To identify signature genes for the pathogenesis of breast cancer, which provides a theoretical support for prevention and early diagnosis of breast cancer. The pattern recognition method was used to analysis the genome-wide gene expression data which was collected from the breast cancer part of TCGA (The Cancer Genome Atlas) database.336 gene expression signature genes were selected by means of a combination of statistical methods such as correlation, t test, confidence interval, etc. The accuracy can be as high as 98% through the machine learning method modeling, which is higher compared with the previous study. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis and GO (Gene Ontology) enrichment analysis indicated the significant correlation among eight and eighteen kinds of genes respectively. A functional analysis of the part of the eight pathways showed theirs close relationship at the level of gene regulation which indicted the identified signature genes play an important role in the pathogenesis of breast cancer and is very important for understanding the pathogenesis of breast cancer and the early diagnosis of breast cancer.