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Genome Biol. 2011 Jun 22;12(6):R57. doi: 10.1186/gb-2011-12-6-r57.

BioGraph: unsupervised biomedical knowledge discovery via automated hypothesis generation.

Author information

  • 1Applied Molecular Genomics group, VIB Department of Molecular Genetics, Universiteit Antwerpen, Universiteitsplein 1, Wilrijk, Belgium. anthony@liekens.net

Abstract

We present BioGraph, a data integration and data mining platform for the exploration and discovery of biomedical information. The platform offers prioritizations of putative disease genes, supported by functional hypotheses. We show that BioGraph can retrospectively confirm recently discovered disease genes and identify potential susceptibility genes, outperforming existing technologies, without requiring prior domain knowledge. Additionally, BioGraph allows for generic biomedical applications beyond gene discovery. BioGraph is accessible at http://www.biograph.be.

PMID:
21696594
[PubMed - indexed for MEDLINE]
PMCID:
PMC3218845
Free PMC Article

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