Abstract
Disease Candidate Genes (DCGene) is an advanced system for predicting the disease related genes, It is a novel computational approach by using the GO annotation information. The performance of the DCGene is evaluated in a set containing 1057 test samples, on both the local region and genome scale. In the local region scale, for 397 of 1057 (37.6%) samples, the disease-associated genes are at the top 1 of the out put gene prioritization list, and if the top 9 genes are all considered, 754(71.3%) disease-associated genes are included in the result. In the genome scale, 55% of the disease-relevant genes are included in the top scoring 3%, and 74% of the disease-relevant genes are included in the top 15%. The performance of the DCGene is demonstrated to be significant better than the others by comparison with the other systems and methods.
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Fang, Y., Wang, H. (2009). DCGene: A Novel Predicting Approach of the Disease Related Genes on Functional Annotation. In: Huang, DS., Jo, KH., Lee, HH., Kang, HJ., Bevilacqua, V. (eds) Emerging Intelligent Computing Technology and Applications. ICIC 2009. Lecture Notes in Computer Science, vol 5754. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04070-2_101
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DOI: https://doi.org/10.1007/978-3-642-04070-2_101
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