A　protein-protein　interaction　(PPI)　network　is　a　biomolecule　relationship　network　that　plays　an　important　role　in　biological　activities.　Studies　of　functional　modules　in　a　PPI　network　contribute　greatly　to　the　understanding　of　biological　mechanism.　With　the　development　of　life　science　and　computing　science,　a　great　amount　of　PPI　data　has　been　acquired　by　various　experimental　and　computational　approaches,　which　presents　a　significant　challenge　of　detecting　functional　modules　in　a　PPI　network.　To　address　this　challenge,　many　functional　module　detecting　methods　have　been　developed.　In　this　survey,　we　first　analyze　the　existing　problems　in　detecting　functional　modules　and　discuss　the　countermeasures　in　the　data　preprocess　and　postprocess.　Second,　we　introduce　some　special　metrics　for　distance　or　graph　developed　in　clustering　process　of　proteins.　Third,　we　give　a　classification　system　of　functional　module　detecting　methods　and　describe　some　existing　detection　methods　in　each　category.　Fourth,　we　list　databases　in　common　use　and　conduct　performance　comparisons　of　several　typical　algorithms　by　popular　measurements.　Finally,　we　present　the　prospects　and　references　for　researchers　engaged　in　analyzing　PPI　networks.