Zobrazeno 1 - 10
of 48
pro vyhledávání: '"Philip A. Romero"'
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
Autor:
Hridindu Roychowdury, Philip A. Romero
Publikováno v:
Cell Death Discovery, Vol 8, Iss 1, Pp 1-8 (2022)
Abstract The human caspase family comprises 12 cysteine proteases that are centrally involved in cell death and inflammation responses. The members of this family have conserved sequences and structures, highly similar enzymatic activities and substr
Externí odkaz:
https://doaj.org/article/2c98510178254f3eb7227b936cd8b4e7
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
Autor:
Sonali Gupta, Tyler D. Ross, Marcella M. Gomez, Job L. Grant, Philip A. Romero, Ophelia S. Venturelli
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-15 (2020)
The spatial organisation of microbial communities is caused by the interplay of biotic and abiotic factors. Here the authors design a microfluidic platform to quantify the spatiotemporal parameters influencing diffusion-mediated interactions, and use
Externí odkaz:
https://doaj.org/article/f4525509e59b46ba9175cd035b955028
Publikováno v:
Cell Death Discovery, Vol 8, Iss 1, Pp 1-1 (2022)
Externí odkaz:
https://doaj.org/article/de51fce9f5d04478b1e96f0583116062
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
Protein engineering has nearly limitless applications across chemistry, energy, and medicine, but creating new proteins with improved or novel functions remains slow, labor-intensive, and inefficient. In this work, we present theSelf-driving Autonomo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dd0de03c7ac13ba9e402823b44204084
https://doi.org/10.1101/2023.05.20.541582
https://doi.org/10.1101/2023.05.20.541582
Autor:
Pete Heinzelman, Philip A. Romero
Publikováno v:
Protein Science. 32
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
Publikováno v:
Protein Engineering. :133-151