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The identification of disease genes is an essential issue to decipher the mechanisms of complex diseases. Many existing methods combine machine learning algorithms and network information to predict disease genes and are based on the ‘guilt by association’ assumption, where disease genes are considered to be close to each other in a biomolecular network. Although these methods have gained many novel...
The identification of disease genes is the first step towards the understanding of genetic disease mechanisms. Although many computational algorithms are proposed to identify disease genes, they either have poor performance in terms of AUC scores or are very time consuming. To overcome these two problems, a logistic regression based algorithm is proposed in this study for identifying disease genes...
With advances in biotechnologies, large-scale biological data has been and will continue to be produced. These large-scale biological data contain insightful information for understanding the mechanism of biological systems and have proven useful in the diagnosis, treatment, and drug design for genomic-alerted diseases. In this special section, five papers in their significantly extended versions...
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