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. 2008 Mar 1:2008:26-30.

GeneRanker: An Online System for Predicting Gene-Disease Associations for Translational Research

Graciela Gonzalez  1 , Juan C Uribe, Brock Armstrong, Wendy McDonough, Michael E Berens
Affiliations

GeneRanker: An Online System for Predicting Gene-Disease Associations for Translational Research

Graciela Gonzalez et al. Summit Transl Bioinform. .

Abstract

With the overwhelming volume of genomic and molecular information available on many databases nowadays, researchers need from bioinformaticians more than encouragement to refine their searches. We present here GeneRanker, an online system that allows researchers to obtain a ranked list of genes potentially related to a specific disease or biological process by combining gene-disease (or genebiological process) associations with protein-protein interactions extracted from the literature, using computational analysis of the protein network topology to more accurately rank the predicted associations. GeneRanker was evaluated in the context of brain cancer research, and is freely available online at http://www.generanker.org.

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Figures

Figure 1.
Figure 1.
Initial set of genes. After the user types a disease or biological process, the GeneRanker system web interface (available at www.generanker.org) displays an initial set of genes obtained from relevant gene-disease associations extracted by CBioC from biomedical literature. Accuracy is estimated at 75% for this initial set.
Figure 3.
Figure 3.
GeneRanker, showing the top ranked genes for glioblastoma. The interface allows users to apply the method to any disease or biological process, obtaining a ranked list of potentially related genes. Precision reaches 91 to 94% for the top 100 genes in the list.
See this image and copyright information in PMC

References

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