請用此 Handle URI 來引用此文件: http://hdl.handle.net/11455/40431
標題: Topology-based cancer classification and related pathway mining using microarray data
作者: Liu, C.C.
陳健尉
Chen, W.S.E.
Lin, C.C.
Liu, H.C.
Chen, H.Y.
Yang, P.C.
Chang, P.C.
Chen, J.J.W.
劉俊吉
關鍵字: gene-expression profiles
acute lymphoblastic-leukemia
lung-cancer
regulatory networks
feature-selection
protein networks
rna
expression
adenocarcinoma
model
discovery
期刊/報告no:: Nucleic Acids Research, Volume 34, Issue 14, Page(s) 4069-4080.
摘要: Cancer classification is the critical basis for patient-tailored therapy, while pathway analysis is a promising method to discover the underlying molecular mechanisms related to cancer development by using microarray data. However, linking the molecular classification and pathway analysis with gene network approach has not been discussed yet. In this study, we developed a novel framework based on cancer class-specific gene networks for classification and pathway analysis. This framework involves a novel gene network construction, named ordering network, which exhibits the power-law node-degree distribution as seen in correlation networks. The results obtained from five public cancer datasets showed that the gene networks with ordering relationship are better than those with correlation relationship in terms of accuracy and stability of the classification performance. Furthermore, we integrated the ordering networks, classification information and pathway database to develop the topology-based pathway analysis for identifying cancer class-specific pathways, which might be essential in the biological significance of cancer. Our results suggest that the topology-based classification technology can precisely distinguish cancer subclasses and the topology-based pathway analysis can characterize the correspondent biochemical pathways even if there are subtle, but consistent, changes in gene expression, which may provide new insights into the underlying molecular mechanisms of tumorigenesis.
URI: http://hdl.handle.net/11455/40431
ISSN: 0305-1048
文章連結: http://dx.doi.org/10.1093/nar/gkl583
顯示於類別:生物醫學研究所

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