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Genes that contribute to complex traits pose special challenges that make candidate disease-associated gene discovery more difficult. In this work, we investigated topological features derived from PPI network to identify the causing genes of four complex diseases: Cancer, Type 1 Diabetes, Type 2 Diabetes, and Ageing genes. We used 10-fold cross-validation to evaluate the predictive capacity of all...
Cancer is a group of complex diseases, in which a relatively large number of genes are involved. One of the main goals of cancer research is to identify genes that causally relevant to the development and progress of cancer. The increasingly identified cancer genes and availability of genomic and proteomics data provide us opportunities to identify cancer genes by computational methods. In this work,...
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