Welcome to CD ComputaBio, your premier provider of AI-Aided Metabolic Engineering Services. Through the integration of cutting-edge artificial intelligence (AI) techniques and metabolic engineering expertise, we strive to revolutionize the field of biotechnology by optimizing metabolic pathways for the production of valuable compounds. Our team of experts combines computational and experimental approaches to accelerate the design and development of efficient bioproduction systems. With our comprehensive range of services, we assist clients in harnessing the power of AI to enhance their metabolic engineering projects.
What is AI-Aided Metabolic Engineering?
Metabolic engineering is a field that involves the manipulation and optimization of metabolic pathways in living organisms, such as bacteria or yeast, to enhance the production of specific compounds. AI-aided metabolic engineering describes the use of artificial intelligence technology to assist and improve the process of engineering metabolic pathways in living organisms. Through leveraging advanced algorithms and machine learning, AI can optimize metabolic pathways and enhance the production of desired compounds for various applications, including biofuels, pharmaceuticals, fine chemicals, and agricultural products.
Our Services
Here, we highlight services where AI is being used to improve different stages of the metabolic engineering development cycle: gene annotation and pathway design, pathway optimization, pathway building, performance testing, and production scale-up.
- AI-Aided Design and Optimization Services of Metabolic Processes
- Design on Circuit Boards
- Prediction of Metabolic Synthetic Pathways
- Metabolic Pathway Optimization
- Identification of Transposable Elements
- Metabolic Flux Optimization
- Metabolic Pathway Reconstruction
- Prediction of Translation Initiation Sites
- Metabolic Pathway Assembly
- Prediction of CRISPR Efficacy
- AI-Aided Metabolic Engineering Services
- AI-Aided Metabolites Screening and Identification
- AI-Aided Gene Annotation
Cases Study
Our computational biology team has extensive experience in the research of metabolic engineering. The following is a small snapshot of our finished projects for reference only. For details, please feel free to consult our professional team.
| Tasks |
Input Features |
Algorithm |
| Identify ORF |
protein amino acid sequence |
deep RNN, random forest, RNN and CNN |
| Annotate ORF |
protein amino acid sequences, subsequence extraction and peptide physicochemical properties |
CNN |
| Enzyme & Pathway Design |
protein sequences represented as voxel-based protein spatial structure |
support vector machines, gaussian process model |
| Pathway Optimization |
plasmid sequences, 50 strains, different promoter combinations |
neural network |
Process of Metabolic Engineering Services
At CD ComputaBio, we understand the paramount importance of metabolic engineering in driving innovation and making advancements in various industries. Our AI-aided metabolic engineering services leverage advanced computational tools and state-of-the-art techniques to streamline metabolic pathways' design, construction, and optimization. If you are interested in our services or have any questions, please feel free to contact us.
Reference:
- Jang W D, Kim G B, Kim Y, et al. Applications of artificial intelligence to enzyme and pathway design for metabolic engineering[J]. Current Opinion in Biotechnology, 2022, 73: 101-107.
