[2]https://www.nature.com/articles/d41586-022-01075-6#ref-CR1 [3]Lu H, Diaz DJ, Czarnecki NJ, et al. Machine learning-aided engineering of hydrolases for PET depolymerization. Nature. 2022 Apr;604(7907):662-667. doi: 10.1038/s41586-022-04599-z. Epub 2022 Apr 27. PMID: 35478237....
参考文献: LuH, Diaz DJ, Czarnecki NJ, et al. Machine learning-aided engineering of hydrolases for PET depolymerization. Nature. 2022 Apr;604(7907):662-667. doi:10.1038/s41586-022-04599-z. Epub 2022 Apr 27. PMID: 35478237. 责任编辑:白芨...
参考文献 Machine learning-aided engineering of hydrolases for PET depolymerization. Nature, 2022, 604, 662-667.
Nature 604, 662–667 (2022). Article ADS MATH Google Scholar Raissi, M., Perdikaris, P. & Karniadakis, G. E. Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations. J. Comput. Phys. 378, 686–...
LuH, Diaz DJ, Czarnecki NJ, et al. Machine learning-aided engineering of hydrolases for PET depolymerization. Nature. 2022 Apr;604(7907):662-667. doi:10.1038/s41586-022-04599-z. Epub 2022 Apr 27. PMID: 35478237. 为了您能正常使用网站功能,建议使用一下浏览器: ...
Nature volume 604, pages 662–667 (2022)Cite this article 130k Accesses 2100 Altmetric Metrics details Abstract Plastic waste poses an ecological challenge1,2,3 and enzymatic degradation offers one, potentially green and scalable, route for polyesters waste recycling4. Poly(ethylene terephthalate) (...
Machine learning-aided engineering ofhydrolases for PET depolymerization.Nature, 2022, 604:662-667 DOI: 10.1038/s41586-022-04599-z. https://www.nature.com/articles/s41586-022-04599-z 【2】Eggo U. Thoden van Velzen & GiusySantomasi. Tailor-made enzymes for plastic recycling.Nature, 2022 ...
Lu, H. et al. Machine learning-aided engineering of hydrolases for PET depolymerization.Nature604, 662–667 (2022). ArticleCASPubMedGoogle Scholar Ulissi, Z. W., Medford, A. J., Bligaard, T. & Nørskov, J. K. To address surface reaction network complexity using scaling relations machine...
Nature 604, 662–667 (2022). Article Google Scholar Norn, C. et al. Protein sequence design by conformational landscape optimization. Proc. Natl Acad. Sci. USA 118, e2017228118 (2021). Article Google Scholar Hsu, C. et al. Learning inverse folding from millions of predicted structures....
2022年4月27日,Nature发文表示研究人员发现了一种可以满足工业规模塑料降解的酶,可稳定高效分解聚对苯二甲酸乙二醇酯(Poly Ethylene Terephthalate,PET)废弃物,再生食品级包装材料(图5)[2]。 图5 研究成果(图源:Nature) 全球主要的塑料消费结...