Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Emily C Hinds"'
Publikováno v:
PLoS Computational Biology, Vol 19, Iss 3, p e1010956 (2023)
Directed laboratory evolution applies iterative rounds of mutation and selection to explore the protein fitness landscape and provides rich information regarding the underlying relationships between protein sequence, structure, and function. Laborato
Externí odkaz:
https://doaj.org/article/4614ccefeebe41d58d180b7e7b05aa3c
Directed laboratory evolution applies iterative rounds of mutation and selection to explore the protein fitness landscape and provides rich information regarding the underlying relationships between protein sequence, structure, and function. Laborato
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f08bab2045e53e40603a31f912fdb095
https://doi.org/10.1101/2022.09.01.506224
https://doi.org/10.1101/2022.09.01.506224
Publikováno v:
Cell Syst
SummaryMachine learning can infer how protein sequence maps to function without requiring a detailed understanding of the underlying physical or biological mechanisms. It’s challenging to apply existing supervised learning frameworks to large-scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3cbac973010069993e3fa7ab5813671
https://doi.org/10.1101/2020.08.19.257642
https://doi.org/10.1101/2020.08.19.257642
Autor:
Emily C. Hinds, Philip A. Romero
Publikováno v:
The FASEB Journal. 32
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7f2e30ca6fb9f77fde9e66d68a4a090a
https://doi.org/10.1096/fasebj.2018.32.1_supplement.792.9
https://doi.org/10.1096/fasebj.2018.32.1_supplement.792.9