Detecting disease associated modules and prioritizing active genes based on high throughput data |
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| Authors: | Yu-Qing Qiu Shihua Zhang Xiang-Sun Zhang Luonan Chen |
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| Institution: | (1) Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, PR China;(2) Key Laboratory of Random Complex Structures and Data Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, PR China;(3) Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for Pre-diabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yue-Yang Road, Shanghai, 200031, PR China;(4) Department of Electrical Engineering and Electronics, Osaka Sangyo University, Osaka 574-8530, Japan |
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| Abstract: | Background The accumulation of high-throughput data greatly promotes computational investigation of gene function in the context of complex
biological systems. However, a biological function is not simply controlled by an individual gene since genes function in
a cooperative manner to achieve biological processes. In the study of human diseases, rather than to discover disease related
genes, identifying disease associated pathways and modules becomes an essential problem in the field of systems biology. |
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