Computational　analysis　is　essential　for　transforming　the　masses　of　microarray　data　into　a　mechanistic　understanding　of　cancer.　Here　we　present　a　method　for　finding　gene　functional　modules　of　cancer　from　microarray　data　and　have　applied　it　to　colon　cancer.　First,　a　colon　cancer　gene　network　and　a　normal　colon　tissue　gene　network　were　constructed　using　correlations　between　the　genes.　Then　the　modules　that　tended　to　have　a　homogeneous　functional　composition　were　identified　by　splitting　up　the　network.　Analysis　of　both　networks　revealed　that　they　are　scale-free.　Comparison　of　the　gene　functional　modules　for　colon　cancer　and　normal　tissues　showed　that　the　modules＇　functions　changed　with　their　structures.