This invention discloses a new generation of
artificial intelligence bioinformatics method for individual geographic tracing, belonging to the field of
wildlife DNA geographic tracing technology, including the following steps: S1, obtaining
DNA from biological samples; S2, constructing a novel
artificial intelligence DNA individual tracing model based on a
convolutional neural network module, combined with a CBAM spatial attention module and a
multilayer perceptron; S3, training the
artificial intelligence DNA individual tracing model using the sample's
genotype data and background sampling geographic data as inputs, and optimizing the
model parameters using cross-validation; S4, using the artificial intelligence DNA individual tracing model to predict the geographic coordinates of individual DNA from unknown samples. This invention has the ability to integrate data from different species and batches, greatly simplifying the dataset integration process, significantly reducing complexity, and improving
repeatability, enabling the prediction of accurate individual geographic locations.