Intelligent Design PlatformDevelop AI technology to improve the design accuracy of synthetic biology
Our platform runs on the basis of artificial intelligence-assisted machine learning to develop a predictive model from underlying algorithms and given data sets. Through conducting a series of circular training methods, including parameter discovery, parameter estimation, model performance evaluation, error identification, and correction, our platform is able to optimize model performance, to find the best model parameter in our database, and to precisely predict the input data, thereby accelerating the directed evolution of enzyme molecules and genetic circuits.
Based on the concept of Intelligent design, our platform uses machine learning to design and modify genetic elements, protein performance, and genetic circuits. In addition, we can build different levels of predictive models from molecular components, to regulatory units, and to metabolic pathways, which serve the research and development of synthetic biology projects multidimensionally.
The volume and quality of input training data are the key factors for machine learning. Our Intelligent design platform has an integrated high throughput screening system, including pipetting workstation, colony picker, and a powerful analysis testing platform, which can provide a large number of high-quality training data sets for machine learning.