# uKIN Combines New and Prior Information with Guided Network Propagation to Accurately Identify Disease Genes

## Author(s): Hristov, Borislav H; Chazelle, Bernard; Singh, Mona

To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1h82r
DC FieldValueLanguage
dc.contributor.authorHristov, Borislav H-
dc.contributor.authorChazelle, Bernard-
dc.contributor.authorSingh, Mona-
dc.date.accessioned2021-10-08T19:45:55Z-
dc.date.available2021-10-08T19:45:55Z-
dc.date.issued2020-06-24en_US
dc.identifier.citationHristov, Borislav H., Bernard Chazelle, and Mona Singh. "uKIN Combines New and Prior Information with Guided Network Propagation to Accurately Identify Disease Genes." Cell Systems 10, no. 6 (2020): 470-479.e3. doi:10.1016/j.cels.2020.05.008en_US
dc.identifier.issn2405-4712-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1h82r-
dc.description.abstractProtein interaction networks provide a powerful framework for identifying genes causal for complex genetic diseases. Here, we introduce a general framework, uKIN, that uses prior knowledge of disease-associated genes to guide, within known protein-protein interaction networks, random walks that are initiated from newly identified candidate genes. In large-scale testing across 24 cancer types, we demonstrate that our network propagation approach for integrating both prior and new information not only better identifies cancer driver genes than using either source of information alone but also readily outperforms other state-of-the-art network-based approaches. We also apply our approach to genome-wide association data to identify genes functionally relevant for several complex diseases. Overall, our work suggests that guided network propagation approaches that utilize both prior and new data are a powerful means to identify disease genes. uKIN is freely available for download at: https://github.com/Singh-Lab/uKIN.en_US
dc.format.extent470 - 479.e3en_US
dc.languageengen_US
dc.language.isoen_USen_US
dc.relation.ispartofCell Systemsen_US
dc.rightsFinal published version. This is an open access article.en_US
dc.titleuKIN Combines New and Prior Information with Guided Network Propagation to Accurately Identify Disease Genesen_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1016/j.cels.2020.05.008-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

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