The　structural　parameters　of　Pearson　correlation　(PC)　and　mutual　information　correlation　(MUC)　network　of　gens　are　used　to　study　the　pathogenic　mechanism　and　the　difference　between　the　two　correlations　in　the　study　of　biological　function.　As　an　example,　the　PC　and　MUC　networks　of　bipolar　disorder　(BD)　are　constructed,　and　the　top　30　genes　(namely,　SKGs)　with　large　difference　in　the　average　degree　of　the　networks　are　analyzed.　It　is　found　that　BD　is　significantly　correlated　with　nervous　system,　and　is　related　to　immune　system,　genetic　regulation,　cell　growth/apoptosis　and　angiogenesis.　In　addition,　PC　has　universality　in　revealing　biological　functions,　but　the　effect　of　MUC　is　obviously　greater　than　that　of　PC.　This　suggests　that　the　influence　of　non-linear　components　on　biological　function　attributes　is　greater　than　that　of　linear　components.　Therefore,　research　methods　based　on　linear　correlation　PC　are　not　enough　to　reveal　the　comprehensive　information　of　biological　mechanism,　and　research　methods　only　using　MUC　also　omit　linear　components.　©　2021　IEEE.