The application discloses a kind of young tumor pre-
cell abnormal dynamic identification method based on multi-
omics data, it is related to
cell abnormality identification technical field, the application is by constructing dynamic correlation strength matrix and
cumulative effect contribution matrix, according to individual
response characteristics Implementation of differentiating screening strategy, realize the
high fidelity identification of young tumor pre-
cell abnormal dynamics.For different
response type individuals, respectively using instant path, long-term path or double-path fusion strategy, accurately screening key behavior data, improve input quality.The method effectively eliminates redundant interference, enhances the model's ability to simulate key processes such as immune suppression and
DNA damage accumulation, significantly improves the biological rationality and prediction accuracy of
cell state evolution sequence, solves the model response
lag, low computational efficiency and output
distortion problems caused by
data noise in the prior art, and provides reliable
technical support for early warning and individualized intervention of pre-tumor lesions.