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.