Cryoelectron microscope atomic model structure building method and system based on deep learning and application

The invention discloses a cryoelectron microscope atomic model structure building method and system based on deep learning and application. The method comprises the steps of: 1, obtaining a cryoelectron microscope density map data set, and carrying out model training and model testing; 2, inputting a cryoelectron microscope density map and a corresponding amino acid sequence; and 3, carrying out feature coding and extraction on the cryoelectron microscope density map and the corresponding amino acid sequence, and building an atomic structure model. According to the measurement method provided by the invention, the generated amino acid atom model has structural biological characteristics, the structural biological rationality of the predicted amino acid atom model is ensured, accurate prediction of the end-to-end all-differentiable amino acid internal atom structure is finally realized, certain superiority is achieved, and the atomic model effect predicted by a plurality of tests is verified. In addition, the