In　order　to　research　the　recognition　method　for　E.　coli　promoter,　E.　coli　promoter　feature　elements　are　researched　combining　with　molecubiology　theory　and　statistical　facts　of　E.　coli　gene　promoters.　Two-structure　neural　network　methods　were　applied　to　analysis　the　promoter　sequence　elements　in　E.　coli　gene　promoters　by　selecting　different　promoter　conservative　sequences.　As　a　result,　we　found　that　the　recognition　rate　of　the　positives　and　negatives　have　the　best　performance　when　the　canonical　elements　and　the　non-canonical　sequence　elements　are　all　included,　which　is　77.67%　and　88.45%　respectively.　This　result　can　provide　help　to　the　feature　selection　and　the　recognition　algorithm　research　of　the　promoters.