| Interaction of cellular-localized signature modules in response to prostate cancer |
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| 作者姓名： | Zhu Jing Guo Zheng Zhang Min Yang D Wang Jing Wang Chenguang |
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| 作者单位： | 1. School of Life Science and Bioinformatics Centre，University of Electronic Science and Technology of China，Chengdu 610054，China; 2. Department of Bioinformatics，Bio-Pharmaceutical Key Laboratory of Heilongjiang Province，Harbin Medical University，Harbin 150081，China |
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| 基金项目： | 国家自然科学基金;国家高技术研究发展计划(863计划) |
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| 摘 要： | Rapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge makes it promising for systematic understanding of complex human diseases at the functional modules level. Current modular categorizations can be defined and selected more specifically and precisely in terms of both biological processes and cellular locations, aiming at uncovering the modular molecular networks highly relevant to cancers. Based on Gene Ontology, we identifed the functional modules enriched with differentially expressed genes and characterized by biological processes and specific cellular locations. Then, according to the ranking of the disease discriminating abilities of the pre-selected functional modules, we further defined and filtered signature modules which have higher relevance to the cancer under study. Applications of the proposed method to the analysis of a prostate cancer dataset revealed insightful biological modules.
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| 关 键 词： | microarray analysis， Gene Ontology， classification analysis， cellular location， functional module. |
Interaction of cellular-localized signature modules in response to prostate cancer |
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| Zhu Jing,Guo Zheng,Zhang Min,Yang D,Wang Jing,Wang Chenguang.Interaction of cellular-localized signature modules in response to prostate cancer[J].Progress in Natural Science,2007,17(11):1368-1375. |
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| Authors: | Zhu Jing Guo Zheng Zhang Min Yang D Wang Jing Wang Chenguang |
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| Abstract: | Rapid progress in high-throughput biotechnologies (e.g. microarrays) and exponential accumulation of gene functional knowledge makes it promising for systematic understanding of complex human diseases at the functional modules level. Current modular categorizations can be defined and selected more specifically and precisely in terms of both biological processes and cellular locations, aiming at uncovering the modular molecular networks highly relevant to cancers. Based on Gene Ontology, we identifed the functional modules enriched with differentially expressed genes and characterized by biological processes and specific cellular locations. Then, according to the ranking of the disease discriminating abilities of the pre-selected functional modules, we further defined and filtered signature modules which have higher relevance to the cancer under study. Applications of the proposed method to the analysis of a prostate cancer dataset revealed insightful biological modules. |
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| Keywords: | microarray analysis Gene Ontology classification analysis cellular location functional module |
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