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New productivity, future industry, policy support, unlimited potential....
Artificial intelligence + synthetic biology has the above characteristics.
Plans, opinions and measures for promoting the development of synthetic biology at the national, provincial, municipal and county levels!
(Precision fermentation, biomedicine, bio-agriculture, biomass substitution, biosafety)
So, in which fields has artificial intelligence + synthetic biology taken the lead?
For example, gene regulation and component design, precise grasp of tiny components
Design and optimization of regulatory elements such as promoters: Use artificial intelligence technology to design new gene promoters and other regulatory elements to better control gene expression.
For example, through deep learning technology to integrate biological prior knowledge, establish a generative model of regulatory elements, generate a large number of promoters with specific functions and characteristics, and provide richer and more efficient component selection for the construction of synthetic biological systems.
Design and construction of gene circuits: Use artificial intelligence to design complex gene circuits to achieve precise regulation of cell functions.
For example, designing gene circuits that can accurately control cells to produce specific products and perform specific functions according to specific environmental signals or input conditions can be applied to biopharmaceuticals, biosensors and other fields.
For example, drug development and screening, related work has won the Nobel Prize many times
Design and discovery of new drugs: using the powerful computing power and pattern recognition capabilities of artificial intelligence to design new drug molecules based on the structure and characteristics of drug targets.
At the same time, a large number of compounds are virtually screened to predict their binding ability with targets, biological activity and toxicity, etc., and potential drug candidates are quickly screened, greatly improving the efficiency and success rate of drug development.
Prediction of drug efficacy and toxicity: Based on artificial intelligence, a large amount of biological data and drug data are analyzed to predict the efficacy and potential toxic reactions of drugs in different populations, providing a basis for the design of clinical trials and personalized drug treatment.
For example, protein engineering and design, this is an area where Internet companies such as Google and Nvidia have placed heavy bets
Protein structure prediction: Artificial intelligence technology can quickly and accurately predict the three-dimensional structure of proteins, providing a basis for protein functional research and design. This is of great significance for understanding the mechanism of action of proteins, designing proteins with specific functions, and developing protein-based drugs and materials.
Protein function design: According to specific needs and application scenarios, artificial intelligence is used to design proteins with specific functions, such as enzymes with high catalytic activity, antibodies with specific binding ability, etc. And the stability, solubility and other properties of proteins can be optimized to improve their performance in practical applications.
In terms of industry applications, there is great potential in the fields of agriculture and food
Crop improvement: Through gene editing and synthetic biology technology, combined with artificial intelligence analysis and prediction of crop genomes, crop varieties with excellent traits are cultivated, such as disease and pest resistance, drought resistance, high yield, etc.
Synthesis and improvement of food ingredients: Use synthetic biology to synthesize important ingredients in food, such as protein, sweeteners, etc., or improve the nutritional content and taste of food to meet people's needs for healthy and delicious food.
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