BioGraph: Unsupervised biomedical knowledge discovery via automated hypothesis generation

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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. © 2011 Liekens et al; licensee BioMed Central Ltd.

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Liekens, A. M. L., De Knijf, J., Daelemans, W., Goethals, B., De Rijk, P., & Del-Favero, J. (2011). BioGraph: Unsupervised biomedical knowledge discovery via automated hypothesis generation. Genome Biology, 12(6). https://doi.org/10.1186/gb-2011-12-6-r57

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