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Nucleic Acids Res. 2018 Jan 4;46(D1):D527-D534. doi: 10.1093/nar/gkx876.

DISNOR: a disease network open resource.

Author information

1
Bioinformatics and Computational Biology Unit, Department of Biology, University of Rome 'Tor Vergata', 00133 Rome, Italy.
2
Laboratory of Bioinformatic, IRCCS Fondazione Santa Lucia, 00143 Rome, Italy.

Abstract

DISNOR is a new resource that aims at exploiting the explosion of data on the identification of disease-associated genes to assemble inferred disease pathways. This may help dissecting the signaling events whose disruption causes the pathological phenotypes and may contribute to build a platform for precision medicine. To this end we combine the gene-disease association (GDA) data annotated in the DisGeNET resource with a new curation effort aimed at populating the SIGNOR database with causal interactions related to disease genes with the highest possible coverage. DISNOR can be freely accessed at http://DISNOR.uniroma2.it/ where >3700 disease-networks, linking ∼2600 disease genes, can be explored. For each disease curated in DisGeNET, DISNOR links disease genes by manually annotated causal relationships and offers an intuitive visualization of the inferred 'patho-pathways' at different complexity levels. User-defined gene lists are also accepted in the query pipeline. In addition, for each list of query genes-either annotated in DisGeNET or user-defined-DISNOR performs a gene set enrichment analysis on KEGG-defined pathways or on the lists of proteins associated with the inferred disease pathways. This function offers additional information on disease-associated cellular pathways and disease similarity.

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