297 related articles for article (PubMed ID: 36227537)
1. Synthetic Biology Meets Machine Learning.
Sieow BF; De Sotto R; Seet ZRD; Hwang IY; Chang MW
Methods Mol Biol; 2023; 2553():21-39. PubMed ID: 36227537
[TBL] [Abstract][Full Text] [Related]
2. In silico, in vitro, and in vivo machine learning in synthetic biology and metabolic engineering.
Faulon JL; Faure L
Curr Opin Chem Biol; 2021 Dec; 65():85-92. PubMed ID: 34280705
[TBL] [Abstract][Full Text] [Related]
3. Dynamic Metabolomics for Engineering Biology: Accelerating Learning Cycles for Bioproduction.
Vavricka CJ; Hasunuma T; Kondo A
Trends Biotechnol; 2020 Jan; 38(1):68-82. PubMed ID: 31473013
[TBL] [Abstract][Full Text] [Related]
4. Opportunities at the Intersection of Synthetic Biology, Machine Learning, and Automation.
Carbonell P; Radivojevic T; García Martín H
ACS Synth Biol; 2019 Jul; 8(7):1474-1477. PubMed ID: 31319671
[TBL] [Abstract][Full Text] [Related]
5. Learning Strategies in Protein Directed Evolution.
Cadet XF; Gelly JC; van Noord A; Cadet F; Acevedo-Rocha CG
Methods Mol Biol; 2022; 2461():225-275. PubMed ID: 35727454
[TBL] [Abstract][Full Text] [Related]
6. Lessons from Two Design-Build-Test-Learn Cycles of Dodecanol Production in Escherichia coli Aided by Machine Learning.
Opgenorth P; Costello Z; Okada T; Goyal G; Chen Y; Gin J; Benites V; de Raad M; Northen TR; Deng K; Deutsch S; Baidoo EEK; Petzold CJ; Hillson NJ; Garcia Martin H; Beller HR
ACS Synth Biol; 2019 Jun; 8(6):1337-1351. PubMed ID: 31072100
[TBL] [Abstract][Full Text] [Related]
7. Machine Learning and Hybrid Methods for Metabolic Pathway Modeling.
Cuperlovic-Culf M; Nguyen-Tran T; Bennett SAL
Methods Mol Biol; 2023; 2553():417-439. PubMed ID: 36227553
[TBL] [Abstract][Full Text] [Related]
8. Systems Metabolic Engineering Meets Machine Learning: A New Era for Data-Driven Metabolic Engineering.
Presnell KV; Alper HS
Biotechnol J; 2019 Sep; 14(9):e1800416. PubMed ID: 30927499
[TBL] [Abstract][Full Text] [Related]
9. Opportunities for yeast metabolic engineering: Lessons from synthetic biology.
Krivoruchko A; Siewers V; Nielsen J
Biotechnol J; 2011 Mar; 6(3):262-76. PubMed ID: 21328545
[TBL] [Abstract][Full Text] [Related]
10. Machine learning for metabolic engineering: A review.
Lawson CE; Martí JM; Radivojevic T; Jonnalagadda SVR; Gentz R; Hillson NJ; Peisert S; Kim J; Simmons BA; Petzold CJ; Singer SW; Mukhopadhyay A; Tanjore D; Dunn JG; Garcia Martin H
Metab Eng; 2021 Jan; 63():34-60. PubMed ID: 33221420
[TBL] [Abstract][Full Text] [Related]
11. [An evolving and flourishing metabolic engineering].
Liu Z; Wang Y
Sheng Wu Gong Cheng Xue Bao; 2021 May; 37(5):1494-1509. PubMed ID: 34085439
[TBL] [Abstract][Full Text] [Related]
12. The ease and complexity of identifying and using specialized metabolites for crop engineering.
Muhich AJ; Agosto-Ramos A; Kliebenstein DJ
Emerg Top Life Sci; 2022 Apr; 6(2):153-162. PubMed ID: 35302160
[TBL] [Abstract][Full Text] [Related]
13. From plant metabolic engineering to plant synthetic biology: The evolution of the design/build/test/learn cycle.
Pouvreau B; Vanhercke T; Singh S
Plant Sci; 2018 Aug; 273():3-12. PubMed ID: 29907306
[TBL] [Abstract][Full Text] [Related]
14. Next-Generation Machine Learning for Biological Networks.
Camacho DM; Collins KM; Powers RK; Costello JC; Collins JJ
Cell; 2018 Jun; 173(7):1581-1592. PubMed ID: 29887378
[TBL] [Abstract][Full Text] [Related]
15. Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges.
Goshisht MK
ACS Omega; 2024 Mar; 9(9):9921-9945. PubMed ID: 38463314
[TBL] [Abstract][Full Text] [Related]
16. Leveraging knowledge engineering and machine learning for microbial bio-manufacturing.
Oyetunde T; Bao FS; Chen JW; Martin HG; Tang YJ
Biotechnol Adv; 2018; 36(4):1308-1315. PubMed ID: 29729378
[TBL] [Abstract][Full Text] [Related]
17. Function2Form Bridge-Toward synthetic protein holistic performance prediction.
Yallapragada VVB; Walker SP; Devoy C; Buckley S; Flores Y; Tangney M
Proteins; 2020 Mar; 88(3):462-475. PubMed ID: 31589780
[TBL] [Abstract][Full Text] [Related]
18. Mechanistic Model-Driven Biodesign in Mammalian Synthetic Biology.
Chew YH; Marucci L
Methods Mol Biol; 2024; 2774():71-84. PubMed ID: 38441759
[TBL] [Abstract][Full Text] [Related]
19. Machine Learning-driven Protein Library Design: A Path Toward Smarter Libraries.
Mardikoraem M; Woldring D
Methods Mol Biol; 2022; 2491():87-104. PubMed ID: 35482186
[TBL] [Abstract][Full Text] [Related]
20. CellBox: Interpretable Machine Learning for Perturbation Biology with Application to the Design of Cancer Combination Therapy.
Yuan B; Shen C; Luna A; Korkut A; Marks DS; Ingraham J; Sander C
Cell Syst; 2021 Feb; 12(2):128-140.e4. PubMed ID: 33373583
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]