Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Sarah A. Fahlberg"'
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Abstract Machine learning (ML) has transformed protein engineering by constructing models of the underlying sequence-function landscape to accelerate the discovery of new biomolecules. ML-guided protein design requires models, trained on local sequen
Externí odkaz:
https://doaj.org/article/e8bffe7bf25249adbc51981c2451ec5c
Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Fatty acyl reductases (FARs) are critical enzymes in the biosynthesis of fatty alcohols and have the ability to directly acces acyl-ACP substrates. Here, authors couple machine learning-based protein engineering framework with gene shuffling to optim
Externí odkaz:
https://doaj.org/article/c7cf4104a3534f20a86d3e06336ff293
Machine learning-guided acyl-ACP reductase engineering for improved in vivo fatty alcohol production
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
Nature Communications
Nature Communications
Alcohol-forming fatty acyl reductases (FARs) catalyze the reduction of thioesters to alcohols and are key enzymes for microbial production of fatty alcohols. Many metabolic engineering strategies utilize FARs to produce fatty alcohols from intracellu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ec1d68b749a8d12aa9f9ff70d9e5f1b
https://doaj.org/article/c7cf4104a3534f20a86d3e06336ff293
https://doaj.org/article/c7cf4104a3534f20a86d3e06336ff293
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance Understanding the relationship between protein sequence and function is necessary to design new and useful proteins with applications in bioenergy, medicine, and agriculture. The mapping from sequence to function is tremendously complex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e5dcc54a6ce26304c58468b86f7e2f8
http://europepmc.org/articles/PMC8640744
http://europepmc.org/articles/PMC8640744
Publikováno v:
Curr Opin Biotechnol
Machine learning (ML) is revolutionizing our ability to understand and predict the complex relationships between protein sequence, structure, and function. Predictive sequence-function models are enabling protein engineers to efficiently search the s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::57e720d32773dc04b18ea063def32f8a
https://doi.org/10.1016/j.copbio.2022.102713
https://doi.org/10.1016/j.copbio.2022.102713