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Background: Cancer is a complex disease where molecular mechanism remains elusive.A system approach is needed to integrate diverse biological information for the prognosis and therapy risk assessment using mechanistic approach to understand gene interaction in pathways, network and functional attributes to unravel the biological behaviour of tumors.Results: We weighted the functional attributes based on various functional properties observed between cancerous and non-cancerous genes reported from literature.This weighing schema is then encoded in the Boolean logic framework to rank differentially expressed genes.We have identified 17 genes to be differentially expressed, where 10 genes are reported to be down-regulated via epigenetic inactivation and 7 genes are up-regulated.Here, we report for the first time that the overexpressed genes IRAK1, CHEK1, CHEK2 and BUB1 may play an important role in ovarian cancer.