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Exploring candidate Genes for Human Brain Diseases Based on a Brain-specific Gene Network

Abstract : It is believed that large numbers of genes are involved in common human brain diseases. Here, we propose a novel computational strategy for simultaneously identifying multiple candidate genes for genetic human brain diseases from a brain-specific gene network-level perspective. By integrating diverse genomic and proteomic datasets based on Bayesian statistical model, we built a large-scale human brain-specific gene network. Based on this network and minor prior knowledge of a specific brain disease, we can effectively identify multiple candidate genes for this disease. When four known Alzheimer's disease genes were used as the prior knowledge, among the top 46 high-scoring genes that we have found, 37 were previously reported to be associated with Alzheimer's disease. And the higher score a gene has, the more likely this gene is a disease-related one. The results suggest that the proposed method is effective, convenient, and applicable in the future genetic studies.
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https://hal.inria.fr/inria-00122880
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Submitted on : Friday, January 5, 2007 - 12:57:13 PM
Last modification on : Saturday, October 9, 2021 - 4:06:41 AM

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Bing Liu, Tianzi Jiang, Songde Ma, Huizhi Zhao, Jun Li, et al.. Exploring candidate Genes for Human Brain Diseases Based on a Brain-specific Gene Network. Biochemical and Biophysical Research Communications, Elsevier, 2006, Biochemical and Biophysical Research Communications, 349 (4), pp.1308-1314. ⟨10.1016/j.bbrc.2006.08.168⟩. ⟨inria-00122880⟩

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