| Biological networks to the analysis of microarray data |
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| 作者姓名： | FANG Zhuo LUO Qingming ZHANG Guoqing LI Yixue |
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| 作者单位： | 1. Hubei Bioinformatics and Molecular Imaging Key Laboratory，Huazhong University of Science and Technology, Wuhan 430074, China； 2. Shanghai Center for Bioinformation and Technology, Shanghai 200235, China |
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| 基金项目： | 国家重点基础研究发展计划(973计划);上海市科委资助项目;国家高技术研究发展计划(863计划) |
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| 摘 要： | Microarray technology, which permits rapid and large-scale screening for patterns of gene expressions, usually generates a large amount of data. How to mine the biological meanings under these data is one of the main challenges in bioinformatics. Compared to the pure mathematical techniques, those methods incorporated with some prior biological knowledge generally bring better interpretations. Recently, a new analysis, in which the knowledge of biological networks such as metabolic network and protein interaction network is introduced, is widely applied to microarray data analysis. The microarray data analysis based on biological networks contains two main research aspects: identification of active components in biological networks and assessment of gene sets significance. In this paper, we briefly review the progress of these two categories of analyses, especially some representative methods.
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| 关 键 词： | biological networks microarray data analysis subnetwork gene set. |
Biological networks to the analysis of microarray data |
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| FANG Zhuo,LUO Qingming,ZHANG Guoqing,LI Yixue.Biological networks to the analysis of microarray data[J].Progress in Natural Science,2006,16(12):1242-1251. |
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| Authors: | FANG Zhuo LUO Qingming ZHANG Guoqing LI Yixue |
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| Abstract: | Microarray technology, which permits rapid and large-scale screening for patterns of gene expressions, usually generates a large amount of data. How to mine the biological meanings under these data is one of the main challenges in bioinformatics. Compared to the pure mathematical techniques, those methods incorporated with some prior biological knowledge generally bring better interpretations. Recently, a new analysis, in which the knowledge of biological networks such as metabolic network and protein interaction network is introduced, is widely applied to microarray data analysis. The microarray data analysis based on biological networks contains two main research aspects: identification of active components in biological networks and assessment of gene sets significance. In this paper, we briefly review the progress of these two categories of analyses, especially some representative methods. |
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| Keywords: | biological networks microarray data analysis subnetwork gene set |
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