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Journal of the American Medical Informatics Association (11 September 2012), doi:10.1136/amiajnl-2012-001168 Key: citeulike:11233238
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Background Many methods have been developed to identify disease genes and further module biomarkers of complex diseases based on gene expression data. It is generally difficult to distinguish whether the variations in gene expression are causative or merely the effect of a disease. The limitation of relying on gene expression data alone highlights the need to develop new approaches that can explore various data to reflect the casual relationship between network modules and disease traits.
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