论文部分内容阅读
In this paper,we firstly identify the functional modules enriched with differentially expressed genes(DEGs) and characterized by biological processes in specific cellular locations,based on gene ontology(GO) and microarray data.Then,we further define and filter disease relevant signature modules accord-ing to the ranking of the disease discriminating abilities of the pre-seleeted functional modules.At last,we analyze the potential way by which they cooperate towards human disease.Application of the proposedmethod to the analysis of a liver cancer dataset shows that,using the same false discovery rate (FDR)threshold,we can find more biologically meaningful and detailed processes by using the cellular localiza-tion information.Some biological evidences support the relevancy of our biological modules to the diseasemechanism.
In this paper, we initially identify the functional modules enriched with differentially expressed genes (DEGs) and characterized by biological processes in specific cellular locations, based on gene ontology (GO) and microarray data. Chen, we further define and filter disease relevant signature modules accord-ing to the ranking of the disease discriminating abilities of the pre-seleeted functional modules. At last, we analyze the potential way by which they seek towards human disease. Application of the proposedmethod to the analysis of a liver cancer dataset shows that, using the same false discovery rate (FDR) threshold, we can find more biologically meaningful and detailed processes by using the cellular localiza tion information. Home biological evidences support the relevancy of our biological modules to the disease mechanism.