Computer Methods and Programs in Biomedicine
VRG: A database of vascular dysfunctions related genes
Computers & Mathematics with Applications
Detecting disease genes based on semi-supervised learning and protein-protein interaction networks
Artificial Intelligence in Medicine
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Over 1600 mammalian genes are known to cause an inherited disorder, when subjected to one or more mutations. These disease genes represent a unique resource for the identification and quantification of relationships between phenotypic attributes of a disease and the molecular features of the associated disease genes, including their ascribed annotated functional classes and expression patterns. Such analyses can provide a more global perspective and a deeper understanding of the probable causes underlying human hereditary diseases. In this perspective and critical view of disease genomics, we present a comparative analysis of genes reported to cause inherited diseases in humans in terms of their causative effects on physiology, their genetics and inheritance modes, the functional processes they are involved in and their expression profiles across a wide spectrum of tissues. Our analysis reveals that there are more extensive correlations between these attributes of genetic disease genes than previously appreciated. For instance, the functional pattern of genes causing dominant and recessive diseases is markedly different. Also, the function of the genes and their expression correlate with the type of disease they cause when mutated. The results further indicate that a comparative genomics approach for the analysis of genes linked to human genetic diseases will facilitate the elucidation of the underlying molecular and cellular mechanisms. Contact:nuria.lopez@crg.es; ouzounis@ebi.ac.uk Supplementary information: http://genome.imim.es/~nlopez/supplements/supp_bioinformatics.pdf