Gene　expression　data　has　the　characteristics　of　small　sample　size,　high　dimension,　nonlinear　and　so　on.　In　order　to　effectively　deal　with　the　gene　expression　data,　a　subspace　clustering　method　is　proposed　via　smooth　neighbour　representation(SNR).　The　neighborhood　linear　representation　of　data　points　is　used　to　describe　the　nonlinear　properties　of　data,　and　the　smooth　constraint　is　added　on　the　representation　which　makes　the　relationship　of　distance　between　data　point　and　its　neighbors　embed　in　the　reconstruction　representation.　Experiment　results　on　gene　expression　data　show　that　the　performance　of　SNR　is　superior　to　several　existing　methods,　and　SNR　can　cluster　gene　expression　data　effectively.　©　2017,　Editorial　Office　of　Control　and　Decision.　All　right　reserved.