Analysis　of　cellular　pathways　and　networks　in　terms　of　logic　relations　is　important　to　decipher　the　networks　of　molecular　interactions　that　underlie　cellular　function.　A　computational　approach　for　identifying　lower　and　higher　order　gene　logic　associations　was　presented　on　the　base　of　graph　coloring　theory　and　applied　it　to　the　colon　cancer　mRNA　microarray　data.　Then　the　logic　relationships　of　51　oncogenes　and　cancer　suppressor　genes　are　analyzed　and　the　logic　association　network　of　them　was　constructed.　The　signal　pathway　of　TGF　beta　from　the　network　model　was　found　and　verified　by　the　colon　cancer　pathway　of　KEGG.　The　model　reveals　many　higher　order　logic　relationships　of　cancer　genes.　These　relationships　illustrate　the　complexities　that　arise　in　cancer　cellular　networks　because　of　interacting　pathways.　The　results　show　that　this　method　is　feasible　and　is　expected　to　give　a　reference　to　the　medical　molecular　biologist.