In　this　paper,　the　stability　analysis　problem　is　investigated　for　a　standard　class　of　genetic　regulatory　networks　(GRNs)　with　stochastic　disturbances　and　time-varying　delays.　The　standard　GRNs　under　consideration　are　based　on　the　model　of　the　recurrent　neural　networks,　the　stochastic　perturbation　is　in　the　form　of　a　scalar　Brownian　motion,　and　the　time-varying　delays　exist　in　the　transcription　and　translation　processes.　Specifically,　we　are　interested　in　(1)　establishing　a　standard　model　for　the　time-varying　delayed　GRNs　and　(2)　establishing　conditions　under　which　the　standard　GRNs　are　exponentially　mean-square　stable　in　the　presence　of　time　delays　and　stochastic　disturbances.　By　using　the　linear　matrix　inequality　(LMI)　technique　and.　S-procedure,　sufficient　conditions　are　first　derived　for　ensuring　globally　asymptotic　and　exponential　stability　that　can　be　easily　solved　by　using　standard　software　packages.　Two　numerical　examples　are　exploited　to　demonstrate　the　effectiveness　of　the　proposed　method.　©　2011　Elsevier　B.V.