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@article{2396578, author = {Martin, Hector Garcia and Mazurenko, Stanislav and Zhao, Huimin}, article_number = {2}, doi = {http://dx.doi.org/10.1021/acssynbio.3c00760}, keywords = {Genetics; Kinetic modeling; Optimization; Peptides and proteins; Synthetic biology}, language = {eng}, issn = {2161-5063}, journal = {ACS Synthetic Biology}, title = {Special Issue on Artificial Intelligence for Synthetic Biology}, url = {https://pubs.acs.org/doi/10.1021/acssynbio.3c00760}, volume = {13}, year = {2024} }
TY - JFULL ID - 2396578 AU - Martin, Hector Garcia - Mazurenko, Stanislav - Zhao, Huimin PY - 2024 TI - Special Issue on Artificial Intelligence for Synthetic Biology JF - ACS Synthetic Biology VL - 13 IS - 2 SP - 408-410 EP - 408-410 PB - American Chemical Society SN - 21615063 KW - Genetics KW - Kinetic modeling KW - Optimization KW - Peptides and proteins KW - Synthetic biology UR - https://pubs.acs.org/doi/10.1021/acssynbio.3c00760 N2 - Synthetic biology presents significant prospects of helping scientists tackle important societal problems. However, a significant hurdle in this endeavor is our inability to predict biological systems as accurately as we predict and simulate physical or chemical ones. This limitation has important fundamental and practical implications: from the practical point of view, we are unable to design biological systems (e.g., proteins, pathways, cells) to a specification (e.g., bind to this molecule with this binding affinity or produce this chemical at this titer, rate, and yield); from the fundamental point of view, we lack an understanding of the underlying mechanisms that produce observed phenotypes. Artificial intelligence (AI) and machine learning (ML) show promise in providing the predictive power that synthetic biology needs and can be applied in all parts of the synthetic biology process (Figure 1). ER -
MARTIN, Hector Garcia, Stanislav MAZURENKO a Huimin ZHAO. Special Issue on Artificial Intelligence for Synthetic Biology. \textit{ACS Synthetic Biology}. American Chemical Society, 2024, roč.~13, č.~2, s.~408-410. ISSN~2161-5063. Dostupné z: https://dx.doi.org/10.1021/acssynbio.3c00760.
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