Nucleic
Acids
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Research KAIST Graduate School of Engineering Biology
Research Area
AI-Driven Synthetic Biology
: Six Strategic Areas of Engineering Biology
The KAIST Graduate School of Engineering Biology advances AI-integrated synthetic biology to lead the next generation of biotechnology and bioindustry.
Artificial intelligence, automation, and data-driven design serve as the digital backbone across all six strategic research areas — enabling high-speed, high-precision, and scalable innovation from nucleic acid design to therapeutic and biomaterial production.
DNA & RNA Engineering
Nucleic Acids DNA & RNA Engineering
Goal
High-precision design and synthesis of artificial genes and RNA sequences
Research Focus
Development of automated large-scale gene synthesis and ultra-high-throughput evaluation pipelines
AI-driven analysis of genomic and transcriptomic data for optimal DNA/RNA design
Protein
Design
Design
Protein Design
Goal
Development of deep learning–based protein structure and function prediction, and new-to-nature protein material design technologies
Research Focus
Creation of next-generation models for protein structure prediction, design, and optimization to revolutionize enzyme-based bioprocessing
Establishment of high-speed development pipelines for therapeutic proteins
Genetic
Logic Circuits
Logic Circuits
Genetic Logic Circuits
Goal
Design of gene-based synthetic logic circuits and regulatory networks that precisely control complex cellular signaling and metabolic pathways
Research Focus
Redesign of next-generation genetic logic gates with multi-input and multi-output capabilities
Implementation of multi-signal–integrated gene circuits ensuring system stability and reproducibility
Microbial Cell
Factories
Factories
Microbial Cell Factories
Goal
Engineering high-efficiency microbial platforms for the production of diverse functional biomaterials
Research Focus
Design of purpose-specific chassis strains and large-scale genome manipulation/synthesis technologies
Genome-scale metabolic network optimization and bioprocess engineering for high-yield, scalable production
Mammalian Cell
Therapeutics
Therapeutics
Mammalian Cell Therapeutics
Goal
Establishment of high-efficiency, animal cell–based biopharmaceutical production platforms for large-scale manufacturing of therapeutics and vaccines
Research Focus
Construction of rapid, stable, and high-productivity mammalian cell line development pipelines
Custom design of viral vectors tailored to specific biotherapeutic products
Automation of pharmaceutical biomanufacturing processes
Plant-Derived
Biomaterials
Biomaterials
Plant-Derived Biomaterials
Goal
Development of plant- and plant cell–based technologies for alternative foods and sustainable biomaterials
Research Focus
Engineering of stress-resistant, high-efficiency plant cell systems
Advanced genome editing technologies for plant cell optimization
Enhanced production of valuable plant-derived compounds
AI Core Platform Across All Areas
Goal
To establish an AI-powered “Design–Build–Test–Learn (DBTL)” framework that accelerates every stage of synthetic biology research.
Research Focus
Integration of machine learning and generative AI models for DNA/RNA, protein, and metabolic pathway design
Development of predictive algorithms for cell behavior, productivity, and system stability
AI-assisted automation of biofoundry workflows for high-throughput experimentation and optimization
Innovation through
Synthetic Biology
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1
DNA/RNA Design
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2
Innovative Protein Design
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3
Genetic Logic Circuits
High-Value Biomaterial
Production
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4
Microbial Cell Factories for Rapid Production of Valuable Biomaterials
-
5
Mammalian Cell Systems for Vaccine and Therapeutic Production
-
6
Plant Cell Platforms for High-Value Biomaterial Production
Synthetic Biology R&D – Linked with Faculty Expertise
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Drag from side to side.
Nucleic Acids (DNA & RNA Engineering) |
Protein Design |
Genetic Logic Circuits |
Microbial Cell Factories |
Mammalian Cell Therapeutics |
Plant-Derived Biomaterials |
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