Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation

Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation

Georgia Tech Research via YouTube Direct link

Summary

24 of 24

24 of 24

Summary

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Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation

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  1. 1 Intro
  2. 2 Microelectronics vs. Biotechnology
  3. 3 What is Synthetic Biology?
  4. 4 Automated Protein Engineering: Fully Automated & HT Synthesis of TALENS
  5. 5 Preventing Transmission of Mitochondrial Diseases
  6. 6 Lycopene Pathway as a Test Case
  7. 7 Automated Cellular Engineering: east strain development via RNAi-assisted Genome Evolution
  8. 8 DOE Center for Advanced Bioenergy & Bioproducts Innovation
  9. 9 Vision: Develop an Automated Cellular Engineering (ACE) Platform
  10. 10 Multi-functional Genome-wide CRISPR System (MAGIC)
  11. 11 3. CRISPR/HDR Assisted Genome- scale Engineering (CHANGE)
  12. 12 Editing Efficiencies and Validation of CHANGE
  13. 13 Genome Editing with Single Nucleotide Precision
  14. 14 Three Main Types of Catalysis
  15. 15 Biocatalysis vs. Chemical Catalysis I
  16. 16 Combining Biocatalysis and Chemical Catalysis
  17. 17 Enzymatic Reduction of E/Z Olefins
  18. 18 Concept: Isomerization and Reduction
  19. 19 Tandem vs Sequential
  20. 20 Proposed Mechanism
  21. 21 Condition Optimization
  22. 22 Substrate Scope
  23. 23 Molecule Maker Lab Institute (an NSF AI Research Institute)
  24. 24 Summary

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