plný text
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