Year: 2025
Type: article
Abstract: Synthetic biology is defined by Design-Build-Test-Learn cycles. Recent advances in machine learning are changing the landscape; thus, we propose that “Learning” can precede “Design”. Moreover, adopting cell-free platforms can further accelerate “Building” and “Testing” for megascale data generation and models.
Source: Nature Communications
Authors: Alia Clark-ElSayed, Isa Madrigal Harrison, Meagan L. Olsen, John T. Lazar, Michael C. Jewett, Andrew D. Ellington
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $6,990
Funders: National Science Foundation, U.S. Department of Energy, National Research Foundation, National Research Foundation of Korea, National Institutes of Health, National Institute of General Medical Sciences, Division of Chemical, Bioengineering, Environmental, and Transport Systems, Army Research Office
Awards: G11630931, Collaborative Research: Cell-free glycoprotein synthesis technology for point-of-care vaccine biomanufacturing, Graduate Research Fellowship Program (GRFP), G2757121588, G3241614447, G3467625884, G4771968897, G4903105778, G5635869474, G5767419451, G6338696783, G6526374922, INTEGRATING CELL-FREE SYSTEMS AND GENOME ENGINEERING TO ACCELERATE BIOSYSTEMS DESIGN FOR CARBON-NEGATIVE BIOMANUFACTURING, Ideas Lab: USPRD: Programmable Small Molecule Biosynthesis, G7452299184, Ideas Lab: USPRD: Enabling cell-free synthesis of longer human milk oliogosaccharides, Ideas Lab: USPRD: AI-designed Enzymes using Non-natural Cofactors for the Production of Bio-based Acrylates, G9000151939
OpenAlex ID: W4415923753